Processes, Tools and Metrics for DevOps Success

DevOps is a topic of great interest for organizations in all sorts of industries. By combining development processes with operations, organizations can speed up application development and improve their agility. That’s not all: Using DevOps processes can maximize the efficiency and the reliability of an application, which improves the end-user experience. 

Improving the user experience is critical in today’s business landscape, so optimizing the software development and delivery process has become a major concern for organizations in the digital age. To achieve these objectives, organizations must understand DevOps processes, the tools that enable them and the metrics that measure their success.

A core objective of DevOps is to improve developer productivity, which historically has been a challenge for many organizations. To do so requires an organization to automate and make enhancements to every step of the agile development process or software development lifecycle (SDLC): building, testing and deployment of an application, then managing the lifecycle and monitoring performance. 

Traditionally, development and operations teams have been siloed. The development team would create an application, then turn it over to the operations team, which was responsible for instantiating the infrastructure on which the application ran and the deployment of the application. Once an application made it into a production environment, the operations team would be required to manage the availability of the resources that supported the application. The DevOps process breaks down these silos, so development and operations teams work together. This enables apps to move through the SDLC with higher quality and velocity, ultimately improving the user experience.

Containerization has become a key technology for DevOps for many reasons, but primarily because it decouples software code from the underlying infrastructure. By decoupling these units, an organization can now do many interesting things as it works with an application. For example, containers enable developers to take advantage of different deployment mechanisms such as rolling upgrades and canary releases. This allows improvements to be made to applications, or new versions can be deployed without requiring downtime. Container orchestration tools allow teams to adopt these more complex deployment patterns more easily, as the logic is built into the platform. Along with decreasing downtime, container orchestrators give more flexibility to developers to define the needs of the applications and the resources they depend on. 

Infrastructure as Code has emerged as another essential element for DevOps. IaC enables DevOps teams to manage IT infrastructure (such as public cloud resources, networking, servers and other equipment) through machine-readable definition files, a process which generates precisely the same environment every time it is applied. This gives organizations the ability to define everything that goes into application development and delivery processes (for example, observability and monitoring, policies, and pipelines) as code and enables them to track and version those resources effectively. 

In order to track and version resources, teams must use a version control system as a common repository for all forms of code. These tools allow teams to collaborate effectively and manage change across files and resources. Many of these systems include tools to automate workflows and provide some (if not all) of the functionality of continuous integration and continuous delivery/deployment systems, more commonly referred to as CI/CD. 

CI/CD tools can take many forms, but they are ultimately the glue the holds the SDLC together. These tools provide a platform for the automation logic needed to build artifacts, test and deliver applications so they can programmatically be assessed for quality and promoted accordingly. Among the many things CI/CD platforms can and should do is allow the integration of tools used for the automated testing of code and artifacts for vulnerabilities and misconfigurations. Everything from application code to infrastructure definitions should be put through such tests, and policies should be put in place for the actions needed when various scenarios arise. Moving security testing to earlier in the SDLC is often referred to as “shifting left” on security. Giving feedback to teams earlier and addressing problems as they are discovered reduces the cost associated with rework and allows more secure software to be developed more quickly. 

These tools together with the right patterns and techniques can allow organizations to have a uniform, reliable process for the deployment of applications regardless of the target environment, whether in a private or public cloud.

To achieve DevOps success, organizations must be able to measure processes and their results to achieve rapid experimentation and incremental improvements. Among many metrics used to measure success, four of the key metrics the industry regards as crucial are: 

• Mean time to resolution: The time it takes to repair a system after a failure
• Change fail rate: The percentage of workflows that fail to enter production
• Deployment frequency: The rate with which increments of code are deployed to staging, testing and production
• Lead time for changes: The time from when a code change is committed to when it is deployable

As organizations improve in these areas, they improve the results of their DevOps efforts. They’re able to build software and features — and thus build value in the interactions they have with end users — more effectively than others in the industry. Their services are more reliable, and they don’t fear change within their systems or applications.

As a result, these organizations have fantastic digital experiences that help them outperform others in their marketplace and even find their way into new markets. In some cases, they may even evolve their business practices to step into new industries.

Story by Kyle Jepson, a senior DevOps field solution architect for CDW. He assists clients with navigating the ecosystem of DevOps and cloud-native solutions and services. He is responsible for delivering technology demos, training and scoping service engagements to help clients build core capabilities for their digital initiatives. He is a Certified Kubernetes Administrator.