Public.com

publiccom

PotCoin is entering into a new era of innovation and community engagement. Introducing exclusive giveaways and rewards for dedicated PotCoin holders. The platform will rejuvenate the PotCoin community and incentivize loyal participants. The High Rollers Club will deliver exclusive benefits to PotCoin holders through a dynamic reward system, reigniting the excitement that first defined the PotCoin movement. The PotCoin High Rollers Vault introduces a straightforward, rewarding experience for dedicated crypto enthusiasts. Members can deposit their tokens into the Vault, where every PotCoin mints a raffle ticket for all exclusive High Roller giveaways. Prizes include limited-edition NFTs that grant access to special events, meeting celebrity stars, branded merchandise, and more; making each PotCoin an entry to exciting rewards. Uniquely, the High Rollers Vault requires no lock-up period; users can withdraw their coins anytime. Secured by the ERC-4626 token vault standard, the High Rollers Vault ensures security and transparency through smart contracts, enabling the most committed holders to benefit from the value they’ve helped create. Winners of the giveaways will automatically receive their unique rewards in their wallets, which are also tradeable on platforms such as OpenSea. Additionally, High Rollers gain access to a privileged check-in ticket system. The goal is to bring the community together and drive engaging experiences within the crypto space, celebrating loyalty and participation with exclusive rewards. An exclusive club where unique benefits and experiences await our most dedicated members. PotCoin is teaming up with superstars who are looking to give back to the community and their fans. These superstars want to meet PotCoin High Rollers in person at their shows and events! High Rollers NFTs PotCoin's inaugural High Rollers NFTs are for Meet & Greets with various superstars. Many more unique and exclusive utilities are coming soon! Exclusive invites to PotCoin-sponsored events! PotCoin sponsors many shows, parties, and events. High Rollers are eligible for special exclusive invites. The upcoming scheduled events will be updated and posted soon! And of course, High Rollers do NOT wait in line! Branded merchandise from our new clothing lines! PotCoin is currently expanding its branded clothing lines to include many options for men and women. We are starting with the most popular based on all the requests we’ve received so far. Additional Giveaways Branded hardware wallets, merchandise, and other items based on public demand from our community. PotCoin is more than just a cryptocurrency—it's a movement powered by community engagement, innovation, and a passion for giving back. We’re committed to creating a fun and rewarding experience for our loyal community. As we continue to push the boundaries of what's possible, we’re focused on building meaningful connections and delivering real value, driven by the belief that our community deserves more than just a token—they deserve opportunity and enjoyable experiences. PotCoin is here to accomplish what no memecoin has done before. Welcome, and thank you for joining us on this journey as we redefine what a cryptocurrency community can achieve together. Launched in 2014, Created by a group of visionary developers in Canada, PotCoin emerged as one of the most popular meme coins representing peace and love. Over the years PotCoin gained a loyal community and garnered global attention in 2017 when it sponsored Dennis Rodman’s Peacekeeping trip to North Korea. As a Legacy coin and one of the first, PotCoin has always stood as a symbol of peace and innovation in the cannabis space. Now, we're building on that legacy with renewed energy and purpose. To learn more about PotCoin, visit our website at www.potcoin.com This article is published under HackerNoon’s Business Blogging program. Do your own research before making any financial decisions. PotCoin is entering into a new era of innovation and community engagement. PotCoin PotCoin Introducing exclusive giveaways and rewards for dedicated PotCoin holders. The platform will rejuvenate the PotCoin community and incentivize loyal participants. The High Rollers Club will deliver exclusive benefits to PotCoin holders through a dynamic reward system, reigniting the excitement that first defined the PotCoin movement. The PotCoin High Rollers Vault introduces a straightforward, rewarding experience for dedicated crypto enthusiasts. Members can deposit their tokens into the Vault, where every PotCoin mints a raffle ticket for all exclusive High Roller giveaways. Prizes include limited-edition NFTs that grant access to special events, meeting celebrity stars, branded merchandise, and more; making each PotCoin an entry to exciting rewards. Uniquely, the High Rollers Vault requires no lock-up period; users can withdraw their coins anytime. Secured by the ERC-4626 token vault standard, the High Rollers Vault ensures security and transparency through smart contracts, enabling the most committed holders to benefit from the value they’ve helped create. Winners of the giveaways will automatically receive their unique rewards in their wallets, which are also tradeable on platforms such as OpenSea. Additionally, High Rollers gain access to a privileged check-in ticket system. The goal is to bring the community together and drive engaging experiences within the crypto space, celebrating loyalty and participation with exclusive rewards. An exclusive club where unique benefits and experiences await our most dedicated members. PotCoin is teaming up with superstars who are looking to give back to the community and their fans. These superstars want to meet PotCoin High Rollers in person at their shows and events! High Rollers NFTs High Rollers NFTs PotCoin's inaugural High Rollers NFTs are for Meet & Greets with various superstars. Many more unique and exclusive utilities are coming soon! Exclusive invites to PotCoin-sponsored events! PotCoin sponsors many shows, parties, and events. High Rollers are eligible for special exclusive invites. The upcoming scheduled events will be updated and posted soon! And of course, High Rollers do NOT wait in line! Branded merchandise from our new clothing lines! PotCoin is currently expanding its branded clothing lines to include many options for men and women. We are starting with the most popular based on all the requests we’ve received so far. Additional Giveaways Additional Giveaways Branded hardware wallets, merchandise, and other items based on public demand from our community. PotCoin is more than just a cryptocurrency—it's a movement powered by community engagement, innovation, and a passion for giving back. We’re committed to creating a fun and rewarding experience for our loyal community. As we continue to push the boundaries of what's possible, we’re focused on building meaningful connections and delivering real value, driven by the belief that our community deserves more than just a token—they deserve opportunity and enjoyable experiences. PotCoin is here to accomplish what no memecoin has done before. Welcome, and thank you for joining us on this journey as we redefine what a cryptocurrency community can achieve together. Launched in 2014, Created by a group of visionary developers in Canada, PotCoin emerged as one of the most popular meme coins representing peace and love. Over the years PotCoin gained a loyal community and garnered global attention in 2017 when it sponsored Dennis Rodman’s Peacekeeping trip to North Korea. As a Legacy coin and one of the first, PotCoin has always stood as a symbol of peace and innovation in the cannabis space. Now, we're building on that legacy with renewed energy and purpose. To learn more about PotCoin, visit our website at www.potcoin.com www.potcoin.com www.potcoin.com This article is published under HackerNoon’s Business Blogging program. Do your own research before making any financial decisions. This article is published under HackerNoon’s Business Blogging program. Do your own research before making any financial decisions. Business Blogging Business Blogging

PotCoin Announces the Launch of the High Rollers Club

PotCoin High Rollers Club-un işə başladığını elan edir

PotCoin annoncerer lanceringen af High Rollers Club

Το PotCoin ανακοινώνει την κυκλοφορία του High Rollers Club

PotCoin anuncia el lanzamiento del High Rollers Club

PotCoinがハイローラークラブの立ち上げを発表

PotCoin High Rollers клубының іске қосылғаны туралы хабарлайды

PotCoin E Tsebiša go Thakgolwa ga High Rollers Club

PotCoin ஹை ரோலர்ஸ் கிளப்பின் துவக்கத்தை அறிவிக்கிறது

PotCoin ифтитоҳи клуби баландро эълон мекунад

ፖትኮይን ምጅማር ክለብ ሃይ ሮለርስ ኣፍሊጡ

“PotCoin” “High Rollers” klubynyň döredilendigini habar berýär

PotCoin 宣布推出 High Rollers Club

Authors:
(1) Xiao-Yang Liu, Hongyang Yang, Columbia University (xl2427,hy2500@columbia.edu);
(2) Jiechao Gao, University of Virginia (jg5ycn@virginia.edu);
(3) Christina Dan Wang (Corresponding Author), New York University Shanghai (christina.wang@nyu.edu). Table of Links Abstract and 1 Introduction 2 Related Works and 2.1 Deep Reinforcement Learning Algorithms 2.2 Deep Reinforcement Learning Libraries and 2.3 Deep Reinforcement Learning in Finance 3 The Proposed FinRL Framework and 3.1 Overview of FinRL Framework 3.2 Application Layer 3.3 Agent Layer 3.4 Environment Layer 3.5 Training-Testing-Trading Pipeline 4 Hands-on Tutorials and Benchmark Performance and 4.1 Backtesting Module 4.2 Baseline Strategies and Trading Metrics 4.3 Hands-on Tutorials 4.4 Use Case I: Stock Trading 4.5 Use Case II: Portfolio Allocation and 4.6 Use Case III: Cryptocurrencies Trading 5 Ecosystem of FinRL and Conclusions, and References 3.4 Environment Layer Environment design is crucial in DRL, because the agent learns by interacting with the environment in a trial and error manner. A good environment that simulates real-world market will help the agent learn a better strategy. Considering the stochastic and interactive nature, a financial task is modeled as a Markov Decision Process (MDP), whose state transition is shown in Fig. 1. The environment layer in FinRL is responsible for observing current market information and translating those information into states of the MDP problem. The state variables can be categorized into the state of an agent and the state of the market. For example, in the use case stock trading, the state of the market includes the open-high-low-close prices and volume (OHLCV) and technical indicators; the state of an agent includes the account balance and the shares for each stock. The RL training process involves observing price change, taking an action and calculating a reward. By interacting with the environment, the agent updates iteratively and eventually obtains a trading strategy to maximize the expected return. We reconfigure real market data into gym-style training environments according to the principle of time-driven simulation. Inspired by OpenAI Gym [5], FinRL provides strategy builders with a collection of universal training environments for various trading tasks. 3.4.1 Standard Datasets and Live Trading APIs. DRL in finance is different from chess, card games and robotics [44, 52], which may have physical engines or simulators. Different financial tasks may require different market simulators. Building such training environments is time-consuming, so FinRL provides a set of representative ones and also supports user-import data, aiming to free users from such tedious and time-consuming work. NASDAQ-100 index constituents are 100 stocks that are characterized by high technology and high growth. Dow Jones Industrial Average (DJIA) index is made up of 30 representative constituent stocks. DJIA is the most cited market indicator to examine market overall performance. Standard & Poor’s 500 (S&P 500) index constituents consist of 500 largest U.S. publicly traded companies. Hang Seng Index Index (HSI) constituents are grouped into Finance, Utilities, Properties and Commerce & Industry [19]. HSI is the most widely quoted indicator of the Hong Kong stock market. SSE 50 Index constituents [12] include the best representative companies (in 10 industries) of A shares listed at Shanghai Stock Exchange (SSE) with considerable size and liquidity. CSI 300 Index constituents [8] consist of the 300 largest and most liquid A-share stocks listed on Shenzhen Stock Exchange and SSE. This index reflects the performance of the China A-share market. Bitcoin (BTC) Price Index consists of the quote and trade data on Bitcoin market, available at https://public.bitmex.com/. 3.4.2 User-Imported Data. Users may want to train agents on their own data sets. FinRL provides convenient support for users to import data, adjust the time granularity, and perform the trainingtesting-trading data split. We specify the format for different trading tasks, and users preprocess and format the data according to our instructions. Stock statistics and indicators can be calculated using our support, which provides more features for the state space. Furthermore, episodic total return and Sharpe ratio can also assist performance evaluation. This paper is available on arxiv under CC BY 4.0 DEED license. Authors: (1) Xiao-Yang Liu, Hongyang Yang, Columbia University (xl2427,hy2500@columbia.edu); (2) Jiechao Gao, University of Virginia (jg5ycn@virginia.edu); (3) Christina Dan Wang (Corresponding Author), New York University Shanghai (christina.wang@nyu.edu). Authors: Authors: (1) Xiao-Yang Liu, Hongyang Yang, Columbia University (xl2427,hy2500@columbia.edu); (2) Jiechao Gao, University of Virginia (jg5ycn@virginia.edu); (3) Christina Dan Wang ( Corresponding Author ), New York University Shanghai (christina.wang@nyu.edu). Corresponding Author Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2 Related Works and 2.1 Deep Reinforcement Learning Algorithms 2 Related Works and 2.1 Deep Reinforcement Learning Algorithms 2.2 Deep Reinforcement Learning Libraries and 2.3 Deep Reinforcement Learning in Finance 2.2 Deep Reinforcement Learning Libraries and 2.3 Deep Reinforcement Learning in Finance 3 The Proposed FinRL Framework and 3.1 Overview of FinRL Framework 3 The Proposed FinRL Framework and 3.1 Overview of FinRL Framework 3.2 Application Layer 3.2 Application Layer 3.3 Agent Layer 3.3 Agent Layer 3.4 Environment Layer 3.4 Environment Layer 3.5 Training-Testing-Trading Pipeline 3.5 Training-Testing-Trading Pipeline 4 Hands-on Tutorials and Benchmark Performance and 4.1 Backtesting Module 4 Hands-on Tutorials and Benchmark Performance and 4.1 Backtesting Module 4.2 Baseline Strategies and Trading Metrics 4.2 Baseline Strategies and Trading Metrics 4.3 Hands-on Tutorials 4.3 Hands-on Tutorials 4.4 Use Case I: Stock Trading 4.4 Use Case I: Stock Trading 4.5 Use Case II: Portfolio Allocation and 4.6 Use Case III: Cryptocurrencies Trading 4.5 Use Case II: Portfolio Allocation and 4.6 Use Case III: Cryptocurrencies Trading 5 Ecosystem of FinRL and Conclusions, and References 5 Ecosystem of FinRL and Conclusions, and References 3.4 Environment Layer Environment design is crucial in DRL, because the agent learns by interacting with the environment in a trial and error manner. A good environment that simulates real-world market will help the agent learn a better strategy. Considering the stochastic and interactive nature, a financial task is modeled as a Markov Decision Process (MDP), whose state transition is shown in Fig. 1. The environment layer in FinRL is responsible for observing current market information and translating those information into states of the MDP problem. The state variables can be categorized into the state of an agent and the state of the market. For example, in the use case stock trading, the state of the market includes the open-high-low-close prices and volume (OHLCV) and technical indicators; the state of an agent includes the account balance and the shares for each stock. The RL training process involves observing price change, taking an action and calculating a reward. By interacting with the environment, the agent updates iteratively and eventually obtains a trading strategy to maximize the expected return. We reconfigure real market data into gym-style training environments according to the principle of time-driven simulation. Inspired by OpenAI Gym [5], FinRL provides strategy builders with a collection of universal training environments for various trading tasks. 3.4.1 Standard Datasets and Live Trading APIs. DRL in finance is different from chess, card games and robotics [44, 52], which may have physical engines or simulators. Different financial tasks may require different market simulators. Building such training environments is time-consuming, so FinRL provides a set of representative ones and also supports user-import data, aiming to free users from such tedious and time-consuming work. 3.4.1 Standard Datasets and Live Trading APIs. NASDAQ-100 index constituents are 100 stocks that are characterized by high technology and high growth. NASDAQ-100 index constituents Dow Jones Industrial Average (DJIA) index is made up of 30 representative constituent stocks. DJIA is the most cited market indicator to examine market overall performance. Dow Jones Industrial Average (DJIA) index Standard & Poor’s 500 (S&P 500) index constituents consist of 500 largest U.S. publicly traded companies. Standard & Poor’s 500 (S&P 500) index constituents Hang Seng Index Index (HSI) constituents are grouped into Finance, Utilities, Properties and Commerce & Industry [19]. HSI is the most widely quoted indicator of the Hong Kong stock market. Hang Seng Index Index (HSI) constituents SSE 50 Index constituents [12] include the best representative companies (in 10 industries) of A shares listed at Shanghai Stock Exchange (SSE) with considerable size and liquidity. SSE 50 Index constituents CSI 300 Index constituents [8] consist of the 300 largest and most liquid A-share stocks listed on Shenzhen Stock Exchange and SSE. This index reflects the performance of the China A-share market. CSI 300 Index constituents Bitcoin (BTC) Price Index consists of the quote and trade data on Bitcoin market, available at https://public.bitmex.com/. Bitcoin (BTC) Price Index 3.4.2 User-Imported Data. Users may want to train agents on their own data sets. FinRL provides convenient support for users to import data, adjust the time granularity, and perform the trainingtesting-trading data split. We specify the format for different trading tasks, and users preprocess and format the data according to our instructions. Stock statistics and indicators can be calculated using our support, which provides more features for the state space. Furthermore, episodic total return and Sharpe ratio can also assist performance evaluation. 3.4.2 User-Imported Data. This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv

Harnessing FinRL's Environment Layer for Advanced Market Modeling

Periwinkle Entertainment, Inc. v. The Walt Disney Company Court Filing retrieved [redacted] is part of HackerNoon’s Legal PDF Series. You can jump to any part in this filing here. This part is 4 of 12. A. Ms. Johansson is Cast in the Role of Natasha Romanoff/Black Widow 18. Ms. Johansson is an esteemed and versatile actress with over 25 years of Hollywood acting experience. Her credits include lead roles in critically-acclaimed films such as Lost in Translation, Match Point, The Prestige, The Other Boleyn Girl, Vicky Cristina Barcelona, Her, Don Jon, Chef, Hail, Caesar!, The Jungle Book, Isle of Dogs, Marriage Story, and Jojo Rabbit. She is a two-time Academy Award nominee, a five-time Golden Globe nominee, winner of a BAFTA award, and winner of the 2010 Tony Award for Best Featured Actress in a Play. She will be honored later this fall as the 35th recipient of the American Cinematheque Award. 19. In 2010, Ms. Johansson made her debut in the MCU in Iron Man 2, and she would go on to star in six additional MCU films between 2012 and 2019. The MCU began as a connected series of films about individual superheroes who would come together to form the Avengers superhero team, which initially consisted of Marvel superheroes Iron Man, the Incredible Hulk, Thor, Captain America, Hawkeye, and Black Widow, played by Ms. Johansson. Over time, the MCU grew in scope, introducing other superheroes and teams from Marvel Comics and culminating in two crossover films, Avengers: Infinity War and Avengers: Endgame, which brought all of these characters together. 20. Black Widow, also known as Natasha Romanoff or Romanova, is an elite spy and assassin. She is a notable member of the Avengers, not only for being the only woman in the initial lineup, but also because she does not have superhuman abilities. Whereas, for example, Captain America obtained extraordinary strength and athleticism from an experimental “supersoldier” serum, and Thor is the god of thunder who fights with a hammer forged by dwarves in the heart of a dying star, Black Widow relies solely upon her wits and her extraordinary skills, including expertise in hand-to-hand combat. Ms. Johansson accordingly prepared for the role with months of strength training as well as extensive training in stunts, hand-to-hand combat, and weapons combat. Continue Reading Here. About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings.
This court case retrieved [redacted] deadline.com is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. Periwinkle Entertainment, Inc. v. The Walt Disney Company Court Filing retrieved [redacted] is part of HackerNoon’s Legal PDF Series. You can jump to any part in this filing here. This part is 4 of 12. Periwinkle Entertainment, Inc. v. The Walt Disney Company Court Filing retrieved [redacted] is part of HackerNoon’s Legal PDF Series . You can jump to any part in this filing here . This part is 4 of 12. HackerNoon’s Legal PDF Series here A. Ms. Johansson is Cast in the Role of Natasha Romanoff/Black Widow 18. Ms. Johansson is an esteemed and versatile actress with over 25 years of Hollywood acting experience. Her credits include lead roles in critically-acclaimed films such as Lost in Translation, Match Point, The Prestige, The Other Boleyn Girl, Vicky Cristina Barcelona, Her, Don Jon, Chef, Hail, Caesar!, The Jungle Book, Isle of Dogs, Marriage Story, and Jojo Rabbit. She is a two-time Academy Award nominee, a five-time Golden Globe nominee, winner of a BAFTA award, and winner of the 2010 Tony Award for Best Featured Actress in a Play. She will be honored later this fall as the 35th recipient of the American Cinematheque Award. Lost in Translation, Match Point, The Prestige, The Other Boleyn Girl, Vicky Cristina Barcelona, Her, Don Jon, Chef, Hail, Caesar!, The Jungle Book, Isle of Dogs, Marriage Story, Jojo Rabbit. 19. In 2010, Ms. Johansson made her debut in the MCU in Iron Man 2, and she would go on to star in six additional MCU films between 2012 and 2019. The MCU began as a connected series of films about individual superheroes who would come together to form the Avengers superhero team, which initially consisted of Marvel superheroes Iron Man, the Incredible Hulk, Thor, Captain America, Hawkeye, and Black Widow, played by Ms. Johansson. Over time, the MCU grew in scope, introducing other superheroes and teams from Marvel Comics and culminating in two crossover films, Avengers: Infinity War and Avengers : Endgame , which brought all of these characters together. Infinity War Avengers Endgame 20. Black Widow, also known as Natasha Romanoff or Romanova, is an elite spy and assassin. She is a notable member of the Avengers, not only for being the only woman in the initial lineup, but also because she does not have superhuman abilities. Whereas, for example, Captain America obtained extraordinary strength and athleticism from an experimental “supersoldier” serum, and Thor is the god of thunder who fights with a hammer forged by dwarves in the heart of a dying star, Black Widow relies solely upon her wits and her extraordinary skills, including expertise in hand-to-hand combat. Ms. Johansson accordingly prepared for the role with months of strength training as well as extensive training in stunts, hand-to-hand combat, and weapons combat. Continue Reading Here. Continue Reading Here . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved [redacted] deadline.com is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved [redacted] deadline.com is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. deadline.com

Scarlett Johansson's Iconic Role as Black Widow in the MCU

MinIO is frequently used to store data from logging, metrics and trace data whether it be ElasticSearch, OpenTelemetry, OpenSearch, OpenObserve or any of the other dozen or so great monitoring solutions. MinIO is more efficient when used with storage tiering, which decreases total cost of ownership for the data stored, plus you get the added benefits of writing data to MinIO that is , and protected by . In addition, saving data to MinIO object storage makes it available to other cloud native machine learning and analytics applications. immutable versioned erasure coding Quickwit and MinIO share a lot of the same principles. Quickwit is designed for sub-second search straight from object storage allowing true decoupled compute and storage. This means you can store your data on cheap commodity hardware, while MinIO handles the and Integrity of the data. As your needs and requirements change, you scale out your cluster as needed. Quickwit has concepts of Tenants similar to MinIO that are easily isolated and can manage their individual usage. Replication In today’s post we’ll show you how to setup MinIO and Quickwit with a specific focus on Configuring MinIO as a storage provider for Quickwit Set up MinIO as a metadata store for Quickwit Installing MinIO In a previous blog we discussed how to configure service. We’ll use the same principles here except instead of a binary it will be installed as an OS package. MinIO as a SystemD Install the MinIO .deb package. If you are using another OS family you can find other packages here root@aj-test-1:~# wget https://dl.min.io/server/minio/release/linux-amd64/archive/minio_20231120224007.0.0_amd64.deb -O minio.deb

root@aj-test-1:~# dpkg -i minio.deb Create a user and group and , respectively minio-user minio-user root@aj-test-1:~# groupadd -r minio-user
root@aj-test-1:~# useradd -M -r -g minio-user minio-user Create the data directory for MinIO and set the permissions with the user and group created in the previous step root@aj-test-1:~# mkdir /opt/minio

root@aj-test-1:~# chown minio-user:minio-user /opt/minio Enable and Start MinIO service root@aj-test-1:~# systemctl enable minio

root@aj-test-1:~# systemctl start minio You can verify MinIO is running either through the console by going to or through mc admin http://localhost:9001 root@aj-test-1:~# wget https://dl.min.io/client/mc/release/linux-amd64/mc

root@aj-test-1:~# chmod +x mc

root@aj-test-1:~# mv mc /usr/local/bin/mc

root@aj-test-1:~# mc alias set local http://127.0.0.1:9000 minioadmin minioadmin

root@aj-test-1:~# mc admin info local
●  127.0.0.1:9000
   Uptime: 5 minutes
   Version: 2023-11-25T07:17:05Z
   Network: 1/1 OK
   Drives: 1/1 OK
   Pool: 1

Pools:
   1st, Erasure sets: 1, Disks per erasure set: 1

1 drive online, 0 drives offline If you see messages similar to these, you can be assured that MinIO has started. Now we’ll create a bucket and later some objects using Quickwit. root@aj-test-1:~# mc mb local/quickwit

Bucket created successfully `local/quickwit`. Now we are ready to install Quickwit and configure it with MinIO as the backend. Configure Quickwit The Quickwit installer automatically picks the correct binary archive for your environment and then downloads and unpacks it in your working directory. In this case since we are running Ubuntu it will install packages related to that OS but it supports all the popular distributions. curl -L https://install.quickwit.io | sh

cd ./quickwit-v*/
./quickwit --version Curl the configuration file and let's modify it to add the MinIO bits. curl -o quickwit.yaml
https://github.com/quickwit-oss/quickwit/blob/main/config/quickwit.yaml Open the yaml and first add the credentials to configure MinIO storage:
   s3:
     flavor: minio
     access_key_id: minioadmin
     secret_access_key: minioadmin
     endpoint: http://127.0.0.1:9000 Next we’ll add the Storage and Metadata store configurations default_index_root_uri: s3://quickwit/indexes metastore_uri: s3://quickwit/indexes Once the above configurations are set in the YAML, save it and close. In order to use it set it as an environment variable and run the service export QW_CONFIG=./quickwit.yaml ./quickwit run We can check if its working by browsing the UI at or doing a GET http://localhost:7280 curl http://localhost:7280/api/v1/version Let's create an index configured to receive Stackoverflow posts. You need to create an index configured with a YAML to map your input documents to your index fields and whether these fields should be stored and indexed. curl -o stackoverflow-index-config.yaml 
https://raw.githubusercontent.com/quickwit-oss/quickwit/v0.6.4/config/tutorials/stackoverflow/index-config.yaml Once the index is downloaded create it ./quickwit index create --index-config ./stackoverflow-index-config.yaml To hydrate the index we just created, we’ll download a sample of the first 10,000 Stackoverflow posts and then feed this data into Quickwit which will store it on MinIO in the backend. curl -O https://quickwit-datasets-public.s3.amazonaws.com/stackoverflow.posts.transformed-10000.json ./quickwit index ingest --index stackoverflow --input-path stackoverflow.posts.transformed-10000.json --force As soon as the ingest command finishes you can start querying data by using the command search ./quickwit index search --index stackoverflow --query "search AND engine" You can use more advanced features such as aggregations like the following query to find the most popular tags used on the questions in this dataset curl -XPOST "http://localhost:7280/api/v1/stackoverflow/search" -H 'Content-Type: application/json' -d '{
    "query": "type:question",
    "max_hits": 0,
    "aggs": {
        "foo": {
            "terms":{
                "field":"tags",
                "size": 10
            }
        }
    }
}' Final Thoughts MinIO is the right choice for Quickwit because of its industry-leading performance and scalability. MinIO’s combination of scalability and high-performance puts every data-intensive workload, not just Quickwit, within reach. MinIO is capable of tremendous performance - a achieved 325 GiB/s (349 GB/s) on GETs and 165 GiB/s (177 GB/s) on PUTs with just 32 nodes of off-the-shelf NVMe SSDs. This makes managing Quickwit with MinIO seamless for log management, distributed tracing, and immutable data such as conversational data, event-based analytics among others. recent benchmark By storing the data in MinIO, Quickwit can be used as a Grafana datasource for achieving fast visibility into the operations of your application. You can see patterns and set alerts in Grafana's graphical interface that would allow you to run historical analysis and act on anomalies based on certain thresholds. For example, you might want to check for trends or bottlenecks and try to identify patterns in workload type during a specific time of the day. Got questions? Want to get started? Reach out to us on . Slack Also published . here

Setting Up MinIO With Quickwit

Quickwit এর সাথে MinIO সেট আপ করা হচ্ছে

MinIO mit Quickwit einrichten

Configurar MinIO con Quickwit

Configuration de MinIO avec Quickwit

क्विकविट के साथ मिनियो की स्थापना

Quickwit を使用した MinIO のセットアップ

Quickwit으로 MinIO 설정하기

Configurando MinIO com Quickwit

Настройка MinIO с помощью Quickwit

Quickwit ile MinIO'yu Kurma

Thiết lập MinIO bằng Quickwit

使用 Quickwit 设置 MinIO

Overview Welcome to part 2 of my blog post on getting started with Containers ( ). In part 2, You will learn about the following concepts. Setting up AWS for Containers, Building, and Packaging Containerized Applications, Setting Up on AWS, Deploying ECS containers. Not to worry, if these terms are new to you — you'll learn about them here! AWS read part 1 here Docker You will learn about the following topics in this second part of the blog post. Setting Up AWS for Containers Creating an AWS account Configuring AWS Identity and Access Management (IAM) roles and policies Creating a VPC with Public and Private Subnets for Your Clusters. Building and Packaging Containerized Applications Choosing a containerization technology (Docker, containerd, etc.) Introduction to Docker Setting Up Docker on AWS How to deploy and manage Docker containers on AWS EC2 Prerequisites To follow this tutorial, It will be great if you read part 1 here. Setting Up AWS for Containers Creating an AWS Account Watch this YouTube video created by Cloud Tech on how to create an AWS account : https://www.youtube.com/watch?v=SFaSB6vgp8k&t=406s&embedable=true Configuring AWS Identity and Access Management (IAM) Roles and Policies Watch this YouTube video created by Inquirinity on how to configure IAM for an AWS account : https://www.youtube.com/watch?v=LhAyqaZwYKE&embedable=true You can also visit the website to learn all about IAM on AWS Amazon Webservice documentation Creating a VPC with Public and Private Subnets for Your Clusters Container instances in your clusters need external network access to communicate with the Amazon ECS service endpoint. However, you might have tasks and services that you would like to run in private subnets. Creating a VPC with both public and private subnets provides you the flexibility to launch tasks and services in either a public or private subnet. Tasks and services in the private subnets can access the internet through a NAT gateway. Services in both the public and private subnets can be configured to use a load balancer so that they can still be reached from the public internet. This tutorial guides you through creating a VPC with two public subnets and two private subnets, which are provided with internet access through a NAT gateway. Step 1: Create an Elastic IP Address for Your NAT Gateway requires an Elastic IP address in your public subnet, but the VPC wizard does not create one for you. Create the Elastic IP address before running the VPC wizard. A NAT gateway To create an Elastic IP address, open the or visit this URL and sign in. Follow the below steps: Amazon VPC console https://console.aws.amazon.com/vpc/ In the left navigation pane, choose Elastic IPs. Choose Allocate new address, Allocate, Close. The Allocation ID for your newly created Elastic IP address; you will enter this later in the VPC wizard. Step 2: Run the VPC Wizard The VPC wizard automatically creates and configures most of your VPC resources for you. To run the VPC wizard, in the left navigation pane, choose VPC Dashboard. Choose Launch VPC Wizard, VPC with Public and Private Subnets, Select. For VPC name, give your VPC a unique name. For Elastic IP Allocation ID, choose the ID of the Elastic IP address that you created earlier. Choose Create VPC. When the wizard is finished, choose OK. The Availability Zone in which your VPC subnets were created. Your additional subnets should be created in a different Availability Zone. Non-default subnets, such as those created by the VPC wizard, are not auto-assigned public IPv4 addresses. Instances launched in the public subnet must be assigned a public IPv4 address to communicate with the Amazon ECS service endpoint. To modify your public subnet's IPv4 addressing behavior In the left navigation pane, choose Subnets. Select the public subnet for your VPC. By default, the name created by the VPC wizard is Public subnet. Choose Actions, Modify auto-assign IP settings. Select the Enable auto-assign public IPv4 address check box, and then choose Save. Step 3: Create Additional Subnets The wizard creates a VPC with a single public and a single private subnet in a single Availability Zone. For greater availability, you should create at least one more of each subnet type in a different Availability Zone so that your VPC has both public and private subnets across two Availability Zones. To create an additional private subnet In the left navigation pane, choose Subnets. Choose Create Subnet. For Name tag, enter a name for your subnet, such as Private subnet. For VPC, choose the VPC that you created earlier. For Availability Zone, choose a different Availability Zone than your original subnets in the VPC. For IPv4 CIDR block, enter a valid CIDR block. For example, the wizard creates CIDR blocks in 10.0.0.0/24 and 10.0.1.0/24 by default. You could use 10.0.3.0/24 for your second private subnet. Choose Yes, Create. To create an additional public subnet In the left navigation pane, choose Subnets and then Create Subnet. For Name tag, enter a name for your subnet, such as a Public subnet. For VPC, choose the VPC that you created earlier. For Availability Zone, choose the same Availability Zone as the additional private subnet that you created in the previous procedure. For IPv4 CIDR block, enter a valid CIDR block. For example, the wizard creates CIDR blocks in 10.0.0.0/24 and 10.0.1.0/24 by default. You could use 10.0.2.0/24 for your second public subnet. Choose Yes, Create. Select the public subnet that you just created and choose Route Table, Edit. By default, the main route table is selected. Choose the other available route table so that the 0.0.0.0/0 destination is routed to the internet gateway (igw-xxxxxxxx) and choose Save. With your second public subnet still selected, choose Subnet Actions, Modify auto-assign IP settings. Select Enable auto-assign public IPv4 address and choose Save, Close. Building and Packaging Containerized Applications Choosing a Containerization Technology Containerization has become a popular approach for packaging and deploying applications. Several containerization technologies are available, including Docker, containerd, and others. In this tutorial, you will focus on Docker as the containerization technology of choice. Introduction to Docker Docker has revolutionized the way developers package and deploy applications, offering a lightweight and portable solution for containerization. With Docker, developers can create self-contained units called containers that encapsulate their applications and all their dependencies, including libraries, frameworks, and runtime environments. This approach ensures that applications run consistently across different environments, from development to production, regardless of the underlying infrastructure. One of the key benefits of Docker is improved application isolation. By leveraging containerization, applications are encapsulated within their own runtime environment, isolated from the host system and other applications. This isolation prevents conflicts between dependencies and ensures that applications operate reliably and predictably. Furthermore, Docker brings consistency to application deployment. With Docker containers, developers can create a standardized environment, ensuring that applications behave consistently across different development machines, testing environments, and production servers. This eliminates the "works on my machine" problem and facilitates smoother collaboration between teams. Setting Up Docker on AWS Docker is a popular containerization technology that enables developers to package and deploy applications in lightweight and portable containers. Web Services (AWS) provides a robust infrastructure for running Docker containers. This guide will walk you through the steps to set up on AWS. Amazon Docker Step 1: Create an AWS Account If you don't have an AWS account already, go to the AWS website (https://aws.amazon.com/) and click on . Follow the instructions to set up your account. You will need to provide billing information and create a new IAM user with appropriate permissions. Create an AWS Account Step 2: Launch an EC2 Instance Once you have an AWS account, launch an EC2 instance to host your Docker containers. Follow these steps: Open the AWS Management Console and navigate to the EC2 service. Click on "Launch Instance" to start the instance creation process. Choose an Amazon Machine Image (AMI) that supports Docker, such as Amazon Linux 2 or Amazon ECS-optimized AMI. Select an instance type based on your application's requirements. Configure the instance details, such as the number of instances, VPC settings, and security groups. Add storage and configure any additional settings as needed. Review your configuration and launch the instance. Step 3: Connect to the EC2 Instance After the EC2 instance is launched, you need to connect to it using SSH. Follow these steps: Locate the public IP address or DNS name of your EC2 instance in the AWS Management Console. Open a terminal on your local machine and run the following command, replacing your-instance-ip with the IP address or DNS name: ssh -i your-key-pair.pem ec2-user@your-instance-ip Note: You may need to adjust the SSH command based on the operating system and key pair you used during the EC2 instance setup. Step 4: Install Docker on the EC2 Instance Once connected to the EC2 instance, install Docker by executing the following commands: Update the package index: sudo yum update -y Install Docker: sudo amazon-linux-extras install docker -y Start the Docker service: sudo service docker start Add the ec2-user to the Docker group to run Docker commands without using sudo: sudo usermod -a -G docker ec2-user Step 5: Verify the Docker Installation To confirm that Docker is installed and running correctly on the EC2 instance, run the following command: docker info If Docker is installed properly, you will see information about the Docker version and configuration. Deploying and Managing Docker Containers on AWS EC2 Once you have Docker set up on your AWS EC2 instance, you can begin deploying and managing Docker containers. This guide will walk you through the steps to deploy and manage Docker containers on your AWS EC2 instance. Step 1: Prepare your Docker Image Before deploying a container, ensure you have a Docker image ready for your application. You can either build your own Docker image using a Dockerfile or pull an existing image from a registry like Docker Hub. Step 2: Pull or Load the Docker Image If you are using an existing Docker image from a registry, use the docker pull command to fetch the image onto your EC2 instance. For example: docker pull your-image:tag If you have a locally-built Docker image or a saved image file, use the docker load command to load the image into Docker on your EC2 instance. For example: docker load -i your-image.tar Step 3: Run the Docker Container To deploy a Docker container based on your image, use the docker run command. Customize the command based on your application's requirements. Here's an example: docker run -d --name your-container -p host-port:container-port your-image:tag Replace your container with a desired name for your container, host port with the port number on your EC2 instance you want to map to the container's port, and container port with the port your application listens on inside the container. Step 4: Manage and Monitor Docker Containers You can manage and monitor your Docker containers on your EC2 instance using various Docker commands. Here are some commonly used commands: : Lists the running containers on the EC2 instance. docker ps : Stops a running container. Replace container-id with the actual container ID or name. docker stop container-id : Starts a stopped container. docker start container-id : Displays the logs of a specific container. docker logs container-id : Accesses the terminal inside a running container for executing commands or debugging. docker exec -it container-id /bin/bash Step 5: Clean Up Unused Containers To keep your EC2 instance clean and efficient, it's essential to remove unused containers. Use the docker rm command followed by the container ID or name to remove a stopped container. For example: Be cautious while removing containers as it permanently deletes the container and its associated data. docker rm container-id Step 6: Automate Container Deployment and Management To streamline container deployment and management, consider using container orchestration tools like Amazon Elastic Container Service (ECS) or Kubernetes on AWS. These tools provide more advanced features, such as automatic scaling, load balancing, and improved container management capabilities. However, if you like this article and want to encourage me to write more articles, you can donate to this ETH, USDC and USDT Address on the Ethereum network: 0xfd446002b2979559ef4Cd06e5DCC84bbCC6b49D3 Feel free to visit the official and explore further resources from . Amazon Container Documentation Website Amazon Also published here. Lead image source.

A Beginner's Guide to AWS Containers - Part 2 

175 Stories To Learn About Developer

Aspect-Oriented Programming (AOP) is a programming paradigm that aims to increase modularity by allowing the separation of cross-cutting concerns. In simple terms, it helps you keep your code clean, modular, and easy to maintain. We can leverage AOP to debug Spring Boot applications more effectively and seamlessly. In this post, we will explore how to use AOP to debug a Spring Boot application effectively. https://youtu.be/6kxpkcEqssw?embedable=true AOP Concepts Before diving into debugging with AOP, it is essential to understand the core concepts. AOP lets us write code that executes before or after a method. It includes the following common terms: An aspect represents the cross-cutting concerns or the functionality that needs to be applied throughout the application. Aspect: A join point is a specific point in the execution flow of the application, where an aspect can be applied. Join Point: The action taken by an aspect at a specific join point is called advice. There are different types of advice, such as before, after, around, and after throwing. Advice: A pointcut is a set of join points where an aspect should be applied. Pointcut: I will skip the discussion on weaving since there’s a lot of nuance related to that and I want to focus on the debugging aspects. I don't want to make this into an AOP tutorial. However, there’s one general aspect of AOP I want to discuss. While AOP offers significant benefits in terms of modularity, maintainability, and debugging capabilities, it's important to be aware of the potential performance implications. Using AOP can introduce some overhead, primarily due to the creation and execution of proxy objects, which intercept method calls and apply the specified advices. The impact on performance can vary depending on the number of aspects, the complexity of pointcut expressions, and the type of advice used. For example, around advice is typically more expensive in terms of performance compared to before and after advice. To minimize the performance impact of AOP, consider the following best practices: Apply AOP to the critical parts of your application where it provides the most value. Avoid using aspects for trivial or infrequent operations. Be selective: Ensure that your pointcut expressions are as precise as possible. This can help minimize the number of unnecessary interceptions and reduce the overhead. Optimize pointcut expressions: Choose the appropriate type of advice for your use case. For example, use before or after advice instead of around advice when possible. Limit advice execution: If some aspects are only required for debugging or development purposes, use conditional aspects that can be enabled or disabled based on a configuration property. This ensures that the performance impact is limited to specific environments or scenarios. Use conditional aspects: Regularly monitor and measure the performance of your application to ensure that the overhead introduced by AOP is within acceptable limits. Use profiling tools to identify potential bottlenecks and optimize your AOP implementation accordingly. Monitor and measure: Logging Aspect Let's create a simple aspect to log the execution time of methods in our Spring Boot application. This can help identify performance bottlenecks. We can create a new class called 'LoggingAspect' and annotate it with and to indicate that it's an aspect and a Spring-managed bean. We implement a pointcut expression to target the methods you want to measure. For example, you can target all public methods in a specific package. We then implement an around advice to measure the execution time and log the results. @Aspect @Component Here's an example of a : LoggingAspect @Aspect
@Component
public class LoggingAspect {
  private static final Logger logger = LoggerFactory.getLogger(LoggingAspect.class);

  @Pointcut("execution(public * com.example.myapp..*.*(..))")
  public void publicMethods() {}

  @Around("publicMethods()")
  public Object logExecutionTime(ProceedingJoinPoint joinPoint) throws Throwable {
    long startTime = System.currentTimeMillis();

    Object result = joinPoint.proceed();

    long elapsedTime = System.currentTimeMillis() - startTime;
    logger.debug("Method [{}] executed in {} ms", joinPoint.getSignature(), elapsedTime);
    return result;
  }
} Pointcut methods are empty because their sole purpose is to define a pointcut expression, which determines the join points (i.e., specific points in the execution of a program) where the aspect should be applied. The method body itself does not contain any logic, as the behavior of the aspect is defined in the advice methods (e.g., , , , etc.). @Before @After @Around The pointcut method serves as a reusable reference to a specific pointcut expression, making it easier to maintain and update if needed. By referring to a pointcut method in your advice methods, you can apply the same pointcut expression to multiple pieces of advice without duplicating the expression. We will see that in action below. After implementing the , we can run our application and observe the logs. We should now see the execution time for each targeted method as a poor man's profiler. Just like a regular profiler, this tool has many disadvantages and impacts the observed application. However, we can extract valuable data if we tune this correctly. LoggingAspect Logging All Methods One of the common problems we face in big projects is flaky tests and failures. These are especially hard to understand as we might not have enough logging data. Adding logs to the entire application is impractical in most cases and we’d only want such logs for specific CI executions. We wouldn’t want to over-log in production or even maintain such logging code. However, knowing the parameters that every method received and its return value can lead us to understand a failure after the fact. The following code shows such a logger that can print out every entry/exit and the arguments or return values: @Aspect
@Component
public class LoggingAspect {
    private static final Logger logger = LoggerFactory.getLogger(LoggingAspect.class);

    @Pointcut("execution(public * com.example.myapp..*.*(..))")
    public void publicMethods() {}

    @Around("publicMethods()")
    public Object logMethodEntryAndExit(ProceedingJoinPoint joinPoint) throws Throwable {
        // Log method entry and arguments
        Object[] args = joinPoint.getArgs();

        logger.debug("Entering method [{}] with arguments: {}", joinPoint.getSignature(), Arrays.toString(args));

        // Execute the target method and capture the return value
        Object result = joinPoint.proceed();

        // Log method exit and return value
        logger.debug("Exiting method [{}] with result: {}", joinPoint.getSignature(), result);

        // Return the result
        return result;
    }
} The Tip of the Iceberg Logging to keep track of performance or method entry/exit is powerful but basic. We can go much deeper than that. We can create an aspect to log incoming HTTP requests and responses. This aspect intercepts the methods with the annotation, which is typically used for handling HTTP requests in Spring Boot applications: @RequestMapping @Aspect
@Component
public class RequestResponseLoggingAspect {
    private static final Logger logger = LoggerFactory.getLogger(RequestResponseLoggingAspect.class);

    @Pointcut("@annotation(org.springframework.web.bind.annotation.RequestMapping)")
    public void requestMappingMethods() {}

    @Around("requestMappingMethods()")
    public Object logRequestAndResponse(ProceedingJoinPoint joinPoint) throws Throwable {
        HttpServletRequest request = ((ServletRequestAttributes) RequestContextHolder.currentRequestAttributes()).getRequest();
        logger.debug("Request: {} {} - Parameters: {}", request.getMethod(), request.getRequestURI(), request.getParameterMap());
        Object result = joinPoint.proceed();
        if (result instanceof ResponseEntity) {
            ResponseEntity<?> responseEntity = (ResponseEntity<?>) result;
            logger.debug("Response: Status {} - Body: {}", responseEntity.getStatusCode(), responseEntity.getBody());
        }
        return result;
    }
} Another important aspect is bean creation and destruction. We can create an aspect to log these events. This aspect intercepts the methods annotated with and which doesn’t apply to all beans but would help us keep track of the applicable code in a large application: @PostConstruct @PreDestroy @Aspect
@Component
public class BeanLifecycleLoggingAspect {
    private static final Logger logger = LoggerFactory.getLogger(BeanLifecycleLoggingAspect.class);

    @Pointcut("@annotation(javax.annotation.PostConstruct)")
    public void postConstructMethods() {}

    @Pointcut("@annotation(javax.annotation.PreDestroy)")
    public void preDestroyMethods() {}

    @After("postConstructMethods()")
    public void logBeanInitialization(JoinPoint joinPoint) {
        logger.debug("Bean Initialized: {}", joinPoint.getTarget().getClass().getSimpleName());
    }

    @Before("preDestroyMethods()")
    public void logBeanDestruction(JoinPoint joinPoint) {
        logger.debug("Bean Destroyed: {}", joinPoint.getTarget().getClass().getSimpleName());
    }
} We can even log dependency injection events. This aspect intercepts the methods with the annotation. It doesn’t track constructor injection though but we can use it to track the instance type that gets injected into a bean: @Autowired @Aspect
@Component
public class DependencyInjectionLoggingAspect {
    private static final Logger logger = LoggerFactory.getLogger(DependencyInjectionLoggingAspect.class);
   @Pointcut("@annotation(org.springframework.beans.factory.annotation.Autowired)")
    public void autowiredMethods() {}

    @Before("autowiredMethods()")
    public void logDependencyInjection(JoinPoint joinPoint) {
        logger.debug("Autowired: {} - Target: {}", joinPoint.getSignature(), joinPoint.getTarget().getClass().getSimpleName());
    }
} Final Word AOP is a fantastic debugging tool. In this post, I skimmed a lot of big ideas and overused logging. When tracking performance a better approach would be to accumulate values and then log the statistics in the end, thus removing the overhead of the logger (which impacts the results). The one thing I recommend is turning this off by default. It’s important to run a CI cycle without AOP, the cost is too big and we can seriously impact the final result. We need to turn this on surgically when we need to understand something deep. In those situations, AOP tooling can make the difference when searching for that needle in the haystack. Also published . here

Spring Boot Debugging with Aspect-Oriented Programming (AOP) to Increase Modularity

Welcome back to the Power Leaders series -- interviews with tech leaders who are leading change, innovation and disrupting their respective industries. The next interview is someone I have followed since practically day one in her role at investing platform Public.com. She has since grown into her current title as GM, IR Innovation and has been one of the key brains behind Public’s viral marketing campaigns, like “ ” with Michael Bolton and this . Break Up with Your Brokerage TikTok ad campaign I’m always excited to learn from people actually DOING in the world -- and Katie is definitely someone who consistently walks the talk. Here we go… SE: What innovations are you bringing to your industry? What sets you apart from your competitors? KP: There are a lot of factors that go into competitive differentiation. For us, it’s always been about playing our own game and building at the intersection of our mission—which is to make the public markets work for all people—and the evolving needs of retail investors. For example, we were the first investing platform to offer real-time fractional investing.  In 2020 we were the first brokerage platform to provide Safety Labels on assets that may be potentially risky. In 2021, we made the decision to eliminate PFOF from our revenue model (most of our peers still make money this way), and we’re also the first and only investing platform to provide live shows that give our users breakdowns of trending market news and events. We’re also one of the few platforms that offer the ability to buy T-bills as a cash-alternative alongside investments in other assets like stocks, ETFs, and cryptos. A mentor of mine used to quote Game of Thrones and say, “Chaos is a ladder.” While nobody wishes for market turbulence, we’ve seen these times drive huge personal growth for our community, and opportunities for us to step up for our customers and delight them with features that help them become better investors. SE: What is a recent win or announcement your company just celebrated? Why does it matter? I’m personally excited about . We’re providing a frictionless way to buy government-backed treasury bills, which are widely regarded as one of the safest places to park uninvested cash since their backed by the full faith and credit of the U.S. government. KP: Treasuries on Public We’ve also been hard at work programming, , a first-of-its-kind retail investor conference that provides a full day of programming that’s free and open to any retail investor, anywhere in the world. The speaker lineup is incredible, and it includes Rep. Abigail Spanberger (VA-07), one of the leading voices advocating for a congressional stock trading ban, A Starting Point co-founder and actor Chris Evans, Cathie Wood, and more than 20+ professors, policy experts, executives, and experts. The conference is taking place on Wednesday, March 29 and you can RSVP .\ Exchange here Finally, I can’t disclose the details just yet, but we’re soon announcing a major content series designed to help investors improve their proficiency when it comes to fiscal and monetary policy. We’ll be announcing that in April, so stay tuned for more. SE: What pain point(s) does your company solve? KP: Public was founded with the mission to make the public markets work for everyone. Our platform makes it possible to manage all of your investments, all in one place, across a range of asset types including stocks, treasuries, crypto, ETFs, and alternative assets. We’ve also differentiated by offering access to insights, via analysts, experts, and executives—as well as advanced data and metrics—so that our members can navigate market events and become better investors. SE: What are your company’s industry major challenges right now? KP: Looking back to the past few years, when most people think of investing democratization, they think of zero-commission structures and making it easier for people to buy and sell assets. Our mission to “make the markets work for all people” includes reducing friction to assets (T-bills being a recent example), but also includes other ways we are aligning our roadmap and business structure to meet the needs of modern retail investors. In 2021, we removed Payment for Order Flow (PFOF) from our business model in order to align our incentives with the best interests of our members. We also believe that access shouldn’t stop at assets, and so we’ve placed a specific focus on embedded context in the platform. This is extremely important during times of uncertainty and volatility. We’re also giving our members direct access to the analysts, experts, execs, and thinkers that have historically only been accessible to institutional investors. On March 29, we’re hosting our first virtual conference, which is free and open to the public. Speakers include Rep. Abigail Spanberger (VA-07), co-author of the TRUST in Congress Act to ban congressional stock trading, __ __s Chris Evans and Mark Kassen, ARK Invest’s Cathie Wood,  NYU Stern professors Scott Galloway and Aswath Damodaran, fintech policy expert and Georgetown Professor Dr. Chris Brummer, and many more. Exchange, A Starting Point’ SE: What stories aren’t currently being told about your industry that your audience should know? KP: To my prior point, I think some of the commentary around retail investors is somewhat reductive and fails to capture the nuances of these investors. In my role at Public I have a front row seat to the evolving behaviors, habits, and strategies of retail investors. The “meme investor” stereotype is inaccurate in our view, because what we’ve seen is an evolution of retail investors with 63% of them telling us that persevering through volatility in 2022 has inspired them to be more focused on fundamental analysis and research. The stock market went mainstream in 2021, and it’s true that for some investors, their first introduction to the market may have been a meme stock or crypto, or perhaps seeing Pete Davidson portray a GameStop trader on SNL. At Public, we think that the more entry points and introductions people have to the market, the better. There shouldn’t be judgment based on someone’s entry point, because that’s just the beginning of the journey. Our data shows that for most people whose first investment on Public was a speculative asset, a majority went on to diversify over time. The more mainstream this stuff is the better, and we’re building Public to be the place where you can invest in almost everything, and level up your skills over time. SE: How do you envision your business changing in the next 3-5 years? KP: We will continue to advance on our mission of making the public markets work for all people. We are constantly listening to our members and adding and shaping our product in response to their evolving needs. This means not just focusing on offering stocks or ETFs, but being the investing platform for everything, including alternative assets like fractionalized real estate and fine art,  and additional fixed-income products. When our members were increasingly craving more ways to research deeper metrics and gain insights, we added Public Premium, which is a subscription offering that provides digestible visualizations of key financial metrics and access to exclusive market briefs from top analysts. When we saw our members were increasingly diversifying and de-risking due to market volatility in 2022, we built a way for them to buy U.S. backed T-bills within our platform, saving them the hassle of doing so on the Treasury Direct website. We will continue to iterate as our member needs change and look forward to continuing to be the platform that is meeting the needs of today’s retail investors. SE: What changes do you think are necessary for your industry to stay competitive in current economic times? KP: I can’t speak for the entire industry, but our mindset has always been a balance of optimism with realism. We’re optimistic because we have seen economic volatility introduce investors to new concepts and give them the ability to learn in real-time, sort of like how one gets more fluent in a foreign language by going to a place where it’s spoken. We’re realistic because we understand that for some investors, this is their first real experience with this level of volatility, and so we really work hard to provide context within our platform so you’re understanding the “why” and not just staring at charts and numbers. I also think fintech companies, especially those within concentrated markets, need to develop a lot of empathy when it comes to their customers, and take the time to listen to and understand them, instead of applying one’s own biases without regard for how a diverse range of customers might think and behave. SE: What measures has your organization taken to ensure you're driving towards the most important goals? Our mission is embedded in the entirety of our platform, from business structure to product to editorial and everything in between. We also have well-established cultural principles that guide our ways of working and how we drive toward our goals. Our #1 principle is “Honesty kills bullshit,” which establishes a baseline of honesty through which we communicate and achieve efficiency. Setting a tone of being (respectfully) candid allows us to move fast, make collaborative decisions quicker, and maintain speed to market as our company scales. KP:

POWER LEADER: Public's Katie Perry talks rise of the retail investor evolution

What can stop a startup from taking off? The idea, the team, and the product are the core of any startup, which grows in sales and takes off into space. To get off the ground, we need a massive acceleration. Whoever is first is the fastest to achieve growth. In this article, I will tell you . how you can speed up the process of product creation and how you can create an admin panel in the shortest possible time What do I need a CMS for? In our company, , we attract developers from different IT sectors to our web platform and suggest they go through our automated system of hard skills assessment. They must pass quizzes and coding tasks. After that, an HR specialist is assigned to the candidate. He conducts an interview with him during which his experience, grade (junior/middle/senior), and soft skills are evaluated. As a result of the interview, HR prepares a detailed CV for the candidate. Insquad Thus, my team of developers and I had the task of creating a CMS system that would allow: Track each candidate’s status and all relevant information in real-time Fill out and edit each developer’s resume Group, filter, sort, and show data in different formats to track statistics and search Manage users with role-based access In addition to the points mentioned above, the system . Since a startup is constantly testing new hypotheses and everything is changing very quickly, you need flexibility. For example, add a column and formula at any time to calculate HR professionals’ KPIs. Besides, creating a simple and intuitive interface is difficult. The CMS needs to implement new features quickly and be flexible, understandable, and scalable. must be flexible with a user-friendly interface What were our solutions? Continuing to process data manually is not our option; we must develop quickly. A customized solution is expensive and time-consuming for a startup like ours. While researching, I identified possible solutions to speed up the creation of the system: Use some libraries, for example, or . This solution has disadvantages: long and expensive to develop; it is not a flexible solution at all) react-admin admin.js An out-of-the-box solution, for example, . It allows you to configure a universal interface for your data storage and has a bunch of integrations. This service provides a dashboard and a set of widgets. It’s a quick solution but not as flexible as I’d like it to be. The big disadvantage of this system is that you have to write a CRUD API to integrate with it. Any addition or change of data involves changes to your working database and changing your API. Forestadmin Airtable is a cloud service with the most versatile interface. It is more flexible than the previous one, because the data is stored on Airtable. The necessary data can be added at any time. For full integration, you only need to implement a synchronization service with your own internal database. Why Airtable? So we settled on Airtable. It acts as a CMS for data processing. How does it differ from Excel spreadsheets and Google sheets? In addition to its user-friendly interface, it is not only about working with spreadsheets. The View functionality in Airtable allows you to show data from a table in various formats: gallery, timeline, calendar, grid, kanban, Gantt chart, etc. Default tools such as sorting, grouping, filtering and views are implemented very simply. Anyone, even a non-programmer, can easily master them. Pros Airtable provides excellent CMS functions for processing and visualizing data Data can be divided into different workspaces, bases and tables For each table, you can customize views Role-based access setup for team members The service is intuitive and easy to learn for employees who are not familiar with programming and databases There are a lot of integrations As a result, you get a large set of features and save time and money. The paid version of Airtable allows you to use the REST API, gives you access to a whole marketplace of integrated services and automations. Automation is a very useful feature of Airtable, which allows you to write JavaScript scripts and automate various processes. In addition to that, Airtable is a stable company with a large capitalization. Cons Now consider the disadvantages of this service: airtable is paid per user A limited number of entries. For example, if you use a Pro subscription, you will be limited to 50k per base You can’t fine-tune access to each field of the table. Everyone has access to the entire workspace at once. API has a limit of 5 requests per second Hack #1 Here’s how I got around this limitation. The data are duplicated in your database and Airtable. It can change for two reasons: Changing data on the side of our server, which updates the data in the private database and Airtable Editing data by the HR department in Airtable To get around the limits in the first case, I wrote a proxy function that buffers all requests and, on timeout, updates the data in Airtable with one batch request. The code of this function: import * as Airtable from 'airtable';
import { RecordData, FieldSet, Table } from 'airtable';

enum Action {
  CREATE,
  UPDATE,
  DELETE,
}

class AirtableProxy {
  private timeout = 1000 * 3; // 3 second delay
  private airtable: Table<FieldSet>;
  private batchCreate: { fields: Partial<FieldSet> }[] = [];
  private batchUpdate: RecordData<Partial<FieldSet>>[] = [];
  private batchDelete: string[] = [];

  constructor() {
    this.airtable = new Airtable({
      apiKey: process.env.AIRTABLE_API_KEY,
    })
      .base(process.env.AIRTABLE_BASE_ID)
      .table(process.env.AIRTABLE_TABLE_NAME);
  }

  private async _registerTimer(action: Action) {
    if (action === Action.CREATE) {
      setTimeout(async () => {
        const data = this.batchCreate;
        this.batchCreate = [];
        await this.airtable.create(data);
      }, this.timeout);
    }

    if (action === Action.UPDATE) {
      setTimeout(async () => {
        const data = this.batchUpdate;
        this.batchUpdate = [];
        await this.airtable.update(data);
      }, this.timeout);
    }

    if (action === Action.DELETE) {
      setTimeout(async () => {
        const data = this.batchDelete;
        this.batchDelete = [];
        await this.airtable.destroy(data);
      }, this.timeout);
    }
  }

  public async create(data: Partial<FieldSet>) {
    const setTimerFlag = !this.batchCreate.length;
    this.batchCreate.push({ fields: data });
    if (setTimerFlag) this._registerTimer(Action.CREATE);
  }

  public async update(data: RecordData<Partial<FieldSet>>) {
    const setTimerFlag = !this.batchUpdate.length;
    this.batchUpdate.push(data);
    if (setTimerFlag) this._registerTimer(Action.UPDATE);
  }

  public async destroy(data: string) {
    const setTimerFlag = !this.batchDelete.length;
    this.batchDelete.push(data);
    if (setTimerFlag) this._registerTimer(Action.DELETE);
  }
}

export default new AirtableProxy(); It is essential to know that the official Airtable for Node.js has built-in logic to handle the speed limit. library Hack #2 To get around the limits in the second option — editing data in the Airtable, we wrote a separate service that transfers all the changes from the Airtable to our private database every few minutes. Link to the repository: https://github.com/AbrSergey/serverless-airtable-sync-cron Overall, I found Airtable suitable for creating a full-fledged CRM system for a project. And the presence of a convenient API and multiple integrations speeds up the project’s launch and saves a lot of money, which is crucial for a startup. Conclusion Since the IT market evolves quickly and unpredictably, a startup needs time to grow and transform at the same speed. Airtable allows you to make a product from scratch in a tight timeframe. And with the several listed hacks, you can build a complex flexible solution. I hope the information I have provided above is helpful and will simplify startup developers' life. If you are scaling your development team, contact us at to scale your team 4x faster with remote startup developers. Insquad

How to Use Airtable as a CMS for a Startup

Public Chain, Cross-Chain, and Everything Else You Need to Know for the Coming Year Views expressed below are the analytical views of the and should not form the basis for making investment decisions, nor be construed as a recommendation or advice to engage in investment transactions LD Capital 2021 proved to be another big year for blockchain technology. Not only did we see the introduction of a variety of new cryptocurrencies, but we officially hit 70 million registered blockchain wallets. And while there was quite a bit of ebb and flow in terms of coin value, the explosion of NFTs proved the blockchain is anything but predictable. But what about 2022? Well, that's what we're going to discuss in this report. Below, you'll find a comprehensive list highlighting everything investors, developers, and blockchain-curious individuals need to know. Ethereum & Layer2 Are Poised for Major Expansion Throughout most of 2021, the development direction of Ethereum primarily focused on decentralization. This made sense, as decentralization is key to developing a safe, reliable, and expandable ecosystem. Of course, developers need to ensure decentralization of the underlying public chain to guarantee high-performance transactions. Therefore, it's necessary to transfer settlement to the Layer2 network, which operates above the main Ethereum network, to improve efficiency. Layer2 is often commonly associated with rollups because it aggregates or "bundles" transactions together, executing them in a new environment before sending the restructured transaction data back to Ethereum. To accomplish this, Layer2 uses two different sets of technical solutions: optimistic rollups and ZK Rollups. Teams are currently developing corresponding networks for both of these technical routes. However, they also have ecological support, such as Arbitrum for Optimistic rollups and dYdX for ZK Rollups. Based on the speed at which things are moving, 2022 may be the year that the Ethereum consensus mechanism will be changed from POW to POS. Currently, we anticipate this milestone event occurring in the second quarter, but things can always change. Once this happens, the general consensus is that Ethereum and its second layer expansion technology will have formed their primary framework. Even without considering if or when sharding technology is implemented, this new framework should be able to handle far more complex and high-frequency applications. That said, if POW turns to POS, a large number of users who staked Ethereum 2.0 may sell their assets on the market. After all, when Ethereum 2.0 started staking, the price was less than $600. However, the price of Ethereum will most definitely be much higher at that time. It would be more than enough temptation to trigger a potential sell-off, but it is far from a certainty. What is clear is that 2022 will be a year of continuous, rapid development of Ethereum technology, and the results will be very interesting. Layer 1 is Currently at a Crossroads After talking about Ethereum, we cannot ignore another major driver of 2021's bull market. Specifically, I'm talking about the increase in the application of Layer 1. As you may know, Layer 1 is currently dominated by new public chains like Solana, Avalanche, Terra, Binance Smart Chain, HECO, OKEX, AVAX, NEAR, and FTM. Altogether, the ecosystem has a net worth of over $10 billion. These new public chain answers can be divided into two categories: those that are incompatible with the Ethereum Virtual Machine (EVM) and those that are. Those in the former group will pose a challenge to the Ethereum ecosystem in the long run, especially those public chains that rely on it to boost capital. After all, the underlying value in the public chain is that it can carry a massive, independent ecology. So if the underlying public chain cannot be as technically decentralized as possible, creating such an ecology would be impossible. There Will Likely Be More Growth in Sidechain In the past year, we saw a growth in another solution known as "sidechain." This is essentially a chain built between Layer 1 and Layer 2. And while it is partially compatible with the Ethereum mainnet, it is not part of Layer 2. Instead, the sidechain is specifically designed to handle the excess capacity of Ethereum and to host Ethereum applications in a complementary way. However, it is not designed to compete with Ethereum as a whole. In mid-2021, a particular sidechain called "Polygon" attracted people's attention. Now – just a few months later - Polygon is an industry leader with a value of nearly $5 billion US. On top of that, its ecosystem has deployed more than 100 DeFi and game applications, including the most mainstream Aave and Sushiswap, among others. Polygon claims to be a scaling solution aggregator, but Uri Kolodny, the co-founder of StarkWare, emphasizes that Polygon is a sidechain rather than Layer 2. This is meant to imply that Polygon's security does not depend on Ethereum. Moreover, it's clear that Polygon is not helping Ethereum grow, but is instead expanding its own capacity. Similar to BSC, it is a completely independent Ethereum clone based on a POS mechanism. It takes advantage of the ready-made Geth by removing the consensus code, increasing the gas limit, and using multisig as a bridge back to Ethereum. Around August of last year, Polygon announced an investment of $1 billion for work related to ZK-rollup. Since then, two acquisitions – totaling $650 million - have since been announced: Hermez and Mir. Even more recently, the group behind Polygon announced "Polygon Miden," a STARK-based Ethereum-compatible rollup, and Polygon Nightfall, a privacy-focused rollup built in partnership with EY. Unlike BSC or Avalanche, which simply copy the Ethereum ecology, Polygon's imitation of Ethereum is far more exact (and more complete). In fact, at the time of this writing, the gas fee of Polygon is less than 0.01% that of Ethereum, and the speed is comparable to that of BSC. This means that if ZK-SNARKs can be realized, it will be the most prominent EVM-compatible option in the public chain. Cross-Chains Are Poised to Be a Game Changer Despite what some "experts" may say, Cross-chain is something we can't avoid discussing. After all, if blockchain technology continues to develop, the future world of web3.com cannot be dominated by only one blockchain. Instead, it must be an ecosystem with multiple chains and currencies coexisting in parallel. Polkadot and Cosmos are two cross-chain architecture projects that have garnered attention in recent months. The vision behind their development is to provide a strong underlying security system to connect various public chains and create a space where different blockchains with different functions can coexist and communicate in this network. Essentially, we're talking about an "Internet of Blockchains." For example, Bitcoin and Ethereum are the two most popular public chains at present. And while they are both blockchains, they are two completely independent and unique animals. They are therefore, unable to communicate with each other. The goal with Polkadot and Cosmos is to enable separate blockchains like Bitcoin and Ethereum to connect and form a network – to "talk" to one another. In simple terms, this would solve the problem of "information islands" existing between chains. With cross-chain infrastructure, we would be able to share data between chains in an extremely secure manner. Developers could also create "cross-chain" applications. For example, the application of views on Ethereum could not only be used on that chain but also on others. That said, these two cross-chain projects have stark differences in both design concept and focus. For instance, Polkadot is lagely focused on centralization. That is, the block verification of the side chain ecology will be provided by Relay chain, as will computing and security. With such a design, any chain accessing the network would not need to recruit verifiers themselves. Cosmos, on the other hand, advocates decentralization. This means that the Cosmos hub is really only there to coordinate interaction and record / transmit data. As a result, other side chains connecting to the network would need to complete their own ecological governance. But there's more to it than that. Polkadot's management philosophy also favors centralization. In a way, it would focus on serving the architecture, much like Dapp. But since Dapp has no verifier ecology and only connects users and chain data, the entire security would be provided by Polkadot itself. Polkadot is also a more long-term and ambitious concept, with plans to emphasize the data exchange of each chain. Cosmos is more pragmatic and more practical, instead emphasizing the exchange value of tokens. In terms of cross-chain focus, Polkadot aims to achieve arbitrary message passing between parachains. Cosmos instead focuses on cross-chain asset transfer, and its protocol is far simpler. From the perspective of ecology, Terra grew significantly in the Cosmos ecosystem throughout 2021. In fact, according to a recent report released by Electric Capital, the number of full-time Terra developers more than tripled from December 2020 to December 2021. Taking this into account, 2022 will likely be marked by cross-chain growth as funds and investors gradually turn their attention to these two ecologies and the projects they contain. If this happens, both Polkadot and Cosmos are likely to give us an impressive performance, offering up multiple high-traffic projects that are likely to be compatible with the Ethereum Virtual Machine (EVM). In terms of technology, Polkadot will probably get the majority of the attention. After all, the scenarios it will be realized are the same that will be realized by Ethereum 2.0 in the future. And while there is still a big gap between Polkadot and Ethereum 2.0 in a lot of ways, the basic technical framework of the two remains quite similar. 2021 was a big year. Still, technology is all about moving forward, not backward. If recent history is any indication, we can expect massive growth and significant advances in multiple areas before the end of the year 2022. From Layer2 to sidechain to cross-chain, there's a lot to look forward to.

The Blockchain Forecast - from Public Chain to Cross-Chain, Everything You Need to Know in 2022

Stories, News & Mentions about PUBLICCOM

Publiccom’s Stories on HackerNoon