Measuring the Impact of DevOps Initiatives
Learn how to assess the impact of your efforts to speed development and improve software quality
In the lead-up to a software launch, DevOps teams often have competing priorities that can create speed bumps on the path to market. Smart DevOps initiatives help engineers and developers streamline their efforts, getting everyone on the same page and aligning their objectives. When done successfully, DevOps initiatives help teams ensure that they launch a competitive, high-quality product on or ahead of schedule. Without proper monitoring, however, it can be difficult to tell whether or not those initiatives are having the desired impact.
By knowing which key metrics to track and measuring the impact of DevOps initiatives, developers and engineers can balance speed and quality control, eventually leading to a successful deployment.
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The Importance of Company Culture in DevOps Initiatives
Before getting any DevOps initiatives underway, it’s important to make sure that everyone working on a project is on the same page. If one team is underperforming, another is resisting changes, and communication breaks down somewhere along the way, those signs all point to DevOps failure — and a rocky path to market.
“One sign that a DevOps initiative isn’t working well is a lack of collaboration between development and operations teams,” according to DevOps expert Monika Mueller. “If development and operations teams continue to operate in isolation, with minimal interaction, it indicates a breakdown in the intended culture of shared responsibility that DevOps promotes.” In order to better encourage collaboration and support DevOps initiatives, company leaders should foster a company culture built on “shared ownership and accountability.”
Measuring the Impact of DevOps Initiatives: Key Metrics
One of the most important metrics to track in DevOps initiatives is deployment frequency, or the rate at which updated code is deployed. A high deployment frequency indicates that your team is agile and working well together. Whether you’re deploying a quick fix or adding an entirely new feature, a cohesive DevOps team should be able to get those changes underway with minimal friction.
Deployment frequency is fairly easy to measure; simply count (or average) the number of deployments over a chosen time period. There’s no single number that indicates a favorable deployment frequency, as this will vary by company and project, but aim for between one deployment a day and one a week. If you find yourself falling behind, it’s likely that you need to implement more automations to increase deployment frequency. Click here to learn how DuploCloud’s no-code/low-code DevOps automation can speed up infrastructure deployment up to ten times faster.
In between committing code and deploying it, there’s a period of implementation and testing known as lead time. Lead time is directly related to deployment frequency, as long lead times tend to correlate with lower rates of deployment. The longer the lead time, the greater the chance of being eclipsed by competitors, as they may have released comparable deployments in the extra time it’s taken to implement new code.
This is another metric that can be improved by automation, specifically continuous integration, delivery, and deployment (CI/CD). By optimizing the CI/CD pipeline, DevOps teams can automate the processes that slow down lead time, like testing and monitoring. This also allows developers to release each feature as soon as it’s available, rather than waiting to deploy changes in a large batch.
Change Failure Rate
What percentage of code deployments cause failures in production? The answer to that equation is your change failure rate. While some degree of failure is always to be expected in DevOps, a higher change failure rate indicates that your current deployment processes are not working or could be more efficient.
Lowering your change failure rate typically means re-examining the testing process and identifying opportunities for improvement. Manual infrastructure is often prone to higher change failure rates, so leverage infrastructure as code to optimize testing and increase success rates.
Mean Time to Recovery
Mean time to recovery (MTTR), sometimes referred to as mean time to restore, is the average amount of time it takes to recover from any failure. Again, some degree of failure is a normal part of the DevOps process, but developers and engineers should still take steps to minimize the time it takes to bounce back from those setbacks. MTTR shows how efficient DevOps teams are in fixing the issues that led to that failure.
Time to recovery varies by the severity of each incident, so calculating MTTR is a good way to get an overview of how efficient your team is when it comes to getting back on track. Failures should not waylay production for days at a time, so if you find that’s the case, it’s time to look at more CI/CD systems to improve testing and pre-deployment failure detection.
DuploCloud Drives DevOps Initiatives
There’s no question that measuring the impact of DevOps initiatives is necessary to gauge progress and efficiency on the path to software release. By adopting a no-code/low-code automation platform, you can improve these metrics, speed up time to market, and minimize downtime. DuploCloud can help by turning high-level specifications into low-level automations, all while lowering costs, meeting regulatory standards, and reducing the rate of human error in DevOps configurations. To learn more about how DuploCloud can help implement successful DevOps initiatives, get in touch to set up a free demo.