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The Sociable's 40 Under 40 Influencers in Blockchain for 2023

Los 40 influencers menores de 40 de The Sociable en Blockchain para 2023

Les 40 influenceurs de moins de 40 ans de The Sociable dans la blockchain pour 2023

2023 के लिए ब्लॉकचेन में सोशिएबल के 40 अंडर 40 प्रभावशाली व्यक्ति

The Sociable の 2023 年のブロックチェーンにおける 40 歳未満のインフルエンサー 40 人

Os 40 influenciadores com menos de 40 anos do Sociable no Blockchain para 2023

Danh sách 40 người có ảnh hưởng dưới 40 tuổi của The Sociable trong Blockchain cho năm 2023

The Sociable 评选 2023 年区块链领域 40 位 40 岁以下影响者

Picture this – you're , sitting in a futuristic spacecraft and tasked with managing a complex network of satellites. So would you rather handle it haphazardly, or do you prefer a well-labeled and meticulously organized system? thousands of miles above the earth Surely, you would choose the latter. Similarly, your and applications are that intricate network and application tagging is your to effortlessly navigate this galaxy of data. cloud infrastructure roadmap At its core, is the simple act of assigning labels – or "tags" – to your resources, offering a whole new level of clarity and control. tagging Whether you're a , enterprise decision-maker, or software engineer, your day revolves around managing and making sense of vast pools of data. With a solid tagging strategy, you enhance tech leader observability, robust decision-making, and seamless operations. From facilitating to and , good tagging is the silent champion that empowers your operations to be more agile, efficient, and effective. Let's look into the optimal strategies for effectively tagging your infrastructure and applications. maintenance optimizing costs security Understanding Tagging Source Tagging, at the basic level, is an to classify, define, and co-relate IT resources and assets within an infrastructure or an application. The purpose of tagging isn't merely regulatory, but rather much more compelling. It and improves transparency within your cloud infrastructure. And that is where the magic happens. organizational practice facilitates smarter resource management, enhances operational efficiency, Let's dive a little deeper. This is the lifeblood of effective tagging. Consistent formatting, naming conventions, and application are what make a tagging strategy truly powerful. It minimizes confusion across your teams. Consistency: Bonus point? When you're handling hundreds, or even thousands, of resources, manual tagging can be quite an arduous task. Incorporating automated tagging into your strategy is like having an invisible army at your disposal. Automation: The more detailed your tags, the better visibility you'll get into your resources. So, don't shy away from creating those detailed, granular tags. Comprehensiveness: Effective tagging isn't a one-and-done move. Revisit, refresh, and revamp - the mantra to add finesse to your tagging strategy in the long run. Review: A well-executed tagging strategy can be your knight in shining armor. It's like the ultimate roadmap to an organized, optimally functioning infrastructure. And who doesn't want that? Best Practices for Infrastructure Tagging Source Now, let's delve deeper into the nitty-gritty of organizing resources for efficient management, creating consistent, descriptive tags, and seamlessly implementing a standard tagging taxonomy. An Efficient Management of Resources Think of your cloud infrastructure as a massive library. Without organized sections and alphabetically arranged books, there is bound to be finding the information you need. The same applies here. chaos in terms of Group similar resources together. For instance, all resources related to your 'Payment Processing Solution' can be combined. This way, you're one search away from all relevant information about that particular application. Cluster wisely: Not everyone in your team needs access to everything. Restrict permissions based on roles to avoid accidental harm to important resources. Implement access controls: Creating Consistent and Descriptive Tags Each tag is a piece of metadata that adds context, making it easier to identify, organize, and search for resources. The key is to create yet tags. Here's how: descriptive consistent Your tags should be short, making them easier to remember and use. For example, instead of tagging a resource as 'PaymentProcessingProductionServer,' consider 'PP_Prod_Server.' Conciseness is key: Consistency across all tags will greatly pay off in the long run. Stick to a specific format so that any team member can understand the tag without much confusion. Stick to a naming convention: Implementing a Standardized Tagging Taxonomy Having a standardized tagging taxonomy means having a set tagging strategy that everyone sticks to. Let's illustrate with a simple example. One team in your organization may prefer the tag 'env=prod' while another may use 'environment=production' for the same thing. This inconsistency not only leads to confusion but also potential losses in resource management. Keep an up-to-date record of all tags and their descriptions for everyone to refer to. Maintain Documentation: Automation reduces human error. Using automated tagging solutions can allow for better accuracy and consistency. Automate the process: In conclusion, with these strategies, you're not just tagging your infrastructure and applications, you're adding a layer of efficiency and productivity that will greatly boost your overall operational success! Application Tagging Techniques Source Do you know what's great? Harnessing the right from the inception of any application. Can you guess why? It's because Yes, you heard that right! power of tagging tagging aligns perfectly with the different stages of an application's lifecycle! Aligning Tags with Application Lifecycle Stages Imagine for a moment that your application is in the development stage. Having , will make information retrieval a breeze during this phase. But, what happens when your application moves to the test stage? Simply tweak those tags from to ! It's like having a virtual assistant guiding your operations team throughout the application lifecycle. tags specific to "Development" "Development" "Testing" Let's have a look! "But how can tagging help in monitoring and troubleshooting?" Leveraging Tags for Enhanced Monitoring and Troubleshooting What's your first response when your application encounters an error? You investigate it, right? Now, imagine if your applications are neatly tagged per their roles, environment, and ownership. saves you from diving into the sea of code or sifting through log data, thus accelerating the troubleshooting process by a huge margin! Now that's what is called efficient monitoring! A simple filter on these tags Apply the tag "FrontEnd" to your application dealing with user-facing roles. When an error occurs, filter by this tag, and you'll instantly focus on resolving bugs that impact user experience! Example: Incorporating Security Measures Through Tagging Whoever thought that tagging could be your silent crusader in securing application infrastructure, right? As astonishing as it may sound, it's true! You can enforce security policies based on tags, thereby enhancing your application's overall security posture. For example, consider having a tag that says "PCI-DSS Compliant." Applying this tag to all relevant applications not only helps in but can also flag any application that isn't compliant! How's that for a guard dog protecting your application on the cloud? streamlining compliances So, isn't it interesting how effective tagging can streamline application lifecycle management, enhance monitoring and troubleshooting, and play a critical role in application security? Go ahead, and start tagging! Automation in Tagging Let's be honest here. As technology leaders and DevOps engineers, keeping track of the countless assets within our businesses may be just as daunting as herding cats. Believe it or not, we're all sailing in the same boat of massive infrastructures and applications. But have you ever wondered if this can be made any easier, smoother, or even automated? Well, here's the solution: automated tagging and streamlining processes that clinch the accuracy, consistency, and efficiency we all seek. Need some kind of for your tagging conundrums? Let's walk you through the game-changers. 'autopilot' With the ability to automatically tag infrastructure elements and applications, these tools can be monumental in minimizing manual intervention. They are, quite literally, lifesavers in AWS, Azure, and more. Some leading solutions include Middleware, AWS Auto Tagging, and Azure Policy. You won't believe the hours of toil they’re saving worldwide. Automated Tagging Tools: These have practically redefined automation. By providing comprehensive orchestration across different cloud environments, CMPs such as CloudCheckr and Flexera make tagging a breeze. They ensure you're not just tagging, but tagging right—with accuracy and consistency. Cloud Management Platforms (CMPs): Needless to say, any automated tagging discourse would be incomplete without acknowledging the role of DevOps tools such as Chef, Puppet, Ansible, and Kubernetes. They have rewritten the rules, enabling automated environment set-up, application deployment, scaling, and yes, even tagging. DevOps Tools: Now, these tools are not magic wands, and you surely can't just go . But if implemented correctly, they can offer , possibly saving you hours and a lot of stress. set it and forget it remarkable reliability and replicability in your tagging practices Case Studies Let's explore some where infrastructure and application tagging have been successfully implemented, and dive into the lessons learned and key takeaways. case studies Case Study 1 - Atlassian - Automating Infrastructure and Application Discovery with CloudSploit There was a time when the discovery of resources was a tedious, error-filled task. The limited insight into how cloud assets interacted elevated the risk of security vulnerabilities and non-compliance with regulations. Challenge: They integrated CloudSploit, which allows for seamless infrastructure and application discovery. It automatically assigns tags to your resources, providing you with crucial data and all the associated application dependencies. Strategy: Experienced a significant decrease in the time devoted to discovery and tagging and bolstered the security stance by promptly identifying and remedying any vulnerabilities. Outcome: Proper tagging, coupled with diligent oversight and automation, can lead to massive cost savings. Key Takeaway: Case Study 2 - Spotify - Streamlining Cloud Management with Tagging in OpenTelemetry Difficulty managing complex microservice architecture with diverse deployment environments. The lack of standardization and consistency in tagging made resource identification difficult. Challenge: Adopted OpenTelemetry, an open-source framework for distributed tracing and monitoring, and implemented a standardized tagging strategy across applications and infrastructure using labels. Strategy: Simplified cloud resource management with consistent and searchable tags. Achieved better observability and troubleshooting through granular tracing data. Outcome: Strategic application tagging can both elevate application performance and fortify security. Key Takeaway: Case Study 3 - Netflix - Scaling Cloud Operations with Tagging in CloudFormation and AWS Cost Tagging Difficulty managing large-scale infrastructure across multiple regions and accounts. The lack of granular costing insights hindered cost optimization efforts. Challenge: Utilized AWS CloudFormation for infrastructure provisioning and tagged resources with application names, environments, and ownership details. Enabled AWS Cost Tagging to track costs by application and team, facilitating granular cost allocation and optimization. Strategy: Improved operational efficiency by automating infrastructure provisioning and tagging. Gained detailed cost insights enabling informed resource allocation and budgeting decisions. Outcome: Effective infrastructure tagging can simplify compliance and create a more efficient audit system. Key Takeaway: These success stories underscore the . When properly implemented and managed, tagging starts to look less like a chore and more like a critical strategy for business success. transformative potential of effective tagging Future Trends in Tagging Practices Let's not beat around the bush here, folks. The breathless pace of technology's evolution has rippled through the world of tagging like a virtual tsunami. Take a minute to consider this. A staggering have adopted some form of cloud technology according to a . The explosion of cloud-native applications has shifted the focus to more effective and precise tagging. As a result, the old tag-and-hope methods just don't cut it anymore. 92% of organizations Faction report The Changing Winds of Tagging With the technological horizon constantly mutating, the ways we handle tagging our infrastructure and applications need to shift gears too. Consider these points: Emerging technologies like AI and ML are making a splash in the tagging world. AI/ML-powered automation can greatly reduce human errors in tagging, making your applications and infrastructure run more smoothly. Artificial Intelligence(AI) and Machine Learning(ML): According to a , 94% of tech leaders emphasize the shift towards observability. This means adopting tagging strategies that highlight and communicate the right information, swiftly and accurately. Shift towards Observability: NewRelic 2020 report We all know that change can be challenging, especially in the volatile realm of technology. But when it comes to preparing for the future of infrastructure and application tagging, it's time to the change. Why merely adapt? Let's evolve, together. embrace Conclusion We can't stress enough how significant it is to have a good grip on your and what role effective tagging plays. Remember, - it's a performance game-changer that can fuel agility, efficiency, and scalability. Making in your IT team isn't just about diligent practice but fostering a better understanding and communication. IT operations tagging is not just a 'nice to have' tagging a culture Let's do a quick recap of best practices for tagging: Uniformity in your tagging approach ensures seamless identification of resources. Be Consistent: Tags should provide clear insights about the resource at a glance. Stay Descriptive: Crafting a classification system expedites resource management. Adopt a Standardized Taxonomy: Tagging is no longer an option; it is an essential tool in the modern IT Toolkit.

Optimal Strategies for Effectively Tagging Your Infrastructure and Applications

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THE ELDER SON.

Working in a startup environment for almost a decade has given me privileged access to a fast-paced culture of innovation, exploration, and a fail-fast approach. I followed the standard progression ladder: intern, junior, mid, senior, and eventually moved to the management track. Over time, many people I grew with later moved on to work at other companies, becoming highly respected contributors there. It would be fair to say they are good engineers. engineering Looking back at the journey of my peers, mentees, and my own, it seems harder than ever to be a engineer. good Defining a engineer good As software engineers, we are: What does it mean to be an engineer? Responsible for translating complex problems into efficient and scalable solutions Tasked with analyzing user requirements, designing software architecture, writing code, and testing and debugging software Expected to stay on top of trends, seeking new business opportunities and ways to improve existing products So, no – engineering doesn’t equal programming. Sometimes, that is the smallest part. It definitely appears so as one acquires more experience, as shown in the figure below. Based on numerous interviews and supporting my mentees’ progress, I noticed that people with different levels of expertise might give different answers. What does it mean to be a engineer? good Someone just starting out might think it’s the number of languages and frameworks a developer knows. A more experienced engineer might not even care about the language they’re using, instead emphasizing code quality - adhering to all coding principles and while moving swiftly. conducting QA Highly experienced engineers place an enormous focus on bringing value. Sometimes, we’ll quickly write throw-away code that breaks all the rules to prove a hypothesis; sometimes, we’ll spend days writing a couple of lines of mission-critical code. But most days, we are making architectural decisions, discussing mission-critical issues, improving processes, etc. Why? Because often, that brings the most value. Although there are always exceptions to the rule, we can say that a good engineer is one who efficiently focuses their effort to bring maximum value in achieving a goal. Growing markets and competition We have all seen massive successes over the years, from WhatsApp to Uber, Airbnb, and TikTok. While these may be exceptions, such examples often set the North Star for people – something they should strive for. This way of thinking puts extra pressure on engineers. They feel stress from the inside, thinking they're doing something wrong, and from the outside, with people comparing their company to many competitors. The tech market is constantly evolving. To succeed in such an environment, companies needed to “move fast and break things,” as the famous Facebook motto says. Today, this is more obvious than ever – almost every company is becoming an “ .” Everyone is integrating ChatGPT, often for no real reason, without a strategy on how it will bring value. AI company – how can we bring more value to our customers – and moving towards beating the competition on the hype train, By moving away from the core principle we get engineers building functionalities that are doomed to fail. The world is a confusing place. What should an enthusiast such as myself do to become a better engineer? Apart from the obvious choice of perfecting coding skills by improving clean code and architecture philosophies, nowadays, there are lots of temptations lurking. Learning TypeScript and that one latest framework that changes everything, diving into the world of blockchain and crypto, experimenting with a myriad of AI products… Options are endless. To be honest, after so many years in the industry, I still felt threatened by the new wave of change brought by ChatGPT, GitHub Copilot, and other emerging tech. My brain started imagining scenarios where I was out of touch with so many things. Am I focusing on the right things to bring value? Am I using my maximum potential? After some time, it became clear we were in a hype. That, too, will pass, leaving only AI companies that are creating long-term value. The number of AI companies in the last five years has doubled in the US, with many startups just adding a feature on top of the newly-released GPT-3. They would later die with the release of , which could do the same thing but better. But that doesn’t stop the hype army of Twitter and other platforms from proclaiming the new world order. ChatGPT or GPT-4 Even with so many years working in tech, I got sucked into the hype. Rookie mistake! Programming languages and constant releases of new frameworks also add to the confusion. Tailwind, TypeScript, Haskell, and Rust are all great; they each have an angle that gives them an advantage. However, people often mistake learning them for something that will give them an edge. It won’t, or at least, it shouldn’t. They are just tools that are nice to know but can’t replace experience. That is why we never put language/framework requirements in our job descriptions. I would be a fool to miss a talented engineer because they don’t know TypeScript, prompt engineering, or microservices. My advice is - don’t get caught up in new trends and hype to the point where you lose focus on bringing value. Fast pace and high expectations Positive stress is one where we perceive a stressful situation as an opportunity leading to a good outcome, while negative stress is one that can have detrimental physical and mental health effects, as seen in the image below. Continuously delivering results on a tight schedule is stressful, and building features for the wrong reasons sways toward the latter. When seeking new challenges, it can be difficult to strive for positive stress while avoiding negative stress. Both as a mentor and as a hard worker, I’ve seen stress lead to burnout. Without exception, having someone go through burnout results in less output than reducing workload, taking a break, and optimizing for the long term. That's why we always try to make raising red flags as straightforward as possible, with periodic team updates, one-on-ones, and a nurturing culture. Still, things will go wrong. When they do, we cut scope, involve people who can help, or communicate with our clients to postpone a launch. Pressure is higher than ever, coming both from within and without. Stay focused and surround yourself with a supportive team optimizing long-term. How can we do better? We all have our down moments – feeling like inadequate engineers, mentors, or colleagues. Things will never be perfect or easy, and they shouldn’t. Without making mistakes and hard times, we don’t learn. But there are some things I find can increase efficiency. stay true to what is really important. Technologies will come and go, but the value you bring to the world is what counts. It’s hard to fake hard work and experience. Individually, start with when making decisions. This is the best way to deliver functionalities that will bring value. Also, make sure the employees know . In my experience, they will make better decisions, give valuable feedback, and be happier. As a company, why why establish processes that will support the employees, optimizing long-term. Together with your colleagues, establish a culture of trust, support, and caring. That way, you will all get the best of one another. Culturally,

Unpopular Opinion: It’s Harder Than Ever to Be a Good Software Engineer

অজনপ্রিয় মতামত: ভালো সফটওয়্যার ইঞ্জিনিয়ার হওয়া আগের চেয়ে কঠিন

Unpopuläre Meinung: Es ist schwieriger denn je, ein guter Softwareentwickler zu sein

Opinión impopular: es más difícil que nunca ser un buen ingeniero de software

Opinion impopulaire : il est plus difficile que jamais d'être un bon ingénieur logiciel

अलोकप्रिय राय: एक अच्छा सॉफ्टवेयर इंजीनियर बनना पहले से कहीं अधिक कठिन है

不人気な意見: 優れたソフトウェア エンジニアになるのはこれまで以上に難しい

인기 없는 의견: 좋은 소프트웨어 엔지니어가 되는 것은 그 어느 때보다 어렵습니다

Opinião impopular: é mais difícil do que nunca ser um bom engenheiro de software

Непопулярное мнение: стать хорошим инженером-программистом сейчас труднее, чем когда-либо

Popüler Olmayan Görüş: İyi Bir Yazılım Mühendisi Olmak Her Zamankinden Daha Zor

Ý kiến không phổ biến: Trở thành một kỹ sư phần mềm giỏi khó hơn bao giờ hết

不受欢迎的观点：成为一名优秀的软件工程师比以往任何时候都难

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