Unmand

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Drones like these allow military personnel to remotely conduct surveillance and occasional combat operations if the UAV has onboard weaponry, while minimizing the risks to their soldiers. Although UAVs were initially used for military applications, they have since expanded into various civilian sectors. When people hear the term UAV (Unmanned Aerial Vehicle), the first thing that comes to mind are the drones used by the military, such as the or the RQ-12 Wasp. MQ-1 Predator 1.Delivery One such use for drones is the use in delivery services. By using UAVs for deliveries, companies such as Amazon could save money on shipping costs, which would reduce costs for consumers, who would receive their packages more quickly and reliably. . In November 2016, Domino’s delivered an order of a Peri-Peri Chicken Pizza and a Chicken and Cranberry Pizza to a customer in Whangaparaoa, New Zealand. The first successful delivery with a UAV was a pizza delivery Delivery drones have also been used to such as blood products, vaccines, pharmaceuticals, and medical samples. Whereas ground vehicles may not be able to reach a remote destination due to difficult terrain, a UAV can make the delivery with ease. These drones have been credited with saving lives by , as well as personal protective equipment and COVID-19 tests during the pandemic in the United States, Israel, and Ghana. transport medicinal products delivering blood in Rwanda 2.Journalism In recent years, UAVs have provided journalists with a unique and cost-effective way to capture footage and images from hard-to-reach places. Using a drone, news reporters can cover important events from various angles that would be impossible for a hand-held camera to capture. Additionally, can be used to capture footage from dangerous or inaccessible locations, such as war zones or natural disasters. drones It’s important to note that the use of drones in these situations must comply with , as well as sports league, venue, and local law enforcement agency rules. Federal Aviation Administration (FAA) regulations 3.Search and Rescue Search and rescue operations are often tricky and unpredictable. Time is paramount, as the missing person is most likely trapped in a life-threatening situation. And depending on the location, the terrain can make things exponentially more difficult for the rescue team. Using UAVs, the rescue team can cover more ground faster than if they were using ground-based vehicles. These drones can also provide an aerial view of the area and carry various sensors to identify specific objects and heat signatures on the ground, providing much-needed situational awareness. in June 2017, two hikers were reported missing in Pike National Forest in Colorado. Search and rescue teams, comprising twenty-five volunteers, searched on foot, with ATVs, and with the aid of a K-9 team. But it was the team using a UAV that found the two hikers in an area spanning thousands of acres in just two hours. In one such case https://www.youtube.com/watch?v=Y1VPZ5jt5Xw&embedable=true 4.Disaster Response By utilizing drones in disaster relief efforts, dangerous situations can be assessed quickly without placing risks on personnel. For example, During the Fukushima Daiichi nuclear disaster in 2011, without risking the lives of the relief workers. They have also proven excellent first responders since they can be deployed fast and easily compared to manned aerial vehicles. drones were used to survey the extent of the disaster As previously mentioned, drones are excellent at providing an aerial view of the area and can be equipped with infrared (IR) cameras to detect heat signatures. This is vital not only in search and rescue operations but also in surveying unstable areas. When dealing with the aftermath of an earthquake, a partially damaged building or a civic structure requires a thorough inspection before it can be deemed safe for humans to go there. Drones with sensors like IR cameras can survey these sites easily and safely. 5.Firefighting UAVs can also be a massive asset to the men and women who risk their lives fighting fires. They can be immensely useful in providing situational awareness about the fire and its surroundings. By using drones equipped with thermal cameras, firefighters can determine the extent of the fire and identify its source, which can greatly aid them in bringing the situation under control and conducting search and rescue operations. UAVs have also been used as effective tools in monitoring and suppressing wildfires. By using real-time data, firefighters can determine where a fire will move next, allowing them to make a plan for movement and evacuation quickly. In addition to providing important tactical data, UAVs are more maneuverable than helicopters or planes. 6.Agriculture Some of the more common agricultural applications for UAVs include pest control, plant health monitoring, livestock management, soil analysis, and aerial survey. Farmers must maintain constant vigilance, as their crops are susceptible to disease, fungus, and bugs. They also need to be aware of the carbon levels and nitrates in the soil, which can impact a plant’s productivity. Traditionally, farmers must monitor these factors by conducting visual inspections and sending soil samples to a laboratory. By using UAVs, however, these factors can be measured in real-time by utilizing a combination of RGB cameras, thermal imaging, and multi-spectral imaging. The Future of UAVs In this day and age, where technology is rapidly evolving to meet new demands, UAVs could fulfill a number of roles in current and future job sectors. Additionally, many people operate drones for various hobbies, such as photography and drone racing. However, no matter how UAVs get used, operators must ensure that they comply with any rules regarding drone operation in their country. For instance, drone operators in the United States need to obtain a from the FAA before flying a UAV. Remote Pilot Certificate What do you think about these use cases? Do you own a drone yourself? Let me know what you think in the comments below!

6 Important Use Cases for UAVs (Unmanned Aerial Vehicles)

6 usos comunes de los UAV (vehículos aéreos no tripulados)

6 utilisations courantes des UAV (véhicules aériens sans pilote)

यूएवी (मानवरहित हवाई वाहन) के लिए 6 सामान्य उपयोग

UAV (無人航空機) の 6 つの一般的な用途

6 Usos Comuns para UAVs (Veículos Aéreos Não Tripulados)

6 Cách sử dụng phổ biến cho UAV (Máy bay không người lái)

UAV（无人驾驶飞行器）的 6 种常见用途

Infrastructure drift, unmanaged resources, ghost assets, these are all well-known “silent killers” in our clouds.  Whether AWS, GCP, Kubernetes, Azure or anything else, when deploying our services to multiple clouds, we know that a unified inventory and management of our cloud resources is complicated, and there are many great tools out there that are looking to help solve this growing complexity. ‍ One thing that is often overlooked though is where our SaaS tooling comes into the mix.  When we adopt SaaS tools, we tend to see them as just that–tools, and not what they eventually actually are: additional siloed, unmanaged clouds with their own proprietary inventory of services, objects and resources. ‍ A phenomenon we have encountered often, when helping companies overcome drift, is a common neglect of cloud infrastructure tooling, such as CloudFlare, Okta, Mongo Atlas, Datadog, Git and many other popular SaaS platforms and tools that are part of our core operations.  How can we make these SaaS clouds immutable, versioned, scalable and monitored if these extensions aren't codified?  Is state drift in Okta less troubling than drift in your IAM roles, for example? How can we guarantee proper monitoring if our Datadog dashboards make it possible for anyone to cause drifts? ‍ These are just some of the questions that come to mind when we see this recurring anti-pattern in cloud operations today. But you may ask, why does this matter? ‍ If a growing understanding is dawning on DevOps engineers that it is much safer and less error prone to codify cloud resources, including the inherent benefits of managing these resources like all other code––whether the git history, peer reviews, PR automation and policy enforcement, it seems that SaaS service have not yet undergone a similar evolution and epiphany.  If clickops for cloud configuration has mostly been abandoned for IaC practices, SaaS tooling is predominantly still configured manually via the UI with minimal codification. Not surprisingly this leads to many similar problems you’d find in your cloud operations. Putting the Git in GitOps When it comes to Kubernetes and cloud native systems, that are so commonly associated with GitOps practices, which is considered the best practice and modern way for managing complex Kubernetes operations––the git part of gitops is all but neglected when it comes to managing these systems.  I’ll explain. ‍ If we look at the top downloaded Terraform providers for SaaS applications that are not clouds, the list and data is extremely compelling: ‍ DataDog/datadog 32.4M+ integrations/github 16.9M+ cloudflare/cloudflare 16.8M+ newrelic/newrelic 12.5M+ hashicorp/consul 9.7M+ PagerDuty/pagerduty 8.6M+ grafana/grafana 5.4M+ gitlabhq/gitlab 4.8M+ mongodb/mongodbatlas 4.2M+ okta/okta 4M+ elastic/ec 3.2M+ ‍ While there is an increasing trend towards codifying these resources through Terraform providers, if we take the number of downloads of the AWS Terraform provider or the next most popular cloud Azure, these are 750M+ and 127M+ respectively, placing the next most popular non-cloud provider at about 5% adoption (and ultimately codification). ‍ This is because not only would this codification need to be done for each SaaS tool individually, once these tools are configured through clickops, just translating this to IaC is an extremely complex undertaking (particularly in large organizations with multiple dashboards, clouds, services and other dependencies and resources). ‍ If we come back to thinking about how we convert our git operations to be GitOps native, we’d likely need to follow a post similar to this one that walks you through the process of .  And this is just one tool of many in a huge stack of SaaS tooling that would need to undergo a similar transformation, this is another example of a post that walks you through a .  And the list goes on.  Now imagine having 10s of tools, in large organizations––multiple teams and clouds.  The task is daunting just to think about.  Until now. managing your Github organization with Terraform similar transition for Datadog Codifying Your SaaS When thinking about the critical aspects of codifying your SaaS, there are a few angles it was important for Firefly to focus on to make this transition truly valuable for all DevOps teams.  The first layer of value is in the unified inventory of both cloud assets and SaaS assets in a single place. Just this alone enables DevOps teams to search, understand, and classify assets across all clouds––the operational ones or the tooling clouds.  Something that wasn’t possible before from a single dashboard or tool. ‍ The next aspect is actually getting all of these tools and assets managed as code.  If this has become the cloud standard, it’s not clear why this hasn’t happened for SaaS apps too.  We’ve spoken about the benefits of managing everything as code, but eventually once managed as code with the relevant guidelines and internal engineering practices applied, these can then be automated as part of CI/CD processes and the relevant gating & guardrails applied here too. ‍ Doing so manually would require engineers to translate all of their manual configurations (that are not always found in a single place in the UI, across the many layers of their application) into the relevant code configurations, and usually many times over if there are multiple applications, dashboards or tools.  This is now possible at the click of a single button, for all SaaS tools, in one place. ‍ If we take a look at a typical Firefly dashboard, we can see that typical SaaS tools have as low as 20%+ of codified resources, vs. 50% in cloud service providers. ‍ The companies that have flipped this number and codified these resources, were able to enjoy the IaC advantages of faster deployment cycles and standby configuration templates for disaster recovery scenarios. We hope you found this useful - feel free to drop any questions you may have in the comments. ‍

Codify your SaaS Apps: The Answer to the Unmanaged SaaS Jungle

Alibaba’s the Tmall Future Store shows how technology can help offline merchants thrive in the e-commerce age If you’ve ever waited in line impatiently to pay for groceries, chances are you’ve wished you could escape the typical service experience we all tend to encounter as shoppers. While delivery and e-commerce services offer one alternative for people hoping to avoid the hassle, a more recent effort at Alibaba is making it likely that you’ll soon be shopping in stores that let you walk in, grab what you need, and pay automatically as you walk out, simplifying retail for shoppers and merchants alike. To showcase its progress, Alibaba recently unveiled an experimental 80-square meter installation of its new Tmall Future Store at the 2018 Yunqi Computing Conference, inviting attendees to explore a convenience store without a single employee on staff. Inside, they were able to browse for food, snacks, and beverages while getting help as needed from a digital T-guide assistant, then settle their bills by simply exiting the premises. Visitors line up outside Alibaba’s Tmall Future Store at the 2018 Yunqi Computing Conference To further highlight this new mode of shopping, senior technical expert Shi Wei of Alibaba’s Taobao Technology Department addressed the conference with a speech covering where the emerging field of new retail has been so far and where it is going next. Inside, we look at highlights of his speech and explore the technology that is helping make unmanned retail a crucial part of that evolution today. From New Retail to Unmanned Retail While Tmall’s unmanned Future Store presents an entirely new paradigm for shopping, it is only one part of a broader movement to upgrade offline shopping through new technologies, business models, and channels, known together as ‘new retail’. At the most basic level, new retail ranges from vending machines that accept mobile payments to the cheap, open-shelved mini shops many workplaces now offer thanks to digitalized business models that expedite stocking and reduce overhead. On a larger scale, it also encompasses supermarkets like Alibaba’s Hema that combine features of online and offline commerce, as well as cooperative ventures with independent retailers like Starbucks. At the heart of new retail is data, and ways it can be used to reduce pain points for consumers and merchants alike in traditional retail settings. Market analysis indicates that early efforts to remove human workers from retail have been met with mixed reactions from consumers. Nevertheless, the output value for such ventures in China is predicted to rise from RMB 20 billion in 2017 to RMB 65 billion in 2020, driven mainly by rising labor costs, offline operating costs, and consumer demand. With technology now able to support the truly futuristic experience the Tmall Future Store captures, unmanned retail can focus on giving consumers a whole new way to shop, rather than simply upgrading existing options. According to an iResearch study of the Chinese market, 8.5 percent of the country’s consumers prefer to make purchases from human cashiers, while 23.7 percent prefer to scan a code as they leave the store. Beyond this, 29.8 percent prefer to pick up goods from a smart settlement basket that they retrieve at the exit, while an overwhelming 39 percent would prefer to simply walk out with their groceries in a form of automatic settlement. Having cleared the initial hurdle of cultivating demand for experiences like the Tmall Future Store, Alibaba has since been able to focus on the ways its new model can enhance business for its partners, as well as the efficiency of labor in the broader marketplace. In one instance, moving the group’s Alicool souvenir shop to a completely automated framework increased annual turnover by 75 percent and sales volume by 20 percent, attracting 56 percent more consumers than during the previous year. At just 120 square meters, the store is now able to handle as many as 2,300 visitors per day, largely owing to the average 4.5 seconds it takes shoppers to complete automatic settlement when exiting. In another example, Alibaba collaboratively renovated the Zhida Bookstore in Shanghai to enable automatic facial recognition-based settlement, greatly increasing the store’s daily turnover. Notably, Alibaba was able to apply findings from previous efforts to complete the installation of the new facilities in just 53 days, raising the store’s daily turnover by 78.3 percent. A Look Inside the Tmall Future Store With the Tmall Future Store, Alibaba has entered a phase it calls ‘unmanned retail 2.0’, significantly expanding on the capabilities Alicool and the Zhida Bookstore demonstrate. As well as a technical upgrade, the new phase involves a shift of emphasis from impressing customers to attracting existing merchants to the concept. Technically, the key advance captured in the Tmall Future Store is computer vision. Upon first entering the shop, customers scan a code with their phones to establish their virtual presence there. Once they have done so, a series of roughly 100 screens will respond as they move through the store, making personalized recommendations and providing directions to help locate items. At shelves, the system uses gravity sensors and built-in cameras to identify and add goods to customers’ virtual shopping carts. This enables customers to simply leave when ready, as the system will automatically collect payment for any items which have not been returned as they exit. To document these transactions, the system generates a virtual bill which appears in customers’ Alipay or Mobile Taobao accounts, and the items in the virtual bill will also include links for repurchasing if they are available online. A view of customer guidance systems inside the Tmall Future Store As a whole, this user experience traces the interaction of three core systemic capabilities: global tracking, product identification, and user-item matching. The last of these is by far the most critical, as any confusion that results in a payment being deducted from the wrong customer can invalidate the idea that automation can replace human services. In an example of how this can happen, visitors to the store at the conference occasionally crossed arms reaching for items, swapped items, or offered to help each other return items, challenging the algorithm to sort out conflicting digital impressions. The best solution to such problems is prevention through the effective digitalization of offline behavior, presenting an ongoing challenge for developers as they seek to make these novel capabilities fully marketable. Continuing Development for the Future In its present state, the Tmall Future Store introduces a coherent “6+1” technical architecture, in which five processing ends and a local gateway interact together with a coherent set of business priorities — namely transaction, processing, operating, and data storage in the cloud. While anyone hoping to open a store could work from this architecture, preparing it for widespread marketing still requires the targeted improvement of algorithm capabilities, reduction of hardware costs, and reduction of deployment costs. An overview of Alibaba’s most recent architecture for unmanned retail environments, now undergoing further development One current example of an algorithmic limitation is the need for customers to cooperate with sensors by standing still while selecting items or completing settlement. Ideally, scanners should be equipped to handle some amount of motion or other variations, presenting a complex deep learning problem for optimization. Further, the system’s facial recognition component uses an initial scan image of each customer as a “one-off” point of reference. As even human observers may struggle to tell whether two images from different angles show the same person’s face, refining the recognition algorithm poses formidable challenges. Another outstanding challenge is to make algorithms more adaptable across environments, as each new unmanned store requires deploying and training the model to work within its specific dimensions and conditions. The key to doing so is separating the tuning of specific parameters from the model, which can be done using information gathered through the repeated deployment of its environmental sensors in different environments. In terms of market entry barriers, hardware costs remain preventive, not because they must be high but because the processing challenges developers currently face place heavy demands on equipment. Moreover, transforming a traditional brick-and-mortar shop into an unmanned store takes up a great deal of time, as engineers need to work on a by-case basis to update devices and systems one by one. To reduce costs, Alibaba is working to narrow down the functionality of devices. Because the cost of increasing computing power is not linear, boosting central server power to cover more end functions is not viable in the age of edge computing. To counter this, cameras and screens deployed in unmanned stores will need upgrades to their own computing power. Another cost reduction approach in the works is device standardization. By making all devices replaceable, repairable, and consistent, developers hope deployment and maintenance processes can be streamlined and standard procedures enabled. This would allow for a robotic approach to off-hours maintenance and inspection for both hardware and AI. With the ultimate goal of establishing a device management system, developers are seeking applications for an Alibaba Cloud product called Linkedge, which can be used to develop a hot-swappable HAL layer for the framework that uploads and downloads device information for monitoring. In effect, this means the system will be remotely upgradable, deployable across different devices, and primed for the addition of new functions — in short, perfectly suited to the mobile era. Looking Ahead To summarize the importance of the Tmall Future Store, Alibaba’s Shi Wei described it as an offline Taobao designed to be as interactive as the mobile phones that shoppers carry in with them. Like the first wave of online commerce that Taobao emerged with, it is offering new ways to study people’s habits and preferences as shoppers, making stores both a laboratory for understanding economic activity and a setting for putting that knowledge to use. Some of the many ways data from unmanned retail stores can help merchants thrive With the rise of e-commerce, many have voiced fears that platforms like Taobao will eventually make offline retail obsolete. With its Tmall Future Store, Alibaba is showing how the technology enabling it might instead be used to improve business for offline merchants, helping them to make smarter choices and better returns on investment. As a first step in unmanned retail, its completion should provide a valuable foundation for developments to come. Alibaba Tech First hand and in-depth information about Alibaba’s latest technology → Facebook: . Twitter: . “Alibaba Tech” “AlibabaTech”

New Meaning to Grab and Go: Alibaba Unveils its Unmanned Store

GOTO Chaos: Spaghetti Code This article is dedicated to the late Thomas E. Kurtz, one of BASIC's creators, as it was the first programming language I learned. TL;DR: GOTO statements create confusing and unmaintainable code Problems Logic becomes unclear
Debugging gets harder
Flow jumps erratically
Code lacks structure
Maintenance becomes difficult Solutions Use structured programming
Replace with loops
Simplify control flow
Avoid unnecessary jumps Context Spaghetti describes code that is poorly structured and difficult to understand. It often involves deeply nested loops, excessive use of goto statements, and complex control flow. When you overuse GOTO statements, your program becomes a tangled mess of uncontrolled jumps. This was common in the 70s when BASIC encouraged GOTO for flow control. While it can solve simple problems quickly, GOTO leads to spaghetti code that’s nearly impossible to debug or extend. Spaghetti Code << Structured Programming << Object-Oriented Programming << Machine Learnign Programming Sample Code Wrong 0 REM Request a Zero
10 INPUT "Enter a number: ", N
20 IF N = 0 THEN GOTO 50
30 PRINT "Number is non-zero"
40 GOTO 10
50 PRINT "Goodbye"
60 END Right 10 DO
20   INPUT "Enter a number: ", N
30   IF N <> 0 THEN PRINT "Number is non-zero"
40 LOOP UNTIL N = 0
50 PRINT "Goodbye"
60 END Detection [x]Automatic You can detect this smell by scanning for frequent GOTO usage, especially when they jump between unrelated code sections. Look for logical breaks caused by excessive jumping and ask if structured control flow can replace them. Tags Coupling Level [x]Beginner AI Generation AI generators can include GOTO when mimicking older coding styles. They might use it for simplicity without considering modern best practices. AI Detection You can instruct AI to replace GOTO with loops or structured constructs like IF-ELSE or WHILE. Try Them! Remember: AI Assistants make lots of mistakes Without Proper Instructions

With Specific Instructions



ChatGPT

ChatGPT



Claude

Claude



Perplexity

Perplexity



Copilot

Copilot



Gemini

Gemini Conclusion Overusing GOTO creates chaotic and unmanageable code. Replace it with structured programming techniques to improve readability and maintainability. Relations https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-xx-we-have-reached-100 More Info https://en.wikipedia.org/wiki/BASIC?embedable=true Disclaimer: Code Smells are my opinion. Credits: Photo by Sofia Ciravegna on Unsplash “Spaghetti code is a program with its logic tangled like spaghetti. Avoid the tangles, and you simplify your life.” - Martin Fowler https://hackernoon.com/400-thought-provoking-software-engineering-quotes?embedable=true This article is part of the CodeSmell Series: How to Find the Stinky Parts of your Code GOTO Chaos: Spaghetti Code GOTO Chaos: Spaghetti Code This article is dedicated to the late Thomas E. Kurtz, one of BASIC's creators, as it was the first programming language I learned. This article is dedicated to the late Thomas E. Kurtz, one of BASIC's creators, as it was the first programming language I learned. This article is dedicated to the late Thomas E. Kurtz , one of BASIC 's creators, as it was the first programming language I learned. Thomas E. Kurtz BASIC TL;DR: GOTO statements create confusing and unmaintainable code TL;DR: GOTO statements create confusing and unmaintainable code Problems Logic becomes unclear Debugging gets harder Flow jumps erratically Code lacks structure Maintenance becomes difficult Logic becomes unclear Debugging gets harder Flow jumps erratically Code lacks structure Maintenance becomes difficult Solutions Use structured programming Replace with loops Simplify control flow Avoid unnecessary jumps Use structured programming Replace with loops Simplify control flow Avoid unnecessary jumps jumps Context Spaghetti describes code that is poorly structured and difficult to understand. It often involves deeply nested loops, excessive use of goto statements, and complex control flow. When you overuse GOTO statements, your program becomes a tangled mess of uncontrolled jumps. This was common in the 70s when BASIC encouraged GOTO for flow control. While it can solve simple problems quickly, GOTO leads to spaghetti code that’s nearly impossible to debug or extend. BASIC GOTO GOTO Spaghetti Code << Structured Programming << Object-Oriented Programming << Machine Learnign Programming Spaghetti Code << Structured Programming << Object-Oriented Programming << Machine Learnign Programming Sample Code Wrong 0 REM Request a Zero
10 INPUT "Enter a number: ", N
20 IF N = 0 THEN GOTO 50
30 PRINT "Number is non-zero"
40 GOTO 10
50 PRINT "Goodbye"
60 END 0 REM Request a Zero
10 INPUT "Enter a number: ", N
20 IF N = 0 THEN GOTO 50
30 PRINT "Number is non-zero"
40 GOTO 10
50 PRINT "Goodbye"
60 END Right 10 DO
20   INPUT "Enter a number: ", N
30   IF N <> 0 THEN PRINT "Number is non-zero"
40 LOOP UNTIL N = 0
50 PRINT "Goodbye"
60 END 10 DO
20   INPUT "Enter a number: ", N
30   IF N <> 0 THEN PRINT "Number is non-zero"
40 LOOP UNTIL N = 0
50 PRINT "Goodbye"
60 END Detection [x]Automatic [x] Automatic [x] You can detect this smell by scanning for frequent GOTO usage, especially when they jump between unrelated code sections. GOTO Look for logical breaks caused by excessive jumping and ask if structured control flow can replace them. Tags Coupling Coupling Level [x]Beginner [x] Beginner [x] AI Generation AI generators can include GOTO when mimicking older coding styles. GOTO They might use it for simplicity without considering modern best practices. AI Detection You can instruct AI to replace GOTO with loops or structured constructs like IF-ELSE or WHILE . GOTO IF-ELSE WHILE Try Them! Remember: AI Assistants make lots of mistakes Remember: AI Assistants make lots of mistakes Without Proper Instructions

With Specific Instructions



ChatGPT

ChatGPT



Claude

Claude



Perplexity

Perplexity



Copilot

Copilot



Gemini

Gemini Without Proper Instructions

With Specific Instructions ChatGPT

ChatGPT Claude

Claude Perplexity

Perplexity Copilot

Copilot Gemini

Gemini Without Proper Instructions With Specific Instructions Without Proper Instructions Without Proper Instructions With Specific Instructions With Specific Instructions ChatGPT ChatGPT ChatGPT ChatGPT ChatGPT ChatGPT ChatGPT ChatGPT Claude Claude Claude Claude Claude Claude Claude Claude Perplexity Perplexity Perplexity Perplexity Perplexity Perplexity Perplexity Perplexity Copilot Copilot Copilot Copilot Copilot Copilot Copilot Copilot Gemini Gemini Gemini Gemini Gemini Gemini Gemini Gemini Conclusion Overusing GOTO creates chaotic and unmanageable code. GOTO Replace it with structured programming techniques to improve readability and maintainability. Relations https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-xx-we-have-reached-100 https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-xx-we-have-reached-100 More Info https://en.wikipedia.org/wiki/BASIC?embedable=true https://en.wikipedia.org/wiki/BASIC?embedable=true Disclaimer: Code Smells are my opinion. Disclaimer: Code Smells are my opinion . opinion Credits: Photo by Sofia Ciravegna on Unsplash Credits: Photo by Sofia Ciravegna on Unsplash Sofia Ciravegna Unsplash “Spaghetti code is a program with its logic tangled like spaghetti. Avoid the tangles, and you simplify your life.” - Martin Fowler “Spaghetti code is a program with its logic tangled like spaghetti. Avoid the tangles, and you simplify your life.” - Martin Fowler Martin Fowler https://hackernoon.com/400-thought-provoking-software-engineering-quotes?embedable=true https://hackernoon.com/400-thought-provoking-software-engineering-quotes?embedable=true This article is part of the CodeSmell Series: How to Find the Stinky Parts of your Code This article is part of the CodeSmell Series: How to Find the Stinky Parts of your Code How to Find the Stinky Parts of your Code

Code Smell 280 - Spaghetti Code

Every now and then, I stumble upon posts such as these here and there: And, you know what? I just look the other way. Why? Because as a veteran I’m “emotionally compromised” (Star Trek), and more importantly: Without thoroughly analyzing, this is nothing more than wishful thinking. Firstly, you’d have more success convincing people that the Earth is flat than convincing them that it’s possible to completely eliminate fiat. “The International Monetary Fund (IMF) recommends against adopting cryptocurrency as a main national currency in its current state due to price volatility. Additionally, the organization feels that the risks of macro-financial stability and lack of consumer protections should be addressed.” But, at the same time: “The IMF does acknowledge that adoption is most likely to occur more rapidly in countries where cryptocurrency risks are an improvement on the financial system in place. For example, many Ukrainians turned to cryptocurrency after fleeing the Russian invasion in 2022. Without cryptocurrency, many might not have had the money to survive.” ("Global Financial Stability Report, Covid-19, Crypto, and Climate: Navigating Challenging Transitions," Page 52) Look, I don’t like playing this blame game at all. What? Crypto ain’t perfect, but neither are you, my dear fiat. That’s why this particular Greek mythology analogy comes in handy to counterbalance the previous argument. If volatility is the Achilles’ heel of Bitcoin or any other cryptocurrency then the same weakness “of the fiat money system lies in its dependence on the demand for money. History demonstrates that the demand for money remains relatively steady when there is a high level of trust in the currency, meaning people are not worried that the purchasing power of their money will decline or be destroyed. Given this insight, it’s clear how states and their central banks seek to handle the fiat money system in their favor. Their primary strategy involves creating illusions and deceiving the populace to maintain control and influence. For instance, people are often fed the narrative that inflation of 2 percent equates to “stable money”—a claim that is, of course, inherently false. In reality, a 2-percent inflation rate destroys the purchasing power of money by 2 percent every year.” Lack of trust = Fiat is past Demand for money is now demand for crypto: “The global user base of cryptocurrencies increased by nearly 190 percent between 2018 and 2020, only to accelerate further in 2022. The projected revenue in the Cryptocurrencies market for Worldwide is estimated to reach US$56.7bn in 2024.” (Source: Statista) No more money for you warmonger honey! Be(A)ware Bitcoin Friends - Every Stick Has Two Ends Buy Bitcoin! Defund the wars! Unfortunately, it’s not that simple. “Ukraine’s government bought weapons, unmanned aerial vehicles (UAVs, better known as drones) and digital rifle scopes, besides non-lethal tools, with some of the $60 million in crypto donated after Russia invaded the European nation earlier this year, an official revealed in a new breakdown of expenditures.” "We (the Digital Ministry) converted crypto and sen[t] it to our Defence Ministry. They decided that they needed something (lethal weapons). We are at war and we can defend ourselves with every means possible,” Deputy Minister Alex Bornyakov responded when asked about the earlier statement that they would only buy non-lethal weapons through crypto donations. It’d be naive to think that the other side wouldn’t do the same by every means possible, also. “Russia’s largest maker of small arms, Kalashnikov Concern, needed electrical parts for drones that have been among the most effective weapons against Ukrainian armor. The smuggler, Andrey Zverev, took the late 2022 order to a Hong Kong electronics distributor. The U.S. was trying to cut off such deals, and even sanctions-wary Chinese banks were blocking payments from Russia. The solution: Zverev used tether, the cryptocurrency, to relay millions of dollars of funds from Kalashnikov to its supplier.” “We will deliver everything you need to exterminate each other,” he wrote in a Telegram chat. Payment was “ideally with crypto, of course.” The Bitcoin Standard is the solution for forever wars. But, how far away is it in the future? In the meantime, we still have our deeply flawed human nature to deal with. “With no physical properties, this decentralized digital money isn't susceptible to state control, and its users don't need permission to spend their holdings. It's also "the hardest money ever invented," Ammous writes, since Bitcoin's fixed supply of 21 million units is coded into the software. Previously it "proved impossible to come up with a form of money of which more cannot be created," which makes bitcoin the "first example of absolute scarcity." When the late economist Julian Simon observed that human time is the only truly limited resource, Ammous has quipped, he was only correct because Bitcoin hadn't yet been invented.” Now, Bitcoin isn’t only being invented, but also widely and rapidly accepted. However, we can’t say that forever war would be ended and prevented. Image copyright: streetcyber_art, Barcelona Every now and then, I stumble upon posts such as these here and there: And, you know what? I just look the other way. Why? Because as a veteran I’m “emotionally compromised” (Star Trek), and more importantly: Without thoroughly analyzing, this is nothing more than wishful thinking. Without thoroughly analyzing, this is nothing more than wishful thinking. Firstly, you’d have more success convincing people that the Earth is flat than convincing them that it’s possible to completely eliminate fiat. “The International Monetary Fund (IMF) recommends against adopting cryptocurrency as a main national currency in its current state due to price volatility . Additionally, the organization feels that the risks of macro-financial stability and lack of consumer protections should be addressed.” International Monetary Fund (IMF) International Monetary Fund (IMF) against adopting cryptocurrency as a main national currency in its current state due to price volatility But, at the same time: “The IMF does acknowledge that adoption is most likely to occur more rapidly in countries where cryptocurrency risks are an improvement on the financial system in place . For example, many Ukrainians turned to cryptocurrency after fleeing the Russian invasion in 2022. Without cryptocurrency, many might not have had the money to survive .” (" Global Financial Stability Report, Covid-19, Crypto, and Climate: Navigating Challenging Transitions ," Page 52) acknowledge that adoption is most likely to occur more rapidly in countries where cryptocurrency risks are an improvement on the financial system in place many might not have had the money to survive Global Financial Stability Report, Covid-19, Crypto, and Climate: Navigating Challenging Transitions Global Financial Stability Report, Covid-19, Crypto, and Climate: Navigating Challenging Transitions Look, I don’t like playing this blame game at all. What? Crypto ain’t perfect, but neither are you, my dear fiat. That’s why this particular Greek mythology analogy comes in handy to counterbalance the previous argument. If volatility is the Achilles’ heel of Bitcoin or any other cryptocurrency then the same weakness “of the fiat money system lies in its dependence on the demand for money . History demonstrates that the demand for money remains relatively steady when there is a high level of trust in the currency , meaning people are not worried that the purchasing power of their money will decline or be destroyed. Given this insight, it’s clear how states and their central banks seek to handle the fiat money system in their favor. Their primary strategy involves creating illusions and deceiving the populace to maintain control and influence. For instance, people are often fed the narrative that inflation of 2 percent equates to “stable money”—a claim that is, of course, inherently false. In reality, a 2-percent inflation rate destroys the purchasing power of money by 2 percent every year.” volatility is the Achilles’ heel of Bitcoin the same weakness “of the fiat money system lies in its dependence on the demand for money the demand for money remains relatively steady when there is a high level of trust in the currency Lack of trust = Fiat is past Lack of trust = Fiat is past Lack of trust = Fiat is past Demand for money is now demand for crypto: “The global user base of cryptocurrencies increased by nearly 190 percent between 2018 and 2020 , only to accelerate further in 2022. The projected revenue in the Cryptocurrencies market for Worldwide is estimated to reach US$56.7bn in 2024.” (Source: Statista) “The global user base of cryptocurrencies increased by nearly 190 percent between 2018 and 2020 No more money for you warmonger honey! Be(A)ware Bitcoin Friends - Every Stick Has Two Ends Buy Bitcoin! Defund the wars! Unfortunately, it’s not that simple. “Ukraine’s government bought weapons, unmanned aerial vehicles (UAVs, better known as drones) and digital rifle scopes, besides non-lethal tools, with some of the $60 million in crypto donated after Russia invaded the European nation earlier this year , an official revealed in a new breakdown of expenditures.” with some of the $60 million in crypto donated after Russia invaded the European nation earlier this year "We (the Digital Ministry) converted crypto and sen[t] it to our Defence Ministry. They decided that they needed something (lethal weapons). We are at war and we can defend ourselves with every means possible ,” Deputy Minister Alex Bornyakov responded when asked about the earlier statement that they would only buy non-lethal weapons through crypto donations . We are at war and we can defend ourselves with every means possible the earlier statement that they would only buy non-lethal weapons through crypto donations It’d be naive to think that the other side wouldn’t do the same by every means possible, also. “Russia’s largest maker of small arms, Kalashnikov Concern, needed electrical parts for drones that have been among the most effective weapons against Ukrainian armor. The smuggler, Andrey Zverev, took the late 2022 order to a Hong Kong electronics distributor. The U.S. was trying to cut off such deals, and even sanctions-wary Chinese banks were blocking payments from Russia. The solution: Zverev used tether, the cryptocurrency, to relay millions of dollars of funds from Kalashnikov to its supplier. ” the most effective weapons The U.S. was trying to cut off such deals , and even sanctions-wary Chinese banks were blocking payments from Russia. The solution: Zverev used tether, the cryptocurrency, to relay millions of dollars of funds from Kalashnikov to its supplier. was trying to cut off such deals “We will deliver everything you need to exterminate each other,” he wrote in a Telegram chat . Payment was “ideally with crypto, of course.” he wrote in a Telegram chat The Bitcoin Standard is the solution for forever wars. But, how far away is it in the future? In the meantime, we still have our deeply flawed human nature to deal with. Bitcoin Standard “With no physical properties, this decentralized digital money isn't susceptible to state control, and its users don't need permission to spend their holdings. It's also "the hardest money ever invented," Ammous writes, since Bitcoin's fixed supply of 21 million units is coded into the software. Previously it "proved impossible to come up with a form of money of which more cannot be created," which makes bitcoin the "first example of absolute scarcity." When the late economist Julian Simon observed that human time is the only truly limited resource, Ammous has quipped, he was only correct because Bitcoin hadn't yet been invented .” because Bitcoin hadn't yet been invented Now, Bitcoin isn’t only being invented, but also widely and rapidly accepted. However, we can’t say that forever war would be ended and prevented. Image copyright: streetcyber_art, Barcelona Image copyright: streetcyber_art, Barcelona

Can Bitcoin Put an End to Forever War?

ለዘለአለም ጦርነት Bitcoin 'ከእንግዲህ አይበልጥም' ሊል ይችላል?

Bitcoin Əbədi Müharibəyə “Daha Yox” deyə bilərmi?

¿Puede Bitcoin decir 'No más' a la guerra eterna?

Voiko Bitcoin sanoa "ei enää" ikuiselle sodalle?

ビットコインは永遠の戦争に「もう終わり」と言えるのか？

შეუძლია თუ არა ბიტკოინს თქვას „მეტი“ სამუდამოდ ომზე?

Биткоин мәңгілік соғысқа «артық емес» деп айта ала ма?

Биткойн мөнхийн дайнд "дахихгүй" гэж хэлж чадах уу?

Kan Bitcoin een einde maken aan eeuwige oorlog?

Bitcoin සදාකාලික යුද්ධයට 'තවත් එපා' යැයි පැවසිය හැකිද?

Bitcoin hemişelik söweşe 'Indi ýok' diýip bilermi?

比特币能够对永久的战争说“不再”吗？

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A microservices architecture is the gold standard for building scalable web applications. Gartner estimates that 74% of organizations use microservices for their web applications, with another 23% planning to use them soon. If you’re an IT leader, architect, or developer, you might have experienced the faster deployments, better fault isolation, and easier scaling that come with microservices. However, the old maxim, “there’s no such thing as a free lunch,” rings true here. Because microservices can also lead to significant operational overhead and complexity. Microservices sprawl, unclear component dependencies, service duplication, and anti-patterns like circular dependencies are all part of the chaos that comes hand-in-hand with microservices. Perhaps you’ve seen some of the common symptoms of this microservices chaos: Engineering velocity drastically slows down
Onboarding new developers grows more difficult
Mean time to recovery (MTTR) for outages or performance issues increases
Overall system resiliency diminishes, putting business outcomes at risk While it’s still best practice to modernize monolithic applications by breaking them into microservices, it’s also best practice to proactively guard against the issues that microservices introduce. Architecture Governance to Control the Chaos The best way to proactively guard against these problems is by using architecture governance — a collection of rules, processes, and practices that manage and control your software architecture. With proper software architecture governance, you can reduce microservices complexity, ramp up developers faster, reduce MTTR, and improve the resiliency of your system, all while building a culture of intentionality. (Note that we’re talking about software architecture governance in this article, not enterprise architecture governance, which has been around for some time and is concerned with the policies, processes, and procedures of enterprise architecture strategies.) But exactly how do you build architecture governance? Governance, whether we’re talking about access, data, or architecture, is often just establishing a set of rules. But for architecture governance, you need more than just rules. You must start with architectural observability. Architectural Observability: The Foundation of Good Governance To implement effective governance, you first need comprehensive visibility into your software architecture. Architectural observability gives you a continuous, real-time view of your architecture. It provides your team with the necessary insights to manage the architecture and interconnectedness of distributed applications. Architectural observability provides documentation from a working system, it shows you systems flows, dependencies, what’s changing, and how your systems interact. It gives your team a thorough understanding of how the architecture works, how it drifts from release to release, and how its changes impact dependent services and resources. Without this visibility, you’re in trouble. If you’ve built a microservices project, you’ve probably encountered the results of a lack of visibility: Microservices that are difficult to manage
Unclear component dependencies
Service duplication
Anti-patterns such as circular dependencies that increase the risk of outages
Performance issues Your overall application resiliency, scalability, and engineering velocity are at high risk. And it only gets worse — the longer you let this lack of visibility continue, the more complex and unmanageable your architecture becomes. Good Observability Equals Good Governance However, with good architectural observability, you can visualize your architecture layer in real-time, gain an understanding of how your system works, and monitor changes as your architecture evolves. With observability, your team can proactively address issues, such as service sprawl and dependency mismanagement — before they lead to technical debt or system failures. And once you have that observability in place — once you know what’s happening and what’s changing — you can now create and enforce your rules of governance. You can implement a governance program that sits over your architecture, monitors, and controls changes, and allows you to build and manage microservices effectively by proactively applying standards and rules to your architecture and codebase as it evolves. Sounds great! But how do you actually build this? Let’s look at an example of how to build this in the real world. Implementing Architectural Observability and Governance First, you need to implement your architectural observability. The domain of architectural observability is new and rapidly evolving. For our example, we’ll use one of the platforms at the forefront — vFunction. vFunction is an AI-driven platform that provides visualizations of software architecture. vFunction leverages AI and OpenTelemetry tracing to enable teams to track every aspect of their architecture and monitor changes between releases. It can quickly identify complex flows, architectural, technical debt, and architectural drift. For example, vFunction allows you to better understand your distributed applications: Visualize the architecture and automatically create exportable sequence diagrams of all system and data flows.
Identify drift, such as new services or dependencies.
Identify resource exclusivity changes (such as multiple new services accessing the same database table) versus previous releases.
Identify circular dependencies between services that could impact resiliency.
Identify duplicate functionality/services that may be merged to remove complexity.
Maintain an up-to-date, real-time view of the global microservices ecosystem. vFunction uses the same data that APM tools use (so it’s straightforward to install) but uses a different layer of intelligence to address the architectural root cause of issues. This is especially important for managing the sprawl and complexity that result from the rapid and frequent deployment of microservices. Implementing Rules to Maintain Standards After implementing your observability, you’re ready to create and enforce your rules of governance. vFunction allows you to create architecture rules and tags and then monitor your architecture in real time against those rules, enforcing your critical governance policies. Any time a deployment or merge request breaks these rules, you can block that action. What type of rules might your governance enforce? You could enforce rules such as: Dependency requirements. For example, certain services should or should not communicate with other services.
Restricted resources.
Multiple services should not depend on the same database table.
Changes should not increase service interdependencies.
Restrictions on new multi-hop flows that could impact performance and resiliency. vFunction can watch and send alerts for all of the above. By implementing a focused set of rules and tags, you can create adaptive governance that guides developers in maintaining an optimal, clean, and efficient architecture. You can build architecture governance into your code and your culture. Conclusion Microservices chaos can threaten to derail development velocity, system resiliency, and operational efficiency. Architecture governance offers a way out of this chaos — a way to regain control over your architecture and steer it toward greater scalability and stability. Whether your organization is just starting to scale with microservices or is already in the depths of microservices sprawl, it’s the right time to introduce architecture governance to ensure that your architecture is efficient and resilient — and ready to support your next phase of growth. A microservices architecture is the gold standard for building scalable web applications. Gartner estimates that 74% of organizations use microservices for their web applications , with another 23% planning to use them soon. 74% of organizations use microservices for their web applications If you’re an IT leader, architect, or developer, you might have experienced the faster deployments, better fault isolation, and easier scaling that come with microservices. However, the old maxim, “ there’s no such thing as a free lunch ,” rings true here. Because microservices can also lead to significant operational overhead and complexity. Microservices sprawl, unclear component dependencies, service duplication, and anti-patterns like circular dependencies are all part of the chaos that comes hand-in-hand with microservices. there’s no such thing as a free lunch Perhaps you’ve seen some of the common symptoms of this microservices chaos: Engineering velocity drastically slows down Onboarding new developers grows more difficult Mean time to recovery (MTTR) for outages or performance issues increases Overall system resiliency diminishes, putting business outcomes at risk Engineering velocity drastically slows down Onboarding new developers grows more difficult Mean time to recovery (MTTR) for outages or performance issues increases Overall system resiliency diminishes, putting business outcomes at risk While it’s still best practice to modernize monolithic applications by breaking them into microservices, it’s also best practice to proactively guard against the issues that microservices introduce . it’s also best practice to proactively guard against the issues that microservices introduce Architecture Governance to Control the Chaos The best way to proactively guard against these problems is by using architecture governance — a collection of rules, processes, and practices that manage and control your software architecture. architecture governance With proper software architecture governance, you can reduce microservices complexity, ramp up developers faster, reduce MTTR, and improve the resiliency of your system, all while building a culture of intentionality. (Note that we’re talking about software architecture governance in this article, not enterprise architecture governance, which has been around for some time and is concerned with the policies, processes, and procedures of enterprise architecture strategies.) But exactly how do you build architecture governance? Governance, whether we’re talking about access, data, or architecture, is often just establishing a set of rules. But for architecture governance, you need more than just rules. You must start with architectural observability. Architectural Observability: The Foundation of Good Governance To implement effective governance, you first need comprehensive visibility into your software architecture . comprehensive visibility into your software architecture Architectural observability gives you a continuous, real-time view of your architecture. It provides your team with the necessary insights to manage the architecture and interconnectedness of distributed applications. Architectural observability Architectural observability provides documentation from a working system, it shows you systems flows, dependencies, what’s changing, and how your systems interact. It gives your team a thorough understanding of how the architecture works, how it drifts from release to release, and how its changes impact dependent services and resources. Without this visibility, you’re in trouble. If you’ve built a microservices project, you’ve probably encountered the results of a lack of visibility: Microservices that are difficult to manage Unclear component dependencies Service duplication Anti-patterns such as circular dependencies that increase the risk of outages Performance issues Microservices that are difficult to manage Unclear component dependencies Service duplication Anti-patterns such as circular dependencies that increase the risk of outages Performance issues Your overall application resiliency, scalability, and engineering velocity are at high risk. And it only gets worse — the longer you let this lack of visibility continue, the more complex and unmanageable your architecture becomes. Good Observability Equals Good Governance However, with good architectural observability, you can visualize your architecture layer in real-time, gain an understanding of how your system works, and monitor changes as your architecture evolves. with With observability, your team can proactively address issues, such as service sprawl and dependency mismanagement — before they lead to technical debt or system failures. And once you have that observability in place — once you know what’s happening and what’s changing — you can now create and enforce your rules of governance. You can implement a governance program that sits over your architecture, monitors, and controls changes, and allows you to build and manage microservices effectively by proactively applying standards and rules to your architecture and codebase as it evolves. Sounds great! But how do you actually build this? Let’s look at an example of how to build this in the real world. Implementing Architectural Observability and Governance First, you need to implement your architectural observability. The domain of architectural observability is new and rapidly evolving. For our example, we’ll use one of the platforms at the forefront — vFunction . vFunction is an AI-driven platform that provides visualizations of software architecture. vFunction vFunction leverages AI and OpenTelemetry tracing to enable teams to track every aspect of their architecture and monitor changes between releases. It can quickly identify complex flows, architectural, technical debt, and architectural drift. OpenTelemetry For example, vFunction allows you to better understand your distributed applications: Visualize the architecture and automatically create exportable sequence diagrams of all system and data flows. Identify drift, such as new services or dependencies. Identify resource exclusivity changes (such as multiple new services accessing the same database table) versus previous releases. Identify circular dependencies between services that could impact resiliency. Identify duplicate functionality/services that may be merged to remove complexity. Maintain an up-to-date, real-time view of the global microservices ecosystem. Visualize the architecture and automatically create exportable sequence diagrams of all system and data flows. Identify drift, such as new services or dependencies. Identify resource exclusivity changes (such as multiple new services accessing the same database table) versus previous releases. Identify circular dependencies between services that could impact resiliency. Identify duplicate functionality/services that may be merged to remove complexity. Maintain an up-to-date, real-time view of the global microservices ecosystem. vFunction uses the same data that APM tools use (so it’s straightforward to install) but uses a different layer of intelligence to address the architectural root cause of issues. This is especially important for managing the sprawl and complexity that result from the rapid and frequent deployment of microservices. Implementing Rules to Maintain Standards After implementing your observability, you’re ready to create and enforce your rules of governance. vFunction allows you to create architecture rules and tags and then monitor your architecture in real time against those rules, enforcing your critical governance policies. Any time a deployment or merge request breaks these rules, you can block that action. What type of rules might your governance enforce ? You could enforce rules such as: What type of rules might your governance enforce Dependency requirements. For example, certain services should or should not communicate with other services. Restricted resources. Multiple services should not depend on the same database table. Changes should not increase service interdependencies. Restrictions on new multi-hop flows that could impact performance and resiliency. Dependency requirements. For example, certain services should or should not communicate with other services. Restricted resources. Multiple services should not depend on the same database table. Changes should not increase service interdependencies. Restrictions on new multi-hop flows that could impact performance and resiliency. vFunction can watch and send alerts for all of the above. vFunction can watch and send alerts By implementing a focused set of rules and tags, you can create adaptive governance that guides developers in maintaining an optimal, clean, and efficient architecture. You can build architecture governance into your code and your culture. Conclusion Microservices chaos can threaten to derail development velocity, system resiliency, and operational efficiency. Architecture governance offers a way out of this chaos — a way to regain control over your architecture and steer it toward greater scalability and stability. Whether your organization is just starting to scale with microservices or is already in the depths of microservices sprawl, it’s the right time to introduce architecture governance to ensure that your architecture is efficient and resilient — and ready to support your next phase of growth.

Mastering Microservices: Building Effective Architecture Governance for Scalability and Stability

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