DevOps adoption has skyrocketed in recent years. Its impact on traditional development platforms has long been well-documented, but in more recent years it has started to influence low-code platforms, too. In its recent survey on the state of Salesforce DevOps, Gearset found that 69% of teams are already using source control and another 20% plan to start this year. Additionally, 45% of companies have implemented CI/CD, and that number is set to increase by 33% this year. However, for high-performing developer teams to recognize the benefits of DevOps and strive for further DevOps adoption, they must use the right KPIs.
While it can be tempting to take a ‘big bang’ approach to DevOps adoption, teams see more success when they take it one step at a time, with each stage building on the last.
That said, to experience the full ROI of DevOps adoption, it’s still critical to see the journey through to the end. It’s not uncommon for teams who begin the process of DevOps adoption to stop halfway through or, worse still, lose motivation and halt the process entirely. DevOps adoption is a process full of technical and cultural change, and one of the most common causes of its failure is an emphasis on the technical at the expense of the cultural.
The best way to tackle this is to encourage teams to take a product mindset and apply it to DevOps adoption. Simply put, rather than tasking your teams with “adopting CI” for instance, they should be asked to solve a specific business problem. For example, “When we finish work on a story, it takes weeks for it to get released!” It sounds obvious, but focusing teams around business impact rather than on individual tasks makes sure that there’s a direct correlation between the work that’s happening and the desired business outcome. This is the crux of adopting a DevOps mindset, rather than a purely technical and perfunctory approach to DevOps adoption.
One of the key things a team can do to drive this type of change—and to avoid common causes of failure—is to use the right metrics at each stage of their DevOps journey.
There are a number of well-recognized metrics for measuring DevOps success, including:
- Deployment time
- Change failure rate
- Release cadence
- Lead time
- Recovery time
These metrics serve two purposes. They’re well-documented and benchmarked indicators of performance that can help teams focus on their biggest problem areas. And they’re measurable outcomes that prove the business benefits of DevOps, such as agility, improved collaboration, higher quality systems and resilience, not to mention significant time and cost savings and efficiency.
Choosing the Right Metrics
Teams must choose the right metrics at the right time to identify their opportunities for improvement and to measure the impact of each stage of DevOps adoption. The right metric empowers a team to solve their most pressing challenges, and to demonstrate the value of their work to their leadership.
Here’s how the benefits of each stage of DevOps maturity should be measured:
Stage of DevOps maturity | Most relevant metric(s) |
Choosing your release tools | Deployment time |
Adopting version control | Change failure rate Recovery time |
Automating testing | Change failure rate |
Automating deployments (CI/CD) | Release cadence Lead time |
Integrating backup into DevOps tools and process | Recovery time |
Let’s expand on each stage and the appropriate KPI.
Choosing Your Release Tools
This is more relevant to low-code platforms, but still broadly applies to the wider tech world. Even in the most mature of development processes, there will be manual steps. Getting changes into version control, reviewing changes, resolving conflicts, triggering releases—each of these is a manual step, and the effort involved in each of these manual steps is heavily dictated by the tools you use.
Finding the right tool for each stage of your development and release process can therefore have a massive impact. The right deployment tool, for instance, can cut down deployment time by as much as 90%. This step alone increases efficiency and ultimately saves companies vast amounts of time and money. In extreme examples, teams that save so much time by picking up a couple of new tools to patch up their manual processes can be tempted to stop there. This is why teams need to look at other metrics as they proceed to adopt more DevOps processes.
Adopting Version Control
For most teams, a world without version control is unthinkable, having built their development and release processes around it a decade or more ago. For others, particularly in the low-code space where it’s yet to reach ubiquity, it can feel like an unnecessary burden. The introduction of version control is an extra step in the releases process and another level of complexity, with new tools and practices to learn. But version control is the foundation of an automated DevOps workflow. This step allows for more team collaboration and visibility into that collaboration, with code reviews and a detailed change history. Version control also allows teams to deal with merge conflicts early, rather than in the middle of a release.
After adopting version control, teams will see a reduction in their change failure rate due to code reviews and their recovery times will be shorter as version control offers rollback and a quasi-backup of the code and config captured by their version control system. But the real benefits of version control are in the DevOps processes it unlocks.
Automating Testing
It goes without saying that the purpose of testing is to improve the quality of releases. It does this in a few ways:
- Unit testing – Exercising individual methods and functions in isolation generally results in more maintainable code, which has positive benefits for developer productivity and even things like handling merge conflicts.
- Static code analysis – While this is not testing in the strictest sense, automatically verifying that code adheres to a set of best practices similarly improves code maintainability.
- Integration testing – This type of testing ensures that combinations of classes interact and generate the expected results when combined together. This brings another level of validation that changes being made are likely correct.
- End-to-end testing – UI testing is an example of this; exercising the system in the way a consumer would and verifying that the results are deterministic and correct. This also includes regression testing for key workflows and sometimes even acceptance testing.
The more of these testing approaches a team uses, the more confidence they’ll have in their changes and the less human verification and intervention will be required. As teams’ DevOps processes mature, it’s often the human element that becomes the biggest bottleneck, so confidence in deploying changes is very valuable.
When teams introduce more testing and test automation to their release pipeline, the right metric to watch is change failure rate—the proportion of releases that include a bug or error. The immediate benefit of higher-quality code translates to savings in the long term as less time is spent finding and fixing bugs or reworking code.
Automating Deployments (CI/CD)
If choosing the right deployment tool significantly reduces deployment times, automating deployments with a CI/CD workflow eliminates the time it would usually take to run those deployments manually. However, deployment times aren’t the key metric for measuring the success of CI/CD implementation. The most important metrics to pay attention to here are release cadence and lead times, which are dramatically improved thanks to painless, automated deployments.
With automated deployments, teams can increase their release cadence; rather than releasing huge batches of changes once a month, they might begin to release smaller packages every week. Ultimately, the goal is to have a steady stream of incremental improvements being released on-demand, and usually multiple times per day. Accelerated release cadences then result in reduced lead times—the period between work being finished and finally released to production. This is beneficial for developers and their end users as more frequent releases create more opportunities to act on user feedback earlier in the process.
Integrating Backup Into DevOps Tools and Process
Recovery times are a key metric for DevOps success, as robust DevOps processes will improve the speed at which teams can restore after an incident. For even better resilience and faster recovery times, teams should integrate backup into their DevOps tools and processes.
Restoring from a backup is comparable to a deployment, and this means that restore processes also can harness the power of DevOps so they feel like a familiar process—not something unusual that teams struggle to execute at the point when it matters most. It’s also important to make it as easy as possible to back up on demand just before a risky release.
Downtime and data loss are massive costs to any business, so improving recovery times is a huge benefit of a fully mature DevOps process.
See the Benefits of Maturing your DevOps Process
When teams pay attention to the right metrics, they understand the benefit of each DevOps process individually and they are motivated to keep maturing their DevOps processes as a whole. It’s all well and good to take the pain out of deployments and releases, but high-performing DevOps teams effectively make deployments an asset for releasing more often and getting feedback earlier. As a result, they are better equipped to deliver more value to their companies—sooner.
