Four DevOps Trends for 2021
There's plenty to talk about when it comes to the year ahead, from disruptive technologies to the continued evolution of DevOps tools and practices.
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After a year that I'm sure we would all like to put firmly behind us, it's important to remember that technology and talent will continue to be the key driving forces for change across industries. With this in mind, here are a my four DevOps trends to look out for over the year ahead.
1. Scaling Containers and Orchestration With GitOps
In previous years, I’ve discussed the rapid adoption of Containers and Orchestration platforms. In 2021, Kubernetes is prevalent. As development teams deploy their products across the globe, we face the problem of scale; operators are burdened with managing multiple instances across multiple clouds.
Typically, operations teams have used a “Push” process in which a delivery pipeline sends updates to a Kubernetes cluster. This model comes with its challenges. For example, two common questions software teams ask are: “What version is deployed in a given environment?” and “Can we quickly rollback to the previous version?” With the push model these questions are difficult to answer.
GitOps is an alternative deployment paradigm, where the cluster itself is “pulling” updates from manifests that reside in source control (making “Git” an integral part of the name). I won’t go into further details, as there are several articles that explain how GitOps works, but rather focus on its value and why I think it will be a key trend in 2021. What is worth restating, however, is things are much easier with GitOps. The contents of the git repository tell you what should be deployed in the cluster and git commit history can essentially function as the cluster deployment history and audit trail.
To start, all components of the deployed application are stored under source control. This means not only the source code itself, but also the Kubernetes manifests that describe how the application is run inside the cluster. This capability means we can store, version, and manage the desired state of our Kubernetes resources.
Following this, we can equate state between the cluster and git, allowing for Repeatable and Auditable Deployments. It is not an uncommon practice where developers or operators are manually performing changes to the cluster. These ad hoc changes are never recorded anywhere and are fragile. With GitOps this is resolved, as manual changes that are not recorded in git can be easily discarded.
Finally, several times teams might make changes to the cluster which are not recorded anywhere. Configuration drift is a notorious problem, and the longer it persists, the more critical it becomes. A typical scenario for failed deployments is the discrepancy between a staging and a production environment. Developers test their application in the staging environment and assume that it will also work in production. With a source of truth, GitOps allows operators to mitigate Configuration Drift.
2. A Focus on Value and Value Stream Management
DevOps teams are still struggling with visualizing and cycle times from ideation to value realization. Millions of dollars have been spent on digital transformation, which typically yields local optimizations but not systemic business outcomes. Value Stream Management drives a focus on applying systems thinking to first identify where and what types of investments will result in delivering desired business outcomes and then scaling these concepts across the organization.
This year, DevOps will expand from product delivery to value delivery, enabling a broader digital transformation by taking an outside-in view from the business outcomes back into the people, processes, and technologies required to power them.
It is vital for DevOps transformations to align with the right goals and business KPIs, such as customer satisfaction, followed by continuous adaptations in processes and technologies to improve them. Increasingly, organizations will be designing DevOps transformation around value streams, with value stream mapping long-established as a practice for laying the groundwork for improvements based on DevOps principles.
By inspecting their value stream management platform’s data and insights, teams will be able to adapt, choose whether to pivot or persevere based on value stream performance, and receive real-time feedback.
From a vendor perspective it is likely clear leaders will emerge in the next 12 months so watch out for the analysts’ top picks.
3. Analytics, AI, and Machine Learning Will Continue to Disrupt Dev, Sec, and Ops
DevSecOps is getting smarter, particularly in risk-based vulnerability management where software security seeks to automate and orchestrate assessment of vulnerabilities into the delivery pipeline.
In 2021, solutions now readily automate policy guardrails and enable risk-based vulnerability management for overburdened, under-resourced security teams that are challenged to get in front of cloud adoption.
However, where we will see evolution is in the use of intelligence to identify material change, understand developer behavior and replace manual attempts to fix vulnerabilities. Teams won't have to spend limited financial and personnel resources building secure infrastructures. Rather, the trend will use artificial intelligence and machine learning to build secure applications and infrastructure.
Expect this trend to permeate across the delivery pipeline as it becomes easier to enable analytical systems that will ingest data across the value stream, including human and machine data, using a variety of techniques such as machine learning, deep learning and NLP.
Intelligent assistance around Deployment, Compliance and Application Operations will drive a reduction in human labor and error.
4. DevOps Platforms
In the new reality, COVID-19 has accelerated the rate of digital disruption. Each company is facing increased pressures of improving delivery velocity and time-to-market in order to remain competitive while on a limited budget.
To solve for this, more firms will turn to a platform approach for their DevOps transformation in order to scale and help accelerate digital transformation.
In a nutshell, platforms aim to eliminate barriers to scale, reduce extraneous cognitive load, and provide paved roads so developers can focus on delivering business value.
The appeal is clear, but in order to succeed with a platform approach a sustained commitment with a product mindset is foundational, and key decisions will arise on whether to build or buy. To learn more, check out this article from my colleague, Leigh Brackley, which sets out the case for scaling DevOps and delivery with a platform.
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