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DevOps metrics
DevOps metrics are data points that directly reveal the performance of a DevOps software development pipeline and help quickly identify and remove any bottlenecks in the process. These metrics can be used to track both technical capabilities and team processes.
At its core, DevOps focuses on blurring the line between development and operations teams, enabling greater collaboration between developers and system administrators. Metrics allows DevOps teams to measure and assess collaborative workflows and track progress of achieving high-level goals including increased quality, faster release cycles, and improved application performance.
Four critical DevOps metrics
Though there are numerous metrics used to measure DevOps performance, the following are four key metrics every DevOps team should measure.
Four critical DevOps metrics
SRE aims to enhance automation of repeatability and predictability, increase scalability for growth that doesn’t interrupt service, and ensure reliability. SRE team members can function as hybrid system admin/developer resources and focus attention where it’s needed when it’s needed. They can identify issues as well as fix them. SRE helps development and operations teams work together more effectively to achieve common goals through their ability to move fluidly between the two areas.
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Other related metrics
Another relevant metric is cycle time, which is the time a team spends working on an item until it is ready for shipment. In the development world, cycle time is the time from when developers make a commit to the moment it's deployed to production. This key DevOps metric helps project leads and engineering managers better understand what works well in the development pipeline. As a result, they can better align their work with the expectations of stakeholders and customers, ensuring their team's ship faster.
Cycle time reports allow project leads to establish a baseline for the development pipeline that can be used to evaluate future processes. When teams optimize for cycle time, developers typically have less work in progress and fewer inefficient workflows.
In Lean product management, there is a focus on value stream mapping , which is a visualization of the flow from product or feature concept to delivery. DevOps metrics provide many of the essential data points for effective value stream mapping and management but should be enhanced with other business and product metrics for a true end-to-end evaluation. For example, sprint burndown charts give insight into the efficacy of estimation and planning processes, while a Net Promoter Score indicates whether the final deliverable meets customers’ needs.
Key principles
DevOps approaches business problems with collaboration, automation, and integration.
One of DevOps’ primary goals is continuous delivery. Lean and agile software development methodologies strive to deliver value to customers continuously. Automation and integration support smaller, more focused releases, which help businesses increase velocity without compromising reliability.
Lean and agile development teams share ideas, work together to deliver solutions, and continuously improve products and processes. DevOps’ commitment to cross-functional collaboration throughout the product lifecycle makes it a natural fit for Lean and agile teams.
Jira Software’s Open DevOps supports agile teams focused on shipping and operating high-quality software with out-of-the-box Open DevOps features.
Differences between SRE vs. DevOps
SRE manages the stability of the tools, methods, and processes businesses use during the product life cycle. It ensures that teams build new products and features with sustainable tools and use processes that deliver optimal success in production.
DevOps manages the end-to-end product lifecycle from development to deployment and maintenance. It is the essence of the “you build it, you run it” approach.
DevOps handles what teams build in companies with both SRE and DevOps teams, while SRE handles how teams build it. Here is a detailed comparison of SRE vs. DevOps:
Focus
SRE focuses on the stability of the tools and features in production. It seeks to maintain low failure rates and high reliability for end users. This includes system scalability and robustness.
DevOps focuses on using a collaborative approach for building tools and features. It strives to identify and implement the best ideas by including the development and operations teams.
Responsibilities
SRE’s primary responsibility is system reliability. Regardless of the features deployed to production, SRE ensures they don't cause infrastructure issues, security risks, or increased failure rates.
DevOps is responsible for building the features necessary to meet customer needs. Unlike older approaches, DevOps increases its efficiency through collaboration across the development and operations teams.
Objectives
SRE strives for robust and reliable systems that allow customers to perform their jobs without disruption.
DevOps aims to deliver customer value through streamlining the product development lifecycle and accelerating the rate of product releases.
Team structure
SRE teams are often highly specialized with a much narrower focus than DevOps teams. SRE may include security specialists whose primary concern is protecting business data and complying with regulations.
DevOps, however, integrates and collaborates across development and operations to collect and implement the best possible solutions. With more varied input, teams can identify and solve problems before they reach production.
Process flow
SRE views the production environment as a highly-available service. Its processes focus on increasing reliability and decreasing failures. This could include security threats and failures from newly deployed features and integrations.
DevOps operates like an Agile development team. It designs processes for continuous integration and faster delivery. This includes breaking large projects into smaller chunks of work and generating and prioritizing ideas based on customer value.
Other related metrics
Another relevant metric is cycle time, which is the time a team spends working on an item until it is ready for shipment. In the development world, cycle time is the time from when developers make a commit to the moment it's deployed to production. This key DevOps metric helps project leads and engineering managers better understand what works well in the development pipeline. As a result, they can better align their work with the expectations of stakeholders and customers, ensuring their team's ship faster.
Cycle time reports allow project leads to establish a baseline for the development pipeline that can be used to evaluate future processes. When teams optimize for cycle time, developers typically have less work in progress and fewer inefficient workflows.
In Lean product management, there is a focus on value stream mapping , which is a visualization of the flow from product or feature concept to delivery. DevOps metrics provide many of the essential data points for effective value stream mapping and management but should be enhanced with other business and product metrics for a true end-to-end evaluation. For example, sprint burndown charts give insight into the efficacy of estimation and planning processes, while a Net Promoter Score indicates whether the final deliverable meets customers’ needs.
In conclusion…
Continuous improvement is a core tenet of teams practicing DevOps. The ability to measure and track performance across lead time for changes, change failure rate, deployment frequency, and MTTR allows teams to accelerate velocity and increase quality. Learn more about how Atlassian helps you deliver better and faster value to customers with Code in Jira and Deployments in Jira.
In conclusion…
Continuous improvement is a core tenet of teams practicing DevOps. The ability to measure and track performance across lead time for changes, change failure rate, deployment frequency, and MTTR allows teams to accelerate velocity and increase quality. Learn more about how Atlassian helps you deliver better and faster value to customers with Code in Jira and Deployments in Jira.
How to measure, use, and improve DevOps metrics
Lead time for changes
High-performing teams typically measure lead times in hours, versus medium and low-performing teams who measure lead times in days, weeks, or even months.
Test automation, trunk-based development, and working in small batches are key elements to improve lead time. These practices enable developers to receive fast feedback on the quality of the code they commit so they can identify and remediate any defects. Long lead times are almost guaranteed if developers work on large changes that exist on separate branches, and rely on manual testing for quality control.
Change failure rate
High-performing teams have change failure rates in the 0-15 percent range.
The same practices that enable shorter lead times — test automation, trunk-based development, and working in small batches — correlate with a reduction in change failure rates. All these practices make defects much easier to identify and remediate.
Tracking and reporting on change failure rates isn’t only important for identifying and fixing bugs, but to ensure that new code releases meet security requirements.
Deployment frequency
High-performing teams can deploy changes on demand, and often do so many times a day. Lower-performing teams are often limited to deploying weekly or monthly.
The ability to deploy on demand requires an automated deployment pipeline that incorporates the automated testing and feedback mechanisms referenced in the previous sections, and minimizes the need for human intervention.
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