Category: DevOps Culture

  • The Business Case for DevOps Culture

    The Business Case for DevOps Culture

    Culture is nebulous. It encompasses all the behaviors and attitudes of an organization, from overarching business values down to the individual actions of an employee. Because culture is transient, it’s unique to every business, feels difficult to change and is even harder to measure. This can make it frustrating to see DevOps research continuously name ‘culture’ as the critical factor for DevOps success.

    Many teams are left wondering what a ‘successful’ culture looks like and struggle to pinpoint what changes they should make. While there isn’t a one-size-fits-all approach to cultural transformation since every business is different, there are three key traits of high-performing DevOps teams: Buy-in to the DevOps process, collaboration and continuous improvement.

    But even once you’ve identified how your team can embody these traits, it can still be difficult to put forward a case for improving culture when it’s so difficult to measure its returns. By linking each of these traits to measurable impacts on the wider business, it’s possible to make a strong business case for improving your DevOps culture.

    Buy-In Makes Your Business More Resilient

    No organization can foster a successful DevOps culture without buy-in from the whole team. Buy-in not only encompasses an understanding and acceptance of the DevOps process but is also a commitment to getting it right.

    Without cultural buy-in to the DevOps process, team members are more likely to circumvent established procedures. Following a DevOps process should overcome unnecessary downtime and failed releases, but neglecting the proper release management strategy will stop your team from seeing these improvements and hinder your ROI.

    Team buy-in to DevOps makes your release process far more resilient. With a common appreciation of and investment in DevOps, teams are far more likely to follow the planned and robust process. This attitude allows businesses to see far higher ROI. For example, Veolia, the energy and utilities giant, secured a 500% return on their DevOps investment within one year of buy-in to a new approach. Team buy-in is the first step you need to take in improving your DevOps culture—it’ll ensure the technical resilience of your processes necessary to secure ROI.

    Collaboration Makes Your Business More Efficient

    DevOps doesn’t just encourage collaboration between Dev and Ops teams—it encourages all team members to work together across functions and share responsibility.

    When only one team member has the expertise or responsibility required to move through a stage in your DevOps process, there’s a single point of failure. If this team member doesn’t have the capacity to unblock others, then the process is slowed and time is wasted. Collaboration and knowledge-sharing can overcome this bottleneck by empowering team members to handle a greater scope of the process. This avoids the significant costs that come with increased labor and missed opportunities by removing the pressure on individuals and drastically increasing the efficiency of the whole system. You’ll see an accelerated project delivery, which will be faster in getting value to your end users and see quicker ROI.

    Further, collaboration across the entire release process encourages all team members to remain mindful of compliance, which ensures you’re practicing DevSecOps at each stage of your release. Rather than handing development over to the dedicated compliance team once it’s complete, shared responsibility ensures that it’s baked into the DevOps process, saving time that could be needlessly spent at the end of development reworking to meet compliance stands. In the 2022 State of Salesforce DevOps Report, teams who self-reported as ‘excellent collaborators’ managed to avoid data and metadata loss in that year’s DevOps process, whereas only 25% of very poor collaborators could say the same. Excellent collaborators were much faster to restore when needed and significantly more likely to state that backups were their responsibility.

    To sum up, collaborative development teams are better at supporting the business growth needed to draw in customers. You’ll be able to sustain this growth, as efficient and secure releases will improve customer retention.

    Continuous Improvement for Your Team and Business

    Many teams only think about digital transformation when their process begins to fail, meaning the necessary changes require a disruptive overhaul of their whole system. Teams that nurture a culture of continuous improvement will make incremental improvements to their system, which avoids drastic ad-hoc changes and ensures the business will see continual value from gradual tweaks.

    It’s difficult to identify a singular ‘best DevOps system,’ as best practices are constantly shifting, but it is easy to realize that something could work better. Teams that reflect on their own systems and keep abreast of the latest tech trends can continually implement process improvements that amount to significant adjustments in the long term. This ongoing optimization of the DevOps process means no stasis and no need for disruptive and costly upgrades every few years.

    Developing your own team members not only creates a better DevOps process but also empowers team members to fill knowledge gaps, lessening the need for costly expert hiring or consultancy. Further, hiring and onboarding is a huge cost, which can be reduced by the morale and retention boost that comes with upskilling and collaboration. This will be critical as companies look at hiring freezes in the upcoming recession.

    Proving that small behavioral shifts can help maximize DevOps ROI will strengthen your business case for DevOps culture and create an agile team that can adapt as the landscape changes. Eventually, your DevOps ROI will become synonymous with your culture.

  • How Developer Productivity Engineering (DPE) Enhances Software Delivery

    How Developer Productivity Engineering (DPE) Enhances Software Delivery

    Developer experience (DX) is in the zeitgeist, and for a good reason. Digital demands are increasing, yet the market faces cautious IT budgeting, workplace burnout, and high resignations. The idea is that quality developer experience can help keep the remaining talent happy and increase productivity. And organizations are considering many strategies for increasing DX, such as creating more usable interface interfaces, maintaining intuitive documentation and abstracting complexity with more automation and low-code.

    Another way to increase productivity is by slimming down the time it takes to test and deliver software. There are many potential hurdles in the way of deploying new code, and a cumbersome pipeline can easily take a programmer out of the flow. The practice of streamlining this toolchain is known by some as Developer Productivity Engineering (DPE). DPE focuses on improving developer productivity through accelerating DevOps processes, like CI/CD pipelines.

    I recently met with Hans Dockter, founder and CEO of Gradle, to understand the core tenants behind DPE. According to Dockter, the dialogue with the toolchain is a developer’s bread and butter, and optimizing this exchange is vital for quickly validating new ideas. Below, we’ll seek to understand what DPE is and how it might increase the pace of software delivery. We’ll also consider some methods for implementing DPE in practice.

    Roadblocks in the Development Toolchain

    Engineers are always experimenting with new feature development. “A developer needs to have a dialogue with their toolchain to see if their hypothesis makes sense,” explained Dockter. Yet, there are many potential barriers to instant feedback. For example, a toolchain may be comprised of code compilation, static code analysis, unit testing, performance testing, security testing and other checks. Running new changes through a CI/CD pipeline can take anywhere from a few seconds to minutes or hours. In his work, Dockter has even encountered teams that deal with a 24-hour feedback cycle time.

    Long wait times can be taxing as they demand users to switch contexts. Neuroscientists say that multitasking depletes glucose in the brain and leads to exhaustion. Similarly, Dockter argued that long waiting periods with the toolchain can take developers out of the flow and slow down the pace of software delivery. “You cannot have a good developer experience without good productivity.”

    Furthermore, he added that engineers often encounter untrustworthy signals from their toolchains. If testing suites produce too many false positives, for example, you can lose faith in the tooling altogether. This equates to a bad experience and may result in developers overlooking important signals that do matter.

    Understanding Developer Productivity Engineering (DPE)

    DPE is all about improving developer efficiency. And quickening the feedback cycle is one method to enhance developer productivity. According to Dockter, DPE applies a few strategies to streamline this feedback loop and shorten the timeframe:

    • Optimizing which tests are run: First, Dockter recommended only running tests relevant to the change at hand. Optimizing test selection can reduce bulky builds and significantly reduce the time it takes.
    • Caching: Caching is integral to any web application, so why not apply similar heuristics for the development pipeline? This could involve caching code that is not changed. “Changes are often incremental from one feedback cycle to the next. A lot of output is produced that can be reused,” said Dockter.
    • Predictive test selection: To automate test optimizations, Dockter recommended predictive test selection to understand which tests are sensitive to which areas of code. This would utilize an AI trained on release mechanics to help pinpoint what components the changes modify and, thus, what tests to run.
    • Test distribution: Another way to accelerate the pipeline is by distributing testing processing. Using multiple machines to test different areas simultaneously could greatly speed up the routine. Test distribution “is a modern approach to test parallelism that accelerates test execution by taking existing test suites and distributing them across remote agents to execute them faster,” wrote Marc Philipp and Hans Dockter in The Developer Productivity Engineering Handbook.
    • Monitor the toolchain: Lastly, it’s good to continuously monitor failure analytics to discover where the toolchain itself is causing trouble, said Dockter. On the side, CI/CD pipelines are not immune to security vulnerabilities and should be treated with the same security standards as other infrastructure.

    DPE principles have already been applied at DoorDash, LinkedIn, Netflix and other organizations.

    Benefits of Developer Productivity Engineering

    In the last few years, DX has moved from niche to mainstream, said Dockter. In fact, DX has even entered the C-suite, as certain companies have embraced the role of chief developer experience officer CDX). And with the emerging discipline of platform engineering, we’re seeing an even greater focus on streamlining internal DevOps workflows.

    And although platform roles may have been viewed as second-class engineers in the past, said Dockter, they are held in high esteem nowadays. “It’s as important as the other engineering work we’re doing,” he said. Developer productivity engineering seems to align with these principles, helping organizations manage the effects of an exponentially expanding code base. In the end, an investment in DPE, like platform engineering, could bring more satisfactory working conditions and accelerate the pace of software development.

    “DX is a transformative opportunity, but most companies invest incrementally. The economic benefits are transformative for companies developing infrastructure to get more output from their developers.”

  • The Power of Observability: Performance and Reliability

    The Power of Observability: Performance and Reliability

    Observability has become an essential aspect of modern IT, and its importance is only expected to increase in the years to come. The ability to monitor and understand the behavior of systems in real-time provides organizations with a wealth of information that can help them improve the performance, reliability, and overall health of their networks and applications.

    By collecting and analyzing data from a variety of sources, observability enables organizations to proactively address issues before they escalate into major problems. This proactive approach to problem-solving can help businesses avoid costly downtime and lost productivity, ultimately leading to increased customer satisfaction and business growth.

    Current Challenges Facing Today’s Organizations

    Despite its many benefits, achieving proper observability can be challenging, particularly in today’s complex and highly dispersed technology landscape. The sheer volume of data generated by siloed networks and applications can overwhelm even the most sophisticated monitoring tools. However, with the right approach, tools and processes, organizations can overcome these challenges and fully realize the potential that observability has to offer.

    One of the biggest obstacles to achieving comprehensive network observability is the fragmentation of data sources. Logs, metrics, events and other types of data all require different tools to collect and store them, making it difficult to get a complete picture of network performance. To overcome this challenge, organizations must adopt a holistic approach that integrates the right tools and processes to collect and analyze all relevant data.

    This holistic approach involves the use of advanced monitoring tools that can collect and analyze data from multiple sources, as well as the implementation of best practices for data management and analysis. By taking a comprehensive approach to observability, organizations can gain a deeper understanding of their networks and applications, identify potential issues before they become major problems, and ultimately drive business growth and success.

    Best Practices for Performance and Reliability

    First, proper tooling is crucial for organizations to perform a comprehensive analysis of data. This enables cross-domain correlation to achieve meaningful insights. A data-centric approach relying on contextual information can help organizations “connect the dots” and make informed decisions. In addition, organizations must also prioritize data quality to ensure that they are analyzing accurate and reliable data. Poor data quality can lead to incorrect conclusions and poor decision-making, which can have negative impacts on network performance and business outcomes. To ensure data quality, organizations must invest in proper tooling and processes that can validate and verify data accuracy, consistency and completeness.

    Second, having a network data source of truth is crucial for organizations to effectively analyze and make informed decisions based on their data. The ability to extract metadata from existing sources to provide contextual information is also vital to “connecting the dots” across multiple domains to uncover valuable insights. The metadata serves as the ultimate enabler in this process, allowing organizations to gain a comprehensive understanding of their data to make informed decisions. By establishing a network data source of truth and extracting the necessary metadata, organizations can effectively analyze and use their data for more meaningful insights.

    Third, it is important to ensure that observability is incorporated into the entire development lifecycle to support end-to-end visibility. This means accounting for instrumentation as part of the design and planning phases, as well as testing, deployment and ongoing maintenance. By making observability a central part of the development process, organizations can identify and resolve issues before they become major problems. Additionally, incorporating observability into the development lifecycle can also improve the overall performance of the system by identifying bottlenecks and areas for optimization. It can also help to improve the overall security of the system by detecting anomalous behavior and potential vulnerabilities. Moreover, having observability throughout the development process can enable teams to make informed decisions based on real-time data and analytics, leading to more efficient and effective development practices.

    The fourth best practice is to use a centralized observability platform that allows for the collection and analysis of data from all systems and infrastructure. This platform should be able to collect data from all parts of the organization’s technology stack, including databases, servers and applications. Additionally, the platform should be able to correlate data from multiple sources to provide a comprehensive view of the organization’s operations. This centralized approach ensures that all stakeholders have access to the same information, reducing the likelihood of miscommunications and ensuring that everyone is working towards the same goals.

    Last is the democratization of data. This is crucial for organizations as it empowers teams from multiple functions to access and use data effectively. This leads to increased transparency and collaboration, allowing organizations to make data-driven decisions and drive innovation. Democratization also helps to break down silos, increase visibility and facilitate faster problem-solving for improved decision-making. The key to achieving comprehensive network observability is collaboration between teams. Siloed teams and processes can lead to gaps in data collection and analysis, as well as delays in issue resolution. Therefore, organizations must encourage cross-functional collaboration between teams responsible for network infrastructure, application development and operations to promote a shared understanding of network performance and enable faster problem resolution.

    Observability is a Key Discipline

    In conclusion, observability is a key discipline that can help organizations achieve superior performance and reliability in their systems. By following the best practices suggested above and embracing a comprehensive approach, organizations can overcome the challenges of data fragmentation and unlock the full potential of observability. As technology continues to evolve and become more complex, observability will only become more important, making it essential for businesses to prioritize this aspect of their IT strategy.

  • Don’t Make Big Tech’s Mistakes: Build Leaner IT Teams Instead

    Don’t Make Big Tech’s Mistakes: Build Leaner IT Teams Instead

    One of the biggest narratives in the U.S. concerning the current wave of tech layoffs is the fact that ‘traditional’ sectors have a prime opportunity to snap up new tech teams and IT talent. This has always been a significant challenge for sectors such as banks, insurance and manufacturing that compete with big tech for talent. In 2022, a majority of CEOs (71%) identified skills and labor shortages to be that year’s biggest business disrupter.

    And they were right to be worried. According to Salesforce, three in four workers do not have the digital skills needed by businesses to prepare for the future of work. The temptation in this environment for many traditional organizations is to enter the labor market to build larger tech teams to help drive their modernization programs. However, this may be a mistake.

    Building large, expensive, bloated tech and IT teams is not always the answer. It’s critical that traditional companies learn this lesson from big tech.

    Instead, traditional organizations should consider other avenues to drive their digital transformation ambitions with their lean resources. What does this look like?

    What is the Real Challenge you are Trying to Solve?

    Since COVID-19 hit, U.S. companies have been forced to reevaluate how they work, with remote working becoming commonplace–even for companies who couldn’t imagine themselves working remotely.

    And the challenges have grown as U.S. businesses seek growth to recover lost gains from the last few years. Evanta’s 2022 CIO Leadership Perspectives study found that CIOs rate data and analytics as their second top priority within the IT function. It is clear that business leaders see advancing organizational use of data, analytics and automation as key to reaching enterprise objectives.

    For many organizations, the biggest challenge they face is the unprecedented amount of data generated. Critically, more than 80% of all new data is unstructured and messy. This makes it difficult for data-driven companies to accurately review, gather, analyze and rely on what is mission-critical information.

    Traditional industries such as health care, banking, insurance or the public sector, have even larger concerns because data is increasingly critical to how they build value and deliver services for customers. So, it is important for their IT teams to create a single source of truth and data governance framework across their organizations to ensure the right people and senior leaders have the most accurate information to make smarter decisions.

    For instance, in the manufacturing industry, no-code database platforms can be leveraged to structure daily operational data and visualize insights through digital dashboards for quality assurance, continuous improvement and health safety.

    Additionally, at Baserow, we work with treasury customers at some of the biggest international banks that use no-code platforms to keep track of local legislation around the world by centralizing information in real-time databases available to relevant teams, including compliance.

    Modern organizations depend on their IT teams to accomplish a lot of their goals. So, it is important to provide them with the tools to focus on more complex development projects. No-code tools free your non-technical teams to address their pressing needs themselves without having to wait for budget or resource availability in the IT department.

    Have you Also Considered Upskilling Your Current Team?

    We know from the Salesforce survey that the vast majority of U.S. workers lack the digital skills to support their organizations’ ambitions and needs. This suggests that there is a wider issue within most companies at large. Do businesses need to prioritize upskilling their current team instead?

    A U.S. Gallup report found that 72% of workers are overwhelmingly interested in pursuing additional digital training to prepare them for an increasingly digitilized workplace. Is there room for no-code technologies to supplement the digital capabilities within companies?

    Enterprises are already expanding the responsibilities of application development outside their IT teams as well as increasing the productivity of their existing IT resources by automating and abstracting repetitive developer tasks. Gartner predicted that by 2025, 70% of apps will employ low-code/no-code technology. This trend aligns neatly with the business needs, such as the development of organization-specific applications and tools, because every business’s requirements are different.

    Furthermore, no-code/low-code technology enables companies to drive innovation and shorten the idea-to-market cycle times. The technology’s pre-built components make it easier for end-users and workers to intuitively assemble the templates that solve their complex needs.

    In Conclusion

    U.S. companies that need to fill the IT skills gap should consider how technology can be leveraged to boost productivity and accelerate the speed of innovation while accepting that new technical resources will continue to be expensive and scarce.

    These organizations are better off taking the lead in the democratization of IT within their teams. Only then can they keep up with the speed and agility required in today´s competitive environment.

  • How to Supercharge Your Engineering Teams

    How to Supercharge Your Engineering Teams

    With the economy still bleak, data and engineering teams that were already struggling to keep pace with business needs are now facing a potential hiring freeze or worse in 2023. That’s why there’s never been a more important time to maximize the productivity and impact of your teams, but the question is how to identify the big changes that move the needle in performance. Incremental adjustments that save a sliver of time here and there are not hard to come by, but what teams need are the breakthroughs that yield giant leaps in productivity and efficiency. Rather than a 10% improvement, it’s the 10x improvements that drive lasting gains.

    As an engineer and CEO of a software company, I’m constantly looking for ways to boost the productivity of our teams. Our guiding principle is simple: Maximize the impact per hour invested for every individual. To do that, we must ensure that individuals maximize the time spent flexing their superpowers, minimize busy work and reduce dependencies on others that delay work or tie them up in meetings. While counterintuitive at first, we consistently find that collections of well-aligned, independently executing individuals produce a far greater impact than a large team swarming on a project. Put another way; the individual impact goes up when the number of people you depend on to deliver the result goes down.

    I’ve developed an approach over the years that has allowed me to identify several opportunities for step-change advancements in productivity and efficiency, and I’d like to share it here, along with two concrete examples. I will also share an exercise we run with our teams to help identify and execute these opportunities.

    First, here are my two main criteria for identifying the projects and tasks where we can effect changes that will have an outsized impact on the company:

    ● Big resource-consumers: Work that’s essential to the business but consumes a large amount of engineering and other resources is a top candidate for optimization.
    ● Big impact, easy win: Areas that will have a significant impact on company performance if we can do them faster and with higher frequency are also great candidates—even if they’re not consuming a ton of resources.

    Here are two examples that illustrate each of those criteria and where we were able to see massive gains in productivity, quality of service, or both.

    Tackling Big Resource-Consumers

    At Ascend.io, we provide a platform for building and automating data pipelines, which requires us to build connectors into a huge variety of data sources. At one time, building a new connector required multiple engineers to spend two to three weeks writing more than 5,000 lines of code that spanned four microservices in three different languages. As we added more customers and needed to support more data sources, this quickly became unsustainable.

    When we looked at this process, we saw two issues: Engineers were writing custom code for each connector in a way that would be better served by a common framework. Moreover, the process required engineers from multiple teams and disciplines to work together and coordinate their priorities. As soon as you get dependencies that require engineers to coordinate with others and wait on the outcomes of other people’s work, you’re wasting time.

    We addressed this by designing a new development framework that exploits commonalities across the connectors we build. This now requires far less unique code and removes the need for multiple engineers to work together. In most cases, one person can build a new connector in days with 100 lines of code. This made us far more nimble and freed up engineering time to do other valuable work.

    Achieving High Impact

    Like most companies building software, we need to convey the capabilities of our product to new and existing users to ensure they receive maximum benefit from their use of Ascend. With new features and enhancements being released on a weekly basis, there is a lot to keep up with. This is high-impact work, however, and if we can do it in a vastly better way, it drives an outsized impact for Ascend and our customers.

    For us, building these automated product tours typically required a product marketer or product manager to design the customer journey, and one or more engineers on a sustained basis to build the actions into the product. This again creates dependencies that slow progress and require significant manual coding.

    The breakthrough for us was a tool called Intercom, which allows you to build sophisticated product tours without needing to write code. Our product team can now build more interesting and complex product tours for customers, and our engineers can stay focused on building new features instead of the code needed to showcase them. What’s more, they are able to design, test and deploy these tours independent of our product and code deployment cycle, further freeing them to iterate as fast as possible.

    A Thought Experiment

    So how do you actually find these opportunities for 10x improvement? I run the following thought experiment with our teams several times a year to uncover these opportunities:

    Imagine your workload scales 10x overnight and you absolutely must meet this increased need, but without hiring more engineers or working more hours. How do you do it?

    It’s amazing what this exercise can uncover—but there are ground rules and it can take time to see results. Coming up with these big ideas is a skill like any other, and most people are not great at it the first time they try it. Your first iteration may produce no options to pursue—some may have high-impact ideas but with even higher investment requirements, while others may reject the premise outright. That’s normal. So, don’t insist they sit in a room until they dream up that 10x breakthrough, because it will be demoralizing. Instead, plant the seeds by establishing the above framework and then let the ideas start to grow.

    More likely, a few days later, they’ll be out for a hike or chatting with an old co-worker and they’ll suddenly have the germ of an idea. That may still not be the winning solution, but someone else will build on it, and then someone else and, finally, you iterate your way to a breakthrough. Pulling the team back together and embracing the “yes, and” approach can be both energizing and highly productive.

    Brainstorming like this is fast and free, and you only need one great idea to have a material impact. We run this exercise a few times a year and have come up with several big ideas that were game-changers for the company. Besides the examples above, we also moved key parts of our software development from Scala and Go to Python a few years ago, which is a much more efficient language (as measured by developer time) and allows our engineers to build things much faster.

    Software engineering is a complex beast that often spans many teams working on multiple processes in parallel. But that complexity is also your opportunity: Every complex system has room for optimization, especially at companies that moved fast in the beginning to build a product and find market fit. Now is the time to lift your gaze, look around and ask where significant gains can be made. They almost certainly exist, and a 10x improvement could be what allows you to not only survive the turbulent year ahead but emerge with a thriving team and business on the other side.

  • 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 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:

    LinkedIn

    M-Logic
    Dallas, Texas/Chicago, Illinois
    Security Engineering – DevOps
    $150,000 to $160,000

    SimplyHired

    Cisco Systems
    Waltham, Massachusetts
    DevOps Engineer
    $134,200 to $197,700

    Indeed.com

    AT&T
    McLean, Virginia
    DevOps/Python Specialist
    $111,000 to $140,000

    Monster.com

    Capgemini FS
    Charlotte, North Carolina
    AEM Full Stack Developer
    $110,000 to $130,000

    Dice.com

    Booz Allen Hamilton
    McLean, Virginia
    Lead DevOps Engineer
    $99,300 to $212,000

  • What DevOps Leadership Should Look Like

    What DevOps Leadership Should Look Like

    Implementing DevOps has become a major focus, but the practice’s attempt to provide organizational support and streamline production systems simultaneously leaves developers with no clear hierarchical structure. We know we need DevOps and we know it helps, but we also know that without proper leadership or structure, it can be misunderstood and undervalued. To build a strong collaborative culture, DevOps leadership, like most other leadership roles, requires a different type of skillset—a skillset that isn’t always prioritized in software development. The ability to understand programming languages, to be versatile and be attentive to detail will take a developer far in their career, but once they’re in a management position, what is needed to be an effective DevOps leader?

    First, what does an effective DevOps leader look like? To start, they need to lead. But to lead a DevOps team, it’s important to not only understand development—including reasonable goals and how to accomplish challenging tasks—but a DevOps leader needs to be able to create an environment that fosters collaboration between teams.

    This is why a DevOps culture is a core value for any high-performing DevOps team. This is due to the cross-functional nature of the practice. The stages of the DevOps cycle (plan, build, test, deploy and manage) rely on different teams with different skill sets.

    Build a Culture Of Ownership and Teamwork

    To effectively collaborate, a strong cross-functional culture of ownership, teamwork, intensity and smart application is needed.

    Clarity can transform a team, and it starts with ownership. Ownership is essential for cross-functional DevOps teams to understand their roles and what they are responsible for. In order for clarity to exist, leaders need to provide clear direction and guidance. It is a leader’s responsibility to set realistic goals and offer support. Group trust is built when a team has a common goal and clear roles and responsibilities are identified.

    Ownership is the foundation of teamwork, and with it, team members can see their individual contributions to a project and can celebrate their successes together. This teamwork then breeds collaboration, improved performance and a cohesive dynamic within the team’s culture.

    Lead With Strategic Intensity and Smart Application

    A DevOps leader can empower their team through ownership and teamwork, but we can’t forget the value of knowing the right level of intensity for a project. Leaders need to understand a situation, the context and how to approach it strategically to avoid burnout and bitterness. They must know when to apply intense sprints and when to pull back and move resources—a leader must know how to play smart with the resources they have.

    Use Soft Skills

    People management skills can be overlooked in a lot of leadership positions. For example, we might see it when a startup chooses a CTO or an engineering lead position based on seniority or developer skills without regard for their ability to actually manage people or their desire to be in such a position. Often, the person in charge of a DevOps team is given this role because of their previous development accomplishments, but they lack the necessary soft skills of communication, conflict management and/or teamwork. Using the four principles above can help accelerate the foundation of culture as well as help compensate for a leader’s lack of soft skills

    DevOps leaders need soft skills. Soft skills include the ability to think critically and project manage while having enough emotional intelligence to inspire, motivate and retain a team of smart engineers. Every leader needs to be able to see their team’s strengths and weaknesses, listen and influence and further develop their members to succeed. The challenge for this role is that, to be successful, it takes both technical expertise and soft skills and knowing how to balance the two.

    Unfortunately, soft skills haven’t been prioritized in the training and career development of most software engineers. Only recently have soft skills been seen as a differentiator in the engineer hiring process or seen as a value-add to an organization. For years, technical skills took precedence and we ignored the areas that would take a software engineer to the next level – the soft skills that will lead to leadership. But it’s a bigger problem; employers say most college grads aren’t learning these soft skills in school.

    Remember the Not-so-Secret Sauce

    Soft skills empower a leader to thrive both within a DevOps team and in collaboration with other departments. The ability to work across teams can exponentially improve business operations. A strong DevOps leader can offer solutions and problem solve for internal issues and customer-facing problems. They are able to bring DevOps into new areas of the company in a strategic and effective way. Collaboration requires working with others, seeing the bigger problem, understanding the business goals and using soft skills to get things done.

    It’s the not-so-secret sauce that makes all the difference when running a powerful DevOps team. A culture of collaboration starts with the leader. A leader’s relationship skills can increase the likelihood of bigger budgets, more tools and recognition. DevOps leaders can build a strong team by leveraging the soft skills within themselves and their team members, applying the right level of intensity and encouraging a culture of ownership, teamwork and collaboration. If these things are missing, whether DevOps or another team, the unit will fall apart.

    This is why a DevOps leader needs to take personal ownership and responsibility for the success of their team and see motivating others, setting a standard of operational excellence and representing the DevOps team as an integral part of their role. Luckily, there are resources to learn and exercise these skills so every leader, newly appointed or veteran, can ensure their team can excel.

  • Why Observability is Important for Development Teams

    Why Observability is Important for Development Teams

    Observability, which allows development teams to understand better how their systems behave in production, is critical to successful software delivery. According to Gartner, by 2026, 70% of organizations that successfully applied this practice will achieve shorter latency for decision-making, enabling competitive advantage for target business or IT processes.

    Observability allows development teams to identify and diagnose issues quickly to make decisions that improve overall software delivery performance. Let’s take a closer look at why this practice is critical for development teams.

    Differentiating Observability and Visibility

    To better understand observability, it’s essential to clear up a common misconception – that observability and visibility are the same. Two critical differences exist between the two. Visibility allows development teams to look at the surface-level aspects of an application or system. In contrast, observability provides deeper insight into what an application is doing in production. Being equipped with a deep knowledge of observability allows developers to be more productive within their respective organizations.

    Impact on Developer Productivity

    With observability, developers can identify and diagnose issues within applications quickly, giving them more time to fix bugs and time for resolution, which are both critical success factors for software delivery. Observability allows organizations to quickly identify and respond to potential problems, such as operational issues or security breaches, before they become issues that impact customers or users. While there is no such thing as perfect software, observability helps developers quickly find and fix issues, bottlenecks, inefficiencies, etc., so they can get back to doing what they love: Creating new software.

    With the benefits of observability, developers naturally gravitate toward tooling and technology. There are many tools available for developers to take advantage of, and development teams must learn how to use these tools to integrate them into their applications and services. Let’s explore some of the more popular options.

    The Shift to Cloud-Native Tools

    The shift to cloud-native tools is driven by the increasing popularity of cloud computing and its benefits, such as scalability, cost-effectiveness and flexibility. The move to cloud-native has made an enormous impact on observability efforts. Having good tooling and processes available positively impacts observability efforts because it’s a critical aspect of the developer communities’ systems. Overall, the shift to cloud-native tools is driven by the need for organizations to take advantage of the benefits of cloud computing and the need for more efficient and flexible deployment and scaling of applications.

    Some of the most common tools in observability include:

    These tools offer developers greater insight and knowledge into how applications behave. The cloud-native approach necessitates a new way to aggregate all of these operations.

    Conclusion

    With observability, developers can understand how their systems work in production. These systems act in different ways depending on the environments they run in. Therefore, organizations must do more to provide developers with sufficient observability because of the limited visibility into the overall system performance.

    Observability allows developers to act quickly and remedy issues before they go into production and organizations can better measure success relative to the application’s performance. Hours of developers’ time are spent manually debugging and troubleshooting when organizations could have a system in place to do this automatically and allow developers to get back to what they love doing most: Creating software. Observability helps organizations make better-informed decisions, improve operations and performance and achieve their objectives more effectively.

  • 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 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:

    LinkedIn

    CVS Health
    Remote
    Lead Director – Enterprise Digital Security
    $140,000 to $280,000

    Indeed.com

    Splunk
    Remote
    DevOps and Observability Assigned Expert
    $143,200 to $196,900

    SimplyHired

    Book of the Month
    New York, New York
    Senior DevOps Engineer
    $140,000 to $180,000

    Monster.com

    Innova Solutions
    Plano, Texas
    DevOps Engineer
    $110,000 to $130,000

    Dice.com

    Solaris Finserv
    Kennesaw, Georgia
    DevOps Engineer
    $100,000 to $120,000

  • SVB: When Silly Valley Sneezes, DevOps Catches a Cold

    SVB: When Silly Valley Sneezes, DevOps Catches a Cold

    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: Silicon Valley Bank and what it means for DevOps. After the débâcle of Wednesday’s fire sale, Thursday’s bank run and Friday’s FDIC seizure, came Saturday’s impotent panic, Sunday’s “not a bailout” federal guarantee and Monday’s tentative restart of “bridge” bank operation. (more…)