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Critical Vulnerability in Swedish BankID Exposes User Data

সুইডিশ ব্যাংকআইডি-তে জটিল দুর্বলতা ব্যবহারকারীর ডেটা প্রকাশ করে

Kritische Sicherheitslücke in Swedish BankID legt Benutzerdaten offen

Vulnerabilidad crítica en BankID sueco expone datos de usuario

Une vulnérabilité critique dans Swedish BankID expose les données des utilisateurs

स्वीडिश बैंकआईडी में गंभीर भेद्यता उपयोगकर्ता डेटा को उजागर करती है

スウェーデンの BankID の重大な脆弱性によりユーザーデータが漏洩

스웨덴 BankID의 심각한 취약점으로 인해 사용자 데이터 노출

Vulnerabilidade crítica no BankID sueco expõe dados do usuário

Критическая уязвимость в шведском BankID приводит к раскрытию пользовательских данных

İsveç BankID'deki Kritik Güvenlik Açığı Kullanıcı Verilerini Açığa Çıkardı

Lỗ hổng nghiêm trọng trong BankID Thụy Điển làm lộ dữ liệu người dùng

瑞典 BankID 存在严重漏洞，导致用户数据泄露

Effective Anomaly Detection Pipeline for Amazon Reviews: References & Appendix

Simplifying Transformer Models for Faster Training and Better Performance

Real-Time tricks: Harnessing Kafka Streams for Seamless Data Tasks

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Sebastien Ferr ´e, Univ Rennes, CNRS, Inria, IRISA Campus de Beaulieu, 35042 Rennes, France and ferre@irisa.fr. Table of Links Abstract & Introduction Abstraction and Reasoning Corpus (ARC) Related Work Object-centric Models for ARC Grids MDL-based Model Learning Evaluation Conclusion and Perspectives, References & Supplementary Materials 7 Conclusion and Perspectives We have presented a novel and general approach to efficiently learn skills at tasks that consist in generating structured outputs as a function of structured inputs. Following Chollet’s measure of intelligence, efficiently learning here means limited knowledge prior for the target scope of tasks, only a few examples per task, and low computational resources. Our approach is based on descriptive task models that combine object-centric patterns and computations, and on the MDL principle for guiding the search for models. We have detailed an application to ARC tasks on colored grids, and sketched an application to FlashFill tasks on strings. We have shown promising results, especially in terms of efficiency, model complexity, and model naturalness. Going further on ARC will require a substantial design effort as our current models cover so far a small subset of the knowledge priors that are required by ARC tasks (e.g., goal-directedness). For FlashFill tasks, the addition of a counterpart for loops and common functions is expected to suffice to match the state-of-the-art. References 1. Acquaviva, S., Pu, Y., Kryven, M., Sechopoulos, T., Wong, C., Ecanow, G., Nye, M., Tessler, M., Tenenbaum, J.: Communicating natural programs to humans and machines. Advances in Neural Information Processing Systems 35, 3731–3743 (2022) 2. Ainooson, J., Sanyal, D., Michelson, J.P., Yang, Y., Kunda, M.: An approach for solving tasks on the abstract reasoning corpus. arXiv preprint arXiv:2302.09425 (2023) 3. Alford, S., Gandhi, A., Rangamani, A., Banburski, A., Wang, T., Dandekar, S., Chin, J., Poggio, T.A., Chin, S.P.: Neural-guided, bidirectional program search for abstraction and reasoning. CoRR abs/2110.11536 (2021), https://arxiv.org/abs/2110.11536 4. Chollet, F.: On the measure of intelligence. arXiv preprint arXiv:1911.01547 (2019) 5. Chollet, F.: A definition of intelligence for the real world. Journal of Artificial General Intelligence 11(2), 27–30 (2020) 6. Devlin, J., Chang, M., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. In: Conf. North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT. pp. 4171– 4186. Assoc. Computational Linguistics (2019). https://doi.org/10.18653/v1/n19-1423 7. Elias, P.: Universal codeword sets and representations of the integers. IEEE Trans. Information Theory 21(2), 194–203 (1975) 8. Ellis, K., et al.: Dreamcoder: Bootstrapping inductive program synthesis with wake-sleep library learning. In: ACM Int. Conf. Programming Language Design and Implementation. pp. 835–850 (2021) 9. Faas, M., Leeuwen, M.v.: Vouw: geometric pattern mining using the MDL principle. In: Int. Symp. Intelligent Data Analysis. pp. 158–170. Springer (2020) 10. Fischer, R., Jakobs, M., Mucke, S., Morik, K.: Solving Abstract Reasoning Tasks with Gram- ¨ matical Evolution. In: LWDA. pp. 6–10. CEUR-WS 2738 (2020) 11. Goertzel, B.: Artificial general intelligence: concept, state of the art, and future prospects. Journal of Artificial General Intelligence 5(1), 1 (2014) 12. Grunwald, P., Roos, T.: Minimum description length revisited. International journal of math- ¨ ematics for industry 11(01) (2019) 13. Gulwani, S.: Automating string processing in spreadsheets using input-output examples. In: Symp. Principles of Programming Languages. pp. 317–330. ACM (2011) 14. Johnson, A., Vong, W.K., Lake, B., Gureckis, T.: Fast and flexible: Human program induction in abstract reasoning tasks. arXiv preprint arXiv:2103.05823 (2021) 15. Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. Advances in neural information processing systems 25, 1097–1105 (2012) 16. Lake, B.M., Salakhutdinov, R., Tenenbaum, J.B.: Human-level concept learning through probabilistic program induction. Science 350(6266), 1332–1338 (2015) 17. Lieberman, H.: Your Wish is My Command. The Morgan Kaufmann series in interactive technologies, Morgan Kaufmann / Elsevier (2001). https://doi.org/10.1016/b978-1-55860- 688-3.x5000-3 18. Menon, A., Tamuz, O., Gulwani, S., Lampson, B., Kalai, A.: A machine learning framework for programming by example. In: Int. Conf. Machine Learning. pp. 187–195. PMLR (2013) 19. Muggleton, S., Raedt, L.D.: Inductive logic programming: Theory and methods. Journal of Logic Programming 19,20, 629–679 (1994) 20. Rissanen, J.: Modeling by shortest data description. Automatica 14(5), 465–471 (1978) 21. Silver, D., Huang, A., Maddison, C.J., Guez, A., Sifre, L., Van Den Driessche, G., Schrittwieser, J., Antonoglou, I., Panneershelvam, V., Lanctot, M., et al.: Mastering the game of Go with deep neural networks and tree search. Nature 529(7587), 484–489 (2016) 22. Vreeken, J., Van Leeuwen, M., Siebes, A.: Krimp: mining itemsets that compress. Data Mining and Knowledge Discovery 23(1), 169–214 (2011) 23. Xu, Y., Khalil, E.B., Sanner, S.: Graphs, constraints, and search for the abstraction and reasoning corpus. arXiv preprint arXiv:2210.09880 (2022) Supplementary Materials We here describe the contents of the supplementary file accompanying the paper. A public repository of the source code is also available at https://github.com/sebferre/ ARC-MDL for ARC and at https://github.com/sebferre/ARC-MDL-strings for FlashFill. There are two main directories: one for ARC tasks and another for FlashFill tasks. Task Sets The public task sets of ARC are available online at https://github.com/fchollet/ARC. There are two task sets: training tasks and evaluation tasks, each containing 400 tasks. The task set of FlashFill is made of the 14 examples in [13]. We provide them as JSON files in FlashFill/taskset/, using the same format as ARC tasks, except that strings and arrays of strings are used instead of colored grids. For convenience, we also provide the file FlashFill/taskset/all examples.json to allow for browsing all examples in one file. Results We provide the learning and prediction logs for each task set: – ARC/training tasks.log – ARC/evaluation tasks.log – FlashFill/tasks.log Each log file starts with the hyperparameter values, and ends with global statistical measures. For each task, it gives: – the detailed DL (description length) of the initial model; – the learning trace (including the pruning phase) as a sequence of refinements, and showing the decrease of the normalized DL; – the learned models before and after pruning and their detailed DL; – the best joint description for each training example, except for ARC evaluation tasks so as not to leak their contents to the AI developer (a recommendation made by F. Chollet); – the prediction for each training and test example; – and finally a few measures for the task. The measures given for each task and at the end are the following: – runtime-learning: learning time in seconds (including the pruning phase); – bits-train-error: the remaining error commited on output training grids, in bits; – acc-train-micro: the proportion of training output grids that are correctly predicted; – acc-train-macro: 1 if all training output grids are correctly predicted, 0 otherwise; – acc-train-mrr: Mean Reciprocal Rank (MRR) of correct predictions for training output grids, 1 if all first predictions are correct; – acc-test-micro: the proportion of test output grids that are correctly predicted; – acc-test-macro: 1 if all test output grids are correctly predicted, 0 otherwise; – acc-test-mrr: Mean Reciprocal Rank (MRR) of correct predictions for test output grids, 1 if all first predictions are correct. The reference measure in ARC is acc-test-macro. The micro measures provide a more fine-grained and more optimistic measure of success. For convenience, we also provide in ARC/solved tasks a picture for each of the 96 training ARC tasks that are solved by our approach. We kindly invite the reader to browse them to get a quick idea of the diversity of the tasks that our approach can solve. The pictures are screenshots from the UI provided along with ARC tasks. This paper is available on Arxiv under CC 4.0 license. This paper is available on arxiv under CC 4.0 license. Authors: (1) Sebastien Ferr ´e, Univ Rennes, CNRS, Inria, IRISA Campus de Beaulieu, 35042 Rennes, France and ferre@irisa.fr. This paper is available on arxiv under CC 4.0 license. Authors: Authors: (1) Sebastien Ferr ´e, Univ Rennes, CNRS, Inria, IRISA Campus de Beaulieu, 35042 Rennes, France and ferre@irisa.fr. Table of Links Abstract & Introduction Abstract & Introduction Abstraction and Reasoning Corpus (ARC) Abstraction and Reasoning Corpus (ARC) Related Work Related Work Object-centric Models for ARC Grids Object-centric Models for ARC Grids MDL-based Model Learning MDL-based Model Learning Evaluation Evaluation Conclusion and Perspectives, References & Supplementary Materials Conclusion and Perspectives, References & Supplementary Materials 7 Conclusion and Perspectives We have presented a novel and general approach to efficiently learn skills at tasks that consist in generating structured outputs as a function of structured inputs. Following Chollet’s measure of intelligence, efficiently learning here means limited knowledge prior for the target scope of tasks, only a few examples per task, and low computational resources. Our approach is based on descriptive task models that combine object-centric patterns and computations, and on the MDL principle for guiding the search for models. We have detailed an application to ARC tasks on colored grids, and sketched an application to FlashFill tasks on strings. We have shown promising results, especially in terms of efficiency, model complexity, and model naturalness. Going further on ARC will require a substantial design effort as our current models cover so far a small subset of the knowledge priors that are required by ARC tasks (e.g., goal-directedness). For FlashFill tasks, the addition of a counterpart for loops and common functions is expected to suffice to match the state-of-the-art. References 1. Acquaviva, S., Pu, Y., Kryven, M., Sechopoulos, T., Wong, C., Ecanow, G., Nye, M., Tessler, M., Tenenbaum, J.: Communicating natural programs to humans and machines. Advances in Neural Information Processing Systems 35, 3731–3743 (2022) 2. Ainooson, J., Sanyal, D., Michelson, J.P., Yang, Y., Kunda, M.: An approach for solving tasks on the abstract reasoning corpus. arXiv preprint arXiv:2302.09425 (2023) 3. Alford, S., Gandhi, A., Rangamani, A., Banburski, A., Wang, T., Dandekar, S., Chin, J., Poggio, T.A., Chin, S.P.: Neural-guided, bidirectional program search for abstraction and reasoning. CoRR abs/2110.11536 (2021), https://arxiv.org/abs/2110.11536 4. Chollet, F.: On the measure of intelligence. arXiv preprint arXiv:1911.01547 (2019) 5. Chollet, F.: A definition of intelligence for the real world. Journal of Artificial General Intelligence 11(2), 27–30 (2020) 6. Devlin, J., Chang, M., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. In: Conf. North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT. pp. 4171– 4186. Assoc. Computational Linguistics (2019). https://doi.org/10.18653/v1/n19-1423 7. Elias, P.: Universal codeword sets and representations of the integers. IEEE Trans. Information Theory 21(2), 194–203 (1975) 8. Ellis, K., et al.: Dreamcoder: Bootstrapping inductive program synthesis with wake-sleep library learning. In: ACM Int. Conf. Programming Language Design and Implementation. pp. 835–850 (2021) 9. Faas, M., Leeuwen, M.v.: Vouw: geometric pattern mining using the MDL principle. In: Int. Symp. Intelligent Data Analysis. pp. 158–170. Springer (2020) 10. Fischer, R., Jakobs, M., Mucke, S., Morik, K.: Solving Abstract Reasoning Tasks with Gram- ¨ matical Evolution. In: LWDA. pp. 6–10. CEUR-WS 2738 (2020) 11. Goertzel, B.: Artificial general intelligence: concept, state of the art, and future prospects. Journal of Artificial General Intelligence 5(1), 1 (2014) 12. Grunwald, P., Roos, T.: Minimum description length revisited. International journal of math- ¨ ematics for industry 11(01) (2019) 13. Gulwani, S.: Automating string processing in spreadsheets using input-output examples. In: Symp. Principles of Programming Languages. pp. 317–330. ACM (2011) 14. Johnson, A., Vong, W.K., Lake, B., Gureckis, T.: Fast and flexible: Human program induction in abstract reasoning tasks. arXiv preprint arXiv:2103.05823 (2021) 15. Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. Advances in neural information processing systems 25, 1097–1105 (2012) 16. Lake, B.M., Salakhutdinov, R., Tenenbaum, J.B.: Human-level concept learning through probabilistic program induction. Science 350(6266), 1332–1338 (2015) 17. Lieberman, H.: Your Wish is My Command. The Morgan Kaufmann series in interactive technologies, Morgan Kaufmann / Elsevier (2001). https://doi.org/10.1016/b978-1-55860- 688-3.x5000-3 18. Menon, A., Tamuz, O., Gulwani, S., Lampson, B., Kalai, A.: A machine learning framework for programming by example. In: Int. Conf. Machine Learning. pp. 187–195. PMLR (2013) 19. Muggleton, S., Raedt, L.D.: Inductive logic programming: Theory and methods. Journal of Logic Programming 19,20, 629–679 (1994) 20. Rissanen, J.: Modeling by shortest data description. Automatica 14(5), 465–471 (1978) 21. Silver, D., Huang, A., Maddison, C.J., Guez, A., Sifre, L., Van Den Driessche, G., Schrittwieser, J., Antonoglou, I., Panneershelvam, V., Lanctot, M., et al.: Mastering the game of Go with deep neural networks and tree search. Nature 529(7587), 484–489 (2016) 22. Vreeken, J., Van Leeuwen, M., Siebes, A.: Krimp: mining itemsets that compress. Data Mining and Knowledge Discovery 23(1), 169–214 (2011) 23. Xu, Y., Khalil, E.B., Sanner, S.: Graphs, constraints, and search for the abstraction and reasoning corpus. arXiv preprint arXiv:2210.09880 (2022) Supplementary Materials We here describe the contents of the supplementary file accompanying the paper. A public repository of the source code is also available at https://github.com/sebferre/ ARC-MDL for ARC and at https://github.com/sebferre/ARC-MDL-strings for FlashFill. There are two main directories: one for ARC tasks and another for FlashFill tasks. Task Sets The public task sets of ARC are available online at https://github.com/fchollet/ARC. There are two task sets: training tasks and evaluation tasks, each containing 400 tasks. The task set of FlashFill is made of the 14 examples in [13]. We provide them as JSON files in FlashFill/taskset/, using the same format as ARC tasks, except that strings and arrays of strings are used instead of colored grids. For convenience, we also provide the file FlashFill/taskset/all examples.json to allow for browsing all examples in one file. Results We provide the learning and prediction logs for each task set: – ARC/training tasks.log – ARC/evaluation tasks.log – FlashFill/tasks.log Each log file starts with the hyperparameter values, and ends with global statistical measures. For each task, it gives: – the detailed DL (description length) of the initial model; – the learning trace (including the pruning phase) as a sequence of refinements, and showing the decrease of the normalized DL; – the learned models before and after pruning and their detailed DL; – the best joint description for each training example, except for ARC evaluation tasks so as not to leak their contents to the AI developer (a recommendation made by F. Chollet); – the prediction for each training and test example; – and finally a few measures for the task. The measures given for each task and at the end are the following: – runtime-learning: learning time in seconds (including the pruning phase); – bits-train-error: the remaining error commited on output training grids, in bits; – acc-train-micro: the proportion of training output grids that are correctly predicted; – acc-train-macro: 1 if all training output grids are correctly predicted, 0 otherwise; – acc-train-mrr: Mean Reciprocal Rank (MRR) of correct predictions for training output grids, 1 if all first predictions are correct; – acc-test-micro: the proportion of test output grids that are correctly predicted; – acc-test-macro: 1 if all test output grids are correctly predicted, 0 otherwise; – acc-test-mrr: Mean Reciprocal Rank (MRR) of correct predictions for test output grids, 1 if all first predictions are correct. The reference measure in ARC is acc-test-macro. The micro measures provide a more fine-grained and more optimistic measure of success. For convenience, we also provide in ARC/solved tasks a picture for each of the 96 training ARC tasks that are solved by our approach. We kindly invite the reader to browse them to get a quick idea of the diversity of the tasks that our approach can solve. The pictures are screenshots from the UI provided along with ARC tasks. This paper is available on Arxiv under CC 4.0 license. Arxiv

Conclusion and Perspectives, References & Supplementary Materials: Our Journey With ARC

Evaluation Our Approach on ARC and Beyond: A Look Back at Our Experiments

MDL-based Model Learning: How It Works

Object-Centric Models for ARC Grids: A Deeper Look

deployments come in all shapes and sizes. We support bare metal installs on any version of , containerized installs on any version of (including Red Hat OpenShift), and installs just about anywhere you can deploy a small lightweight single binary. But with flexibility comes the inevitability that edge case issues will require debugging. MinIO Linux Kubernetes In this blog post, we’ll show you how to debug a MinIO install running in Kubernetes and also some of the common issues you might encounter when doing bare metal installation and how to rectify them. Kubernetes Debugger Pod There are a few ways to access the MinIO API running inside a Kubernetes cluster. We can use or set up a listening on to be able to access the API. Both of these methods offer a way to access the service from outside the network, but they do come with one major downside: You can only access the Service that the NodePort or Port Forwarding references on an available port (not the usual configuration for the application). For example, you have to access the MinIO API, usually found on port , via a randomly assigned port. kubectl port-forwarding Service NodePort 9000 3xxxx What if I told you there was a better way – and it's not novel? When debugging applications you want to have full access to the native run-time environment so you can use various tools to troubleshoot and debug the cluster. One way to do that is launching a “busybox” style pod and installing all the required tools needed to debug the application. First launch a into the same namespace as your MinIO install. In order to do this create a yaml file called with the following yaml. Pod debugger-pod.yaml apiVersion: v1

kind: Pod

metadata:

  name: mc

  labels:

    app: mc

spec:

  containers:

  - image: minio/mc:latest

    command:

      - "sleep"

      - "604800"

    imagePullPolicy: IfNotPresent

    name: mc

  restartPolicy: Always The above Pod configuration is pulling the image for MinIO utility. In order to ensure the pod doesn’t just launch and then exit, we’ve added a command. mc sleep Once the yaml is saved apply the configuration to the Kubernetes namespace where the MinIO cluster is running kubectl apply -f debugger-pod.yaml Once the pod is up and running access it via shell $ kubectl exec -i -t -n default mc -c mc -- sh -c "(bash || ash || sh)"

[root@mc /]# Then with you can access the MinIO cluster mc [root@mc /]# mc alias set myminio    --insecure

Added `myminio` successfully. Now that we have a debugger pod up and running, you can perform action on the cluster directly within the same network. For example, if the replication was broken due to an site going offline or a hardware failure, you can resync any pending objects to be replicated using the following command [root@mc /]# mc admin replicate resync start minio1 minio2


[root@mc /]# mc admin replicate resync status minio1 minio2


✔ ✔ ✔

ResyncID: 		 2248d1d1-633f-4d61-b938-d8ea0b9b2d31

Status:   		 Completed

Objects:  		 2225

Versions: 		 2225

FailedObjects:     0

Throughput:   	 5.3 MiB/s

IOPs:     		 124.23 objs/s

Transferred:  	 94 MiB

Elapsed:  		 17.909833202s

CurrObjName:  	 testbucket/web-app/tsconfig.json Another reason you would run the debugger pod is if there are some file system permissions or invalid groups configurations in your pod, you can update them using the debugger pod [root@mc /]# chgrp -R 1000780050 .minio.sys/ The above debugging method can also be used in bare metal environments. For instance you can launch a busybox or bastion node with installed and follow the same instructions as above. mc Debugging Bare Metal Bare metal Linux installs are the most straightforward. In fact it just takes a few commands to get MinIO installed and running with SystemD. For details, please see . Configuring MinIO with SystemD Once in a great while, bare metal installs go awry. Here are some of the (not-so-common) pitfalls that we are asked about  in or . These pitfalls are not hardware or operating specific but can be useful to know in any kind of environment. SUBNET Slack File Permission One of the most common pitfalls is the file permissions of the MinIO binary and the configuration file. If this occurs, when you start MinIO using SystemD you will see and here is the full stack trace Assertion failed for MinIO. # systemctl status minio.service

● minio.service - MinIO

     Loaded: loaded (/etc/systemd/system/minio.service; enabled; vendor preset: enabled)

     Active: inactive (dead)

     Assert: start assertion failed at Tue 2023-12-26 18:21:38 PST; 8s ago

             AssertFileIsExecutable=/usr/local/bin/minio was not met

       Docs: https://docs.min.io


Dec 26 18:13:37 minio1 systemd[1]: minio.service: Starting requested but asserts failed.

Dec 26 18:17:50 minio1 systemd[1]: Assertion failed for MinIO.

Dec 26 18:21:38 minio1 systemd[1]: minio.service: Starting requested but asserts failed.

Dec 26 18:21:38 minio1 systemd[1]: Assertion failed for MinIO. This could be caused by a number of reasons, let's go down the list and check for each of them. : The binary, in this example located at needs to have permission for user and group, respectively. MinIO Binary /usr/local/bin/minio root:root # ll /usr/local/bin/minio

total 93804

-rwxr-xr-x 1 root    root    96018432 Nov 15 16:35  minio* : The MinIO service needs to run under a unique Linux user and group for security purposes, never run as a user. By default we use for the user and group names. In the SystemD service config file you should see something like this MinIO Service User and Group root minio-user User=minio-user

Group=minio-user : The directory where MinIO data will be stored needs to be owned by or whichever user you decide to run the MinIO service as above. MinIO Data Dir minio-user:minio-user # ls -l /mnt

total 4

drwxrwxr-x 2 minio-user minio-user 4096 Dec 27 09:58 data : Both the config files should have permissions for user and group like so SystemD and MinIO config root:root # ls -l /etc/default/minio

-rw-r--r-- 1 root root 1330 Dec 27 09:52 /etc/default/minio


# ls -l /etc/systemd/system/minio.service

-rw-r--r-- 1 root root 941 Dec 26 17:13 /etc/systemd/system/minio.service : The entire install process should be run as . You can also try if your user has permissions but the recommendation is to run as root as the install needs to place files in a bunch of places that only the user can access. Your bash prompt should have a and not a like so Run as Root root sudo root # $ vs # $ If none of the above work, the best approach is to remove the app, directories and configs and start a fresh install as a root user. Port conflict Another common issue related to deleted files which still hold on to the process, which causes port conflicts. Even when a service is not running, you may be unable to start a new service on the existing port or the service that is running will misbehave (such as not allowing you to login). # lsof -n | grep (deleted)

COMMAND PID USER FD TYPE DEVICE   SIZE 	NODE NAME

nginx   	13423 root 5u  	REG 253,3   42949672960 	17 (deleted)

minio 	13423 minio 6u    REG 253,3 	0         	      18 (deleted)

minio       13423 minio 7u    REG 253,3 	0         	      19 (deleted) You might see errors such as those below on a MinIO install Login Failed net::ERR_FAILED 500 Internal Server Error 401 Unauthorized The screenshot above shows an internal server error and an unauthorized error. While looking at the surface it looks unclear what has caused this error, we can debug with a little linux knowledge what to look for that could cause this, let's take a gander. There are several ways to debug this issue, first lets check to see if multiple MinIO processes are running on the same node # ps aux | grep -i minio

minio-u+    5048  0.3  1.7 1594008 144384 ?      Ssl  11:03   0:01 /usr/local/bin/minio server --console-address :9001 /mnt/data/disk1/minio


minio-u+    9276  0.3  1.7 1594208 144301 ?      Ssl  11:25   0:01 /usr/local/bin/minio server --console-address :9001 /mnt/data/disk1/minio As we can see above there are 2 MinIO processes running. Start by killing the process that is older or has been running the longest, in this case it seems to be the process ID . 5048 kill -9 5048 Sometimes even after killing the process the service might still not start or might still get hung up because it has reserved a process number but not let it go. This can be caused by files that have been deleted but are still being tracked by the operating system. You can find the deleted files via LSOF lsof -n | grep '(deleted)' Last but not least, if there are no deleted files left over or hung processes and if everything looks absolutely clean, the last resort is to quickly restart the node. This is a no-nonsense method that  shuts down and clears any pending files and processes so you start a fresh install. SUBNET to the rescue Although rare, installation edge cases will always exist. MinIO customers know that they have nothing to worry about because they can quickly message our engineers – who have written the code – via the portal. We've seen almost everything under the sun, so while the issue might look cryptic or mind boggling at first glance, we'll put our years of expertise debugging installations in many varied environments to work and help you in a jiffy. SUBNET If you have any questions on troubleshooting and debugging installs be sure to reach out to us on ! MinIO Slack

Pro Tips for Debugging MinIO: Overcoming Common Issues in Kubernetes and Bare Metal Environments

MinIO ডিবাগ করার জন্য প্রো টিপস: কুবারনেটস এবং বেয়ার মেটাল পরিবেশে সাধারণ সমস্যাগুলি অতিক্রম করা

Profi-Tipps zum Debuggen von MinIO: Überwindung häufiger Probleme in Kubernetes- und Bare-Metal-Umgebungen

Consejos profesionales para depurar MinIO: superar problemas comunes en Kubernetes y entornos bare metal

Conseils de pro pour déboguer MinIO : surmonter les problèmes courants dans les environnements Kubernetes et Bare Metal

मिनियो डिबगिंग के लिए प्रो टिप्स: कुबेरनेट्स और बेयर मेटल वातावरण में आम समस्याओं पर काबू पाना

MinIO デバッグのプロのヒント: Kubernetes とベアメタル環境での一般的な問題の克服

MinIO 디버깅을 위한 전문가 팁: Kubernetes 및 베어메탈 환경의 일반적인 문제 극복

Dicas profissionais para depuração do MinIO: superando problemas comuns em ambientes Kubernetes e Bare Metal

Советы для профессионалов по отладке MinIO: решение распространенных проблем в Kubernetes и средах с голым железом

MinIO'da Hata Ayıklamaya Yönelik Profesyonel İpuçları: Kubernetes ve Bare Metal Ortamlarında Yaygın Sorunların Aşılması

Mẹo chuyên nghiệp để gỡ lỗi MinIO: Khắc phục các sự cố thường gặp trong môi trường Kubernetes và Bare Metal

调试 MinIO 的专业技巧：解决 Kubernetes 和裸机环境中的常见问题

How to Keep Your Fonts in Embedded SVG

In this article, we will create a web application using the latest version of Angular, generate a Docker image, and then execute this image within a Docker container. Prerequisites Before you start, you need to install and configure the tools below to create the Angular application and the Docker image. : Git is a distributed version control system and it will be used to sync the repository. git : Node.js is a JavaScript code runtime software based on Google's V8 engine. npm is a package manager for Node.js (Node.js Package Manager). They will be used to build and run the Angular application and install the libraries. Node.js and npm : Angular CLI is a command line utility tool for Angular and it will be used to create the base structure of the Angular application. Angular CLI Docker Engine: Docker Engine is a command line utility tool for Docker and it will be used to create and run containers. IDE (e.g. or ): IDE (Integrated Development Environment) is a tool with a graphical interface to help in the development of applications and it will be used to develop the Angular application. Visual Studio Code WebStorm Getting started Create the Angular application is a development platform for building WEB, mobile and desktop applications using HTML, CSS and TypeScript (JavaScript). Currently, Angular is at version 17 and Google is the main maintainer of the project. Angular Let's create the application with the Angular base structure using the with the server-side rendering (SSR) disabled, the route file and the SCSS style format. 1. @angular/cli g new angular-docker --ssr false --routing true --style scss
CREATE angular-docker/README.md (1067 bytes)
CREATE angular-docker/.editorconfig (274 bytes)
CREATE angular-docker/.gitignore (548 bytes)
CREATE angular-docker/angular.json (2806 bytes)
CREATE angular-docker/package.json (1045 bytes)
CREATE angular-docker/tsconfig.json (903 bytes)
CREATE angular-docker/tsconfig.app.json (263 bytes)
CREATE angular-docker/tsconfig.spec.json (273 bytes)
CREATE angular-docker/.vscode/extensions.json (130 bytes)
CREATE angular-docker/.vscode/launch.json (470 bytes)
CREATE angular-docker/.vscode/tasks.json (938 bytes)
CREATE angular-docker/src/main.ts (250 bytes)
CREATE angular-docker/src/favicon.ico (15086 bytes)
CREATE angular-docker/src/index.html (299 bytes)
CREATE angular-docker/src/styles.scss (80 bytes)
CREATE angular-docker/src/app/app.component.scss (0 bytes)
CREATE angular-docker/src/app/app.component.html (20884 bytes)
CREATE angular-docker/src/app/app.component.spec.ts (940 bytes)
CREATE angular-docker/src/app/app.component.ts (373 bytes)
CREATE angular-docker/src/app/app.config.ts (227 bytes)
CREATE angular-docker/src/app/app.routes.ts (77 bytes)
CREATE angular-docker/src/assets/.gitkeep (0 bytes)
✔ Packages installed successfully.
    Successfully initialized git. Now we will run the application with the command below. 2. npm start

> angular-docker@0.0.0 start
> ng serve


Initial Chunk Files | Names         |  Raw Size
polyfills.js        | polyfills     |  82.71 kB | 
main.js             | main          |  23.23 kB | 
styles.css          | styles        |  96 bytes | 

                    | Initial Total | 106.03 kB

Application bundle generation complete. [1.504 seconds]
Watch mode enabled. Watching for file changes...
  ➜  Local:   http://localhost:4200/ Ready! Next, we will access the URL and check if the application is working. 3. http://localhost:4200/ Create the Docker image is a software that allows developers to create and run container applications. Docker Let's create the file with the Docker image configuration in the root directory of the Angular application. 1. Dockerfile touch Dockerfile Now we will configure the Dockerfile file with the content below. 2. FROM node:alpine

WORKDIR /usr/src/app

COPY . /usr/src/app

RUN npm install -g @angular/cli

RUN npm install

CMD ["ng", "serve", "--host", "0.0.0.0"] Notes: The setting defines the base Docker image. FROM node:alpine The setting defines the default application directory. The defined directory is created if it does not exist. WORKDIR /usr/src/app The setting copies the local application files and directories to the defined directory. COPY . /usr/src/app The setting installs the global command line dependency for Angular. npm install -g @angular/cli The setting installs the Angular application dependencies. RUN npm install The setting creates and runs the Angular application for external access. CMD ["ng", "serve", "--host", "0.0.0.0"] Next, we will create the image with with the command below. 3. docker build -t angular-docker . After create the image, we will check if the image was created with the command below. 4. docker images
REPOSITORY       TAG      IMAGE ID       CREATED          SIZE
angular-docker   latest   73bfa0093a57   10 seconds ago   463MB Ready! The Docker image with ID and 463MB was created. 5. 73bfa0093a57 Run the Docker container Let's run the Docker container using the image created of the Angular application with the command below. 1. docker run -p 4201:4200 angular-docker Now we will check if the container is running with the command below. 2. docker ps
CONTAINER ID   IMAGE            COMMAND                  CREATED         STATUS         PORTS                                       NAMES
b9f106cbdcca   angular-docker   "docker-entrypoint.s…"   5 seconds ago   Up 4 seconds   0.0.0.0:4201->4200/tcp, :::4201->4200/tcp   eloquent_elgamal Ready! Next, we will access the URL and check if the application is working inside the Docker container. 3. http://localhost:4201/ The application repository is available at . https://github.com/rodrigokamada/angular-docker Conclusion Summarizing what was covered in this article: We create an Angular application. We create a Docker image. We run a Docker container. We tested the Angular application inside the Docker container. You can use this article to create a Docker container with an Angular application image. Thank you for reading and I hope you enjoyed the article! This tutorial was posted on my in portuguese. blog To stay updated whenever I post new articles, follow me on and . Twitter LinkedIn

Creating and Running an Angular Application in a Docker Container

Vectors and vector search are key components of large language models (LLMs), but they are useful in a host of other applications across many use cases that you might not have considered. How about the most efficient way to deliver retail goods? In two prior articles in this series, I told a story of a hypothetical contractor who was hired to help implement AI/ML solutions at a big-box retailer and then explored how this distributed systems and AI specialist used vector search to drive results with customer promotions at the company. Now, I’ll walk you through how this contractor uses vector search to optimize trucking routes. The problem While we were looking at our options for scaling-down (and ultimately disabling) the recommendation batch job from the first story in this series, we were invited to a meeting with the Transportation Services team. They had heard how we assisted the Promotions team and were wondering if we could take a look at a problem of theirs. BigBoxCo has its products trucked in from airports and shipping ports. Once at the distribution center (DC), they are tagged and separated into smaller shipments for the individual brick-and-mortar stores. While we have our own semi trailers for this part of the product journey, the fleet isn’t efficiently organized. Currently, the drivers are given a list of stores on the truck’s digital device, and the supervisor suggests a route. However, the drivers often balk about the order of store stops, and they often disregard their supervisors’ route suggestions. This, of course, leads to variances in expected shipment and restock times, as well as in total time taken. Knowing this, the DC staff is unable to fill each truck container completely, because they have to leave space in the truck for access to the product pallets for each store. Ideally, the product pallets would be ordered with the first store's pallet in the most accessible position in the trailer. Improving the experience The Transportation Services team would like us to examine the available data and see if there is a smarter way to approach this problem. For instance, what if there was a way that we could pre-determine the best possible route to take by determining the order in which the driver should visit the stores? This is similar to the “traveling salesman problem” (TSP), a hypothetical problem in which a salesman is given a list of cities to visit, and needs to figure out the most efficient route between them. While coded implementations of the TSP can become quite complex, we might be able to use a vector database like Apache Cassandra’s for vector search capability to solve this. The obvious approach is to plot out each of the geolocation coordinates of each destination city.  However, the cities are only spread out over a local, metropolitan area, which means that latitude and longitude whole numbers would be mostly the same. That isn’t going to lead to a lot of easily detectable variance, so we should refocus that data by just considering the numbers to the right of the Geo URI scheme decimal point. For example, the city of Rogersville (the location of one of our BigBoxCo stores) has a Geo URI of 45.200,-93.567. We’ll be able to detect variance from this and other vectors more easily if we look to the right of each decimal point of our coordinates, arriving at adjusted coordinates of 200,-567 (instead of 45.200,-93.567). Taking this approach with the local metro cities with our stores gives us the following data: Implementation Now that we have data, we can create a table in our Cassandra cluster with a two-dimensional vector. We will also need to create a SSTable attached secondary index (SASI) on the vector column: CREATE TABLE bigbox.location_vectors (
  location_id text PRIMARY KEY,
  location_name text,
  location_vector vector<float, 2>);
CREATE CUSTOM INDEX ON bigbox.location_vectors (location_vector) 
USING 'StorageAttachedIndex'; This will enable us to use a vector search to determine the order in which to visit each city. It’s important to note, however, that vector searches are based on cosine-based calculations for distance, assuming that the points are on a flat plane. As we know, the Earth is not a flat plane.  Calculating distances over a large geographic area should be done using another approach like the , which takes the characteristics of a sphere into account. But for our purposes in a small, local metro area, computing an approximate nearest neighbor (ANN) should work just fine. Haversine formula Now let us load our city vectors into the table, and we should be able to query it: INSERT INTO bigbox.location_vectors (location_id, location_name,
location_vector) VALUES ('B1643','Farley',[86, -263]);
INSERT INTO bigbox.location_vectors (location_id, location_name,
location_vector) VALUES (B9787,'Zarconia',[37, -359]);
INSERT INTO bigbox.location_vectors (location_id, location_name,
location_vector) VALUES (B2346,'Parktown',[-52, -348]);
INSERT INTO bigbox.location_vectors (location_id, location_name,
location_vector) VALUES ('B1643','Victoriaville',[94, -356]);
INSERT INTO bigbox.location_vectors (location_id, location_name,
location_vector) VALUES ('B6789','Rockton',[11, -456]);
INSERT INTO bigbox.location_vectors (location_id, location_name,
location_vector) VALUES ('B2345','Maplewood',[73, -456]);
INSERT INTO bigbox.location_vectors (location_id, location_name,
location_vector) VALUES ('B5243','Rogersville',[200, -567]); To begin a route, we will first consider the warehouse distribution center in Farley, which we have stored with a vector of 86, -263.  We can begin by querying the ` ` table for the ANNs of Farley’s vector: location_vectors SELECT location_id, location_name, location_vector,
similarity_cosine(location_vector,[86, -263]) AS similarity
FROM location_vectors
ORDER BY location_vector
ANN OF [86, -263] LIMIT 7; The results of the query look like this: location_id | location_name | location_vector | similarity 
-------------+---------------+-----------------+------------
       B1643 |        Farley |      [86, -263] |          1 
       B5243 |   Rogersville |     [200, -567] |   0.999867
       B1566 | Victoriaville |      [94, -356] |   0.999163 
       B2345 |     Maplewood |      [73, -456] |   0.993827 
       B9787 |      Zarconia |      [37, -359] |   0.988665
       B6789 |       Rockton |      [11, -456] |   0.978847
       B2346 |      Parktown |     [-52, -348] |   0.947053

(7 rows) Note that we have also included the results of the ` ’ function, so that the similarity of the ANN results is visible to us. As we can see, after disregarding Farley at the top (100% match for our starting point), the city of Rogersville is coming back as the approximate nearest neighbor. similarity_cosine Next, let’s build a microservice endpoint that essentially traverses the cities based on a starting point and the top ANN returned. It will also need to disregard cities that it’s already been to.  Therefore, we build a method that we can POST to, so that we can provide the ID of the starting city, as well as the list of cities for the proposed route in the body of the request: curl -s -XPOST http://127.0.0.1:8080/transportsvc/citylist/B1643 \
-d'["Rockton","Parktown","Rogersville","Victoriaville","Maplewood","Za
rconia"]' -H 'Content-Type: application/json' Calling this service with the ` ’ “B1643” (Farley) returns the following output: location_id ["Rogersville","Victoriaville","Maplewood","Zarconia","Rockton","Parktown"] So this works great in the sense that it’s providing some systematic guidance for our trucking routes. However, our service endpoint and (by proxy) our ANN query don’t have an understanding of the highway system that connects each of these cities. For now, it’s simply assuming that our trucks can travel to each city directly “as the crow flies.” Realistically, we know this isn’t the case. In fact, let’s look at a map of our metro area, with each of these cities and connecting highways marked (Figure 1). One way to increase accuracy here would be to create vectors for the segments of the highways. We could create a highway table and generate vectors for each by their starting and ending coordinates based on how they intersect with each other and our cities. CREATE TABLE highway_vectors (
 highway_name TEXT PRIMARY KEY,
 highway_vector vector<float,4>);

CREATE CUSTOM INDEX ON highway_vectors(highway_vector) USING 
'StorageAttachedIndex'; We can then insert vectors for each highway. We will also create entries for both directions of the highway segments so that our ANN query can use either city as the starting or ending points. For example: INSERT INTO highway_vectors(highway_name,highway_vector) 
VALUES('610-E2',[94,-356,86,-263]);
INSERT INTO highway_vectors(highway_name,highway_vector) 
VALUES('610-W2',[86,-263,94,-356]); Going off of the result from our original query, we can run another query to pull back highway vectors with an ANN of the coordinates for the DC in Farley (86,-263) and our store in Rogersville (200,-567): SELECT * FROM highway_vectors
ORDER BY highway_vector
ANN OF [86,-263,200,-567]
LIMIT 4;

 highway_name | highway_vector
--------------+-----------------------
       610-W2 |  [86, -263, 94, -356]
         54NW | [73, -456, 200, -567]
        610-W |  [94, -356, 73, -456]
        81-NW |  [37, -359, 94, -356]

(4 rows) Looking at the map shown in Figure 1, we can see that Farley and Rogersville are connected by highways 610 and 54. Now we’re on to something! We could build another service endpoint to build a highway route from one city to another based on the coordinates of the starting and ending cities. To make this service complete, we would want it to eliminate any “orphan” highways returned (highways that aren’t on our expected route) and include any cities with stores that we may want to stop at on the way. If we used the ` of Farley (B1643) and Rogersville (B5243), we should get an output that looks like this: location_ids ’ curl -s -XGET
http://127.0.0.1:8080/transportsvc/highways/from/B1643/to/B5243 \
-H 'Content-Type: application/json'
{"highways":[
    {"highway_name":"610-W2",
        "Highway_vector":{"values":[86.0,-263.0,94.0,-356.0]}},
    {"highway_name":"54NW",
        "highway_vector":{"values":[73.0,-456.0,200.0,-567.0]}},
    {"highway_name":"610-W",
        "highway_vector":{"values":[94.0,-356.0,73.0,-456.0]}}],
 "citiesOnRoute":["Maplewood","Victoriaville"]} Conclusions and next steps These new transportation services should significantly help our drivers and DC management. They should now be getting mathematically significant results for route determination between stores. A nice side benefit is that DC staff can fill the truck more efficiently.  With access to the route ahead of time, they can load pallets into the truck in a first-in-last-out (LIFO) approach, using more of the available space. While this is a good first step, we could make some future improvements once this initiative is deemed successful. A subscription to a traffic service will help in route planning and augmentation. This would allow a route recalculation based on significant local traffic events on one or more highways. We could also use the n-vector approach for coordinate positioning instead of using the abbreviated latitude and longitudinal coordinates. The advantage here is that our coordinates would already be converted to vectors, likely leading to more accurate nearest-neighbor approximations. Check out this GitHub repository for code for the above-described , and learn more about how . example transportation service endpoints DataStax enables generative AI with vector search By Aaron Ploetz, DataStax

Vector Search Applications: Optimizing Retail Trucking Routes

Aplicaciones de búsqueda de vectores: optimización de rutas de transporte minorista

Applications de recherche de vecteurs : optimisation des itinéraires de camionnage pour le commerce de détail

वेक्टर खोज अनुप्रयोग: खुदरा ट्रकिंग मार्गों का अनुकूलन

ベクトル検索アプリケーション: 小売トラック輸送ルートの最適化

Aplicações de pesquisa vetorial: otimizando rotas de transporte rodoviário de varejo

Ứng dụng tìm kiếm Vector: Tối ưu hóa các tuyến đường vận tải đường bộ bán lẻ

矢量搜索应用：优化零售货运路线

Introducing the Project In my recent mobile application development project with ALX Africa, I created a cutting-edge mobile banking application with a focus on providing users with a secure and convenient way to manage their finances. With a timeline of four months, I worked to deliver a feature-rich and user-friendly app that caters to the needs of my target audience. The project was created for individuals seeking a modern and streamlined approach to banking. I aimed to empower users by giving them access to essential financial services on their mobile devices, eliminating geographical barriers, and enhancing financial inclusivity. By leveraging the power of technology, my goal was to simplify banking processes and provide a seamless user experience. Project Role Definition Project Manager: Ensured smooth coordination and timely delivery of the project. UX/UI Designer: Created an intuitive and visually appealing user interface. Mobile App Developer: Implemented the app's functionality and optimized its performance. Quality Assurance Engineer: Conducted thorough testing to ensure a bug-free user experience. Backend Developer: Built a secure and scalable backend infrastructure. Frontend Developer: Developed a responsive and user-friendly frontend. The Personal Focus As a solo team member, my personal focus was on developing a robust and secure backend infrastructure, ensuring seamless integration with banking systems and . I worked to ensure smooth data flow and a seamless user experience. APIs Accomplishments and Key Design Features Project Result and Architecture I successfully delivered a mobile banking application that enables users to perform various financial transactions, including account management, fund transfers, and bill payments. The architecture diagram below illustrates the flow of data through our application, highlighting the secure connection between the user's device, the app's backend, and the banking systems. Technologies and Development Overview For the , I opted for a native mobile app approach, using for iOS and Kotlin for Android, to provide optimal performance and a native user experience. On the backend, I implemented Python with the Django framework to ensure robust security and seamless integration with banking APIs. The app features secure user authentication, real-time transaction tracking, and personalized financial insights. Here's a detailed technical summary of how a mobile banking app was developed end-to-end using Python for the backend and React for the frontend: frontend Swift 1. Backend Development with Python The backend of the mobile banking app was built using Python and a web framework like Django or Flask. Python's versatility, extensive libraries, and strong community support make it an excellent choice for backend development. The following steps were involved: Setting up a virtual environment to isolate dependencies. Creating models to represent entities such as users, accounts, and transactions using an Object-Relational Mapping (ORM) tool like Django ORM. Implementing RESTful APIs using frameworks like Django Rest Framework or Flask-RESTful to handle HTTP requests for user authentication, account management, transaction processing, and more. Integrating with external services like payment gateways or SMS notification APIs using Python libraries or SDKs. Implementing security measures such as input validation, authentication, and encryption to protect sensitive user information. Writing unit tests to ensure the stability and correctness of the backend code. Code Snippet (Python - Django) from django.db import models class User(models.Model): name = models.CharField(max_length=100) email = models.EmailField(unique=True) password = models.CharField(max_length=255) class Account(models.Model): user = models.ForeignKey(User, on_delete=models.CASCADE) account_number = models.CharField(max_length=20, unique=True) balance = models.DecimalField(max_digits=10, decimal_places=2) . // ... more components and API integration ... 2. Frontend Development with React For the frontend development of the mobile banking app, React was chosen due to its component-based architecture, reusability, and fast rendering capabilities. The following steps were involved: Setting up a React project using tools like Create React App. Designing and developing user interfaces with React components, JSX syntax, and CSS frameworks like Bootstrap or Material-UI. Implementing user authentication flows, forms for data input, and UI components for displaying account details, transaction history, and other relevant information. Consuming backend APIs using libraries like Axios or the built-in fetch API to fetch and send data to the backend. Incorporating state management tools like Redux or React Context for managing application state and handling data flow between components. Implementing client-side form validation and user-friendly error handling to provide a smooth and intuitive user experience. Code Snippet (JavaScript - React) import React, { useState, useEffect } from 'react'; import axios from 'axios'; const TransactionHistory = () => { const [transactions, setTransactions] = useState([]); useEffect(() => {
    axios.get('/api/transactions')
        .then(response => {
            setTransactions(response.data);
        })
        .catch(error => {
            console.error('Error fetching transactions:', error);
        });
}, []);

return (
    <div>
        <h2>Transaction History</h2>
        <ul>
            {transactions.map(transaction => (
                <li key={transaction.id}>
                    {transaction.amount} - {transaction.description}
                </li>
            ))}
        </ul>
    </div>
);

// ... more components and API integration ... Integration and Deployment: Once the backend and frontend were developed, they needed to be integrated and deployed as a cohesive mobile banking app. This involved the following steps: Configuring the backend server to serve the frontend build files and handle API requests from the frontend. Optimizing the app's performance, including bundling and minifying frontend assets for faster loading times. Deploying the backend to a web server using platforms like Heroku, AWS, or GCP. Deploying the frontend to a static file hosting service or utilizing a Content Delivery Network (CDN) for optimal delivery and caching. 4. Testing and Quality Assurance: Throughout the development process, thorough testing and quality assurance were crucial. This included: Writing unit tests for backend API endpoints to ensure proper functionality and error handling. Implementing automated tests for frontend components using tools like Jest and React Testing Library. Conducting manual testing on various devices and browsers to ensure cross-browser compatibility and responsiveness. Performing security assessments and vulnerability testing to identify and fix potential security issues. This end-to-end development process, combining Python for the backend and React for the frontend, enabled the creation of a robust, secure, and user-friendly mobile banking app. Tackling the Toughest Challenge One of the most significant technical challenges I encountered was implementing robust security measures to protect user data and transactions. By utilizing encryption protocols, secure authentication mechanisms, and comprehensive testing, we successfully ensured the privacy and integrity of sensitive information. This required meticulous attention to detail, extensive research, and the collaboration of the entire team. Lessons Learned Throughout this project, I gained valuable insights and experiences that have shaped our technical expertise and professional growth. Some key takeaways include: The criticality of robust security measures in mobile banking applications. The importance of seamless integration with banking systems and APIs. The significance of thorough testing and quality assurance to ensure a bug-free user experience. The value of collaboration and effective communication within a development team. The need for continuous learning and staying updated with the latest industry trends and technologies. About Me As a dedicated engineer, I thrive on challenging projects that push the boundaries of innovation. With a passion for mobile development and a drive to create impactful solutions, I continually seek opportunities to contribute to cutting-edge projects that improve people's lives. I believe in the power of technology to transform industries and make a positive difference in society. Project Github - https://github.com/DukeMavor/bank_app Project Landing Page - https://vicbank-b914bbaff374.herokuapp.com/home My LinkedIn Profile - https://www.linkedin.com/in/victor-awunudo/ The lead image for this article was generated by HackerNoon's AI Image Generator via the prompt "mobile banking application".

Lessons Learned Developing a Mobile Banking Application 

Hello friends, The Oracle DBA occasionally needs to update some of the Oracle Clusterware network configurations. Today let's check how to update the private network part. The Environment Oracle RAC with 2 nodes: ol8-19-rac1 and ol8-19-rac2

Oracle Linux Server release 8.8

Grid Version
34318175;TOMCAT RELEASE UPDATE 19.0.0.0.0 (34318175)
34160635;OCW RELEASE UPDATE 19.16.0.0.0 (34160635)
34139601;ACFS RELEASE UPDATE 19.16.0.0.0 (34139601)
34133642;Database Release Update : 19.16.0.0.220719 (34133642)
33575402;DBWLM RELEASE UPDATE 19.0.0.0.0 (33575402)

DB Version
34086870;OJVM RELEASE UPDATE: 19.16.0.0.220719 (34086870)
34160635;OCW RELEASE UPDATE 19.16.0.0.0 (34160635)
34133642;Database Release Update : 19.16.0.0.220719 (34133642)

When you see <dbenv>, load the DB HOME variables.
When you see <gridenv>, load the GRID HOME variables.

IPs
# Public
192.168.56.161  ol8-19-rac1.localdomain  ol8-19-rac1
192.168.56.162  ol8-19-rac2.localdomain  ol8-19-rac2

# Virtual
192.168.56.163  ol8-19-rac1-vip.localdomain    ol8-19-rac1-vip
192.168.56.164  ol8-19-rac2-vip.localdomain    ol8-19-rac2-vip

# Private
10.1.2.161  ol8-19-rac1-priv.localdomain   ol8-19-rac1-priv
10.1.2.162  ol8-19-rac2-priv.localdomain   ol8-19-rac2-priv As the grid user, take a backup of profile.xml on all cluster nodes before proceeding. [oracle@ol8-19-rac1 ~]$ cp -p $ORACLE_HOME/gpnp/`hostname`/profiles/peer/profile.xml $ORACLE_HOME/gpnp/`hostname`/profiles/peer/profile.xml.bkp

[oracle@ol8-19-rac1 ~]$ ll $ORACLE_HOME/gpnp/`hostname`/profiles/peer/profile.xml.bkp

-rw-r--r--. 1 oracle oinstall 2171 May 27 20:09 /u01/app/19.0.0/grid/gpnp/ol8-19-rac1/profiles/peer/profile.xml.bkp Now, let’s check the Oracle CRS networks and the Linux networks. It’s possible to identify that Oracle is using the network as his private one. “eth2 10.1.2.0” [oracle@ol8-19-rac1 ~]$ oifcfg getif
eth1  192.168.56.0  global  public
eth2  10.1.2.0  global  cluster_interconnect,asm

[oracle@ol8-19-rac1 ~]$ ip -c -br a
lo               UNKNOWN        127.0.0.1/8 ::1/128
eth0             UP             10.0.2.15/24 fe80::a00:27ff:fe63:d73f/64
eth1             UP             192.168.56.161/24 192.168.56.163/24 192.168.56.166/24 192.168.56.165/24 fe80::a00:27ff:fe4f:b8aa/64
eth2             UP             10.1.2.161/24 169.254.1.211/19 fe80::a00:27ff:fe01:a7de/64
eth3             UP             10.1.3.161/24 fe80::a00:27ff:fef3:172b/64

[oracle@ol8-19-rac2 ~]$ ip -c -br a
lo               UNKNOWN        127.0.0.1/8 ::1/128
eth0             UP             10.0.2.15/24 fe80::a00:27ff:fe63:d73f/64
eth1             UP             192.168.56.162/24 192.168.56.164/24 192.168.56.167/24 fe80::a00:27ff:fe76:b954/64
eth2             UP             10.1.2.162/24 169.254.26.118/19 fe80::a00:27ff:fe7f:8663/64
eth3             UP             10.1.3.162/24 fe80::a00:27ff:fea8:d7c3/64 Let’s also check the ASM Listener configuration and take note. [oracle@ol8-19-rac1 ~]$ srvctl config listener -asmlistener
Name: ASMNET1LSNR_ASM
Type: ASM Listener
Owner: oracle
Subnet: 10.1.2.0
Home: <CRS home>
End points: TCP:1525
Listener is enabled.
Listener is individually enabled on nodes:
Listener is individually disabled on nodes:

[oracle@ol8-19-rac1 ~]$ srvctl status listener -l ASMNET1LSNR_ASM
Listener ASMNET1LSNR_ASM is enabled
Listener ASMNET1LSNR_ASM is running on node(s): ol8-19-rac2,ol8-19-rac1

[oracle@ol8-19-rac1 ~]$ srvctl config asm
ASM home: <CRS home>
Password file: +CRS/orapwASM
Backup of Password file: +CRS/orapwASM_backup
ASM listener: LISTENER
ASM instance count: 2
Cluster ASM listener: ASMNET1LSNR_ASM Firstly, let’s check if both nodes are able to reach the network we intend to use. [oracle@ol8-19-rac1 tmp]$ ping -c 3 10.1.3.161
PING 10.1.3.161 (10.1.3.161) 56(84) bytes of data.
64 bytes from 10.1.3.161: icmp_seq=1 ttl=64 time=0.010 ms
64 bytes from 10.1.3.161: icmp_seq=2 ttl=64 time=0.014 ms
64 bytes from 10.1.3.161: icmp_seq=3 ttl=64 time=0.018 ms

--- 10.1.3.161 ping statistics ---
3 packets transmitted, 3 received, 0% packet loss, time 2052ms
rtt min/avg/max/mdev = 0.010/0.014/0.018/0.003 ms

[oracle@ol8-19-rac1 tmp]$ ping -c 3 10.1.3.162
PING 10.1.3.162 (10.1.3.162) 56(84) bytes of data.
64 bytes from 10.1.3.162: icmp_seq=1 ttl=64 time=0.168 ms
64 bytes from 10.1.3.162: icmp_seq=2 ttl=64 time=0.151 ms
64 bytes from 10.1.3.162: icmp_seq=3 ttl=64 time=0.171 ms

--- 10.1.3.162 ping statistics ---
3 packets transmitted, 3 received, 0% packet loss, time 2068ms
rtt min/avg/max/mdev = 0.151/0.163/0.171/0.013 ms

[oracle@ol8-19-rac2 tmp]$ ping -c 3 10.1.3.161
PING 10.1.3.161 (10.1.3.161) 56(84) bytes of data.
64 bytes from 10.1.3.161: icmp_seq=1 ttl=64 time=0.153 ms
64 bytes from 10.1.3.161: icmp_seq=2 ttl=64 time=0.156 ms
64 bytes from 10.1.3.161: icmp_seq=3 ttl=64 time=0.176 ms

--- 10.1.3.161 ping statistics ---
3 packets transmitted, 3 received, 0% packet loss, time 2081ms
rtt min/avg/max/mdev = 0.153/0.161/0.176/0.017 ms

[oracle@ol8-19-rac2 tmp]$ ping -c 3 10.1.3.162
PING 10.1.3.162 (10.1.3.162) 56(84) bytes of data.
64 bytes from 10.1.3.162: icmp_seq=1 ttl=64 time=0.010 ms
64 bytes from 10.1.3.162: icmp_seq=2 ttl=64 time=0.025 ms
64 bytes from 10.1.3.162: icmp_seq=3 ttl=64 time=0.015 ms

--- 10.1.3.162 ping statistics ---
3 packets transmitted, 3 received, 0% packet loss, time 2037ms
rtt min/avg/max/mdev = 0.010/0.016/0.025/0.007 ms Since everything seems OK, now we will start changing the private network. We will change it from the subnet to . As the grid user, proceed as below in only one of the nodes. eth2:10.1.2.0 eth3:10.1.3.0 [oracle@ol8-19-rac1 ~]$ oifcfg setif -global eth3/10.1.3.0:cluster_interconnect,asm
[oracle@ol8-19-rac1 ~]$ srvctl add listener -asmlistener -l ASMNEWLSNR_ASM -subnet 10.1.3.0
[oracle@ol8-19-rac1 ~]$ srvctl update listener -listener ASMNET1LSNR_ASM -asm -remove -force

--The error below is expected, as we are only testing if the previous listener still exists.
[oracle@ol8-19-rac1 ~]$ lsnrctl stop ASMNET1LSNR_ASM

LSNRCTL for Linux: Version 19.0.0.0.0 - Production on 28-MAY-2023 07:55:09

Copyright (c) 1991, 2023, Oracle.  All rights reserved.

TNS-01101: Could not find listener name or service name ASMNET1LSNR_ASM Check if the ASM Listener was created correctly. [oracle@ol8-19-rac1 ~]$ srvctl config asm
ASM home: <CRS home>
Password file: +CRS/orapwASM
Backup of Password file: +CRS/orapwASM_backup
ASM listener: LISTENER
ASM instance count: 2
Cluster ASM listener: ASMNEWLSNR_ASM

[oracle@ol8-19-rac1 ~]$ srvctl config listener -asmlistener
Name: ASMNEWLSNR_ASM
Type: ASM Listener
Owner: oracle
Subnet: 10.1.3.0
Home: <CRS home>
End points: TCP:1526
Listener is enabled.
Listener is individually enabled on nodes:
Listener is individually disabled on nodes: In the 19c version, we also have one more resource to handle, the ASM Network. [oracle@ol8-19-rac1 ~]$ srvctl config asmnetwork
ASM network 1 exists
Subnet IPv4: 10.1.2.0//
Subnet IPv6:
Network is enabled
Network is individually enabled on nodes:
Network is individually disabled on nodes:

[oracle@ol8-19-rac1 ~]$ srvctl status asmnetwork
ASM network is running on ol8-19-rac2,ol8-19-rac1 As the root user, proceed as below. [root@ol8-19-rac1 scripts]# srvctl remove asmnetwork -netnum 1 -force
[root@ol8-19-rac1 scripts]# srvctl add asmnetwork -netnum 1 -subnet 10.1.3.0 Now let’s restart the entire cluster. [root@ol8-19-rac1 ~]# crsctl stop cluster -all -f
CRS-2673: Attempting to stop 'ora.crsd' on 'ol8-19-rac2'
CRS-2673: Attempting to stop 'ora.crsd' on 'ol8-19-rac1'
...
CRS-2673: Attempting to stop 'ora.cssd' on 'ol8-19-rac1'
CRS-2677: Stop of 'ora.cssd' on 'ol8-19-rac1' succeeded

[root@ol8-19-rac1 ~]# crsctl stop crs -f
CRS-2791: Starting shutdown of Oracle High Availability Services-managed resources on 'ol8-19-rac1'
...
CRS-2793: Shutdown of Oracle High Availability Services-managed resources on 'ol8-19-rac1' has completed
CRS-4133: Oracle High Availability Services has been stopped.

[root@ol8-19-rac2 ~]# crsctl stop crs -f
CRS-2791: Starting shutdown of Oracle High Availability Services-managed resources on 'ol8-19-rac2'
...
CRS-2793: Shutdown of Oracle High Availability Services-managed resources on 'ol8-19-rac2' has completed
CRS-4133: Oracle High Availability Services has been stopped.

[root@ol8-19-rac1 ~]# crsctl start crs
CRS-4123: Oracle High Availability Services has been started.

[root@ol8-19-rac2 ~]# crsctl start crs
CRS-4123: Oracle High Availability Services has been started. Check if everything is OK. [oracle@ol8-19-rac1 tmp]$ crsctl status res -t
--------------------------------------------------------------------------------
Name           Target  State        Server                   State details
--------------------------------------------------------------------------------
Local Resources
--------------------------------------------------------------------------------
ora.LISTENER.lsnr
               ONLINE  ONLINE       ol8-19-rac1              STABLE
               ONLINE  ONLINE       ol8-19-rac2              STABLE
ora.chad
               ONLINE  ONLINE       ol8-19-rac1              STABLE
               ONLINE  ONLINE       ol8-19-rac2              STABLE
ora.net1.network
               ONLINE  ONLINE       ol8-19-rac1              STABLE
               ONLINE  ONLINE       ol8-19-rac2              STABLE
ora.ons
               ONLINE  ONLINE       ol8-19-rac1              STABLE
               ONLINE  ONLINE       ol8-19-rac2              STABLE
ora.proxy_advm
               OFFLINE OFFLINE      ol8-19-rac1              STABLE
               OFFLINE OFFLINE      ol8-19-rac2              STABLE
--------------------------------------------------------------------------------
Cluster Resources
--------------------------------------------------------------------------------
ora.ASMNEWLSNR_ASM.lsnr(ora.asmgroup)
      1        ONLINE  ONLINE       ol8-19-rac1              STABLE
      2        ONLINE  ONLINE       ol8-19-rac2              STABLE
ora.CRS.dg(ora.asmgroup)
      1        ONLINE  ONLINE       ol8-19-rac1              STABLE
      2        ONLINE  ONLINE       ol8-19-rac2              STABLE
ora.DATA.dg(ora.asmgroup)
      1        ONLINE  ONLINE       ol8-19-rac1              STABLE
      2        ONLINE  ONLINE       ol8-19-rac2              STABLE
ora.LISTENER_SCAN1.lsnr
      1        ONLINE  ONLINE       ol8-19-rac2              STABLE
ora.LISTENER_SCAN2.lsnr
      1        ONLINE  ONLINE       ol8-19-rac1              STABLE
ora.LISTENER_SCAN3.lsnr
      1        ONLINE  ONLINE       ol8-19-rac1              STABLE
ora.RECO.dg(ora.asmgroup)
      1        ONLINE  ONLINE       ol8-19-rac1              STABLE
      2        ONLINE  ONLINE       ol8-19-rac2              STABLE
ora.asm(ora.asmgroup)
      1        ONLINE  ONLINE       ol8-19-rac1              Started,STABLE
      2        ONLINE  ONLINE       ol8-19-rac2              Started,STABLE
ora.asmnet1.asmnetwork(ora.asmgroup)
      1        ONLINE  ONLINE       ol8-19-rac1              STABLE
      2        OFFLINE OFFLINE                               STABLE
ora.cdbrac.db
      1        ONLINE  ONLINE       ol8-19-rac1              Open,HOME=/u01/app/o
                                                             racle/product/19.0.0
                                                             /dbhome_1,STABLE
      2        ONLINE  ONLINE       ol8-19-rac2              Open,HOME=/u01/app/o
                                                             racle/product/19.0.0
                                                             /dbhome_1,STABLE
ora.cvu
      1        ONLINE  ONLINE       ol8-19-rac1              STABLE
ora.ol8-19-rac1.vip
      1        ONLINE  ONLINE       ol8-19-rac1              STABLE
ora.ol8-19-rac2.vip
      1        ONLINE  ONLINE       ol8-19-rac2              STABLE
ora.qosmserver
      1        ONLINE  ONLINE       ol8-19-rac1              STABLE
ora.scan1.vip
      1        ONLINE  ONLINE       ol8-19-rac2              STABLE
ora.scan2.vip
      1        ONLINE  ONLINE       ol8-19-rac1              STABLE
ora.scan3.vip
      1        ONLINE  ONLINE       ol8-19-rac1              STABLE
-------------------------------------------------------------------------------- In my case, the ASM Network was not running on node 2, so I started it manually, and I will check in future reboots if I face the same issue again. [oracle@ol8-19-rac2 tmp]$ srvctl start asmnetwork

[oracle@ol8-19-rac2 tmp]$ srvctl status asmnetwork
ASM network is running on ol8-19-rac2,ol8-19-rac1 Since everything is running smoothly, let’s remove the previous network from the Oracle CRS. As the grid user, proceed as below. [oracle@ol8-19-rac1 tmp]$ oifcfg delif -global eth2/10.1.2.0

[oracle@ol8-19-rac1 tmp]$ oifcfg getif
eth1  192.168.56.0  global  public
eth3  10.1.3.0  global  cluster_interconnect,asm In the next article, I will explain how to update the IP from the other layers of the Oracle CRS. That’s it!

How to Modify Private Network Information in Oracle Clusterware 19c

It's not new to anyone that has changed the way we ship software. The primary goal of using is containerization, and that is to have a consistent environment for your application and does not depend on the host machine where it runs. Docker Docker Also, is becoming a popular architectural choice for writing services. You can check this to get a glance of how to implement a service in . gRPC quick start gRPC Golang In this article, we'll see how to write and run a service with . We'll also cover a lot of cool and useful things, like: gRPC Docker How to compile files without the burden of installing locally; .proto protoc How we can easily use for parameterizing our application; environment variables How to write a so we end up with a small, optmized image; multistage build Docker How to easily invoke the service without having to manually write a client for it. gRPC Golang Let's go! The proposed application We'll write a service that is used to retrieve a number of random poetries. In order to achieve that, we'll use , an awesome free API for internet poets. gRPC PoetryDB We can see a simple to show how it will work: sequence diagram Protobuf Here's our file where we define the service, 'poetry.proto': .proto syntax = "proto3"


package proto;
option go_package = "bitbucket.org/tiagoharris/docker-grpc-service-tutorial/proto/poetry";


message Poetry {
    string title = 1;
    string author = 2;
    repeated string lines = 3;
    int32 linecount = 4;
}


message RandomPoetriesRequest {
    int32 number_of_poetries = 1;
}


message PoetryList {
    repeated Poetry list = 1;
}


service ProtobufService {
    rpc RandomPoetries(RandomPoetriesRequest) returns (PoetryList);
} Now we need to compile it in order to have: Code for populating, serializing, and retrieving 'RandomPoetriesRequest' and 'PoetryList' message types; Generated client and server code. We compile it using . Generally we would need to install it, but a better idea would be to use a image that has installed, pretty much similar to what we do when we want to use for example; instead of installing it, we could use a image for it. protoc Docker protoc MySQL Docker And is exactly what we need. docker-protoc Here's our Makefile target that we use to invoke it so we compile the file: .proto .PHONY: proto
## proto: compiles .proto files
proto:
    @ docker run -v $(PWD):/defs namely/protoc-all -f proto/poetry.proto -l 
go -o . --go-source-relative The '--go-source-relative' option is to keep the generated 'poetry.pb.go' file at the same folder of our file 'poetry.proto'. .proto When you call it for the first time, it will download 'namely/protoc-all:latest' image and then will compile our file: Docker .proto $ make proto
Unable to find image 'namely/protoc-all:latest' locally
latest: Pulling from namely/protoc-all
72a69066d2fe: Pull complete 
92b40fad93be: Pull complete 
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c4795970891a: Pull complete 
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c5446e8648ec: Pull complete 
f3170de720de: Pull complete 
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fd5de9fd6a61: Pull complete 
35f2a04b2c22: Pull complete 
075200f557a8: Pull complete 
017c387ae8e9: Pull complete 
Digest: sha256:5406210e1dc68ffe4f36fa1ee98214bb50614d3a44428bf33ffca427079dd3d2
Status: Downloaded newer image for namely/protoc-all:latest Reading environment variables Before implementing our service, let's make an engineering decision about parameterizing the application. A good idea would be to parameterize the base for , as well as how many seconds we want to wait until an HTTP timeout occur. So how can we achieve that in a safe, clean way? gRPC URL PoetryDB Using is a common technique, right? A good solution would be: environment variables Defining the variables in some sort of file; Reading this file and exporting those values as ; environment variables Get those into a so we can easily use them. environment variables struct Godotenv is a package that solves the two bullet points defined above. We define our variables in an '.env' file and then we invoke it to export all those values as . Godotenv Golang environment variables Here's our 'config.env' file: POETRYDB_BASE_URL=https://poetrydb.org
POETRYDB_HTTP_TIMEOUT=10 Envconfig is a package that solves the last bullet point: it encapsulates that are correctly exported into a . Envconfig Golang environment variables struct Here's 'configreader/config_reader.go', which we use to get a configuration fulfilled with : struct environment variables // Copyright (c) 2022 Tiago Melo. All rights reserved.
// Use of this source code is governed by the MIT License that can be found in
// the LICENSE file.


package configreader


import (
    "github.com/joho/godotenv"
    "github.com/kelseyhightower/envconfig"
    "github.com/pkg/errors"
)


// These global variables makes it easy
// to mock these dependencies
// in unit tests.
var (
    godotenvLoad     = godotenv.Load
    envconfigProcess = envconfig.Process
)


// GoDotEnv is an interface that defines
// the functions we use from godotenv package.
// It enables mocking this dependency in unit testing.
type GoDotEnv interface {
    Load(filenames ...string) (err error)
}


// EnvConfig is an interface that defines
// the functions we use from envconfig package.
// It enables mocking this dependency in unit testing.
type EnvConfig interface {
    Process(prefix string, spec interface{}) error
}


// Config holds configuration data.
type Config struct {
    PoetrydbBaseUrl     string `envconfig:"POETRYDB_BASE_URL" required:"true"`
    PoetrydbHttpTimeout int    `envconfig:"POETRYDB_HTTP_TIMEOUT" required:"true"`
}


// ReadEnv reads envionment variables into Config struct.
func ReadEnv() (*Config, error) {
    err := godotenvLoad("configreader/config.env")
    if err != nil {
        return nil, errors.Wrap(err, "reading .env file")
    }
    var config Config
    err = envconfigProcess("", &config)
    if err != nil {
        return nil, errors.Wrap(err, "processing env vars")
    }
    return &config, nil
} gRPC service implementation Now that we compiled our file 'poetry.proto', we'll write a server that implements the service defined in 'poetry.pb.go': .proto gRPC // Copyright (c) 2022 Tiago Melo. All rights reserved.
// Use of this source code is governed by the MIT License that can be found in
// the LICENSE file.


package server


import (
    "context"
    "encoding/json"
    "fmt"
    "net"


    "bitbucket.org/tiagoharris/docker-grpc-service-tutorial/configreader"
    "bitbucket.org/tiagoharris/docker-grpc-service-tutorial/poetrydb"
    poetry "bitbucket.org/tiagoharris/docker-grpc-service-tutorial/proto"
    "github.com/pkg/errors"
    "google.golang.org/grpc"
    "google.golang.org/grpc/reflection"
    "google.golang.org/protobuf/encoding/protojson"
)


// These global variables makes it easy
// to mock these dependencies
// in unit tests.
var (
    netListen           = net.Listen
    configreaderReadEnv = configreader.ReadEnv
    jsonMarshal         = json.Marshal
    protojsonUnmarshal  = protojson.Unmarshal
)


// Server defines the available operations for gRPC server.
type Server interface {
    // Serve is called for serving requests.
    Serve() error
    // GracefulStop is called for stopping the server.
    GracefulStop()
    // RandomPoetries returns a random list of poetries.
    RandomPoetries(ctx context.Context, in *poetry.RandomPoetriesRequest) (*poetry.PoetryList, error)
}


// server implements Server.
type server struct {
    listener   net.Listener
    grpcServer *grpc.Server
    poetryDb   poetrydb.PoetryDb
}


func (s *server) Serve() error {
    return s.grpcServer.Serve(s.listener)
}


func (s *server) GracefulStop() {
    s.grpcServer.GracefulStop()
}


// NewServer creates a new gRPC server.
func NewServer(port int) (Server, error) {
    server := new(server)
    listener, err := netListen("tcp", fmt.Sprintf(":%d", port))
    if err != nil {
        return server, errors.Wrap(err, "tcp listening")
    }
    server.listener = listener
    config, err := configreaderReadEnv()
    if err != nil {
        return server, errors.Wrap(err, "reading env vars")
    }
    server.poetryDb = poetrydb.NewPoetryDb(config.PoetrydbBaseUrl, config.PoetrydbHttpTimeout)
    server.grpcServer = grpc.NewServer()
    poetry.RegisterProtobufServiceServer(server.grpcServer, server)
    reflection.Register(server.grpcServer)
    return server, nil
}


func (s *server) RandomPoetries(ctx context.Context, in *poetry.RandomPoetriesRequest) (*poetry.PoetryList, error) {
    pbPoetryList := new(poetry.PoetryList)
    poetryList, err := s.poetryDb.Random(int(in.NumberOfPoetries))
    if err != nil {
        return pbPoetryList, errors.Wrap(err, "requesting random poetry")
    }
    json, err := jsonMarshal(poetryList)
    if err != nil {
        return pbPoetryList, errors.Wrap(err, "marshalling json")
    }
    err = protojsonUnmarshal(json, pbPoetryList)
    if err != nil {
        return pbPoetryList, errors.Wrap(err, "unmarshalling proto")
    }
    return pbPoetryList, nil
} Running it Here's the related targets in to run the server: Makefile .PHONY: build
## build: builds server's binary
build:
    @ go build -a -installsuffix cgo -o main .


.PHONY: run
## run: runs the server
run: build
    @ ./main So let's run the server: $ make run
GRPC SERVER : 2022/03/21 10:07:14.846821 main.go:19: main: Initializing GRPC server
GRPC SERVER : 2022/03/21 10:07:14.847286 main.go:32: main: GRPC server listening on port 4040 Invoking the gRPC service Now the cool part: what if we wanted a nice, clean tool like (used to test APIs) to makes it easy to call services? Postman REST gRPC is here to help. You just browse your files and you'll be ready to invoke it: Bloomrpc .proto And here you go. We've asked one random poetry, and now we can appreciate it. Time to Dockerize it! Now that our app is working, let's bake a image for it. Docker Here's our : Dockerfile FROM golang:alpine


# Install git and ca-certificates (needed to be able to call HTTPS)
RUN apk --update add ca-certificates git


# Move to working directory /app
WORKDIR /app


# Copy the code into the container
COPY . .


# Download dependencies using go mod
RUN go mod download


# Build the application's binary
RUN CGO_ENABLED=0 GOOS=linux go build -a -installsuffix cgo -ldflags '-extldflags "-static"' -o main .


# Command to run the application when starting the container
CMD ["/app/main"] Notice: we're installing git because tooling uses it, otherwise we would get an error "go: missing Git command. See https://golang.org/s/gogetcmd"; Golang we're installing 'ca-certificates' because uses , otherwise we would get an error "certificate signed by unknown authority". PoetryDB HTTPS Building the image Now let's build it. Here's the target: Makefile .PHONY: build-docker-image
## build-docker-image: builds the docker image
build-docker-image:
    @ docker build . -t docker-grpc-service-tutorial Invoking it: $ make build-docker-image
Sending build context to Docker daemon  13.71MB
Step 1/7 : FROM golang:alpine
 ---> 0e3b02146c47
Step 2/7 : RUN apk --update add ca-certificates git
 ---> Using cache
 ---> c326d9aa8cfc
Step 3/7 : WORKDIR /app
 ---> Using cache
 ---> 6c485ff6b69d
Step 4/7 : COPY . .
 ---> 9af131a39537
Step 5/7 : RUN go mod download
 ---> Running in a644255b6578
Removing intermediate container a644255b6578
 ---> 3b43ba797d11
Step 6/7 : RUN CGO_ENABLED=0 GOOS=linux go build -a -installsuffix cgo -ldflags '-extldflags "-static"' -o main .
 ---> Running in 01b6ce6172a9
Removing intermediate container 01b6ce6172a9
 ---> b1eaebffb306
Step 7/7 : CMD ["/app/main"]
 ---> Running in e0ed88e2a687
Removing intermediate container e0ed88e2a687
 ---> edb7869f01a6
Successfully built edb7869f01a6
Successfully tagged docker-grpc-service-tutorial:latest


Use 'docker scan' to run Snyk tests against images to find vulnerabilities and learn how to fix them Running it as a Docker container Here's the target: Makefile .PHONY: build-docker-image
## build-docker-image: builds the docker image
build-docker-image:
    @ docker build . -t docker-grpc-service-tutorial


.PHONY: run-docker
## run-docker: runs the server as a Docker container
run-docker: build-docker-image
    @ docker run -p 4040:4040 docker-grpc-service-tutorial Invoking it: $ make run-docker
Sending build context to Docker daemon  13.71MB
Step 1/7 : FROM golang:alpine
 ---> 0e3b02146c47
Step 2/7 : RUN apk --update add ca-certificates git
 ---> Using cache
 ---> c326d9aa8cfc
Step 3/7 : WORKDIR /app
 ---> Using cache
 ---> 6c485ff6b69d
Step 4/7 : COPY . .
 ---> 95f88bbbc63e
Step 5/7 : RUN go mod download
 ---> Running in 227656a7a691
Removing intermediate container 227656a7a691
 ---> b6765354b254
Step 6/7 : RUN CGO_ENABLED=0 GOOS=linux go build -a -installsuffix cgo -ldflags '-extldflags "-static"' -o main .
 ---> Running in a8e881248c52
Removing intermediate container a8e881248c52
 ---> a05de0412553
Step 7/7 : CMD ["/app/main"]
 ---> Running in e0009bc99088
Removing intermediate container e0009bc99088
 ---> 351069eab03d
Successfully built 351069eab03d
Successfully tagged docker-grpc-service-tutorial:latest


Use 'docker scan' to run Snyk tests against images to find vulnerabilities and learn how to fix them
GRPC SERVER : 2022/03/21 13:30:18.404250 main.go:19: main: Initializing GRPC server
GRPC SERVER : 2022/03/21 13:30:18.404646 main.go:32: main: GRPC server listening on port 4040 And then you can invoke the service via like we did before. Bloomrpc Multistage build One of 's best practice is keeping the image size small, by having only the binary file then we make our image even smaller from the previous one. To achieve this we will use a technique called which means we will build our image with multiple steps. Docker multistage build Here's our .multistage: Dockerfile FROM golang:alpine AS builder


# Install git and ca-certificates (needed to be able to call HTTPS)
RUN apk --update add ca-certificates git


# Move to working directory /app
WORKDIR /app


# Copy the code into the container
COPY . .


# Download dependencies using go mod
RUN go mod download


# Build the application's binary
RUN CGO_ENABLED=0 GOOS=linux go build -a -installsuffix cgo -ldflags '-extldflags "-static"' -o main .


# Build a smaller image that will only contain the application's binary
FROM scratch


# Move to working directory /app
WORKDIR /app


# Copy certificates
COPY --from=builder /etc/ssl/certs/ca-certificates.crt /etc/ssl/certs/ca-certificates.crt


# Copy application's binary
COPY --from=builder /app .


# Command to run the application when starting the container
CMD ["./main"] Here are the targets: Makefile .PHONY: build-docker-image-multistage
## build-docker-image-multistage: builds a smaller docker image
build-docker-image-multistage:
    @ docker build -f Dockerfile.multistage  . -t docker-grpc-service-tutorial


.PHONY: run-docker-multistage
## run-docker-multistage: runs the server as a Docker container, using the smaller image
run-docker-multistage: build-docker-image-multistage
    @ docker run -p 4040:4040 docker-grpc-service-tutorial Notice that we can name whatever we want it, as long as we speficy if via '-f' flag. Dockerfile Invoking it: $ make run-docker-multistage
Sending build context to Docker daemon  13.71MB
Step 1/11 : FROM golang:alpine AS builder
 ---> 0e3b02146c47
Step 2/11 : RUN apk --update add ca-certificates git
 ---> Using cache
 ---> c326d9aa8cfc
Step 3/11 : WORKDIR /app
 ---> Using cache
 ---> 6c485ff6b69d
Step 4/11 : COPY . .
 ---> 8be509098958
Step 5/11 : RUN go mod download
 ---> Running in 776490901c8e
Removing intermediate container 776490901c8e
 ---> ec0d94130a65
Step 6/11 : RUN CGO_ENABLED=0 GOOS=linux go build -a -installsuffix cgo -ldflags '-extldflags "-static"' -o main .
 ---> Running in fa2e87f052ad
Removing intermediate container fa2e87f052ad
 ---> 57680526aaa1
Step 7/11 : FROM scratch
 ---> 
Step 8/11 : WORKDIR /app
 ---> Running in 0cc6905bb002
Removing intermediate container 0cc6905bb002
 ---> e41a9cb16982
Step 9/11 : COPY --from=builder /etc/ssl/certs/ca-certificates.crt /etc/ssl/certs/ca-certificates.crt
 ---> 8429312feec5
Step 10/11 : COPY --from=builder /app .
 ---> 3d1c20349d38
Step 11/11 : CMD ["./main"]
 ---> Running in a4a88a400a96
Removing intermediate container a4a88a400a96
 ---> 0d27b2b85769
Successfully built 0d27b2b85769
Successfully tagged docker-grpc-service-tutorial:latest


Use 'docker scan' to run Snyk tests against images to find vulnerabilities and learn how to fix them
GRPC SERVER : 2022/03/21 13:37:50.456686 main.go:19: main: Initializing GRPC server
GRPC SERVER : 2022/03/21 13:37:50.457085 main.go:32: main: GRPC server listening on port 4040 And then you can invoke the service via like we did before. Bloomrpc Conclusion In this article, we've covered a lot of nice things when building a service in from scratch: gRPC Golang How to read into a so we can easily use them; environment variables struct How to delegate to an external image to compile our files; Docker .proto How to easily invoke service via ; gRPC Bloomrpc How to create a image using . Docker multistage build Download the source Here: https://bitbucket.org/tiagoharris/docker-grpc-service-tutorial/src/master/ Also Published Here

Running a gRPC Service with Docker

What you will be building: see the and the . live demo git repo Introduction Are you looking to create a cutting-edge platform that leverages the power of web3 to transform the way people book and share accommodations? If so, this tutorial on building a web3 Airbnb clone using React, Solidity, and is for you. CometChat By integrating blockchain technology, real-time communication, and user-generated content, you can create an interactive platform that revolutionizes the traditional apartment booking experience. Whether you're an experienced developer or just starting out, this step-by-step guide will walk you through the process of bringing your vision to life. So why not start building your own Web3 Airbnb clone today and disrupt the travel industry? Prerequisites You will need the following tools installed to build along with me: Nodejs (Important) Ethers js Hardhat Yarn Metamask React Tailwind CSS CometChat SDK Installing Dependencies Clone the starter kit and open it in VS Code using the command below: git clone https://github.com/Daltonic/tailwind_ethers_starter_kit <PROJECT_NAME>
cd <PROJECT_NAME> https://gist.github.com/covelitein/8c3e1d7b53034eccd82649fe839a0092?embedable=true Now, run on the terminal to have all the dependencies for this project installed. yarn install Configuring CometChat SDK Follow the steps below to configure the ; at the end, you must save these keys as an environment variable. CometChat SDK Head to Dashboard and create an account. STEP 1: CometChat Log in to the dashboard, only after registering. STEP 2: CometChat STEP 3: From the dashboard, add a new app called . DappBnb Select the app you just created from the list. STEP 4: From the Quick Start copy the , , and , to your file. See the image and code snippet. STEP 5: APP_ID REGION AUTH_KEY .env Replace the placeholder keys with their appropriate values. REACT_COMET_CHAT REACT_APP_COMETCHAT_APP_ID=****************
REACT_APP_COMETCHAT_AUTH_KEY=******************************
REACT_APP_COMETCHAT_REGION=** The file should be created at the root of your project. .env Configuring the Hardhat script At the root of this project, open the file and replace its content with the following settings. hardhat.config.js https://gist.github.com/covelitein/492156fb20fd064e230a1ac1df364a99?embedable=true The above script instructs hardhat on these three important rules: : This block contains the configurations for your choice of networks. On deployment, hardhat will require you to specify a network for shipping your smart contracts. Networks : This describes the version of the compiler to be used by hardhat for compiling your smart contract codes into and . Solidity bytecodes abi : This simply informs hardhat of the location of your smart contracts and also a place to dump the output of the compiler which is the ABI. Paths Configuring the Deployment Script Navigate to the scripts folder and then to your file and paste the code below into it. If you can't find a script folder, make one, create a file, and paste the following code into it. deploy.js deploy.js https://gist.github.com/Daltonic/252a5c3189e9b283c031bc228613b627?embedable=true When run as a Hardhat deployment command, the above script will deploy your specified smart contract to the network of your choice. Check out this video to learn how to properly set up a web3 project with ReactJs. https://www.youtube.com/watch?v=-q_6CyGNEDw&embedable=true The Smart Contract File Now that we've completed the initial configurations, let's create the smart contract for this build. Create a new folder called in your project's directory. contracts src Create a new file called within this contracts folder; this file will contain all of the logic that governs the smart contract. DappBnb.sol Copy, paste, and save the following codes into the file. See the complete code below. DappBnb.sol https://gist.github.com/Daltonic/ed5c64d39ac49b570eed351371b04a03?embedable=true I have a book to help your master the web3 language (Solidity), . grab your copy here Now, let's go over some of the details of what's going on in the smart contract above. We have the following items: IMPORTED DEPENDENCIES The statements in this smart contract are used to import external dependencies from the OpenZeppelin library, which is a widely-used and trusted collection of pre-built smart contract components. "import" The first dependency, , is used to access the deployer of the contract. The "Ownable" contract provides a basic access control mechanism where there is an account that is designated as the owner, and this owner can modify the state of the contract. The deployer of the contract is typically the owner by default, and this dependency allows the contract to identify and interact with the owner. "@openzeppelin/contracts/access/Ownable.sol" The second dependency, , is used to attach unique IDs to apartments. The "Counters" library provides a simple way to increment and decrement counters, which is useful for creating unique IDs for each apartment listed on the platform. "@openzeppelin/contracts/utils/Counters.sol" The third dependency, is used to protect a specific function from reentrancy attacks. Reentrancy is a type of attack where an attacker can call a function multiple times before the first call has finished executing, which can lead to unexpected behavior and security vulnerabilities. The "ReentrancyGuard" contract provides a simple way to protect functions from this type of attack, which is important for ensuring the security and integrity of the platform. "@openzeppelin/contracts/security/ReentrancyGuard.sol", STRUCTS This contains the necessary information about every apartment that is been posted on the platform. AppartmentStruct: This contains details about every booking done on the platform. BookingStruct: This contains the reviews for each apartment by other users of the platform. ReviewStruct: STATE VARIABLES This variable uses OpenZeppelin’s library to initialize the counter and assign unique ids to newly created apartments. _totalAppartments: Counter This variable holds the percentage that the owner of the contract gets from every booked apartment. TaxPercent: This variable holds the amount that the apartment owner holds when a user books the apartment. SecurityFee: Mappings This mapping variable stores a newly created apartment with a specific Id. apartments: This mapping variable holds the total bookings for a particular apartment. bookingsOf: This mapping variable holds the reviews an apartment has. reviewsOf: : This mapping variable checks for the existence of an apartment. apartmentExist This mapping variable holds the list of dates booked by users for a particular apartment. bookedDates: This mapping checks if the date of booking for an apartment has been taken. isDateBooked: : This mapping checks if a user has at least booked an apartment once. hasBooked Constructor This is used to initialize the state of the smart contract variables and other essential operations. In this example, we assigned the tax percent and security fee a value. Events This event fires when the deployer updates the security fee. SecurityFeeUpdated: Apartment Functions This function is used to add an apartment to the platform. CreateApartment: This function is used to edit certain information about an apartment on the platform supplied by the owner of the apartment. UpdateApartment: This function is used to delete an apartment from the platform supplied by the owner of the apartment. DeleteApartment: This function is used to list the available apartments on the platform. GetApartments: This function is used to get a single apartment on the platform. GetApartment: Booking functions This function is used to book a specific apartment for a number of days, it is used to secure a date or dates for the apartment, and some necessary funds are been sent for the booking of the apartment to the platform. BookApartment: This function checks if the dates a user is booking an apartment are free. DatesAreCleared: This function checks the date a user booked an apartment. HasBookedDateReached: This function returns all the days that have been booked on the platform. GetUnavailableDates: This function lists the total bookings for an apartment. GetBookings: This function returns a single booking for an apartment. GetBooking: : This function returns true or false if a user has checked into an apartment. TenantBooked Reviews Function This function receives review data from other users from the platform reviewing an apartment on the platform. AddReview: This returns the total reviews for an apartment. GetReviews: Payment Functions This function is used to check-In on the day the apartment booking was anticipated, and it disburses the funds to necessary accounts. CheckInApartment: This function is used to reclaim the funds before the day that was booked by the user who is anticipating the apartment. RefundBooking: This function is used by the apartment owner to disburse funds in the apartment when the day the booker anticipated passes without him or her checking-In. ClaimFunds: This function sends money to an account. PayTo: TaxPercent and Security Fee Functions This function is used to edit or change the security fee value. UpdateSecurityfee: This function is used to edit or change the tax percent value. UpdateTaxPercent: Time function This function adjusts the date returned by the solidity to avoid conflicts when it’s retrieved by the React frontend because the timestamp returned by solidity’s is three (3) digits less than the javascript time function. CurrentTime: block.timestamp block.timestamp With all the above functions understood, copy them into a file named in the contracts folder within the src directory. DappBnb.sol Next, run the commands below to deploy the smart contract into the network. yarn hardhat node # Terminal #1
yarn hardhat run scripts/deploy.js # Terminal #2 If you need further help configuring Hardhat or deploying your Fullstack DApp, watch this video. https://www.youtube.com/watch?v=hsec2erdLOI&embedable=true Developing the Frontend Now that we have our smart contract on the network and all of our artifacts (bytecodes and ABI) generated, let's get the front end ready with React. Components In the src directory, create a new folder called to house all of the React components for this project. components Header component This component contains the logo and relevant navigations and a connect wallet button, see the code below. https://gist.github.com/Daltonic/078cb829fd75707b089304e66d8165d8?embedable=true Within the components folder, create a file called and paste the above codes into it. Header.jsx Category Component This component carries rental categories, as shown above, see the code below. https://gist.github.com/covelitein/4107034f658c64aa25bc481f7e823d3e?embedable=true Again, in the components folder, create a new file called and paste the above codes into it. Category.jsx Card Component This component contains the images of the apartment in slides and some other relevant information as seen above. see the code below. https://gist.github.com/Daltonic/267566f8421f76f2f1947181a617c3c1?embedable=true Now again, in the components folder, create a new file called and paste the above codes into it. Card.jsx ImageSlider component This component contains a SwiperJs slider which is used for the apartment images display, see code below. https://gist.github.com/Daltonic/48467114b5ca759bb0d52e8c4b79d7ed?embedable=true In the components folder, create a new file called and paste the above codes into it. ImageSlider.jsx CardCollection Component This component loads collections of different posted apartments see the code below. https://gist.github.com/covelitein/6f2867f66666488462ac9d630a7b77c1?embedable=true This time again, in the components folder, create a new file called and paste the above codes into it. CardCollection.jsx AddReview Component This component is a modal component for adding reviews see the code below. https://gist.github.com/Daltonic/dd7d283569e420a0b03ef49d77897ef4?embedable=true Create a new file called in the components folder and paste the above codes into it. AddReview.jsx AuthModal Component This component authenticates a user either to log in or sign up before being able to chat it uses the CometChat SDK for authentication, see the code below. https://gist.github.com/Daltonic/75281de7ef5279350a12b0c626c57bab?embedable=true Add it to the list by creating a new file called in the components folder and paste the above codes into it. AddModal.jsx Footer Component This component carries certain information like site name and copywriting information. https://gist.github.com/Daltonic/b13088cc698ee41d18675a9bdca1be7a?embedable=true Create another file called in the components folder and paste the above codes into it. Footer.jsx Views Create the folder inside the directory and sequentially add the following pages within it. views src Home view This page contains the available apartments on the platform see the code below. https://gist.github.com/covelitein/328d3889b1f5eed95afd07f9318c2478?embedable=true Create a file called in the views folder and paste the above codes into it. Home.jsx AddRoom View This page contains a form that is used for adding apartments to the platform. See the code below. https://gist.github.com/Daltonic/22a340622fca45da1fbce5c4d4e1277c?embedable=true Ensure that you create a file called in the views folder and paste the above codes into it. AddRoom.jsx UpdateRoom Component This page contains a form that is used for editing an apartment by the apartment owner.
see the code below. https://gist.github.com/Daltonic/a1c3e5850754e2c7e95eb73f69c64c5c?embedable=true Again, make sure that you create a file called in the views folder and paste the above codes into it. UpdateRoom.jsx Room page This page displays a single apartment and its information, it also carries the form for booking and also a button for getting the bookings of a particular user and relevant pieces of information like reviews. See the code below. https://gist.github.com/Daltonic/8ef4a09cb82378fd778bd94ada1311a2?embedable=true Don’t forget to create a file called in the views folder and paste the above codes into it. UpdateRoom.jsx Bookings Page This page displays information depending on who the user is, if the user is the apartment owner it displays booking requests if not it displays the booking a user has done
see the code below. https://gist.github.com/Daltonic/2d8d81aec00a99499750658a956a1ef9?embedable=true As always, create a file called in the views folder and paste the above codes into it. UpdateRoom.jsx Recent Conversations View This view is only accessible by the apartment to check for messages sent to him or her, see the code below. https://gist.github.com/Daltonic/eaab85a33934d2dcaa43772658102da5?embedable=true Again, create a file called in the views folder and paste the above codes into it. RecentConversations.jsx Chats View This is where all the chatting happens on the platform between apartment owners and other users. See the code below. https://gist.github.com/Daltonic/b9cd98938f1e4ccc819cddb91c37468b?embedable=true Now as before, create another file called in the views folder and paste the above codes into it. Chats.jsx The App.jsx file We'll look at the file, which bundles our and . App.jsx components pages https://gist.github.com/Daltonic/8501785cc58f5091491dcb8ef876f2c3?embedable=true Update the file with the above codes. App.jsx Other Essential Services The services listed below are critical to the smooth operation of our application. The application relies on critical services, including the “ ” which uses the library to manage the application's state. To set up the Store Service, create a " " folder within the "src" folder and create an " " file within it, then paste and save the provided code. The Store Service Store Service react-hooks-global-state store index.jsx https://gist.github.com/Daltonic/3d435edb31132fce74070ab77e7cf341?embedable=true Create a file named "Blockchain.service. " , and save the provided code inside the file. The Blockchain Service js https://gist.github.com/Daltonic/325f5831976ab60a8db472ffc4953b8e?embedable=true Create a file named " " within the " " folder and copy the provided code into the file before saving it. The Chat Service Chat.jsx services https://gist.github.com/Daltonic/b91f8b1e7d9359e2a082c7323afaf632?embedable=true Now update the index entry file with the following codes. The Index.jsx file https://gist.github.com/Daltonic/9d414eae297a6ef74816dceb142ce78a?embedable=true To start the server on your browser, run these commands on two terminals, assuming you have already installed Metamask. # Terminal one:
yarn hardhat node
# Terminal Two
yarn hardhat run scripts/deploy.js
yarn start Running the above commands as instructed will open your project on your browser. And there you have it for how to build a blockchain voting system with React, Solidity, and CometChat. Conclusion In conclusion, the decentralized web and blockchain technology are here to stay, and creating practical applications is a great way to advance your career in web3 development. This tutorial has shown you how to create a web3 version of the popular Airbnb application using smart contracts to facilitate payments, along with the CometChat SDK for one-on-one discussions. That being said, I'll see you next time, and have a wonderful day!

'DappBnB' — How to Create a Web3 Equivalent of AirBnB Using React, Solidity, and CometChat

Why we cannot see any aliens out there. TL;DR:  I will explain The Fermi Paradox in five levels to different audiences. Disclaimer: Research and sources for this article are mine. I’ve used , and partially to rewrite some parts. English is not my first language so, for each of the 5 levels, I utilize them to refine the text and adjust the tone to suit the appropriate audience, passive voice, complexity and spelling. ChatGPT Grammarly HemmingwayApp Explaining the Fermi Paradox to a Child Have you ever looked up at the stars at night and wondered if there might be aliens out there on other planets? Scientists have been wondering about this too for a long time. There are many stars in the sky and some of them might have planets around them. Some of those planets might have creatures like us living on them. If there are so many planets and so many stars, why haven't we seen any aliens yet? This is a big question that scientists have been trying to figure out for a long time. It's called the Fermi Paradox. A paradox is a problem that seems to have a solution, but when you try to solve it, you realize that it doesn't make sense. It's like a very hard puzzle because the missing piece does not match. Explaining the Fermi Paradox to a Teenager The Fermi Paradox is a fascinating question. It has puzzled scientists and thinkers for decades. It's all about the possibility of the existence of extraterrestrial life and why we haven't yet found any evidence of it. The basic idea behind the Fermi Paradox is that the universe is vast. There are billions of stars and planets out there. Some of these planets might have conditions suitable for the development of life. If life is so likely to exist, why haven't we detected any signs of it yet? Some scientists believe that the likelihood of life emerging is very low, while others suggest that the development of advanced civilizations is very rare. Other explanations include the possibility that advanced civilizations might self-destruct. They might not have any interest in communicating with us. We still don't have a definitive answer to the Fermi Paradox. The search for extraterrestrial life is a fascinating and important area of study. There are many exciting discoveries ahead. The Fermi Paradox is a mystery. Why we haven't found any evidence of aliens, in a universe so vast with so many places where life could exist? It is like a tricky riddle. College Student Astronomer Frank Drake developed the Drake equation, a mathematical formula, in 1961. The equation estimates the number of intelligent civilizations in our galaxy, based on different factors. It takes into account the fraction of stars with planets, the number of planets that might be habitable, and the probability of life arising on a habitable planet. https://www.youtube.com/watch?v=MlikCebQSlY&embedable=true The equation provides a framework for thinking about the factors that might influence the probability of finding intelligent life in our galaxy. Many of the variables it takes into account are still uncertain. We don't yet know how common habitable planets are, or how likely it is that life will emerge on a habitable planet. The estimate of the number of intelligent civilizations provided by the Drake equation is a rough approximation. The Drake equation remains an important tool for thinking about the possibility of extraterrestrial life. By considering the different factors that might influence the emergence of intelligent life, we can gain a deeper appreciation for the complexity and wonder of the universe. The equation has played a significant role in shaping our understanding of the Fermi Paradox. it predicts a lot of alien civilizations out there but we have not made contact with any of them. Explaining the Fermi Paradox to a Graduate Student The Fermi Paradox is the mystery of why we haven't found any evidence of extraterrestrial life, despite the vast size of the universe. There are many different possible solutions to the paradox. Self-Destruction This theory suggests that advanced civilizations might self-destruct, either through nuclear war, environmental collapse, Artificial Intelligence uprising or some other means. https://www.youtube.com/watch?v=T8y5EXFMD4s&embedable=true Alien Isolation: This theory proposes that other civilizations might exist, but they are too far away to communicate with us. Zoo Hypothesis: This hypothesis suggests that advanced civilizations might be deliberately avoiding contact with us, either to observe us or to avoid interfering with our development. This is like Star Trek's Prime Directive. https://www.youtube.com/watch?v=BKCtUvi-p9I&embedable=true Interstellar Travel is Impossible Iinterstellar travel is not possible. Even if other civilizations do exist, they are unable to visit or communicate with us. Fermi Paradox is a Fallacy The Fermi Paradox is a false premise. We shouldn't assume that advanced civilizations would want to communicate with us or make their presence known. Cosmic Catastrophes Cosmic events like supernovas, black hole merging, gamma-ray bursts, or asteroid impacts might be responsible for wiping out advanced civilizations. The Simulation Hypothesis: We live in a simulation, created by a more advanced civilization. The lack of evidence for extraterrestrial life is part of the simulation. https://www.youtube.com/watch?v=pAqdN8lGDHo&embedable=true Different Forms of Life Life on other planets might be so different from what we're used to that we wouldn't be able to recognize it as life. Radio Silence Other civilizations might be trying to communicate with us. They use radio waves, but we haven't been able to detect them yet due to technological limitations. https://www.youtube.com/watch?v=UUsACggHyQM&embedable=true Rare Earth Hypothesis The development of complex life forms is very rare. The Earth is one of the few places in the universe where this has happened. The relationship between the Earth and its moon is an example of one of these specific conditions. The moon's gravitational pull helps to stabilize the Earth's rotation and climate. The moon's pull has been critical for the development and sustenance of life on our planet. The moon also played a role in the evolution of life on Earth by contributing to the tides, which may have influenced the development of early life forms. The Great Filter There is some kind of obstacle or challenge that prevents civilizations from advancing beyond a certain point. This could be something like environmental collapse, war, or natural disasters. We Haven't Looked Hard Enough We haven't searched enough of the universe to find evidence of extraterrestrial life yet. The search for life is ongoing and incomplete. There are many other possible solutions to the Fermi Paradox. Scientists continue to study this fascinating question in the hopes of finding new answers and insights. Explaining the Fermi Paradox to an Expert There are many possible solutions to the Fermi Paradox. The Protein Folding The protein folding solution to the Fermi Paradox is a new idea that has gained popularity among some scientists in recent years. The process of protein folding, which is crucial for the development of complex life, is more difficult than we thought. Proteins are the building blocks of life. They are essential for the functioning of cells and organisms. In order for a protein to work, it must fold into a specific three-dimensional shape. The process of protein folding is incredibly complex, and even small errors can lead to serious health problems. The probability of a planet developing the necessary conditions for life, and also the ability to correctly fold proteins, is very low. Even if there are many planets with the potential for life, the chances of finding one that has both the right conditions and the ability to correctly fold proteins are very small. This theory offers an interesting perspective on why we have not found any evidence of extraterrestrial life yet. The solution highlights the complex nature of the building blocks of life. This is a subset of the Rare Earth Hypothesis solution. https://www.youtube.com/watch?v=k_B9YP5nEWw&embedable=true What is your opinion? The lead image for this article was generated by HackerNoon's via the prompt "alien species". AI Image Generator

The Fermi Paradox Explained in 5 Levels of Difficulty

ফার্মি প্যারাডক্স 5 স্তরের অসুবিধায় ব্যাখ্যা করা হয়েছে

Das Fermi-Paradoxon in 5 Schwierigkeitsgraden erklärt

La paradoja de Fermi explicada en 5 niveles de dificultad

Le paradoxe de Fermi expliqué en 5 niveaux de difficulté

फर्मी विरोधाभास को कठिनाई के 5 स्तरों में समझाया गया है

Stories, News & Mentions about B9

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