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Have you ever found yourself in the position of a test engineer embedded in one of the Agile engineering teams? While you have daily interactions with peers, connecting with them on a profound level for the successful execution of job duties might be challenging. Although there is a shared goal to release features successfully, we often experience isolation, especially while others, like developers, find comfort within the team. In the realm of dispersed Agile teams with time zones adding an extra layer of complexity, the longing for a team to resonate with, connect with, and brainstorm on all test automation challenges is prevalent. In the expansive landscape of test automation, the creation of an automation guild is more than just collaboration; it stands as a testament to the resilience of SDETs working across diverse time zones and Agile teams. Through this guide, I aim to share the benefits and challenges overcome, the enrichment of test engineers or SDETs, and the establishment of a collective force dedicated to advancing excellence in testing. Breaking Silos In a world where time zones separate teams and Agile methodologies dictate the rhythm of development, test engineers face a unique challenge. Even though they are part of an Agile team with a shared goal, i.e., successful release, they must navigate independently without a clear direction or purpose. The guild, however, becomes a bridge across these temporal gaps, offering a platform for asynchronous collaboration. It not only allows them to demo their progress, accomplishments, and new utility that can be leveraged by others but also their challenges and blockers. It will surprise you to see how often those obstacles are common among other guild members. Now that they have each other, all heads come together to brainstorm and find common, effective solutions for any testing problem. Fostering Through Training and Contribution As important as regular guild meet-ups and collective commitment are, continuous learning and training initiatives are equally vital to empower test engineers to contribute effectively. From workshops on emerging testing methodologies to skill-building webinars, the guild evolves into a learning haven where members grow together, ensuring each test engineer is equipped to make a meaningful impact. It enhances members’ efficiency by reducing redundant efforts. Understanding what others are working on and what tools are available for use, such as common utilities and shared definitions, enables them to save time by avoiding duplication of efforts and contribute more effectively. This isn’t just about individual efficiency; it’s a strategic move toward collective empowerment. Grow Your Network and Your Profile Within the guild, networking is not confined to individual teams. It offers the creation of a network that spans across Agile teams, allowing Test Engineers to understand overall solutions from diverse perspectives. This isn’t just about sharing knowledge; it’s about broadening domain knowledge. Turning new members into seasoned members who can then mentor new juniors, ensuring that the guild is not just a community but a mentorship ecosystem that thrives on collective wisdom. If there’s one aspect that has been repeatedly demonstrated in the guild, it would be that challenges are not roadblocks but opportunities for innovation and collaboration. The guild stands as a testament to the fact that, even in the world of test automation, where distances and time zones pose challenges, excellence can be achieved through collective strength. Automation guild is not just about crafting code; it’s about crafting a community that advances excellence in testing, collectively and collaboratively. The future, as envisioned through the chronicles, is one where Test Engineers, regardless of time zones, work seamlessly in a guild that stands as a beacon of innovation, knowledge-sharing, and collective growth.
March 2020. We anxiously watched COVID spread, first through Asia and then Europe before it really impacted the United States. In the second week in March, retail businesses started closing and office workers were instructed to work virtually from home. "Just a couple of weeks, maybe a month," we were told. And now, four years hence, I continue to work full-time from home and don’t expect to change: my employer has stated that in-office or remote work is the employee’s, not the employer’s choice. Cool. “MDI Siemens Cube farm” by babak_bagheri is licensed under CC BY-SA 2.0 Truthfully, my employer is not in a position to force RTO, even scheduled hybrid, as many employees relocated away from headquarters, often leaving the state. Employees have been hired remotely, both before and since the pandemic started. Technically I am a Minnesota – Remote employee even though I am less than ten miles from headquarters. To force in-office work would be hypercritical, though they continue to try and encourage more attendance. [An end-of-summer ice cream party is not an incentive to come into the office!] Not Everyone Is As Lucky Many big-tech behemoths – e.g., Amazon, Apple, Google, IBM, Salesforce – have created various carrot-stick mandates to get their employees in multiple days per week, accepting the negative impact on morale and increasing employee attrition. Friends are increasingly acceding to RTO mandates, usually hybrid, with no obvious benefit to either the employee or the employer: An Amazon friend who manages two teams in three locations and is always remote for the majority of his direct reports A Dell friend who took the pandemic stipend to become full-time remote and is now required to go into the office twice weekly even though her entire team is two timezones away, plus no local storage means she brings in her own (working) keyboard/mouse each day (as well as tea, cup, snacks, etc.) A General Dynamics friend whose management silo requires her team to be full-time in the office while teams with whom she works are hybrid or remain work-from-home A Thompson Reuters friend who is required to badge in two days per week just because and still primarily works alone A friend who works for USBank supports teams across the country and now has the same virtual meetings she would have from home Many reasons are given which are often lame and apocryphal: we’re not living our culture, we’re not collaborating, we’re not ideating, we’re not as fast-to-market, we’re not serving our customers, people are not working hard, our finances are worse off. No doubt there is some truth, individual examples, but those are the exceptions and not the rule. [A previous company installed employee monitoring software that identified multiple employees who didn’t open their laptops or check their emails for months after being sent home. So yeah, I get it, it does occur.] Microsoft appears to understand that, "It can’t go back to the way it used to be," but seems to be an outlier across Fortune 100 companies. And organizations are not always prepared for employees to return - multiple discussions about returning to the office without a place to actually work. Unspoken Reasons For all the bullshit reasons spewed by leaders, I have three basic reasons that companies are trying to force some form of return-to-office: Senior leaders are often extroverts and derive energy from those personal interactions; software engineers and technologists (of which I am one) are more introverted and may even feel threatened by large-scale personal interactions Mid-level managers who rely on butts-in-seats and keyclicks to measure performance, don’t know how to motivate without in-person bullying or intimidation and have shown themselves to be incapable of change CEOs, CFOs, and bean counters who fiscally interpret their mostly empty corporate offices as wasteful, and, lacking any meaningful way to sell buildings or modify existing leases, view return-to-office mandates as a net positive to overall finances. And Then It Got Real This paper was recently published by a professor and Ph.D. student at the Katz Graduate School of Business at the University of Pittsburgh, which correlated return-to-office mandates with positive financial impact for Fortune 500 companies. The findings showed otherwise: "Also, our findings do not support the argument that managers impose mandate because they believe RTO increases firm values. Further, our difference in differences tests report significant declines in employees’ job satisfactions mandates but no significant changes in financial performance or firm values after RTO mandates." Final Thoughts “My WFH setup is getting crazier and crazier” by Sergiy Galyonkin is licensed under CC BY-SA 2.0 Obviously, I’m unabashedly pro-WFH, bookmarking stories that support my views, and debating whomever on the advantages/disadvantages of full-time WFH. And I totally get how fortunate I am: while firms struggled to redefine their business virtually, while many took unpaid leave when businesses that required customers closed, and while students transitioned to virtual education, it was mostly a non-event for me. Other than a changed location, almost nothing else changed. [I even dressed business casual for a few months.] The uncomfortable truth is change was afoot prior to the pandemic, working an occasional day from home was not unheard of. Companies often have multiple locations, both national and international, requiring virtual meetings and digital collaboration tools that we rely on today. My previous five employers each had fully remote employees who occasionally flew in for planning, catch-up, or training. So a transition was in progress, the pandemic just forced everything into hyperdrive. Is remote work for everyone? Unequivocally no. Are there advantages to occasional in-person meetings? Unequivocally yes, especially for major planning or direction-setting events. Does it negatively impact overall business progress and performance? I don’t believe so (even before the paper was published), though actual numbers aren’t available for my paid grade. My current boss said he doesn’t question my work, and I believe I am more productive than when a daily slog commute to an office was required: my equipment setup is better, my environment is nicer (windows!), I take small quick breaks than rather than having to leave, I know how to communicate well with others. It’s not for everyone, I know it won’t last forever, but I really wish companies would stop trying to force something that doesn’t appear necessary.
Artificial intelligence (AI) is one of the twenty-first century's most exciting and rapidly developing fields. Artificial intelligence has the potential to transform a variety of industries, including education, healthcare, retail, e-commerce, public relations, small businesses, recruitment, services, and manufacturing. AI can also improve the quality of life for millions of people worldwide by solving complex problems, increasing efficiency, and developing novel solutions. But how do you become an AI expert and enter this exciting field? What skills, education, and career paths should you pursue? In this blog post, we will answer these questions and provide you with a detailed guide on how to become an AI expert. What Is an AI Expert? An AI expert is a professional who understands the fundamentals, methods, and applications of artificial intelligence. An AI expert can create, develop, and deploy intelligent systems capable of performing tasks that would normally require human intelligence, such as natural language processing, computer vision, speech recognition, machine learning, and robotics. An AI expert can work in a variety of fields, including research, engineering, consulting, and teaching. An AI expert can also focus on a specific subfield of AI, such as machine learning, deep learning, computer vision, natural language processing, or robotics. What Are the Skills and Education Required To Become an AI Expert? To become an AI expert, you must have a solid foundation in mathematics, statistics, computer science, and programming. You also need a solid understanding of AI fundamentals such as algorithms, data structures, data analysis, machine learning, and deep learning. Depending on your desired career path, you may also need a bachelor's, master's, or doctoral degree in AI, computer science, or a related subject. Alternatively, you can take online courses, certifications, or boot camps to learn the fundamental skills and concepts of artificial intelligence. Coursera, Udemy, edX, and Udacity are some of the most popular online platforms for AI courses. Some popular AI certifications include the IBM AI Engineering Professional Certificate, Google TensorFlow Developer Certificate, and Microsoft Azure AI Engineer Associate. What Are the Career Paths and Opportunities for AI Experts? There are numerous career paths and opportunities for AI experts across industries and sectors. Some of the most popular and lucrative AI jobs are: AI engineer: An AI engineer is a professional who uses AI and machine learning techniques to create applications and systems that improve organizational efficiency. An AI engineer creates the tools, systems, and processes that allow AI to be applied to real-world problems. An AI engineer may also work with data scientists, machine learning engineers, and other AI professionals to develop and implement AI solutions. The average salary for an AI engineer is $113,000. Machine learning engineer: A machine learning engineer is a professional who conducts research, builds, and designs the artificial intelligence (AI) that powers machine learning. A machine learning engineer maintains and improves existing AI systems while also conducting experiments and tests to assess and optimize their performance. A machine learning engineer collaborates closely with data scientists and AI engineers to create machine learning models and algorithms. The average salary for a machine learning engineer is $123,000. Data engineer: A data engineer is a professional who creates systems for collecting, managing, and converting raw data into information that data scientists, business analysts, and other data professionals can interpret. A data engineer makes data accessible and reliable, allowing organizations to evaluate and improve their performance. A data engineer works with a variety of data sources, including databases, APIs, web scraping, and cloud services. The average salary for a data engineer is $104,000. Robotics engineer: A robotics engineer is a professional who creates robotic applications for a variety of industries, including automobiles, manufacturing, defense, and medicine. A robotics engineer creates, tests, and implements new products or prototypes that incorporate robotic technology. A robotics engineer also works with a wide range of hardware and software components, including sensors, actuators, controllers, and programming languages. The average salary for a robotics engineer is $96,000. AI researcher: An AI researcher is a professional who conducts scientific research into the theory and application of artificial intelligence. An AI researcher investigates new ideas, methods, and applications of AI and publishes their findings in academic journals, conferences, and books. An AI researcher collaborates with other researchers, academics, and industry partners to further the field of AI. The average annual salary for an AI researcher is $119,000. AI consultant: An AI consultant is a professional who offers expert advice and guidance on the use and implementation of artificial intelligence to a variety of clients and organizations. An AI consultant analyzes the client's needs and goals and recommends the best AI solutions to help them achieve their goals. An AI consultant also assists clients with the planning, execution, and evaluation of their AI projects. The average annual salary for an AI consultant is $102,000. How To Become an AI Expert: A Summary Becoming an AI expert is a rewarding and challenging career path that can lead to numerous opportunities and possibilities for you. To become an AI expert, you must have a solid background in mathematics, statistics, computer science, and programming. You should also have a solid understanding of the fundamentals and applications of artificial intelligence. You can learn these skills and knowledge through formal education, online courses, certifications, or boot camps. There are numerous career paths and opportunities for AI experts across industries and sectors. AI engineer, machine learning engineer, data engineer, robotics engineer, AI researcher, and AI consultant are among the most sought-after and lucrative AI positions. You can choose a career path that aligns with your interests, skills, and goals. Suppose you are interested in artificial intelligence and want to become an AI expert. In that case, you can begin your journey today by enrolling in one of the many online courses or certifications that will teach you the fundamental skills and concepts of AI. You can also look into the various resources and communities available to help you learn more about AI and keep up with the latest trends and developments in the field. We hope this blog post provided you with a comprehensive guide on how to become an AI expert. If you have any questions or comments, please post them below. We'd love to hear from you.
In this article, we are going to look at the challenges faced when rapidly scaling engineering teams in startup companies as well as other kinds of companies with a focus on product development. These challenges change between different types of companies, sizes, and stages of maturity. For instance, the growth of a consultancy software company focused on outsourcing is so different from a startup focused on product development. I've faced much team growth and also seen the growth of teams in several companies, and most of them have faced the same challenges and problems. Challenges The following are some of the challenges or problems that we will have to address in high-growth scenarios: Growth is aligned with productivity: many companies grow, but the output is unfortunately far from the goals. Avoid team frustration due to failure to achieve growth goals. Avoid too much time being consumed with the hiring process for the engineering teams. Avoid the demotivation of newcomers due to chaotic onboarding processes: the onboarding process is the first experience in the company. Maintain and promote the cultural values defined by the organization. The impact on delivery is aligned with the defined goals and risks. New hires meet expectations and goals in terms of value contribution. Navigating the Challenges Goals Goals are the main drivers of the growth strategy. They need to be challenging, but also realistic, and linked to mid-term and long-term vision. Challenging: Push the team to go beyond their comfort zone and strive for excellence. It requires effort, innovations, planning, and agility. Realistic: Ensure the goals can be achieved to avoid lead with frustration and burnout. The growth of the company and its success have to enhance the motivation and inspiration of the team. Long-term: Goals have to be aligned with the company's long-term vision and in a wide range. Large growth cannot be organized with the next three months in mind, because that may be the time it takes to find suitable candidates. Goals have to be measurable, clear, and specific to: Promote accountability Evaluate and measure the goal's success Take data-driven decisions All growth requires dedication and effort from the team; time that they will not dedicate to product evolution or development. Example: Unrealistic Goal Let's suppose we have a team of 10 engineers divided into 2 squads: backend and platform. The company set the following goals: Triplicate the team in 1 year, from 10 to 30 engineers. Keep the delivery performance. Create three news squads: DevOps, Data Platform, and Front End. Promote the culture. Only hire top-tier engineers. Most likely, the number of candidates we will have to evaluate in interviews and technical exercises will be at best four candidates for each position in addition to the time dedicated to the onboarding process. Usually, there is more than one engineer collaborating in the hiring process so we are likely to have a significant impact on delivery. Finding a team of experienced and highly qualified people is not an easy task. It is necessary to define what we consider "talent" and the different levels at which we can hire. Maintaining and promoting the culture in a high-growth environment where in one year there are more new people than the team we have is very complex and requires a good strategy, definition of objectives, and agility in decision-making. With this, we want to reflect that one of these objectives would already be ambitious - but all of them together make it practically impossible to achieve success. Talent Acquisition and Hiring Process The talent acquisition team plays a crucial role in a company's growth strategy, but they need the support of all of the company. C-Levels and hiring managers have to provide all the support and be involved as the same team. Clear Communication Foster open and clear communication between teams to ensure that everyone understands the goals and the role each team plays in the process. Review Pipeline Quality Sometimes many candidates go through the early stages of the pipeline and are ultimately discarded, and this generates a lot of frustration in the engineering team because the analysis of each candidate requires significant effort. It is important to adjust the requirements and search criteria for candidates in the early stages of the pipeline and this requires constant communication between the teams. Market Knowledge Talent acquisition teams should provide insights into market trends and competitor strategies. This knowledge provides important information to the company to define the expectations and strategy and stay ahead in the market. Cultural Values It is important to keep in mind that each engineer who joins our team brings his or her own culture based on factors such as work experience, personality, or the country where they live. Although these people fit the cultural pattern we are looking for, most of the time they do not have the culture of the company, and the hiring process is not reliable. If maintaining the culture is important to the company, we need to mentor new employees starting with the recruitment process itself. Promote values in the hiring process. Promote values in the company and team onboarding process. Promote values during the first years through the mentoring process. Promoting the cultural values and the company's goal are tasks that must be done continuously, but we must reinforce and review them with new hires more frequently. On-Boarding In my opinion, the onboarding process has a huge role in almost all companies and is not given enough attention. It is especially important in high-growth companies. The two main problems are: No onboarding process: Onboarding is focused on a meeting with human resources, another with the manager, and finally the team: a three-hour process. This can only be considered as a welcome meeting. Highly technical processes: Processes very oriented to perform your first deployment and that mainly promote knowledge silos and little engagement with the company. The onboarding process must be led by the organization. It must be structured and must encourage a smooth integration of new hires into the organization, minimizing disruptions and maximizing productivity over time. In addition, the entire onboarding process should be a step-by-step process with as much documented support as possible. This would be a base structure for a complete onboarding process: Pre-boarding: It includes all the activities that occur between the acceptance of the offer and the new hire's first day. Continuous communication is important because it promotes motivation and cultural values and helps to create a feeling within the company. Welcome Day: Welcome meeting, company overview, review of company policies and cultural values Paperwork, documentation, and enrollment processes Initial equipment setup Introduction to Team and Manager Security training Company 360 (scheduled by month): 360-degree meetings with leaders from all departments provide valuable insights, foster collaboration, and help new employees understand the broader organizational context. Starting the first week: Cultural values and goals: The manager and the team share the same cultural values and team goals. The goals have to be clear and most of them measurable. Mentorship: Assign a mentor to support the integration process at least during the first year. Engineering Tech best practices and tools: Share the vision of architecture principles, DevOps, data principles, tools, and best practices of the organization. Roles-specific training Team integration: Start participating in team meetings. Feedback and evaluation: Feedback must always be continuous, honest, and constructive. We must put more emphasis on new hires to adjust goals, mentoring, or training. It would be better to start with one-to-one and include this evaluation and feedback in these sessions. Starting in the third month: Performance evaluation Continuous learning is part of the cultural values but at this time learning paths could be considered Initiate conversations about long-term career paths. It is important to avoid onboarding processes based solely on pairing or shadowing strategies because they require too much effort and also only generate silos and misalignment. These sessions are important but must be supported by documentation from both the organization and the team itself. Impact on Delivery The growth phase often requires a high investment of time, effort, and people in the hiring and onboarding process. Hiring process: Participating in technical sessions, reviewing candidate profiles, and reviewing technical exercises. Onboarding: The process of onboarding a new engineer to a team is always time-consuming and usually involves a learning curve until these people can offer more value than the effort invested in their integration. In the case of large growth, there may be situations in which teams are formed entirely by new engineers. This also has an impact on delivery, because these teams need: Mentors and support to adapt to the new environment Transversal coordination with other squads Talent Density In my opinion, growth should be based on the amount of talent and not on the number of engineers. At this point, there are a number of aspects to consider: What does talent mean to our organization? Finding talent is very complicated. There is a lot of competition in the market, people specialized in hiring processes, and the pressure to grow. Many people mistake talent for knowledge or years of experience. In my case, I have always given more value to the person's potential for the new role and for the organization rather than the experience in the role or the companies in which he/she has worked. The fit of a new hire is not only restricted to the hiring process but also to the evaluation period. Moreover, it is during the evaluation period that we can really evaluate the person. It is in this period when the decision is less painful for both parties, a person who does not fit in the organization will generate a negative impact both for him and for the organization. Team Topology These growth scenarios require changes in the organization and the creation of new teams or departments. Two fundamental factors must be taken into account: Team creation strategy Conway's Law Team Creation Strategy There are several strategies for developing the organization of teams: Integrate new hires into existing squads. Integrate new hires into existing squads and after some time, divide the team in two. Create entirely new teams with new hires. Create a new team from current leadership and new hires. The decision to apply a single approach or a combination of several approaches depends on several factors, including the organization's specific needs, resource availability, and long-term objectives. Conway's Law Conway's Law is a principle in software engineering and organizational theory: Any organization that designs a system (defined broadly) will produce a design whose structure is a copy of the organization's communication structure. Conway's Law suggests that the communication patterns, relationships, and team structures within an organization are reflected in the architecture, design, and interfaces of the software or systems they build. Summary The growth of engineering teams is one of the most complex challenges facing a growing organization, especially if this growth must be aligned with productivity and cultural goals. Hiring the number of people we have set as a target can be easy. Hiring the right people can be almost impossible and hiring a ratio of enough talented people is very difficult. This can only be done well if you work as a team.
Hello DZone Community! 2023 was certainly an exciting year for us here at DZone, and I hope it was filled with lots of love, laughter, and learning for you as well! One of the coolest things we did during the year was our latest DZone Community Survey! At DZone, our community is the heart and soul of who we are and what we do. We literally would not exist without each and every one of you, and the strength of our community is what sets us apart and makes us the go-to resource for developers around the world. And as with any relationship, the best way to grow and improve is to learn more about each other. That was our goal with the 2023 DZone Community Survey: to learn more about you, our community, so we can better serve you content that is relevant, helpful, and engaging for you while continuing to build the best platform on the planet for software developers to grow, connect, and share knowledge. We learned quite a lot about our community from the survey, and I wanted to share some of the highlights with you: Java is still the most dominant language, with Python being a close second. AI and applications for automating code processes are the topics of greatest interest. 90% of respondents prefer to learn through online communities like DZone and StackOverflow. This is just a small preview of what we learned, but what this means for you is that Java and AI content is continuing to see a lot of engagement on DZone, and AI specifically will be a hot topic to discuss on the site this year. (Read: If you’re looking for a topic to write about, Java and AI would be a great place to start.) It also reiterates why DZone is such a great place for developers to gather and share knowledge. We also saw some interesting changes from our last survey in 2020, such as nearly double the number of respondents working at the C-suite level and that 60% of you have a significant impact on the technology your company purchases and implements. We love that the DZone community is filled with so many expert, experienced developers. The level of knowledge here is unmatched, so when you add your voice to the conversation, you know you’re in strong company. In conclusion, we’re really excited about the results of our 2023 Community Survey, mainly because what we learned will help us continue to improve the content and experience we provide on DZone. We can’t tell you how much we appreciate everyone who took the time to respond to our survey, and we look forward to the 2024 DZone Community Survey! Thank you and Happy New Year! -The DZone Team
The software development landscape is constantly evolving with new technologies, techniques, and priorities. As we enter 2024, several key trends are poised to have a major impact on how software teams operate and the kinds of applications they build. Getting a head start on understanding these trends can help developers, designers, product managers, and technology leaders better meet user needs in the years ahead. Low-Code/No-Code Tools One of the biggest ongoing tech trends is the expansion of low-code/no-code development platforms that allow people with little to no coding experience to build applications. As these tools become more advanced and flexible, expect them to transform software creation in 2024 by opening development to non-technical personnel. Features like visual programming interfaces, drag-and-drop components, and AI assistance will provide faster and easier app generation for businesses looking to digitize operations without heavy coding skills. Advances in AI Functionality Artificial intelligence and machine learning are making apps smarter and more intuitive. In 2024, expect to see AI powering functionality like enhanced chatbots for customer service, predictive analytics that flag issues before they occur, and more human-like interactions. Frameworks like TensorFlow, PyTorch, and Keras will continue to improve to make AI integration simpler for developers. Natural language processing will also advance to understand context and intent better. Growth of WebAssembly WebAssembly is a cross-platform execution format poised for major adoption in 2024. It allows code written in multiple languages like C++, C#, or Rust to run on web browsers at near-native speeds. As WebAssembly usage increases, count on faster web apps with improved functionality, 3D graphics and gaming capability, math-heavy computations, and Environmental and Social Governance (ESG) assessments. Immersive Experiences Consumer desire for apps with immersive digital environments will drive the adoption of augmented reality (AR), virtual reality (VR), and mixed reality in business and gaming apps. Lightweight headsets like Meta Quest Pro with improved graphics will provide vivid 3D virtual collaboration tools and Training environments. Multi-sensory interfaces will engage more of the human perception system for rich experiences. Connected Applications A growing number of ordinary products will include embedded sensors and connect over IoT networks to provide real-time data and receive remote updates. App functionality will adapt to be the interface for querying device data and states as well as adjusting configurations. Home automation, industrial equipment monitoring, and transportation fleet coordination are some areas ripe for connected app innovation. Enhanced App Security As software becomes intertwined with more aspects of business operations and daily life, securing applications from cyber threats is increasingly vital. Developers will place greater emphasis on building security into design with techniques like DevSecOps, specialized testing, infrastructure as code, and component approval workflows in 2024. Compliance mandates will also expand. Rise of Metaverse Platforms The Metaverse concept involving collective, immersive virtual worlds will accelerate with more usable platforms tailored around branded spaces, video games, distributed workplaces, and event venues. Building the underlying virtual reality infrastructure and scalable networks will be a major undertaking needing collaborative teams of developers and engineers. Growth of Blockchain Applications The blockchain ecosystem will continue expanding through 2024, with application developers creating decentralized apps spanning finance, contracts, data integrity, identity security, and supply chain visibility. Smart contracts that automatically execute rules and procedures with less overhead will become more widespread. Various support tools will make blockchain integration simpler. Improved Developer Productivity Task automation, collaborative tools, and cloud-powered "software factories" with reusable components will improve application development speed and efficiency under the application development operations approach. Low-code tools and AI assistance will also reduce redundant work to allow innovation focus. Rapid 5G Adoption As 5G networks expand globally in 2024, software creators will need to adapt applications for speed, scale, and functionality advances to delight users with near real-time responsiveness. Testing applications will mandate mobile devices and environments reflecting 5G's multi-Gbps throughput and low latency capabilities. Expanded Use of Micro Frontends The micro frontends approach structures apps as independently deployable components owned by separate teams to allow parallel work and simplify maintenance. The methodology will compound in popularity given the benefits around modular development, choosing an ideal language for components, scalability, and resiliency. Increase of Multicloud Systems Rather than rely on one provider, development teams will increasingly leverage services from AWS, Microsoft Azure, Google Cloud, and other sources simultaneously. Multicloud architectures provide flexibility to use the best capabilities for specific workloads. The distributed model also avoids vendor lock-in and mitigates downtime risk. Growth in Neo Banks and FinTechs Financial applications will continue migrating toward mobile-centric neobanks and fintech disruptors updating legacy processes. Developers will focus on modernization and customer experiences, combining AI insights for personalization with automation for transferring funds, securing loans, and managing portfolios. Test Automation Priorities Pressure to release quality code quickly will drive automated testing tools and frameworks like Selenium, TestComplete, QMetry, and Cypress. AI-assisted technology can generate test scripts, identify impacted code areas to validate after changes, flag jagged system performance, and recommend security controls. Increased Monitoring and Observability To optimize user experience, developers will implement more sophisticated monitoring for application performance metrics, infrastructure health statistics, and business outcome KPIs. Unified observability pipelines will provide early insights into emerging issues so teams can get ahead of problems detected. Renewed Demand for Web Skills While native mobile development maintains solid demand, given enterprises adopting smartphones and tablets, developing interactive websites, web applications, and PWAs using HTML, JavaScript, CSS, and frameworks like React and Node.js will resurge. Practical web languages fit small business budgets while meeting customer expectations. Prominence of Data Streaming Architectures Streaming data patterns will become conventional, given usage growth for aggregating real-time system events, IoT telemetry, ad engagement, and other continuous inputs for driving instant analytics and decision-making versus traditional queries on stationary data. Apache Kafka, Spark, and Flink are common examples. Customer-Focused Design Priorities Software groups will emphasize designing inherently customer-focused apps upfront per models like the Kano Method versus later attempting culture changes among internal teams. Developers will also apply more UX research throughout build cycles to create human-centered experiences fostering customer delight and retention. Conclusion In closing, 2024 promises exciting innovation opportunities for software developers, particularly in the realm of enterprise mobile app development, as tools improve and new trends like low-code platforms and immersive interfaces gain prominence across consumer and business markets. Teams staying up-to-date on emerging technologies and best practices while focusing efforts based on customer needs will thrive in the years ahead. The advancements ahead will challenge development groups to adapt quickly but also provide them with more options than ever to deliver compelling solutions.
The profession of software engineering is one of the most dynamic and sought-after in today’s job market. To excel in this field, one must consistently refine their skill set, stay abreast of industry developments, and continually enhance their abilities. Drawing from over six years of professional development experience, I am presently engaged in mobile application development with the Alpha Mobile team. Coming from a non-traditional background without a foundational education in computer science, I vividly recall the early days of my career when I eagerly sought out any helpful information to navigate my path forward. This article will explore key strategies and practical advice for advancing your software engineering career. Whether you’re a budding developer or a seasoned professional, this piece will offer valuable insights into specialization selection, education, skill enhancement, and other vital facets of professional development. Rethinking Full Stack Positions In the evolving landscape of application development, the landscape has shifted significantly over the past decade. Previously, backend and frontend tasks of applications were typically integrated into a single monolithic process, with minimal focus on infrastructure and automation tasks. Developers often handled both client and server-side code, sometimes embedding application logic directly within the database through PL/SQL procedures, while the server side functioned predominantly as an intermediary layer for service functions. However, the current tech environment prioritizes rapid delivery of updates to end-users, necessitates scalable applications, and favors serverless microservice architectures as the industry norm. Consequently, backend developers are expected to have an intricate understanding of various patterns to ensure cluster resilience and system efficiency without bottlenecks. In this milieu, it’s becoming increasingly challenging for a software engineer to maintain expert-level proficiency in both frontend and backend development. Specialization has emerged as more than a trend—it’s an indispensable necessity. While full-stack developer roles continue to exist, they are often tied to projects with less complexity and have become more niche. It’s also observed that such roles may command slightly lower compensation compared to specialized positions. Major projects and reputable companies have recognized that delineating responsibilities is vital for delivering a high-quality product and facilitating a faster and more streamlined development process. Embracing a DevOps Culture and the Power of Automation In contemporary backend development, DevOps practices have become integral. The adoption of microservice architectures and “infrastructure as code” tools has led many organizations to move infrastructure management responsibilities onto the shoulders of developers. This transition, however, can distance backend developers from a thorough understanding of their system’s operations, potentially limiting their capacity to utilize resources effectively and architect applications efficiently. For robust architectural development, an intimate knowledge of the infrastructure specifics—such as traffic routing, load balancer locations, and the infrastructure components acting as cache or database storage—is essential. Commencing with the fundamentals is key. Take the time to comprehend the intricacies of technologies like Kubernetes and become proficient in the use of automation tools such as Ansible. A deeper understanding of these tools is pivotal to gaining insights into the underlying infrastructure, which in turn can significantly optimize work processes. Cultivating a DevOps culture goes beyond technology; it facilitates a closer synergy between developers and operations teams. This symbiosis enhances process efficiencies and elevates developmental quality. It promotes a shared responsibility for the delivery and lifecycle of applications, thereby reinforcing collaboration, streamlining workflows, and ultimately contributing to the success of the product. Seeking Opportunities in Product Companies The job market bifurcates largely into two types of companies: outsourcing companies specializing in custom software development and product companies designing, building, and marketing their own software products. The distinction between the two is not just in their products and services but also in their operational and developmental philosophies. Product companies place significant emphasis on code quality and robustness of their information systems. They maintain high standards, leverage cutting-edge technologies, and offer ample compensation to their developers in recognition of their expertise. Working within such companies amidst a cadre of exceptional developers provides a fertile environment for nurturing your skills and elevating your competencies swiftly to industry standards. For instance, at Alfa-Bank, 20% of our working hours are specifically earmarked for technical debt resolution and enhancement works. During this time, we focus on optimizing our extensive cluster of over 300 microservices, actively updating dependencies, and transitioning to more modern and efficient technologies. Some milestones achieved by the Alfa-Mobile development team in the past year include: Migrating our entire caching system from Hazelcast to Redis. Upgrading Java microservices to version 17. Updating all Spring Boot starters to version 3. Shifting the cluster from Mesos Marathon to Kubernetes. Gradually transition from Java to Kotlin and adopt the reactive stack for legacy microservices. Establishing an autonomous environment where new developers can both construct a microservice and deploy the required infrastructure using Ansible during onboarding. These initiatives not only bolster our system’s stability and performance but are also instrumental in sustaining its ongoing evolution—a hallmark of a product-focused company. The Value of Certifications in Professional Advancement Earning certificates can significantly bolster your proficiency in a specific programming language or technology and enhance your marketability as a professional. Outsourcing companies, in particular, may require a quota of certified specialists on their teams to qualify for certain projects or to stand out in competitive tenders. Consequently, these companies often subsidize training and examination costs for their employees and may offer higher salaries to recruits who already possess requisite certifications. However, the benefits of certification extend beyond the outsourcing realm. The process of preparing for certification exams compels you to engage with the material on a deeper, more systematic level. The act of repetitive learning ingrains knowledge in your long-term memory. This retained knowledge can remain relevant for years, compared to information from specialized books or online videos, which one might easily forget within weeks. Moreover, certifications can be pivotal during your job hunt. They serve as concrete proof of your expertise, enabling you to answer technical questions with greater confidence during interviews. They also showcase your drive and determination; allocating months of personal time to exam preparation is a commitment that few are willing to make. This dedication can set you apart in the job market, marking you as a highly motivated candidate with a clear focus on achieving your professional objectives. Building Your Personal Brand in the Tech Community Having a personal brand in the tech industry means being known and respected for your expertise and contributions to the professional community. This can encompass activities like authoring insightful articles, speaking at conferences, engaging in meetups and podcasts, and mentoring others. For many, these endeavors are not just avenues for personal fulfillment but also a means to give back to a community that once provided them with valuable information at the outset of their careers. The advice and knowledge you impart could be transformative for someone else’s professional journey. Psychological research suggests that the act of helping others and sharing knowledge creates a sense of happiness that often surpasses that derived from the passive consumption of information and services. But beyond the intangible rewards, such as personal satisfaction, these efforts yield tangible benefits. They allow for the further development of soft skills, deepen knowledge in specific subject areas, and elevate your status within the community. Your community engagement is not only personally enriching; it enhances your visibility and desirability as a job candidate. A strong personal brand can often tip the scales in your favor during interviews with recruiters and prospective team members, marking you as a specialist who not only excels technically but also demonstrates thought leadership and a proactive approach to professional growth. The Importance of Soft Skills for Developers While the primary responsibilities of developers may not traditionally center on intensive communication as they do for analysts or product managers, the cultivation of soft skills is nonetheless vital for both career success and daily interactions. In the recruitment process, companies evaluate candidates not only for their “hard skills”—the technical expertise—but also for “soft skills,” referring to one’s ability to communicate and interact effectively with others. Even candidates with impressive technical qualifications might find themselves at a disadvantage if they lack the ability to express ideas clearly, collaborate efficiently, or maintain pleasant interactions with team members. Possessing strong, soft skills can dramatically enhance your effectiveness in the workplace. This is particularly true in larger companies where coordination with different teams and departments is frequent. The ability to quickly relay and receive information can directly influence productivity and the capability to tackle complex problems. Moreover, productive and concise communication fosters a collaborative team environment, leading to better outcomes. As you progress in your career, especially if you aspire to roles like manager or technical lead, soft skills become increasingly critical. Skills such as team management, conflict resolution, and fostering positive interpersonal relationships become central to your daily functions. In leadership positions, your technical prowess is augmented by your ability to guide others, shape a productive work culture, and liaise effectively between different stakeholders. Thus, investing in your soft skill development is not just beneficial but essential for upward mobility in your career. Continual Learning as a Pillar of IT Success In the dynamic realm of information technology, perpetual learning isn’t just a recommendation—it’s a necessity for maintaining your competitive edge as a professional. As technologies advance and industry paradigms shift, the lifespan of technical skills can become increasingly short-lived. To ensure that your expertise remains relevant and that you continue to be a preferred candidate in the tech market, an ongoing commitment to education is vital. Engaging with various educational resources—whether it be formal courses, self-paced learning through books and videos, attendance at industry conferences, or the pursuit of personal coding projects—keeps your skills sharp and your knowledge contemporary. These learning avenues not only help you stay informed about the latest tech evolutions but also enable you to experiment with new concepts and tools practically, ensuring that theoretical knowledge translates into real-world proficiency. By fostering a mindset of continuous improvement and embracing the habit of lifelong learning, you position yourself to grow alongside the technology sector, adapting to its changes rather than being left behind. Remember, in a field driven by innovation, the most successful professionals are those who are as adaptive and forward-thinking as the technologies they master. Choosing Between Startups and Large Corporations Aligned with Your Career Goals The work environments and rhythms of startups contrast sharply with those of large corporations, and understanding these variations can steer you toward a path that resonates with your professional aspirations and lifestyle preferences. In a startup setting, the relatively nascent stage of the company often translates to less defined processes and roles. The fluid nature of startups could have you wearing multiple hats—not just developing but also testing, conducting requirements analysis, and providing support. This dynamic landscape offers a unique opportunity to engage with diverse projects, grasp the intricacies of different system components, and tackle a wide array of challenges. However, this comes with the expectation of high velocity, requiring you to handle a broader scope of tasks swiftly and adapt to frequent task-switching. Conversely, larger companies provide an environment of established procedures and more specialized roles. Here, the focus shifts to the quality and depth of each assignment over the sheer speed of delivery. Communication takes on heightened importance due to the need to collaborate across various departments. This can lead to extensive meeting schedules, which might feel excessive to some, but also creates space for you to develop skills that extend beyond the coding sphere, such as mentorship, interview conduction, and creating educational resources. For beginners eager to rapidly accumulate experience or those without substantial personal commitments, starting in a startup could be most beneficial. The breadth of exposure in startups can catalyze swift, professional growth. As expertise accumulates, preferences often evolve, with some developers transitioning to more established organizations where there’s a premium on the quality of work rather than on pace. Ultimately, whether to dive into the vibrant uncertainty of a startup or anchor yourself in the more predictable waters of a large company should reflect a harmony between the choice and your personal objectives and principles. The Merits of Specialization in Your Tech Career Career progression in the technology industry is often fostered by in-depth specialization rather than frequently shifting fields or programming languages. Many developers, seeking novelty or experiencing boredom, entertain the notion of changing their specialty. However, such transitions can erode previously acquired expertise and dilute the specialization, potentially rendering you less competitive in the job market. It could take years to regain the level of proficiency you had achieved prior to the shift. History has shown that sustained success in one’s career is usually the result of deepening one’s knowledge and skills within a particular niche. Specialists who have honed their expertise over time become invaluable assets, adept at handling complex and significant challenges. Consequently, their remuneration is often substantially higher than that of generalists who only have a cursory understanding of multiple domains. If there’s an area that particularly captivates you, investing your energy and commitment to it can be most rewarding. Of course, life can bring about profound shifts in interests and values, and if such changes lead to a disconnection from your current specialty, exploring other avenues can be warranted. However, it’s crucial to discern whether the root of the discontent lies in the specialization itself or in external factors such as the nature of the projects, team dynamics, or company culture. If it’s the latter, seeking a different environment that better aligns with your skills and passions might be a more prudent approach than a complete overhaul of your professional focus. Embracing AI Assistance for Enhanced Productivity in Development Incorporating Artificial Intelligence (AI) into your work routine can transform your productivity by automating mundane tasks and providing insightful guidance. The internet offers a wealth of resources detailing how AI can enhance your efficiency in development—these should be studied meticulously and applied judiciously. The AI sector is progressing swiftly, with the scope and capabilities of AI tools expanding continuously. These advancements are paving the way for deeper integration with development environments and tools. As such, proficiency in interacting with AI is becoming as essential as the knowledge of Integrated Development Environments (IDEs) and other development tools. Begin by gently integrating AI assistants into your daily tasks, which can include the automation of repetitive processes, analysis of extensive datasets, or furnishing thoughtful recommendations based on pattern recognition. Leveraging AI assistants in this manner allows for a smarter allocation of time and resources, fostering more strategic and innovative work in development. Moreover, it ensures that you stay attuned to the latest advancements in technology, keeping you ahead of the curve in a rapidly evolving digital landscape. The Timeless Value of a Healthy Lifestyle for Professional Productivity The principle of a healthy lifestyle may indeed seem trite, given its widespread acknowledgment, yet its consistent application in daily life is rarer than one might expect. Many individuals experience lapses in self-discipline, succumbing to the myriad temptations that can derail a healthy regime. Nonetheless, there are occasions—spanning weeks to months—when the focused intensification of efforts toward a disciplined lifestyle is paramount. Such dedication can be likened to an investment capable of yielding substantial returns in the form of enhanced productivity, sustained motivation, and a decrease in procrastination. A healthy lifestyle encompasses both physical and mental well-being, as the two are inextricably linked and pivotal to overall productivity. The following principles could have a profound impact on your efficiency: Curtail dependencies, ranging from social media and video content to news consumption. Disconnecting periodically from constant streams of content can serve as a catalyst for breaking out of stagnation and fostering increased productivity. Refrain from alcohol and tobacco use, both of which can have deleterious effects on your physical health and mental sharpness. Commit to regular physical activity—at least twice a week—or, at the very least, ensure a routine of daily walks to reap the benefits of freshness and exercise. Prioritize sufficient sleep, which typically means 7-8 hours nightly, although requirements may escalate with age. Adhere to a structured daily routine that balances work and rest, making you more organized and focused. Nourish your social connections, as interactions with friends and family play a critical role in maintaining emotional stability and mental health. Abiding by these principles is not just about feeling better in the short term; it’s about setting the groundwork for a prosperous, enduring, and fulfilling professional journey. A sound mind and a robust body are not mere benefits of a successful career; they are its very foundation. Conclusion As fledgling developers embark on their professional voyage, they often find themselves navigating a sea of questions and uncertainties. The advice offered throughout this discourse aims to illuminate pathways not only for career advancement and financial well-being but also for achieving a holistic and balanced life. The reminder that work is but a single facet of existence cannot be overstated. Equally crucial is the investment in one’s personal life—fostering relationships with family and friends, nurturing hobbies, and ensuring adequate rest and recreation. It is the harmonious consideration of these elements that culminates in a rich, fulfilling life. Thus, as you stride forward in cultivating your expertise and shaping a successful career, never lose sight of the personal joys and satisfactions that lie beyond the workstation. Cherish and cultivate your well-being and happiness as diligently as you do your professional skills. May your journey be marked by growth, fulfillment, and prosperity. Wishing you all the best as you forge a path to success that is uniquely yours.
Last year, I wrote my first yearly retrospective. I liked the experience, so I'm trying one more time. Let the future decide if it will become a trend or not. Before diving into our safe technological world, my thoughts go to Ukraine, to my friends who had to flee their own country, to other friends who fought on the front to defend it from imperial power, and to all victims of an old kleptocrat who clings to power despite the cost to others. The free world needs to support Ukraine more. I hope 2024 will be the year of Ukrainian victory. The AI Revolution Last year, I kept the post focused on what I did. However, AI is pervasive in our tech world, if not the whole world, and deserves a dedicated section. Nobody even remotely connected to tech can ignore the buzz surrounding AI. Even friends and families who don't work near tech probably talk about it. So far, I haven't woven any AI-related thing into any of my talks, despite the huge incentive to do so: having AI in your CFP proposal vastly increases your chances of being selected. And yet, it doesn't mean that I'm not playing with it on a personal level. Here's my experience so far. I've been playing with Dall-E as a use case to try out web development in Rust. I found the results mind-blowing. However, the limitations are enormous; it seems the size is always square, and the set of possible dimensions is limited. I've used ChatGPT in several areas. First, I tried to generate conference abstracts. I fed an entire blog post and asked ChatGPT to turn it into an abstract. Despite my lack of prompt engineering skills, I've found results severely lacking. Abstracts felt artificial, like any content created with ChatGPT, but worse, the abstract revealed too much or not enough. I also tried to use it to refactor two nested if else Kotlin statements, one nested in the other, to the null-safe let construct. The first result didn't compile; the second one forgot a branch. It led me to the correct solution, though. Finally, I recently started using GitHub Copilot as an extension inside of IntelliJ IDEA. Its behavior is fascinating: most of the time, it does nothing, but once in a while, it offers a snippet of a couple of lines, which is either entirely correct or at least very close to the target solution. Even better, the suggestions seem to be more frequent and even more relevant with time. All in all, I'm far from impressed by the current state of AI. However, I like Copilot a lot: I prefer rare advice that is relevant to the opposite. Technical Content Next February will mark the two-year milestone that I'm working for: API7.ai on Apache APISIX. I'm still very pleased about both. It allows me to do things I like a lot, such as writing posts and giving talks. In 2023, I published fifty blog posts on this blog: one each week on Sunday, but on Christmas and the New Year — for obvious reasons. Here are the top most viewed pages: Rank Post Views Avg. time on page #1 Leverage the richness of HTTP status codes 14,848 :29 #2 A list of cache providers 12,770 1:15 #3 Calling Rust from Python 8,780 :52 #4 My final take on Gradle (vs. Maven) 8,238 2:11 #5 Learning by doing: An HTTP API with Rust 6,642 1:00 I continue to cross-post on different sites. Here are the numbers compared with last year's: Site 2023 2022 Medium 741 564 Dev.to 8156 1,838 Hashnode 89 80 Absolute numbers are not that interesting, but comparing them is. Interestingly, numbers on dev.to are growing wildly, while on Hashnode, they plateau. Note that other sites provide no precise follower count or no count. Besides, I created a script to track daily metrics across sites and social media, just as I did for Apache APISIX. It displays interesting results: As above, numbers are much less important than the trend. Growth visibly happens mainly on dev.to and Bluesky for reasons I cannot fathom (yet?). Finally, I started a weekly newsletter, unoriginally named A Java Geek weekly. So far, I've written a couple of them. I list the posts and videos I found interesting during the week. Note that they contain the same links I post on LinkedIn, Mastodon, and BlueSky, with a bit more content, either a summary or my opinion. Open Source Contributions In 2023, after over twenty years in software, I finally became an Apache committer! I'm both excited and impressed; it's like belonging to a group of mythical beings I'd only heard about. Of course, working on Apache APISIX helped a lot. Yet, the exciting bit is that all my contributions are entirely unrelated to code; they are blog posts, reviews of blog posts written by others, issues, comments on issues, etc. Here's the GitHub summary: Conclusion Last year, my resolutions were: To deepen my understanding of the Apache APISIX ecosystem Write as many blog posts as in 2022 — it's hard to do better, anyway Design at least three new talks I fulfilled the two first goals but unfortunately failed the last item. I have only created two new talks, both based on previous posts. I'll keep them secret for now; they should appear soon on my Speaking page in case they are selected. I lack imagination, so I'll keep the same goals for this year as last year's and add exploring the API7.ai ecosystem as well. Let's see how it fares. Happy New Year!
Are you tired of your development team spending countless hours on repetitive tasks instead of focusing on innovation? Are you looking for a solution that can boost their productivity while reducing business costs? Look no further than platform engineering! In this blog post, we will explore how platform engineering revolutionizes the way developers work, enabling them to unleash their full potential and create amazing products. Join us as we witness increased efficiency, reduced downtime, and a significant drop in operational expenses through platform engineering for both developers and businesses alike. Introduction to Platform Engineering Platform engineering is not a new concept in terms of what developers have been building for end-consumers or teams creating products for developers, such as Postman and GitHub. However, in recent years, this term has become more associated with teams building platforms for internal use, bridging gaps within organizations. DevOps emerged to bridge the gap between development (devs) and operations (ops), achieving notable success. However, as technology advanced and new challenges arose, DevOps teams often faced recurring issues. To overcome these challenges, the concept of self-service DevOps platforms or platform engineering is now buzzing in the technology market. Platform engineering involves designing, building, and managing infrastructure and tools for efficient application development and deployment. In simpler terms, it acts as the bridge between software development and IT infrastructure. The goal of platform engineering is to provide developers with a consistent and reliable environment for developing, testing, and deploying their code. This encompasses everything from hardware resources such as servers and databases to software tools like version control systems, continuous integration/continuous delivery (CI/CD) pipelines, monitoring systems, and more. Traditionally, these infrastructure tasks were handled by IT operations teams, separate from the development team. However, with the rise of agile methodologies in software development, there has been a shift towards integrating these two teams into one cross-functional unit. Platform engineering facilitates this seamless collaboration, enabling developers and IT operations to jointly build high-quality software at scale. Why Is Platform Engineering Becoming Increasingly Important? The main goal of platform engineering is to reduce the time and effort required for software development by providing a stable foundation for building applications. This enables developers to concentrate on writing code rather than managing complex infrastructure challenges, leading to faster and higher-quality feature delivery. Here are some key reasons for its growing importance: Increased demand for digital products: The surge in e-commerce, mobile apps, and other digital services compels businesses to continuously innovate and release new features to remain competitive. This demands that developers deliver quickly while upholding high-quality standards. Growing complexity of systems: The complexity of modern software systems is escalating due to factors like cloud computing, microservices architecture, and big data processing requirements. Platform engineering streamlines this complexity by providing standardized processes and tools, ensuring consistency across applications. Need for scalability: As businesses expand or experience fluctuating demand, their software systems must scale accordingly. Platform engineering facilitates this scalability by ensuring that infrastructure can handle increased loads without compromising performance or reliability. This adaptability is crucial for businesses to respond to market changes and customer demands efficiently. Enhancing collaboration and efficiency: By bridging the gap between development and operations teams, platform engineering fosters a more collaborative and efficient environment. This integration results in fewer silos, better communication, and a more cohesive approach to software development and deployment. Emphasis on automation and continuous improvement: Platform engineering often incorporates automation in building, testing, and deploying applications, which significantly reduces manual errors and speeds up the development process. This continuous integration and delivery model enables teams to iterate rapidly and respond to feedback more effectively. Benefits of Platform Engineering for Developers Platform engineering is a crucial aspect of software development that focuses on building and maintaining the underlying infrastructure that supports a software platform. It involves creating a stable, scalable, and secure foundation for developers to build upon and deliver high-quality products efficiently. In this section, we will delve deeper into the benefits of platform engineering for developers. Increased Productivity Platform engineering is a rapidly growing field that focuses on creating and managing platforms for software development. These platforms provide a centralized, streamlined environment for developers to work in, allowing them to increase productivity and reduce business costs. In this section, we will delve into the ways in which platform engineering can help increase developers' productivity. Standardized Infrastructure One of the key benefits of platform engineering is the creation of a standardized infrastructure for development teams. This means that all developers are working with the same tools, frameworks, and environments, eliminating any inconsistencies or compatibility issues. With a unified infrastructure in place, developers can spend less time troubleshooting technical problems and more time actually coding and developing new features. Automation Platform engineering also involves implementing automation processes throughout the software development lifecycle. This includes automated testing, deployment pipelines, and continuous integration/continuous delivery (CI/CD) practices. By automating repetitive tasks such as testing and deployment, developers can focus their time and energy on more complex tasks that require their expertise. This not only improves productivity but also ensures higher-quality code with fewer errors. Collaboration Another crucial aspect of platform engineering is fostering collaboration among team members. With a centralized platform in place, developers can easily share code, collaborate on projects, and communicate effectively without having to switch between different tools or systems. This streamlines communication and promotes teamwork among developers, which ultimately leads to increased productivity. Scalability Platform engineering facilitates rapid scalability, enabling teams to efficiently adjust resources to meet fluctuating project demands. This adaptability is vital in fast-paced markets, allowing for seamless scaling in response to business growth or changing requirements. By simplifying resource management, platform engineering ensures consistent developer productivity, even as project scopes evolve, freeing developers to concentrate on innovation and problem-solving instead of infrastructure concerns. Lower Business Costs One of the most significant benefits of platform engineering is its ability to lower business costs. By streamlining development processes and improving efficiency, businesses can save time and money in various areas. Here are some ways in which platform engineering helps reduce business costs: Faster Time-to-Market With traditional software development methods, it can take months or even years to develop a product and release it into the market. However, with platform engineering, developers can create a functional minimum viable product (MVP) quickly, allowing businesses to get their products to market faster. This reduced time-to-market results in cost savings for the business as they can start generating revenue from their product sooner. Reduced Maintenance Costs Platform engineering emphasizes creating reusable components that can be used across multiple applications and projects. It reduces the need for maintaining separate codebases for each application, resulting in significant cost savings on maintenance efforts. Additionally, by using standardized components and frameworks, developers spend less time troubleshooting issues, further reducing maintenance costs. Efficient Resource Management Platform engineering allows for efficient resource management by automating repetitive tasks and optimizing resources like servers, databases, etc., based on demand. With automated resource allocation and usage monitoring tools, businesses can avoid unnecessary expenses on underutilized resources while ensuring optimal performance. Cost-Effective Scalability Scalability is crucial for any growing business or application. Traditional software development methods often require significant investments when scaling up an application’s infrastructure or adding new features. Streamlined Processes Streamlined processes are an essential component of platform engineering that can greatly impact the productivity of developers and ultimately lower business costs. Businesses need to adapt quickly to changing market demands and customer needs. This requires a high level of efficiency in developing, deploying, and managing software applications. The best example is the SAAS product, which might require new deployment to onboard new customers, which can be streamlined to deliver within hours rather than days or weeks. Key Components of Platform Engineering Infrastructure as Code (IaC) Infrastructure as Code is a pivotal aspect, allowing for the automation of infrastructure provisioning and management. Tools like Terraform and Cloudformation enable developers to define infrastructure using code, making it easy to create, modify, and share infrastructure safely and efficiently. IaC integrates seamlessly with containerization and orchestration tools, creating a cohesive and automated environment for platform engineering. This approach ensures that infrastructure provisioning is as agile and manageable as application development, reinforcing the principles of speed, scalability, and reliability. Containerization Containerization is central to platform engineering and revolutionizes the way applications are developed, deployed, and managed. By encapsulating an application and its dependencies in a container, it ensures consistency across different environments. Docker Docker is a pivotal tool in this domain, enabling developers to easily create, deploy, and run applications in containers. It streamlines the process of packaging an application with all its dependencies into a single container, which can then be run on any system that supports Docker. This simplifies development and testing, ensuring that applications work seamlessly in any environment. Kubernetes Kubernetes is an advanced container orchestration platform that further enhances container management. It automates the deployment, scaling, and operation of containerized applications, efficiently managing clusters of containers across multiple hosts. Kubernetes' ability to orchestrate complex container setups makes it indispensable for modern cloud-native applications. Helm Helm, often termed as the 'package manager for Kubernetes', simplifies Kubernetes deployments. It allows developers to define, install, and upgrade even the most complex Kubernetes applications. Helm charts help manage Kubernetes applications through easy-to-understand configuration files, streamlining the deployment process and ensuring consistent deployments across different environments. Challenges and Solutions in Adopting Platform Engineering Future Outlook and Trends in Platform Engineering The field of platform engineering is rapidly evolving, driven by technological advancements and changing business needs, as indicated by the 2023 Platform Engineering survey and Gartner's insights. Here's a look at the key trends and future outlook in this domain: Increased Emphasis on Automation and AI Future platform engineering will likely see more extensive use of automation powered by Artificial Intelligence (AI) and Machine Learning (ML). These technologies will enable even smarter automation of development and operational tasks, reducing manual effort and improving efficiency. Growth of Serverless Architectures Serverless computing, where cloud providers dynamically manage the allocation of machine resources, is expected to gain more traction. This shift will further simplify infrastructure management, allowing developers to focus purely on code. Rise of Edge Computing With the growth of IoT and the need for faster processing, edge computing will become more integral in platform engineering. This involves processing data closer to where it's generated, reducing latency and bandwidth use. Enhanced Focus on Security (DevSecOps) Security will continue to be a top priority, leading to the further integration of security practices into the DevOps pipeline (DevSecOps). This will ensure continuous security monitoring and compliance throughout the software development lifecycle. Multi-Cloud and Hybrid Cloud Strategies The adoption of multi-cloud and hybrid cloud approaches will increase, allowing businesses more flexibility in their cloud strategies and avoiding vendor lock-in. Greater Adoption of Microservices and Containers The trend towards microservices architecture and containerization (using tools like Kubernetes and Docker) will continue to grow, providing more agility and scalability in application development and deployment. Expansion of Infrastructure as Code (IaC) IaC will become more prevalent as it provides a more efficient way of managing infrastructure with the benefits of version control and documentation. Enhanced Observability and Monitoring Observability will become more critical in platform engineering, enabling teams to monitor applications more effectively and understand the deeper context behind data and trends.
Hit Pause! I've been on break for the past few days, completely unplugged from work. It's been a time of reflection, diving into fiction, and sometimes simply sitting and doing nothing. I've wandered through various Christmas markets and taken a few spontaneous day trips to nearby towns, enjoying holiday cheer. Sure, at times, I felt physically tired, but never exhausted. It made me realize how crucial it is to hit pause. In our hectic day-to-day lives, we constantly find ourselves making decisions. From the moment we wake up — deciding on breakfast, travel to the office or work from home, and so on — to big decisions such as where to attend university, which car to buy, or where to live, each carrying its weight. Internet sources claim that we make roughly whooping 35,000 decisions a day! If we assume an adult sleeps for eight hours, thankfully decision-free, that amounts to more than 2,100 decisions per waking hour or about three decisions every five seconds. Tech World of Constant Choices In recent years, the software realm has experienced exponential growth and acceleration. Being an IT pro means mastering multiple tools, navigating diverse platforms, operating within larger teams, and meeting heightened client expectations to turn those innovative ideas into life. Take, for example, full-stack developers today — they are juggling front-end technologies, backend languages, databases, cloud solutions, web architecture, versioning, testing methodologies, and Agile approaches. And guess what? That's just scratching the surface! Diving into the front end alone, like choosing a JavaScript solution, you are filtering through numerous frameworks, each necessitating careful selection and combination for optimal outcomes. But wait, it does not end there, and the technology continually evolves, with new frameworks and significant updates emerging almost daily, making it nearly impossible to make a perfect decision. We, tech professionals, encounter essential decisions that demand cohesive teamwork to devise strategies, deliver secure, scalable solutions, and visualize development roadmaps. These decisions necessitate focused efforts like workshops or sessions. Then, we have routine tasks such as coding, refining, and documenting, which need constant thinking. Amidst these concrete decisions, we must make countless tiny choices, often termed micro-decisions. Should I respond to this Slack message now? Answer this call or let it ring? Must I attend this meeting? Does this email need an immediate reply? With our workplaces all tangled up in a web of apps, these tiny choices sometimes trip us up, disrupting our workflow and elevating stress levels. The Cost of Choice: Decision Fatigue Decision Fatigue isn't a new concept; it was introduced by social psychologist Roy F. Baumeister. Every decision has a cost, tapping into our limited mental decision-making power. Keep making choices, and the strain piles up. Psychology professors Michael Inzlicht and Brandon Schmeichel suggested that there's a cap to what we can accomplish in a day. Consequently, as our mental energy dwindles, it starts impacting our decision-making, specifically challenging choices. Instead of the most effective solution, we opt for a known effortless approach because the mental toll is lower. I believe every developer has encountered one-dimensional reasoning — decisions that seemed sound initially but led to incidents in production. I'm no exception. I work in a platform team that creates and maintains shared business service libraries. I've seen scenarios where the team caught up in endless meetings and rushed changes towards the day's end. Only to realize later that it suited only the team that asked for it, a quick fix. Instead, we needed a robust, more comprehensive, generalized, and future-proof solution that required much more effort and thoughtful decisions to benefit everyone. As decision-making fatigue mounts, so does stress. This piled-up stress can lead to burnout, affecting our job performance negatively. But it does not stop at work; it also seeps into our personal lives. From Overwhelmed To Optimized To ensure we are operating at our best, we must either avoid decision fatigue or design ways to recover. World leaders like Obama and Zuckerberg have their strategies to combat decision fatigue, keeping things simple with daily routines that preserve mental energy for critical decisions. Stealing their proven techniques could serve as an excellent starting point. But apart from holding the mental energy, we can also refill it by taking regular breaks, especially when we notice signs of fatigue. I actively keep an eye out for these signals. For example, whenever I find myself easily distracted during work, I know something is going wrong. If I am checking phone notifications or skimming through news headlines more than I should, it is a clear sign that I have lost interest. Forcing myself to power through the task despite a lack of interest will drain my willpower unnecessarily. It is a clear signal for me to pause, take a breather, glance out the window, and get some fresh air. Another effective method for me has been the Pomodoro Technique. It's all about laser-focused work intervals. I lock into a 25-minute Google timer session, shutting down all notifications to banish distractions. No emails or Slack pings — just me and the task at hand. Then, after that intense session, I take a quick 5-minute breather. Trust me, after these power-packed sessions, I've consistently found myself more productive and less drained. Final Words The research and articles I referenced above suggest interesting hacks like avoiding late-day decision-making or simplifying decisions such as having a wardrobe with identical plain t-shirts and suits. But hey, not all studies have the same findings. For instance, in a study led by Stanford psychologist Carol Dweck and her colleagues, she concluded that waning willpower was apparent only in participants who believed willpower was a finite resource. Decision-making isn't a one-size-fits-all deal. While cutting down on small choices can save time and enhance efficiency, rigid routines might feel monotonous, confining, or impossible for some. Regardless, buying into the idea of limited decisiveness or willpower probably won't do us any favor. Instead, I would say acknowledging that mental energy is a depleting resource and can drain over time, like a muscle that fatigues with exercise, can be practical to avoid exhaustion. I wish you more power in the year 2024. Happy New Year!
Miguel Garcia
VP of Engineering,
Nextail Labs
Jade Rubick
Engineering advisor,
Jade Rubick Consulting LLC
Dan Lines
COO,
LinearB