Your free practical guide to Software Engineering Intelligence platforms. Download now >

Top 5 DevOps Metrics That Make an Immediate Impact

Reporting as a Delivery Manager

How can DevOps metrics help managers make an impact and implement change?

Agile DevOps metrics are an increasingly hot topic. Up until recently, DevOps metrics (sometimes known as DevOps KPIs) have been constrained by the analytical capabilities of the underlying DevOps toolsets.

But with a new generation of Value Stream Management tools, it is possible to surface and synthesise data from multiple DevOps tools (e.g. workflow management tools, code repos, CI/CD tools and APM/ITSM tools).

As a result, a new wave of more powerful DevOps metrics and DevOps analytics are now helping DevOps practitioners deliver valuable software much more effectively.

 

Selecting the top 5 DevOps Metrics

We’ve selected the most popular DevOps metrics among our clients and have focused on those DevOps metrics that give you ‘the biggest bang for your buck’, no matter your current level of Agile DevOps maturity.

The DevOps metrics selected are similar to the DORA metrics as popularised by the DevOps Research and Assessments (DORA) group. In this article, however, we’ve chosen our top 5 DevOps metrics selection based on actual feedback (and usage) from a wide variety of Plandek clients at all levels of Agile DevOps maturity.

As such, our picks for the top five DevOps metrics reflect what we actually see being used to drive value among our clients.

 

Deployment Frequency

Deployment Frequency is perhaps the most fundamental DevOps metric as it measures the ability of an organisation to develop and deploy to live small software increments rapidly. More specifically, it tracks the frequency with which increments of code are deployed to staging, testing and production.

As the core objective of Agile software delivery is ‘..the early and continuous delivery of valuable software..’, Deployment Frequency is a core Agile metric and represents a core objective of effective DevOps. Deployment Frequency is also one of the four DORA metrics.

Example Deployment Frequency chart – Plandek DevOps metrics Dashboard

 

The calculation of Deployment Frequency requires surfacing data from CI/CD tools (e.g. Jenkins, CircleCI). This is typically done via reporting plug-ins to such tools or via an end-to-end delivery metrics dashboard like Plandek.

Delivery metrics dashboards like Plandek enable you to analyse delivery, engineering and DevOps metrics in a number of different ways. For example, you can analyse Deployment Frequency by branch, portfolio, programme, repository or team. As such, targets can be set, and practical actions are taken to increase Deployment Frequency, increasing your project turnover and, ultimately, your product’s value.

Deployment Frequency Drill Down Chart
Example Deployment Frequency drill-down chart – Plandek DevOps metrics dashboard

 

Code Cycle Time

Code Cycle Time is a key DevOps metric as it tracks the efficiency of the Pull Request process – which itself is a critical element of the end-to-end software delivery process.

More specifically, Code Cycle Time analyses all completed Pull Requests (PRs) – such as closed, merged, and declined – within the specified time range and shows the average hours to complete.

Not only that, but Code Cycle Time provides full insight into the different stages that a PR goes through, such as Time to Review, Time to Approve, Time to Merge/Close and Time to Deploy.

The method of calculation of Code Cycle Time is shown below:

Code Cycle Time Calculation: Code Cycle Time = Elapsed time of all stages on completed pull request / Count of completed pull requests
Code Cycle Time Chart
Example Code Cycle Time chart – Plandek DevOps metrics Dashboard

 

A powerful DevOps analytics tool like Plandek enables you to analyse Code Cycle Time using a number of different filters in order to identify bottlenecks and reduce them significantly. Such filters include analysis by PR author, PR participant, Code Cycle Time Stage, Repository and Ticket Issue Type.

Code Cycle Time Drill Down Chart
Example Code Cycle Time drill-down chart – Plandek DevOps metrics Dashboard

 

Mean Build Time

Mean Build Time is a very impactful DevOps metric for organisations at all levels of Agile DevOps maturity. It analyses the time taken for a build and is typically analysed by workflow.

It is a very good indicator of core DevOps process health as a steadily increasing mean workflow build time will drive longer Cycle Times.

We particularly like filtering by status to help you keep an eye on slow builds, which ultimately end in failure.

Mean Build Time Chart
Example Mean Build Time view by Workflow Name

 

Mean Time to Recover from Build Failures

Mean Time to Recover from Build Failures is a key DevOps KPI as build failure is such a common occurrence and the main source of friction in the deployment process. As such, it needs to be tracked and managed.

The metric identifies how long it takes for the next successful workflow on a branch that has failed. Mature Agile DevOps organisations become very good at managing this recovery time and so improve their deployment frequency.

Mean Time to Recover from Build Failures Chart
Example Mean Time to Recover from Build Failures metric view

 

Flakiest Files

Flakiest Files is a really helpful DevOps metric aimed at identifying fragile source code files in your codebase, which can be targeted for refactoring in order to reduce your Build Failure Rate.

The darker the shade of red, the more often a commit has resulted in a failed build. Plandek’s drill-down enables you to filter by file extension to help focus on a particular subset of files.

Flakiest Files Chart
Example Flakiest Files DevOps metric view

 

Build Failure Rate

Eagle-eyed readers will have noticed that this is the sixth metric in our Top 5 DevOps metrics guide, but we’ve included it as it’s another key DevOps KPI that really shouldn’t be left out.

Indeed, Build Failure Rate is an extremely helpful DevOps metric as it identifies the percentage of workflows which fail and the overall risk this poses to development.

As such, Build Failure Rate helps track and manage a significant source of risk both in day-to-day development and responding to incidents due to delays. Taking all your workflows over a period, it calculates the percentage that ended in failure.

Build Failure Rate Chart
Example Build Failure Rate DevOps metric view

 

About Plandek

Plandek is an intelligent analytics and performance platform to help software delivery teams deliver valuable software faster and more predictably.

Plandek enables technology teams to track and drive their improvement and share understandable KPIs with stakeholders interested in accelerating value creation/ improving delivery efficiency.

Plandek works by mining data from delivery teams’ toolsets (such as issue tracking, code repos and CI/CD tools) to provide actionable and intelligent insight across the end-to-end software delivery process.

Plandek is recognised as a top global vendor in the DevOps Value Stream Management space by Gartner and Forrester and is used by private and public organisations globally to optimise their technology delivery and accelerate R&D ROI.

For more information, please visit www.plandek.com.

View more blog posts

Unlock the power of data with Plandek's intelligent insights

Choose the Plandek plan that suits your organization size and delivery objectives. To compare, see Pricing & Plans →

Plandek SmartDelivery: start your free 30-day trial now

Get Plandek SmartDelivery for real-time insights to deliver sprints & epics faster & more predictably. Powered by AI to help mitigate risks and blockers.

No payment details required. From $59 per month after free trial.

Plandek Enterprise: the complete engineering intelligence platform

Enterprise-level intelligent analytics to accelerate your roadmap delivery, improve delivery capability & communicate better with stakeholders.

Free technical POC available to get started with no upfront costs.