Category: DevOps Culture

  • Internal Developer Platform (IDP) Reference Architectures

    Internal Developer Platform (IDP) Reference Architectures

    If you’ve been following the DevOps space recently, you’ve probably noticed the excitement brewing around platform engineering. Despite uncertainty in other areas of tech, it seems like platform engineering is poised for growth—Gartner even expects that by 2026, 80% of software engineering organizations will have established platform teams.

    The platform engineering idea hinges on an internal tooling system known as an internal developer platform (IDP), which platform teams own and operate and is exposed to developers to improve their efficiency, satisfaction and release fluidity. IDPs have been the talk of the town. But what does an IDP actually look like? What sort of components are they usually composed of?

    Well, at PlatformCon 2023, McKinsey representatives shared a reference architecture for building out IDPs. This framework was modeled after hundreds of internal platforms and could be a helpful benchmark for other organizations as they begin developing and standardizing their internal developer platforms.

    Below, we’ll examine the sample IDP reference architecture and its components. We’ll also have a refresher on the platform engineering concept and offer some expert tips on overcoming potential obstacles while implementing platform engineering and IDPs.

    Why Engineer Internal Platforms, Why Now?

    First, for those new to the idea, let’s explain what platform engineering is. I’ve previously defined platform engineering as “maintaining an internal self-service platform that serves the needs of developer consumers.” The practice doesn’t necessarily supplant DevOps, rather, the experts I’ve spoken to view it as the next evolution.

    This trend is essentially a response to developers overseeing more and more aspects of software life cycle management. Complexity in enterprise-level software delivery workflows has escalated in the last decade, leading to what The State of Platform Engineering Report describes as “increased cognitive load on engineers.” This is negative, as it could lead to shadow operations and burnout.

    The fact is, most developers require the same sort of technologies, which could be standardized across the board. For instance, take the consolidation around containers and Kubernetes, infrastructure-as-code and the need to implement similar build configurations and security policies across applications.

    By outsourcing the maintenance of tools for shipping and running cloud-native applications to a common platform, you take the burden off developers and free them up to code. Also, by centralizing DevOps tooling, you can enforce more governance and build out internal standards. Which should help reusability and overall deployment agility … at least, that’s the promise of it all. 😉

    Sample IDP Reference Architectures

    So, let’s turn to some real-world examples to see how this is being implemented. Mike Gatto, senior DevOps engineer, McKinsey, shared an internal platform reference architecture for AWS-specific environments:

    McKinsey’s Internal Developer Platform reference architecture

    As you can see, the architecture is divided into these subgroups. At a high level, they perform the following functions:

    • Developer control plane: This is the version control, where developers publish their code. They provide a workload specification (in McKinsey’s case, a Score file) that codifies specific configurations.
    • Integration and delivery: This includes the CI pipeline to build application code into a container and publish it to a registry. This notifies the platform orchestrator to initiate a build. Then, resources are provisioned. This area also includes a CD pipeline and infrastructure control plane.
    • Monitoring and logging: This plane includes tools for observability, analytics, and application performance monitoring.
    • Security plane: This area includes tools for secrets management, policies, and security vetting.
    • Resource plane: This plane encompasses cluster management, database tools, networking, and messaging architectures.

    “By separating developer and platform team concerns and allowing them to control the respective areas they’re experienced in separately, without requiring too much overlap,” said Gatto, “we’re making deployments more compliant and better aligned with client initiatives.”

    Humanitec has also created internal developer platform reference architectures for GCP and Azure, displayed below.

    IDP Reference Architecture for GCP
    IDP Reference Architecture for Azure

    PlatformEngineering.org has also expanded McKinsey’s original IDP reference architecture with a tooling landscape that adopts the same umbrella subgroupings but includes other pluggable tools.

    The Internal Developer Platform tooling landscape

    Roadblocks to Developer Platforms

    Starting from a blueprint could be a big help to rapidly construct IDPs. Yet, there will still be some potential roadblocks associated with adopting an internal developer experience platform. One of them is creating common platforms that actually cater well to all environments.

    “You can not and should not try to please everybody,” said Kaspar von Grünberg, CEO and co-founder of Humanitech. “Platform engineering is an 80/20 game.”

    “Platform organizations often face a lot of pressure when it comes to meeting demands for building more services that are both agile and agnostic to cloud and data center environments,” said Venkat Ramakrishnan, VP, product management and engineering, Portworx by Pure Storage. “At the same time, almost all platform engineering teams are understaffed while facing the need to support large application development initiatives and developer teams twice their size.”

    Tips to Get Platform Engineering On Track

    Reference architectures for various clouds could help cater IDPs to different scenarios. But outside of that, it will take a product mindset approach to strategically accept feedback and iterate the platform. This will involve doubling down on developer experience and adopting cloud-native foundations that can scale.

    “Platform engineering teams must consider adopting Kubernetes as it enables them to manage and deploy applications in production at scale, without having to manage applications at the individual level,” added Ramakrishnan. “Additionally, it may not be realistic to expand platform engineering teams alongside growing platforms, so teams should also consider leveraging automation and self-service capabilities to help them better manage projects at scale.”

    Is ‘You Build It, You Run It’ Dead?

    The idea of ‘you build it, you run it’ is starting to look a little antiquated next to the new and shiny platform model. It’s tough to say, but I’ll be keeping an eye on this area to see if all the effort to standardize the internal engineering approach pays off!

  • Does Platform Engineering Make DevOps & DevSecOps Irrelevant?

    Does Platform Engineering Make DevOps & DevSecOps Irrelevant?

    For those of us old enough to remember, the DevOps movement came onto the scene somewhere around 2007/2008. Its proponents railed against the traditional software model at the time, which called for the developers who wrote the code to be organizationally and functionally separate from those who deployed and supported the code. The reasoning behind the movement is that these siloed teams, concerned only with their own objectives, resulted in botched releases, significant delays, poor communication and, ultimately, unhappy customers. It took a few years to gain traction, but when Gartner got on board with the concept in 2011, adoption soared, and Agile development practices like automated build and test and continuous integration and delivery became the new norm.

    Security and Compliance Join the Mix

    Agile, DevOps and its promise of continuous integration and continuous delivery … well, delivered. Development and operations teams were finally on the same page, each able to see a current phase’s end goal, providing the flexibility to make changes and improvements along the way, speeding the delivery of quality software. Unfortunately, in these early years of DevOps success, security and compliance generally remained siloed. That silo resulted in security being an afterthought—stuck near the end of the application development life cycle. Consequently, security took the blame for release-delaying bottlenecks.

    The year 2014 was notable for an exponential increase in security breaches compared to the year before. According to an article in Security Week, 2014 marked the year that, for the first time, one billion records were compromised in more than 1,500 notable data breaches, an increase of 80% from 2013. Home Depot, JP Morgan Chase and eBay were among the many exposed to attackers. Given these and other high-profile breaches, it was time to re-evaluate development processes and give security and compliance a seat at the table.

    With research by Microsoft and others showing that 80% of security breaches were related to configuration errors, the concept of DevSecOps, putting security front and center in the Agile development process, ensures that assets are configured correctly in the first place, providing continuous compliance by running constant scans to identify configuration drift.

    This approach can be extended beyond the data center to any cloud to any edge, where even applications can be managed and checked against compliance and security standards. You can even extend a single DevSecOps compliance framework to cloud native assets including Kubernetes and public cloud services. 

    Today, it is safe to say that the term “DevOps” is likely losing its relevance, but “DevSecOps” is alive and well, as long as the organization embraces the cultural, people and process changes necessary for success. Tools and technology are essential to DevSecOps, as is adopting a culture that security is everyone’s responsibility. That culture requires instigating a security-first mindset among teams as well as implementing essential automated security testing tools.

    What About Platform Engineering?

    Platform engineering has recently captured interest and is now generating considerable buzz due to its focus on building and operating self-service internal developer platforms (IDPs) for software delivery and life cycle management. The platform is supported by layered services or tools, created and maintained by a dedicated product team, designed to support the needs of software developers by essentially stitching together components to create a frictionless developer experience.

    As Gartner says, “Platform engineering is an emerging technology approach that can accelerate the delivery of applications and the pace at which they produce business value.” In fact, Gartner expects “[t]hat by 2026, 80% of software engineering organizations will establish platform teams as internal providers of reusable services, components and tools for application delivery. Platform engineering will ultimately solve the central problem of cooperation between software developers and operators.”

    In that context, platform engineering certainly builds upon the Agile concepts of DevOps and DevSecOps. Looking deeper at DevOps/DevSecOps and platform engineering shows that they both share many characteristics, while they can also be combined in a way that provides greater benefits to organizations that think about them in tandem. It is easy to see the integral link between platform engineering and DevSecOps and the broader infrastructure management landscape. For example,

    • Developer Experience and Productivity – DevSecOps extends experience and productivity support beyond the developer to IT Ops, security and compliance.
    • Automation – Automating infrastructure configuration as well as compliance tasks using a policy-as-code approach is the lynchpin of DevSecOps. Platform engineering provides the opportunity to extend automation to the other parts of the development lifecycle.
    • Self-service – This is another common concept where platform engineering can build off of the automation and services-oriented approach that DevSecOps uses to not only enable developer self-service for code/test/deploy, but also to enable developers to be more proactive and effective in the security/compliance realm.
    • Accelerate Value – Accelerating value is the focus of any tech enabler, from platforms to tools and processes.

    From an Agile development approach supported by DevOps/DevSecOps and extending now to platform engineering, the end game is all about speeding delivery of high-impact applications with continuous updates that are highly resilient, reliable and secure. Given the synergies and the pressure on organizations to rapidly deliver applications while combatting cyberthreats, any platform engineering effort should ensure that DevOps/DevSecOps plays a central role.

    While the term DevOps and, to some extent, DevSecOps, sound a bit dated and irrelevant and could maybe use a new moniker, the evolving role they are certain to play as platform engineering gains a foothold are not to be underestimated. 

  • 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:

    Indeed.com

    MasterCard
    O’Fallon, Missouri
    Principal DevOps Engineer
    $160,000 to $202,000

    Dice.com

    ITC Federal
    Remote
    Technical Lead – DevOps
    $130,000 to $150,000

    SimplyHired.com

    JP Morgan Chase
    Jersey City, New Jersey
    AWS DevOps Software Engineer
    $128,500 to $180,000

    LinkedIn

    Accenture Federal Services
    Springfield, Virginia
    DevOps Services Specialist
    $122,600 to $198,800

    CareerBuilder.com

    NextZen Tek Solutions
    Alpharetta, Georgia
    Azure DevOps Lead
    $120,000 to $170,000

  • New Relic Extends AI to Identify Alert Coverage Gaps

    New Relic Extends AI to Identify Alert Coverage Gaps

    New Relic this week added additional artificial intelligence (AI) capabilities to its observability platform that make it possible to detect and resolve alert coverage gaps.

    Camden Swita, a senior product manager for New Relic, said it’s not uncommon for DevOps teams to discover an issue that the existing alerts they put in place were not designed to address. New Relic is adding machine learning algorithms at no additional cost that are designed to identify anomalies indicative of those potential issues. The platform then surfaces recommended alerts that DevOps teams can apply or further customize as they see fit, he added.

    Those machine learning algorithms ensure DevOps teams are tracking the right thresholds to ensure there are no blind spots that could adversely affect application performance, noted Swita.

    New Relic is employing both predictive and generative AI to enable DevOps team to detect and resolve issues faster. The company has been using machine learning algorithms for predictive AI for several years and, more recently, started providing early access to a generative AI tool dubbed Grok.

    The overall goal is to make the capabilities of an observability platform more accessible, Swita said. This is accomplished by surfacing issues without requiring a software engineer to craft intricate queries to interrogate metrics, logs and traces, he noted.

    The AI capabilities also serve to reduce the amount of alert noise; it’s now possible to more easily understand the root cause of an issue and reduce the total number of alerts that might otherwise be sent, he added.

    While there’s no doubt AI will help democratize DevOps by making it possible to write scripts and better manage workflows, it might be a while before DevOps teams trust the recommendations made. AI models typically require some time before they understand how an IT environment functions, and not every initial recommendation may be valid. In time, however, DevOps teams will find themselves increasingly supervising processes that AI models are executing.

    In addition, there are competing approaches to building large language models (LLMs) that drive generative AI. For example, it’s not clear whether chaining LLMs together will be more efficient than creating a single large ‘parent’ LLM that has ‘child’ relationships with smaller LLMs, noted Swita.

    In the meantime, DevOps teams would be well-advised to list tasks that are likely to be automated by AI models. Many of them will tend to be manual tasks that most software engineers don’t especially relish, so in that regard, there’s naturally a lot of interest in AI. It remains to be seen, however, whether various forms of AI might one day automate an entire DevOps workflow. In fact, most DevOps engineers are going to set a high bar for AI models that, at the very least, will be expected to perform a task as well as humans before it’s trusted completely.

  • IBM LLM AI: COBOL to Java ASAP ¦ ARM IPO is GO!

    IBM LLM AI: COBOL to Java ASAP ¦ ARM IPO is GO!

    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: Translating legacy COBOL code to a slightly more modern language, and Arm will go public (again) next month. (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 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:

    Dice.com

    FICO
    New York, New York
    Senior Director of DevOps Enablement
    $140,000 to $220,000

    Indeed.com

    Cisco Systems
    Research Triangle Park, North Carolina
    DevOps Engineer
    $139,000 to $176,000

    SimplyHired.com

    Candid Health
    San Francisco, California
    DevOps/Infrastructure Engineer
    $121,000 to $154,000

    CareerBuilder.com

    CACI
    Springfield, Virginia
    DevOps/Cloud Engineer
    $110,000 to $180,000

    LinkedIn

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

  • 80% of Bosses ‘Regret’ Stopping WFH ¦ PSA: Disable STS!

    80% of Bosses ‘Regret’ Stopping WFH ¦ PSA: Disable STS!

    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: Rethinking return-to-office mandates and a ridiculous, ancient Windows bug. (more…)

  • Using Observability to Create a Smart Data-Driven Culture

    Using Observability to Create a Smart Data-Driven Culture

    The first words that come to mind when talking about smart technologies are often artificial intelligence, machine learning and automation. While these smart technologies play a crucial role in smart-driven cultures, they are not the sole factor in making workplaces “smart.” Organizations that have a smart-driven culture, or data-driven culture, also promote innovation. An innovative organization actively encourages creativity, exploration and the pursuit of new ideas, continuously developing and implementing groundbreaking solutions, products and processes. Innovative companies with a culture of learning and growth are often seen as desirable employers and have high employee retention rates, attracting top talent.

    Let’s go over the benefits of a smart-driven culture and how an observability platform can help your company become data-driven in five steps.

    Why is Smart-Driven Culture Important

    You can increase efficiency and productivity among your employees by fostering a smart-driven culture. Smart technologies are able to automate repetitive tasks and streamline processes, which helps free up workers’ time and focus on other issues instead.

    A data-driven culture can also drastically improve decision-making on a company level. Your organization will begin to strategize and act on objective insights rather than guesswork or assumptions. Through collecting, analyzing and interpreting data, you will not only be able to make informed decisions but also know how to optimize processes and mitigate risks.

    Use data to better understand your customers’ preferences and improve your products to meet their demands more effectively. For example, leverage smart technologies and create high-tech touchpoints to tailor each of your customer’s experiences. A culture that encourages continuous learning, experimentation and adaptation is ready to navigate market shifts, changing customer needs and emerging technologies.

    How to Create a Data-Driven Culture in Five Steps

    According to the 2023 Data Analytics Survey conducted by New Vantage Partners, 79.8% of data leaders identified people, business processes and organizational alignment as the principal challenge to becoming data-driven. These folks cited cultural issues, including organizational receptivity to change, communication and organizational alignment, as the greatest obstacles to realizing business value.

    One way to overcome these challenges is by harnessing the power of observability, building data literacy and organizational transformation. Observability refers to the practice of gaining real-time insights into systems, applications, and processes through the collection and analysis of relevant data. Real-time insights will enable your organization to make data-driven decisions, understand your customers better and quickly identify areas of optimization to improve your products.

    These characteristics are fundamental to smart-driven companies, enabling them to stay competitive and drive innovation in the market. Take the following five steps to ensure you’re maximizing the potential of observability and paving the way toward becoming a smart-driven organization:

    1. Define Clear Goals

    Start by defining what a smart-driven culture means for your company. Write down clear outcomes that you want to achieve with a new culture, and identify the specific areas where observability can make a significant impact on your team.

    Focus on areas where real-time insights derived from observability can generate substantial business value. Set SMART (specific, measurable, achievable, relevant and time-bound) goals that can be tracked over time. For example, you could aim to reduce website loading time by 20% in the next two months in order to increase customer conversion.

    2. Implement Robust Observability Tools

    Evaluate and choose observability tools that align with your organization’s specific needs and goals. Look for tools that offer features such as real-time monitoring, log management, distributed tracing, advanced analytics and visualization capabilities.

    Consider factors like scalability, ease of use, integration with existing systems, and the ability to handle diverse data sources. Remember that the availability of accurate and timely insights promotes a culture that values data and encourages performance for achieving business objectives.

    Ask your IT department to help set up your observability tools to gather the relevant data. For our previous example goal of improving website loading times, this will mean gathering real-time data on website performance, such as server response times, page load speeds, and user interactions.

    3. Promote Data Literacy

    Your observability tools are of little help if no one understands how to use and derive helpful insights from the data you gather. Educate all of your employees on good data practices and the role of analytics in decision-making.

    Provide training and support on the data tools you have chosen and encourage your employees to understand, interpret and utilize data effectively in their day-to-day work. For instance, in meetings, you can ask for data points to back up business decisions.

    4. Encourage Collaboration and Knowledge Sharing

    Creating cross-functional teams and encouraging collaboration among different departments, such as IT, operations and analytics, is crucial for the successful implementation of observability practices.

    Taking an interdisciplinary approach allows for a better understanding of the systems and data within the organization. This can lead to the identification of optimization opportunities, help break data silos and practice collective problem-solving as a result.

    5. Iterate and Improve

    Embrace a culture of experimentation and continuous improvement by using observability data to identify areas for optimization and innovation. Encourage teams to test hypotheses, implement changes and measure the impact, fostering a cycle of learning and refinement. Track progress against the goals you set at the beginning and adjust your trajectory if needed.

    Coming back to our goal to improve website loading time. Now that your interdisciplinary team implemented some changes and reduced the loading times, you can assess the impact on user experience and business metrics, such as bounce rates, conversion rates and customer satisfaction.

    Becoming a smart-driven organization will grant you a great competitive advantage. You will make better and faster decisions, employ the best talent, maximize their productivity, and provide an enhanced experience for your customers.

  • The Skills Successful DevOps Pros Need in 2023

    The Skills Successful DevOps Pros Need in 2023

    In the last decade, DevOps adoption has grown considerably. An increasing number of companies across a wide range of industries are embracing the benefits of DevOps, and we have not seen the end of the growth cycle yet. Indeed, the total DevOps market is expected to continue to grow significantly in the next few years, with one recent market survey projecting an annual revenue growth of no less than 24.7% from 2023 to 2030 (which will bring the market value to about 51 billion dollars).

    Further, DevOps is continuously integrating with and accommodating new technologies, which are themselves evolving quickly. This means DevOps professionals will have to invest more and more time each year to stay current and effective at their job. But, this predicament comes with a silver lining. By staying current and even ahead of the game, DevOps professionals are better able to differentiate themselves and deepen their level of expertise—and with that comes the ability to increase their income potential over time.

    In this article, we take a look at what knowledge, skills and abilities (KSAs) DevOps professionals should bring to the table if they want to keep up with the fast pace of change in the industry in 2023—and beyond.

    Knowledge – What Pros Need to Know

    As always, DevOps professionals are expected to have a baseline level of knowledge before taking on a new role, internally or externally. But, as DevOps adoption grows, professionals will need to make a concerted effort just to stay abreast of current trends.

    Platform Nuances

    Each platform places limitations on DevOps processes, and their successful implementation within a company will vary depending on the platform. It’s not uncommon to have to tailor your approach in particular circumstances. In the case of Salesforce, for example, successful DevOps processes must begin with improved deployment speed and accuracy. Only once this is achieved can Salesforce DevOps professionals move onto more mature processes such as automated testing and releases.

    Industry Standards

    DevOps professionals should understand the constraints of the technology they are working with. and within their industry. Both factors may place limitations on or add additional requirements to what they do. Any given technology platform comes with its own unique constraints, such as file sizes or limits on API usage. This is especially true of cloud-hosted systems like Salesforce, where there are multitenant architectures and resources are allocated to customers. Similarly, different industries are faced with differing constraints, such as the HIPAA requirements for companies handling health care data in the U.S. As a result, DevOps professionals will need to understand these tied to specific standards or processes of their given industries.

    Transferable knowledge

    As a final word on knowledge, it’s critical to make sure you are aware of DevOps trends and best practices on platforms other than your own. There are times, more often than we realize, that your knowledge of what has been successfully utilized on other platforms can be transferred to your own. Even if these practices are not directly transferable, they can point you in directions that can ultimately prove beneficial to your DevOps work on a completely different platform.

    Skills—What Professionals Need to Master

    While there are a huge number of skills that DevOps professionals need in order to stay current and further their career growth, I’d suggest paying particular attention to…

    Version control

    This skill is fundamental—you just can’t do the job without it. Make sure you thoroughly understand its nuances: Branching strategies, rebasing or merging, rollbacks, cherry-picking, etc. It’s also valuable to understand different approaches’ limitations and use cases.

    Automation

    Become well-versed in the differences between continuous integration and continuous deployment/delivery (CI/CD) and how they form the CI/CD pipeline. Knowing where and when to apply it and how to apply it are also critical skills to master.

    Successful teams also benefit from building automated workflows. A recent survey Gearset ran with Salesforce DevOps professionals showed that 85% of teams were either currently using or planning to use source control over the next year. Automated workflows are critical to optimizing ROI in DevOps, as they reduce manual processes and unlock some of the most valuable benefits of DevOps for teams of all sizes.

    Testing

    Test automation is increasingly central to achieving DevOps success. As such, you would be wise to develop expertise in environmental testing, unit testing (integrated with automation and release gating) and UI test automation.

    Monitoring

    Application monitoring for performance, errors, data anomalies and security is arguably as crucial as testing. DevOps professionals must apply the same level of diligence to routine system operations as they do to deployments. As DevSecOps becomes more prominent in 2023, it’s expected that there will be increased collaboration and integration with infosec teams.

    Backup

    It’s critical to master the backup and restore process, no matter which platform you work on. It should absolutely be included as part of a comprehensive DevOps skill set. This is because skill underpins the mean-time-to-recovery metric. DevOps professionals must be familiar with the processes and tools necessary for restoring systems and data to achieve a rapid and secure return to business as usual.

    Demonstrating ROI of DevOps

    Finally, it’s essential for team leads, or those hoping to advance their DevOps career, to effectively convey the performance of DevOps, which can be measured using indicators such as Google’s DORA metrics. This means translating DevOps metrics into quantifiable business value that can be easily understood. It is crucial for managers to not only motivate their teams but also to validate the return on investment (ROI) in DevOps to critical stakeholders. By connecting the performance improvements resulting from DevOps practices with tangible business outcomes and demonstrating the ROI, managers can secure continued support for the DevOps approach within their organization.

    Abilities—What Professionals Need

    This final aspect of KSA plays an important role in fostering the collaborative culture that is the hallmark of DevOps success.

    Communication

    DevOps is not just about the tools—you need to maximize communication effectiveness so that the team aligns their goals with the least amount of friction. If everyone is using the same model to reach the same goal, you will achieve success that much faster.

    Continuous improvement

    DevOps success is not a fixed goal. Rather, there are always elements of the process, or your team’s skills, that can be tweaked, changed or improved.

    Making training a priority

    As per the aforementioned Gearset survey, 45% of teams who train once a month rate their team’s collaboration as ‘excellent’ compared with only 13% of untrained teams. Teams that prioritize training outperform all others on a wide range of metrics, including but not limited to seeing fewer bugs and data loss incidents.

    This Challenge is an Opportunity

    There’s a huge range of KSAs that DevOps professionals will need to master if they want to thrive in 2023. Clearly, working in DevOps has never been more demanding than it is today. But, from this challenge, there’s also a tremendous opportunity for professionals to make themselves indispensable.

  • Five Great DevOps Job Opportunities

    Five Great DevOps Job Opportunities

    devopsy.kinsta.cloud 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

    Well
    Raleigh-Durham-Chapel Hill, North Carolina
    Principal DevOps Engineer – Team Lead
    $180,000 to $200,000

    CareerBuilder.com

    Apple
    Cupertino, California
    Cloud DevOps Engineer – Enterprise Systems
    $138,900

    Indeed.com

    General Dynamics Information Technology
    Indianapolis, Indiana
    Capado Salesforce DevOps Engineer
    $116,000 to $174,000

    SimplyHired

    John Hancock
    Boston, Massachusetts
    Senior DevOps Engineer
    $109,000 to $138,000

    Dice.com

    IT Trailblazers
    Houston, Texas
    DevOps Lead
    $100,000 to $120,000