DevOps Trends for 2020 and Beyond

Significant strides have been made since the introduction DevOps, and technologists continue to to create benefits from ongoing developments. However, despite the advancements made and the benefits derived so far, there’s still a lot to be done to eliminate the core challenges that are prevalent within enterprises.

These challenges still hinder effective work because of tool sprawl, the poor visibility between development teams and operations teams, and manual processes that weaken agility. However, because of progressive advancements, organizations looking to leverage DevOps shouldn’t lose hope.

Over the past decade, we have witnessed exciting DevOps trends that put the field on a path to revolutionize how information technology experts and organizations will go about business in the future. To achieve maximum agility in the next decade, organizations need to get in on the DevOps secret: to consistently get the right work to the right team at the right time.

The following are among the DevOps trends that will allow development and operations teams to get closer to hacking the formula.

Policy Driven Data and Automation

Although much of the investments have been made to double down on DevOps initiatives, the fact of the matter is that downstream processes, which include change management, are still manual and time-consuming. It’s no surprise that developers still must log in, generate change requests, and manually fill out forms find the process rather frustrating. It can be a strained and unnecessary process.

The hope is that manual processes in DevOps will not continue beyond 2020 as they create friction and disrupt the flow between development and operations teams.

Nevertheless, the tide has started to turn as organizations realize true CI/CD by implementing automation in tasks like change management with dynamic controls, policy, and data automation. As automation picks up, developers will realize they are spending less time developing along with deploying apps faster and with improved efficiency.

Tool Sprawl Remains a Challenge but DevOps Management Platforms Will Surface

As cloud and microservices architectures continue their adoption surge, the emergence of new tools is inevitable as different teams and departments require different tools for version control, planning, testing, build automation, deployment, etc.

As the industry moves closer to platforms that streamline management across teams and tools to improve the speed of development and agility, new DevOps trends are emerging. Such platforms also allow IT teams to rapidly accommodate the fast addition of features to software, while at the same time automating the approval process, thus making product development much more efficient and faster, and breaking down known silos.

Heavy Reliance on AI/ML and Analytics by Organizations to Drive Efficiency and Greater Visibility

Although the last decade has seen tremendous improvements in DevOps trends, limited visibility across all pipelines from development connection to understanding what changed, how it’s testing has been done, knowing its impacts as well assessment of the risk, etc., have remained real hurdles to be resolved. Lack of visibility results in challenges that may include slower approvals, distrust among teams, inefficient processes, and bottlenecks.

But, there’s hope as organizations are beginning to recognize this challenge and are starting to address it. This has been prompted by the realization of the gains from local optimization within departments as time goes by. And as organizations continue in this path, they will increasingly rely on analytics to improve end-to-end visibility and drive efficiency across processes.

Furthermore, they will still rely on analytics to draw data relating to planning, test, repository, performance, and deployment across the DevOps lifecycle and use these insights to understand how they can reduce cycle times, project outcomes, and risks. At the same time, AI and ML will influence the most part in leveraging the insights to better direct work and to fine-tune stage gates and policies, reading from prior performance, and more.

Analytics, at its core, allows IT teams to implement changes at the pace of DevOps trends, while unmatched visibility abetted by ML places IT at the center of the developer’s mindset and culture.

The Bottom Line

The advancements of DevOps in the last decade notwithstanding, much more is expected to take place to realize the true value of DevOps and increase its adoption. The massive number of tools used by IT teams and developers makes it hard for leaders to achieve a holistic view of individual teams. The manual processes paired with the lack of visibility hinders the cultural and behavioral change necessary for success with DevOps trends.

However, as we get into the next decade of DevOps, teams are poised for success if they arm themselves with analytics, automation, and workflow platforms. If you are looking for a trusted DevOps partner to walk the implementation with you, talk to Plumlogix.com (888) 318-8883.