What is DevOps automation?

Staying ahead of customer needs requires speed and agility from all phases of the software development life cycle (SDLC). DevOps automation can help to drive reliability across the SDLC and accelerate time-to-market for software applications and new releases.

Because organizations face increasing pressure in today’s competitive digital landscape, employing DevOps automation tools is essential to provide a frictionless digital experience that customers can access on any device, from anywhere, and at any time.

DevOps automation is a set of tools and technologies that perform routine, repeatable tasks that engineers would otherwise do manually. Automating tasks throughout the SDLC helps software development and operations teams collaborate while continuously improving how they design, build, test, deploy, release, and monitor software applications. The two primary goals of automating DevOps are to increase cross-team collaboration and automate repetitive manual tasks.

DevOps automation tools speed up delivery cycles by reducing human error and bottlenecks, resulting in fewer and shorter feedback loops. This increased efficiency applies to the most recent code committed to a repository to the final release and delivery of an application or service upgrade.

This incremental software development and continuous deployment approach evolves and is optimized further with Kubernetes, containers, and microservices infrastructure.

Automation is critical for organizations looking to scale. According to the 2021 DevOps report, a majority of DevOps leaders (98%) report that extending DevOps to more applications is key to digital transformation. They also agree that modernizing their tool stacks is a priority to increase developer productivity.

As your team begins its journey toward DevOps automation, consider tracking key DevOps metrics such as the following to help assess your organization’s progress and to encourage buy-in from reluctant stakeholders:

• Deployment frequency measures how often a team successfully releases to production. It helps to assess the long- and short-term efficiency and speed of DevOps.
• Deployment speed is the time you need to roll out a continuous integration and continuous delivery (CI/CD) deployment into production after approval.
• Change failure rate is the percentage of DevOps code changes that lead to failure in production.
• Mean time to recovery (MTTR) is the time it takes an organization to recover from a partial service interruption or total failure in production.
• Defect escape rate is the rate of issues and bugs that escape testing and arise after a software application is in production.
• Application availability measures the time an application is available and fully functional for end users. It’s also a component of digital experience monitoring (DEM).

Automation across the SDLC breaks down isolated, company-wide silos and reduces time-intensive, manual CI/CD processes. The result is that development teams become proactive rather than reactive. Moreover, automation frees up time for fail-safe innovation, and shifting left supports event-driven, SRE-inspired DevOps.

Some benefits of DevOps automation include the following:

• Improved frequency and velocity of releases. DevOps automation drives IT operational efficiency and reduces the potential for human errors which slows down release cycles.
• Less complexity in software releases. Releasing frequent, small builds as code evolves reduces the risk of failed releases and allows for faster adoption of customer feedback.
• Aligning business goals with customer-facing impacts. Automatic validation against business-critical metrics not only prevents bad code from reaching production but ensures code meets both business and end-user goals
• Better developer experience: With greater automation, developers spend less time on maintaining and updating toolchains. Automating processes also means better cross-team collaboration and more time spent on innovation.
• Cultural shift. Organizational buy-in of DevOps automation reflects support for structural solutions that build community and strategies that scale.

Depending on existing business goals, desired outcomes, and the current state of an organization’s unique cloud adoption journey, implementing an automated DevOps and IT framework solution can be straightforward or relatively challenging.

Whether the computing environment is located on-premises, in a public cloud service, or in a hybrid cloud infrastructure, the following DevOps processes are good candidates for automation:

• Automated CI/CD. These pipelines are a best practice for agile DevOps teams. Automating CI/CD is crucial for producing quality, secure code and meeting critical business requirements. This also extends to continuous deployment — when applicable — where every successful change is automatically deployed to production.
• Automated testing. Automated end-to-end testing focuses on detecting errors, defects, and bugs early in the CI/CD pipeline. This process helps ensure frequent, quality releases of software updates to end users.
• Automated application monitoring. Automated application and log monitoring gives deep insights into application performance and monitors issues reported through logs or DEM management for fast MTTR. The end goal is 24/7 uninterrupted service on any device, from any location.
• Automated network provisioning. This delivers computing capacity on demand using predefined procedures and without needing human intervention. Depending on the IT solution, it can also support application deployment in software containers such as Kubernetes.

There is no standard approach to DevOps automation. Organizations can drive automation, observability, self-healing, and vulnerability management across the SDLC in many ways, including self-service observability and monitoring-as-code approaches across the DevOps lifecycle. These methods allow development and IT operations teams to build feedback loops into their applications in just a few clicks. In addition, implementing AIOps as part of any cloud adoption strategy is critical to driving innovation forward.

Dynatrace’s approach to DevOps, driven by answers and intelligent observability, can help your organization jumpstart its DevOps automation journey. With AI at its core, the Dynatrace platform’s precise root cause and auto-remediation capabilities eliminate silos and improve collaboration to help you streamline and scale your DevOps efforts.