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Category: DevOps Practice

  • Best of 2022: Agile/Scrum is a Failure – Here’s Why

    Best of 2022: Agile/Scrum is a Failure – Here’s Why

    As we close out 2022, we at DevOps.com wanted to highlight the most popular articles of the year. Following is the latest in our series of the Best of 2022.

    Welcome to The Long View—where we peruse the news and strip it to the essentials. Let’s work out what really matters.

    This week, something a bit different: I’m devoting my entire column to Agile and Scrum. They’re increasingly getting a bad reputation, being associated with the worst aspects of toxic workplace culture: Sexism, racism, burnout, micromanagement. (more…)

  • Five Great DevOps Job Opportunities

    Five Great DevOps Job Opportunities

    DevOps.com is now providing a weekly DevOps jobs report through which opportunities for DevOps professionals will be highlighted as part of an effort to better serve our audience.

    Our goal in these challenging economic times is to make it easier for DevOps professionals to advance their careers. Of course, the pool of available DevOps talent is still relatively constrained, so when one DevOps professional takes on a new role it tends to create an opportunity for others.

    The five job postings shared this week are selected based on the company looking to hire, the vertical industry segment and, naturally, the pay scale being offered.

    We’re also committed to providing additional insights into the state of the DevOps job market. In the meantime, for your consideration:

    ZipRecruiter

    CapitalOne
    New York, New York
    Lead Software Engineer
    $190,950 to $225,278

    Monster.com

    UMD Energy Solutions
    Bonita Springs, Florida
    AWS Cloud Engineer
    $140,000 to $150,000

    Dice.com

    Cox Communications
    Atlanta, Georgia
    Lead DevOps Engineer
    $105,700 to $176,100

    Indeed.com

    Northrup Grumman
    Dulles, Virginia
    Senior/Principal DevOps Engineer
    $104,600 to $157,000

    SimplyHired

    Visa
    Miami, Florida
    DevOps Engineer
    $85,000 to $120,000

  • Best of 2022: We Must Kill ‘Dinosaur’ JavaScript | Microsoft Open Sources 3D Emoji

    Best of 2022: We Must Kill ‘Dinosaur’ JavaScript | Microsoft Open Sources 3D Emoji

    As we close out 2022, we at DevOps.com wanted to highlight the most popular articles of the year. Following is the latest in our series of the Best of 2022.

    Welcome to The Long View—where we peruse the news of the week and strip it to the essentials. Let’s work out what really matters.

    This week: JavaScript is a bloated barrier to progress, and Microsoft’s emoji are on GitHub. (more…)

  • Best of 2022: Three Cloud Trends to Watch in 2022

    Best of 2022: Three Cloud Trends to Watch in 2022

    As we close out 2022, we at DevOps.com wanted to highlight the most popular articles of the year. Following is the latest in our series of the Best of 2022.

    Many developers and startups view cloud services as simply “compute”, “storage” and “networking.” The cloud has matured to the point where customers often don’t think about the underlying infrastructure, service levels or debate the merits of on-premises versus cloud&;mdash;instead, they are increasingly cloud-first. In fact, December of 2021 marked Amazon Web Services (AWS) marked its tenth AWS re:Invent conference—the company’s annual conference for customers and partners.

    While many startups don’t think twice about centering their IT strategy around the cloud and SaaS offerings, the enterprise has been slower to adopt cloud computing at scale. The conversation for these companies revolves around security, compliance, SLAs and the loss of control over their technology stack. In many ways, little has changed about the questions that enterprises are asking about the cloud.

    As the year starts, I’ve been reflecting on various conversations I’ve had with a variety of IT and business leaders, Digital CxOs and vendors. Below are three trends that I will be tracking this year.

    1. Alternative Vendors Gain Momentum

    The “big three” hyperscalers continue to dominate the market and garner the bulk of customer and partner attention. However, we are seeing increasing interest in the alternative cloud market. The alternative market includes vendors outside of the big names (AWS, Microsoft Azure, Google Cloud, Oracle, IBM and Salesforce). Developers and businesses are increasingly looking at alternative vendors and their offerings because they are easier to use than hyperscalers, less expensive and offer more predictable pricing models. In addition, with the tight labor market, hiring developers that are, for example, AWS certified can be extremely expensive. On the other hand, because alternative clouds are less complex, developers do not need to have the same certifications.

    You might ask: What about the global scalability, quantum computing and/or the thousands of APIs that the hyperscalers offer? The truth is that most small and midsize businesses don’t actually need any of those capabilities and don’t want to help subsidize the R&D that these technologies require. Companies to watch in the alternative cloud market include Linode, Digital Ocean, OVHcloud, UpCloud, Hetzner and Equinix Metal. In 2021, Techstrong Research published a report, DevOps and the Alternative Cloud, that dives deeper into these alternatives.

    2. Industry-Specific Cloud Ecosystems Expand

    Banking, insurance and companies in other highly-regulated industries have been slow to adopt cloud computing. However, the market is quickly evolving and businesses are rethinking their approach to the cloud. One of the reasons these regulated companies are starting to invest more heavily in the cloud is because customers have heightened expectations when it comes to how they engage with businesses. If customers are unhappy, it’s easier than ever to find alternatives. These highly-regulated companies and industries are being increasingly challenged by fintech, insurtech, healthtech and other industry-focused startups.

    Just as importantly, vendors are realizing that one size doesn’t fit all. Regulated industries need specific clouds that meet their regulatory and compliance needs. These industry-focused clouds aren’t being designed as an entire ecosystem where a variety of technology partners can offer their software to regulated industries. Instead, vendors have taken two different approaches to offering industry-specific offerings. Some providers are offering pre-built but customizable applications. Some notable announcements in the area of banking clouds include the following:

    • Goldman Sachs and AWS are working together to create data management and analytics solutions for financial services organizations (announced at re:Invent 2021). The result of this collaboration is the Goldman Sachs Financial Cloud for Data. It’s unclear if AWS will be offering a more general financial services ecosystem in the future.
    • IBM continues to grow its Cloud for Financial Services in terms of signature clients and partners. IBM built its cloud for financial services in collaboration with Bank of America, then hired the bank’s CTO, Howard Boville, to head up IBM’s hybrid cloud business.
    • Microsoft announced general availability of the Microsoft Cloud for Financial Services in November of 2021 (interestingly, it’s not named Azure for Financial Services). The company already has a large footprint in the financial services industry, and we’ll be tracking the adoption of Microsoft Cloud for Financial Services closely. In September 2021, Wells Fargo unveiled their digital infrastructure strategy that relies heavily on its partnership with Microsoft, but there is no mention of Wells Fargo using the Microsoft Cloud for Financial Services.

    I expect other industry-specific clouds to follow a similar pattern—with large vendors partnering with key industry incumbents to create cloud ecosystems that meet the performance, security and compliance requirements for that industry. For example, you can certainly imagine Oracle creating a Cloud for Health Care after the acquisition of Cerner closes.

    3. Software Supply Chain Becomes a Key Security Focus

    “Supply chain” was a key phrase across all industries and job functions in 2021. I’m particularly tracking the software supply chain—which, as you can imagine, is immense and complex. In essence, your software supply chain includes anything that might impact your software. That includes APIs, cloud services, containers, your DevOps pipeline and all of the open source components that you use. Software has many dependencies, and understanding the supply chain is critical to knowing your security and risk exposure. Take, for instance, the recent Apache Log4j vulnerability. Use of Log4j is pervasive, but how many companies were actually able to quickly identify what software is at risk? Check out Alan Shimel’s December blog post, Log4j: It’s All About the Supply Chain, Baby! to learn more about software supply chain security. In addition, API security is going to be a very hot topic in 2022.

    However, people remain the number-one cybersecurity threat. Although complex cyberattacks by ransomware gangs and state-sponsored actors get much of the attention, cloud misconfigurations and unpatched software are likely your biggest threats. Understanding your software supply chain will help uncover potential weak points and allow you to add automation, observability and/or other security tools to help spot potential problems.

    The Cloud Evolution

    Although the cloud isn’t new, the cloud market is continually evolving. While the developer community has been quick to adopt cloud computing, large enterprises have lagged—and regulated industries have been even slower. The alternative cloud market is offering different options for developers and businesses that don’t want the complexities of hyperscalers and don’t need their endless options and global footprint. At the same time, regulated industries are changing their cloud strategies thanks to cloud offerings that are uniquely focused on the challenges of their industry. Finally, you need to secure your software and data no matter where it resides. Focusing on your software supply chain will help ensure you can react to security vulnerabilities and update elements when needed.

  • Best of 2022: Using Event-Driven Architecture With Microservices

    Best of 2022: Using Event-Driven Architecture With Microservices

    As we close out 2022, we at DevOps.com wanted to highlight the most popular articles of the year. Following is the latest in our series of the Best of 2022.

    Microservices architecture is on the rise, already forming a key part of several current transformation projects, breaking down traditionally monolithic applications into self-contained, independently deployed services that are identified using domain-driven design.

    Stats from a recent study found that more than 60% of respondents have been using microservices for a year or more. In particular, finance and banking lead the way in using microservices, but many other industries are following suit including retail/e-commerce and telecoms.

    Not only do microservices hold the potential for enhanced scalability, flexibility and durability, but the time taken to deploy and maintain components is also significantly improved. This isn’t the case for all microservice architectures. Major impediments come in the form of ecosystem integration challenges and weak distribution processes.

    Busting the Myths of Distributed Computing 

    The implementation of microservices is more complex than one may first think, exacerbated by the fact that many DevOps teams fall into the trap of making false assumptions about distributed computing.

    The list of distributed computing fallacies was originally addressed in 1994 by L. Peter Deutsch and others at Sun Microsystems, and still holds true today. There are key fallacies that hold special importance to microservices implementation: reliable, homogenous, and secure networks, latency is zero and transport cost is zero.

    The smaller you make each microservice, the larger your service count, and the more the fallacies of distributed computing impact stability and user experience/system performance. This makes it mission-critical to establish an architecture and implementation that minimizes latency while handling the realities of network and service outages. 

    Uncovering the New, Updating the Old

    Microservices require connectivity and data to perform their roles and provide business value, however, data acquisition/communication has been largely ignored and tooling severely lags behind. We can see this with API management or gateway products that only support synchronous, request/reply exchange patterns. This only goes to exacerbate the challenges of distributed computing – they don’t have the ability to integrate with or acquire data from legacy systems.

    At the same time, eventing/messaging tools have also been stuck in the antiquated, non-agile world, being incompatible with many of the guiding principles of microservices such as DevOps and self-service. 

    Solving the Logistical Maze of Integration 

    As services become smaller and their purpose more singular, the potential for reusability increases, but that’s contingent on the ability for services to collaborate. Acquiring data for greenfield systems is easy, but microservices almost always come as a side effect of digital transformation, modernization — or the need to build new capabilities at a more rapid pace. 

    The Disconnect

    Most existing systems live on-premises, while microservices live in private and public clouds so the ability for data to transit the often unstable and unpredictable world of wide area networks (WANs) is tricky and time-consuming. 

    There are mismatches everywhere: updates to legacy systems are slow, but microservices need to be fast and agile. Legacy systems use old communication mediums, but microservices use modern open protocols and APIs. Legacy systems are nearly always on-premise and at best use virtualization, but microservices rely on clouds and IaaS abstraction. 

    The case becomes clear – organizations need an event-driven architecture to link all these legacy systems versus microservices mismatches.

    Creating the Perfect Microservices Harmony 

    The smaller the service, the less value it offers the end-user – value comes from orchestration. Historically, orchestration was handled by a central component like BPEL engines or ESBs, or, these days, API gateways.

    Orchestration is a good description – composers create scores containing sheets of music that will be played by musicians with differing instruments. Each score and its musician are like a microservice. In a complex symphony with a hundred musicians playing a wide range of instruments – like any enterprise with complex applications – far more orchestration is required. 

    Microservices are Well-rehearsed

    So, an example of microservices orchestration is when a microservice performs a series of steps within the code. The input or output of a microservice is a data event that has domain significance. But what is key is that since the microservice is merely producing an event, it does not have knowledge of if or when it will be processed. Other services must register their interest in the event, or set of events, and react accordingly. This all needs microservices orchestration. 

    Time to Shift the Focus

    Event-driven maximizes agility as it liberates data from being ‘at rest’ to being ‘in motion’ – consumable in real-time. Choosing the right eventing or messaging platform is one of the most critical steps to realizing the vast benefits of microservices.

    Microservices per se are not enough. Gartner has identified this need as far back as 2018 when it spotlighted ‘event-driven’ as one of its top strategic technology trends, citing “Digital business is event-driven, so organizations need to invest in event-centric design practices and technologies to exploit digital business moments.”

    The Full Potential of Event-driven Microservices

    Merging event-driven architecture with microservices can house major benefits. Developers can build highly scalable, accessible, robust and versatile systems that can digest and aggregate exceptionally large amounts of events and information in real-time. 

    Not only should modern events platforms be able to be deployed in every cloud and platform as a service, but they should also support DevOps automation. In such an ever-changing world, developers need a seamless self-service experience – only made possible with event-driven microservices.

  • Best of 2022: 6 Top Technology Trends to Watch

    Best of 2022: 6 Top Technology Trends to Watch

    As we close out 2022, we at DevOps.com wanted to highlight the most popular articles of the year. Following is the latest in our series of the Best of 2022.

    Technology trends simply cannot be ignored in today’s dynamic environment. As the world enters a post-digital era, organizations are exploring disruptive technology trends. Artificial intelligence, machine learning, intelligent process automation, advanced analytics, and robotic process automation (RPA) are among the top DevOps technology trends to watch. According to a survey by Accenture, 94% of IT and business experts reported that emerging technologies have accelerated firms’ innovation pace in the last three years. 

    Winning This Decade in the Context of the Next Normal

    This decade continues to witness further development in technology, as innovation transforms industries such as insurance, banking, and healthcare. It is crucial to look beyond seeking operational efficiency and decreasing cost — particularly as customer expectations, regulatory requirements and business landscapes are rapidly evolving. 

    Take a look at six vital technology trends that have gained momentum in today’s hyper-digital world: 

    Trend 1: Artificial Intelligence (AI), Machine Learning (ML) – Integrating Intelligence 

    Technologies like AI and ML have existed for some time, but only now have they started maturing from their perception of “interesting” to “organizationally effective.” Artificial intelligence and machine learning are digital transformation catalysts, and some of the capabilities that fall under this technology include pattern recognition, natural language processing and sentiment analysis. Artificial intelligence has become increasingly important because it provides companies with a competitive edge, is cost-effective and allows them to future-proof themselves. 

    Trend 2: Predictive Analytics – Harnessing New Opportunities 

    In this digital-savvy environment, it has become crucial for organizations to employ tools like predictive analytics.  An advanced form of data analytics, it’s used to extract information and predict trends, behavior and activities with precision. It is increasingly being introduced across industries as it optimizes productivity, helps understand customers better, identifies revenue opportunities and areas of attrition. Financial institutions have already begun to deploy predictive analytics, helping them customize the product offerings, detect fraud and identify new opportunities for cross-selling.

    Trend 3: Low code – Accelerating Innovation 

    Gartner forecasts that low code application platforms will be responsible for 65% of application development activity by 2024. Organizations are rapidly leveraging low code to cater to the growing needs of the digital-first customers, deliver mission-critical and enterprise-grade applications quickly and respond rapidly to unforeseen scenarios. 

    Trend 4: Intelligent Process Automation (IPA): Unifying Processes

    Another technology trend that has paved its path in the digital world is intelligent process automation (IPA). IPA is a group of technologies that work together to organize and digitize the end-to-end business processes and the customer journey. The key drivers of IPA are the need for continuous improvement, retaining data consistency and bridging existing silos.  The technology offers several benefits to an organization, such as reducing error rates, unifying operations, and accelerating processes, but more importantly, assisting in streamlining employee and customer-facing journeys.  

    Trend 5: Contextual Content Services – ECM: Leveraging Context in Content

    Contextual content services, an evolution of traditional enterprise content management (ECM), play a key role in powering automation initiatives. The right tools in ECM like intelligent taxonomy and cognition can bring context to business processes. Empowering users to make smart decisions with relevant information ensures accurate data extraction, and mitigates risks by managing the overall content lifecycle. 

    Trend 6: Robotic Process Automation (RPA): Improving Productivity 

    Robotic process automation is rapidly becoming an integral cog in the wheel of the end-to-end digital journey of organizations. RPA can be the last mile of process automation — or in between — but is key to streamlining and optimizing customer-facing and back-office tasks. The use of bots helps automate repetitive tasks and liberate knowledge workers to focus on other value-added tasks.  The capabilities of RPA offer several benefits, including faster turnaround times, process optimization, sustaining consistency and increasing employee productivity.  

    Future-proofing the Enterprise

    A close eye on the different technology trends can help enterprises leverage the right tools to optimize their business processes and adapt to the changing market needs. Technologies like low code platforms, advanced analytics, AI, and ECM are already being implemented by some organizations to stay ahead of the competition. Ensure your enterprise is tapping into these technology trends to thrive in the next normal.

  • Best of 2022: Environments-as-a-Service: Free Your Devs

    Best of 2022: Environments-as-a-Service: Free Your Devs

    As we close out 2022, we at DevOps.com wanted to highlight the most popular articles of the year. Following is the latest in our series of the Best of 2022.

    Environments are the bane of a DevOps engineer’s existence and have been since the invention of the server. They can create giant bottlenecks that hamper productivity and suck the life and motivation out of developers. But they’re also completely necessary.

    DevOps teams spend a ton of time building and maintaining their development environments. They are critical to testing new websites, apps, products and updates; making sure everything works the way it is supposed to. And not having enough environments can slow down workflows as developers wait their turn to use an environment.

    There is a new push in the software industry to provide environments-as-a-service (EaaS), removing the annoying yet necessary work of building and maintaining environments and giving DevOps engineers more freedom to tackle more challenging, revenue-generating projects.

    EaaS enables companies to use a third-party service to create a new development environment on-demand, including data, infrastructure and code—all the things necessary to build and run an app. Environments-as-a-service bring major improvements to businesses, saving money and time while increasing the velocity, delivery and deployment speed.

    EaaS offers automation and codification of all the things that would otherwise waste DevOps and infrastructure folks’ time. They should be focused on higher-value tasks, like creating and refining what makes the company or product unique.

    Removing Bottlenecks

    When prepping for a new product or service, teams have to test all associated code to make sure it is functional, secure and that there are no hiccups. Multiple environments are crucial to this process. However, in many cases, teams work within a single, shared staging environment.

    This setup means developers have to wait in line to test their part of the product. These bottlenecks are among the biggest causes of delayed releases.

    Time is money, and in this case, lost time costs money. We estimated the total cost of managing environments exceeded $45 billion annually, and release delays cost organizations millions of dollars every year.

    Organizations can layer EaaS on top of their infrastructure-as-code (IaC) frameworks, agile workflows and other important software. By doing this, developers can create a new environment with a single click.

    That means developers can make a new environment for every feature branch pull request. EaaS also unlocks customization capabilities, as well. For example, testing requires larger and faster environments that integrate with other key services, while more scaled-down environments work well for processes like demos.

    Now, developers are free to test and develop software, without waiting or stepping on anyone else’s toes. Plus, on-demand environments can also be destroyed when they are no longer needed. That’s capacity planning in real-time.

    Save Time and Money

    Capacity knowledge and better capacity planning mean money saved. Knowing how many environments are needed, and what types, helps organizations avoid over- or under-spending on cloud infrastructure.

    Building out environments can take more than a year for even sizable DevOps teams and cost hundreds of thousands of dollars, not to mention the challenges of ongoing management, integration of new tech and management of cloud resources and costs. A third-party EaaS provider takes care of all of that, freeing DevOps engineers to work on hard problems, rather than maintenance and repeating work that has already been done as technology advances.

    Is Your Organization EaaS Ready?

    Any time a company automates something as important as staging and testing environments, though, it’s important to have all their ducks in a row. Luckily, the best ways to do that match up pretty well with best practices for building out any infrastructure platform:

    ● Using infrastructure-as-code automates the provisioning of infrastructure instead of doing it manually.

    ● Containerizing custom code makes it easier to quickly reproduce it for new environments.

    ● Finally, carefully think about how your environments will behave when they are created dynamically. Simple things like creating environment variables for hostnames and trying not to hardcode variables that are environment-specific are a must.

    Organizations that have followed these steps are EaaS-ready. By automating these painstaking tasks, companies can unleash their DevOps teams to be superheroes for the organization, solving the biggest problems and letting tech take care of the rest.

  • 4 Ways to Build With an Accessibility-First Mindset

    4 Ways to Build With an Accessibility-First Mindset

    Over 1.3 billion people live with some form of disability. This accounts for almost 20% of today’s workforce in the U.S. While great strides have been made in closing the disability inclusion gap in the workforce, more needs to be done. 

    As the popularity of hybrid and remote work continues to grow, workers who live with a disability and work from home increasingly need accessible collaboration tools made available to them. 

    To meet this demand, developers need to build with accessibility in mind. By doing so, they can create more accessible software to help workers with disabilities overcome any unique challenges they may find when interacting with technology while creating an enjoyable working environment for everyone. 

    There are many ways to do this, however, here are some best practices and key learnings to help developers build with an accessibility-first mindset. 

    Challenge the Status Quo

    Innovation is always about challenging the norm, and this is especially the case when it comes to developing more equitable products. There are many ways to do this, depending on what processes are already in place. Still, one area that I believe can always be adapted is the way accessibility is thought of and managed internally, especially with regard to product design. 

    While the vast majority of companies today prioritize accessibility in some way or another, often it’s done by having a team—or, in the case of smaller departments, an ambassador—tasked with managing this work. This approach often leads to accessibility being seen as an add-on to design, something that happens at the end of the process. In reality, it’s better for developers and DevOps teams to take a hub-and-spoke approach to accessibility. In this model, there is one central source of expertise that people can go to for advice, but individual teams also are tasked with working on and being mindful of accessibility at the same time. The results as a collective would be far more collaborative and impactful. 

    Likewise, challenging the status quo could be as simple as encouraging conversations about accessibility with your team. If accessibility is a subject you want to discuss with your team but don’t know how to bring it up, remember that most accessibility problems stem from a lack of awareness. It’s usually an oversight, and ideas begin to flow once the conversation starts. So why not kickstart the conversation? Come prepared with user stories and potential solutions and your team will immediately start seeing all the appropriate changes that need to be made.

    Work Directly With People With Disabilities 

    When building any software, it’s important to gather feedback from all kinds of people so you can be sure you’re building the features and experiences people need. 

    When we begin a project or an update, we strive to understand how current functions or other similar products are (or are not) accessible so we can better understand our customers’ expectations or frustrations. There are a number of ways to do this, but perhaps the most broadly impactful is hiring people with disabilities and having an open discussion with them about the product. Along with hiring, it’s also valuable to contract specific companies that employ people with disabilities to test products and give their feedback. 

    Receiving this feedback is key to developing a successful product and usually results in a more flexible and well-rounded user experience. For example, a text-based app with extensive text scalability designed for people who are blind or low-vision will be equally as useful to a user who prefers their text to be small or uses the product in a language requiring different string lengths. Similarly, captions designed for people who are deaf or hard of hearing can be useful to anyone who might be in a noisy environment or who prefers to consume written rather than audio content. When you make a product work really well for a particular group, you inherently create a better and more adaptable experience for everyone; you are meeting users where they are. 

    Don’t Make Assumptions

    It’s incredibly important when you’re having conversations with people with disabilities or when designing a new product to not make assumptions. For example, early in my career, I would have assumed that an image-based program would be completely uninteresting to someone who is blind; I now understand that is categorically not true. By integrating interesting and vivid descriptions of images into the product, an image-based program can become accessible and engaging to all. 

    By avoiding assumptions about what someone can or cannot do based on their abilities, we open ourselves up to a world of creative solutions and possibilities that we might have otherwise not considered.

    While people with disabilities ultimately provide the best feedback, don’t forget to spend time on your own or as a team actively challenging your design and looking for ways to improve its accessibility. Spend an hour or two as a team using your product with a screen reader such as VoiceOver or TalkBack or use your application using only the keyboard but no mouse. By constantly engaging with and testing your own design, you will better understand the user experience and may catch bugs or accessibility issues on your own.

    Be Prepared for Trial and Error and Share What you Learn

    Twelve years ago when I first started to focus on prioritizing developing for accessibility, there was very little documentation on accessibility in this space–especially when designing for mobile technology. This caused a great deal of frustration and often slowed our work down as we tried (and failed) to get it right. Sometimes this involves a delicate balance of adhering to your product’s established standards (i.e. how things should be labeled or how things should look) while solving for accessibility and efficiency in tandem.

    Since then, things have changed a lot in the developer space. Today, there is a lot more material out there about the topic as well as industry standards to abide by. Universities are now offering more accessibility training within computer science courses, content creators with disabilities share more of their experiences, and companies are more open about sharing accessibility resources. 

    However, trial and error is still vital to building with an accessibility-first mindset, especially as we continue to innovate in this sector. So be patient and trust the process. 

    Inclusive design results in better products for everyone and, in particular, for all the people around the world experiencing some form of disability. Make sure you are a part of the solution and share your learnings with your developer community to continue this movement. 

    As a developer, the more time you spend learning and listening to your community and making them your number-one resource the more understanding you will be of their needs and how you can create the ultimate user experience. In turn, this empowers users to do their best work regardless of their abilities or circumstances. 

  • Best of 2022: SRE Vs. Platform Engineering: What’s the Difference?

    Best of 2022: SRE Vs. Platform Engineering: What’s the Difference?

    As we close out 2022, we at DevOps.com wanted to highlight the most popular articles of the year. Following is the latest in our series of the Best of 2022.

    Site reliability engineering (SRE) teams and platform engineering teams share similar goals—like maximizing automation and reducing toil—and similar methodologies. But they have different priorities, and use somewhat different tools to achieve them.

    What are SREs? What are platform engineers? How is each role similar and different? This article will answer all your questions.

    Responsibilities of SREs and Platform Engineers

    The main responsibility of site reliability engineers is ensuring that IT systems are reliable, which means that the systems meet performance requirements. Part of their job includes working with developers and IT operations teams to maximize the reliability of applications as they move down the software delivery pipeline.

    Meanwhile, platform engineers focus on managing and optimizing the software delivery process. You could think of this role as one that translates DevOps principles into practice by finding ways to implement continuous delivery, continuous improvement and other DevOps priorities.

    Thus, both SREs and platform engineers play a role in managing the software delivery process and finding ways to make it as smooth and efficient as possible. They also share a common enemy—toil—in the sense that both groups seek to avoid manual, inefficient processes by automating as much as possible. SREs automate complex incident response operations using tools, for example, while platform engineers might deploy methods like GitOps to automate some aspects of software delivery.

    Differences Between SRE and Platform Engineering

    That said, SRE and platform engineering are distinct roles. The key differences boil down to:

    • Goals: The main job of SREs is maximizing reliability, which is different from optimizing the speed and efficiency of software delivery operations. Theoretically, you could have a highly reliable system even if your software delivery chain is manual and slow.
    • Scope of role: Software delivery operations are the main focus of platform engineers. SREs care about software delivery, too, because the way applications are created plays a role in reliability and fixing issues. But SREs also have many other responsibilities, like incident response and helping to manage infrastructure, which fall beyond the scope of software delivery.
    • Tools: SREs rely on tools that help them discover and solve various types of reliability issues. In contrast, platform engineers leverage tools like source code managers and continuous integration (CI) servers to help automate software delivery.

    So, although SREs and platform engineers may use similar methodologies and possess similar skills, their day-to-day operations tend to look quite different.

    Should You Pursue an SRE or Platform Engineer Career?

    Given the skills overlap between SRE and platform engineering, some engineers are a good fit for either role. But which one is better, from a career perspective?

    Salary-wise, there’s not a whole lot of difference. Glassdoor pegs the average salary of platform engineers at about $115,000 compared to $127,000 for SREs. SREs may earn a little more (and it’s worth noting that SRE salaries can vary widely), but the difference in pay is not as great as that between, say, IT operations engineers (who make a mere $77,000, according to Glassdoor) and SREs.

    The roles are also similar in terms of demand. Unlike software engineering or even DevOps engineering, SRE and platform engineering are both roles that have begun to become popular only in recent years. SRE as a concept has been around for a while—it originated at Google in the early 2000s—but it wasn’t until recently that most companies began seeking SREs for their teams. Likewise, platform engineering didn’t become a thing until the advent of microservices and cloud-native everything pushed companies to devote more engineering resources to manage their increasingly complex software delivery processes.

    What this means is that, at least for now, it’s easy to find jobs in SRE and platform engineering as long as you have the right skills. Many companies are eager to hire for both types of roles.

    Choosing the role that is right for you, then, depends mostly on your preferences and how you like to work. The life of a platform engineer is likely to be somewhat more predictable than that of an SRE because platform engineers don’t have to take the lead in managing incidents when something breaks at 2:00 a.m. On the other hand, SREs enjoy a more diverse set of responsibilities, which can make the job more exciting—especially if software delivery tools like Git or Jenkins don’t make you excited to get out of bed in the morning.

    Conclusion

    Platform engineers and SREs play central roles in automating complex processes and eliminating toil. But they tackle these issues from different angles and they use different tools. The right role for you depends on what you enjoy doing most.

  • Best of 2022: Trends in Blockchain for 2022

    Best of 2022: Trends in Blockchain for 2022

    As we close out 2022, we at DevOps.com wanted to highlight the most popular articles of the year. Following is the latest in our series of the Best of 2022.

    Blockchain is hot right now. The industry has a staggering CAGR rate of over 69% between 2019 to 2025. Blockchain is no longer only relevant to cryptocurrency, either—blockchain-based applications are emerging to support many other scenarios that require decentralized data storage and accessibility.

    I recently met with Medha Parlikar, co-Founder and CTO, CasperLabs, to learn about some of the top trends that will likely impact this burgeoning sector in the coming months. According to Parlikar, we are still in the early stages of both blockchain and NFT development, and 2022 will see continued growth in the sector.

    These movements will likely include more significant investment into blockchain technologies and the emergence of nuanced business models that leverage NFTs. Proof-of-stake (PoS) models will likely become more critical to curbing negative climate impacts and more solutions will emerge to support the development and operations that sustain blockchain-based applications.

    Continued Blockchain Investment

    First, we will likely see greater investment in blockchain technology in the coming year. Unsurprisingly, finance will probably experience the most adoption, as the use of blockchain in the financial sector is anticipated to reach a value of 22.5 billion U.S. dollars by 2026. But outside of finance, blockchain investment will seep into innovative areas as well. For example, spending on blockchain in health care is expected to rise to $5.61 billion by 2025.

    Blockchain not only appeals to corporate interests—developers on the ground seem excited as well. “Developers are waking up to the opportunities that blockchain brings,” explained Parlikar. “We’ll see a big increase in developers moving into blockchain.” She pointed to a surge of developer interest in blockchain to construct tools that go beyond widgets to extract real business value.

    We’re also seeing a peak of interest in blockchain funding from nation-states. For example, in 2021, the European Union announced plans for a multibillion-euro investment into blockchain infrastructure.

    Uncertainties Around Regulation

    Blockchain is ushering in major economic shifts. But the cryptocurrency market is still a ‘wild west’ with little regulation. According to recent reports, it appears the U.S. Securities and Exchange Commission is gearing up to more closely regulate the cryptocurrency industry in 2022.

    “More investment in blockchain is bringing it into the mainstream, but what’s holding back a lot of adoption is regulatory uncertainty,” said Parlikar. Forbes similarly reports regulatory uncertainty as the biggest challenge facing blockchain entrepreneurs.

    Blockchain is no longer relegated to the startup domain, either; well-established financial institutions also want to participate in the massive prosperity, said Parlikar. This excitement is causing a development-first, law-later mindset, similar to the legal grey area that followed Uber as it first expanded its rideshare business.

    “[Blockchain] businesses are trying to hedge risk,” Parlikar explained. “We want to comply and aren’t doing nefarious things intentionally—there’s just a tremendous opportunity to innovate and streamline operations and increase the end-user experience.”

    New NFT Strategies to Emerge

    If you follow any artist accounts on Twitter, you’ve probably heard a lot about NFTs lately. Non-Fungible Tokens (NFTs) use blockchain technology to imprint ownership and value onto all types of assets.

    “I see NFTs as a great representation of the real world,” said Parlikar. Blockchain-fueled NFT technology is creating marketplaces out of ephemeral or purely digital things—such as 3D artwork—which could not be easily traded on typical markets.

    But, we’re likely only on the cusp of overall NFT usage. “The value of NFTs is still underutilized,” said Parlikar. Right now, NFT marketplaces are mainly just about asset ownership. But there’s no reason one couldn’t build, for example, an NFT rental system that shares access for a period of time, or one that offers subscriptions for recurring revenue, she suggested.

    “[There are a] lot of interesting markets that could emerge,” said Parlikar. For example, combining NFTs with the internet of things (IoT) could bridge the metaverse to the real universe, proving ownership for our physical assets.

    Proof-of-Stake (PoS) Response to Energy Backlash

    The dark side of cryptomining is that it takes significant computational power. Unnecessary computation is a drain on energy that exacerbates humanity’s environmental impact. And, if your say in a network is correlated solely with computational power, there will inevitably be an escalating computational arms race to one-up others in the network.

    This is why Parlikar is putting faith in proof-of-stake blockchains. “Proof-of-stake is definitely the way to go,” she said. In PoS networks, power is tied to the state of each actor in the network, which can be determined or modified by a consortium. Participants can agree on the governance model and set boundaries. This is opposed to proof-of-work (PoW), in which your power in the network is directly correlated to computational power.

    PoW systems become unsustainable for enterprises trying to spin up their own blockchain networks, or when attempting to lift up an entire industry, Parlikar explained, as well as increasing negative environmental impacts. Thus, PoS are a better fit to bring collaboration to enterprise-grade consortium networks.

    More Blockchain DevOps Solutions

    Overall, blockchain penetration is still relatively low. This is, in part, due to the fact that it’s still tough to use. As I’ve covered before, blockchain-based development is still relatively inaccessible. It requires nuanced theory to grasp and specific technical knowledge to implement. “It’s not trivial,” added Parlikar. “Dealing with private keys, obtaining keys—it’s still very complicated to get started.”

    Managing a blockchain could also use a dose of DevOps. Yet, blockchain’s immutability and decentralized nature create friction with traditional DevOps. “The majority of protocols will not allow you to put a smart contract under CI/CD,” Parlikar explained. Thus, organizations may opt for blockchain solutions that play nicely with test-driven development. These solutions will likely enable the ability to iteratively develop using established DevOps pipelines.

    Benefits and Challenges Ahead

    Interest in blockchain and distributed ledger technologies continue to surge. But, what are the end benefits of this blockchain and NFT-infused reality? According to Parlikar, we are heading toward “a world with greater trust and transparency.”

    Blockchain ensures provenance. To put it plainly, it validates that something was done at a certain point in time. With this knowledge, participants in a network could prove things beyond a shadow of a doubt.

    This has the power to avoid corruption and unlock more collaboration and value potential. “You don’t have to trust an individual—you can trust the information they are providing,” said Parlikar.

    It’s still early in the blockchain revolution. “Blockchain technology is still at the embryonic stage and facing many challenges,” wrote the European Commission in their report, Blockchain Now and Tomorrow: Assessing Multidimensional Impacts of Distributed Ledger Technologies. For blockchain to reach ubiquity, the community will have to overcome challenges, including lowering the energy footprint, improving developer usability and responding to impending legislation.