Top 10 DevOps Success Metrics To Track For Massive Scalability

2023 will mark the dawn of DevOps first software development as it is set to witness the highest levels of market acceptance so far. Gartner predicts that by 2025, more than 85% of organizations will have a cloud computing strategy while 95% of new digital workloads will be executed on cloud platforms, a 30% jump from 2021.

Also, 2022 witnessed a 28% YoY growth in the amount spent on cloud infrastructure services globally as it climbed to $63.1 billion in Q3 2022, an increase of $13.8 billion when compared to the same period in the previous year. Having said that, it is necessary to understand that streamlining parallel software development is a taxing, continuous process that continues to evolve. Moreover, DevOps cannot be fully standardized, making it difficult for teams to stay aligned and agile.

Thankfully, the experts at Talent500 have outlined a list of ten DevOps success metrics that you must track to ensure massive scalability and high DevOps ROI.

Let’s get started!

#1 DORA Metrics

To begin with, DORA metrics provide a high-level understanding of whether DevOps is yielding the desired results and if the team is experiencing any frequent bottlenecks:

Deployment frequency (DF): It indicates the frequency of successful product releases/deployments to production. 

Lead time to changes (LT): It indicates the time required for achieving production/release after a commit has been made.

Mean time to restore service (MTTR): It defines the time consumed for recovering from an error/failure in the production version.

Change failure rate (CFR): It describes the number of times a release or deployment causes failure in production.

#2 Availability And Uptime

Availability and uptime are two of the most sensitive metrics when DevOps implementation is concerned, as speed and quality are byproducts of checks and balances in SDLC. 

While they are used interchangeably at times, uptime defines reliability by expressing the percentage of time the solution is working continuously. On the contrary, availability is the probability of the solution working as intended. 

Though 100% uptime and availability aren’t achievable, a higher value indicates the ability of the DevOps team to revive the solution in case of any issue.

#3 Defect Escape Ratio

It describes the rate of errors that escape detection during the CI/CD process and reflects the state of DevOps software testing at your organization.

Naturally, a high value translates to issues in the testing suite, and immediate attention must be paid to the same.

#4 Service Level Indicators (SLI)

SaaS companies sign SLAs (service level agreements) with their customers wherein software performance parameters are defined. 

The SLIs provide you with a concrete understanding of how your overall DevOps efforts are working out for the end users and if there is any discrepancy in your team’s KPI evaluation and actual delivery.

#5 Cycle Time

Cycle time is defined as the average time between the moment we decide to add a feature and its deployment or release to the public or customer.

It is a core DevOps metric largely utilized by the engineering and project leads to keep a ta of the development pipeline and the factors that increase the velocity,

#6 Customer Feedback

Though it doesn’t always qualify as a numeric metric, it is among the most crucial DevOps metrics when it comes to evaluating the DevOps team’s performance.

You may use Net Promoter Score (NPS), Customer Satisfaction (CSAT), Customer Effort Score (CES), brand perception/loyalty surveys, or other similar methods to collect and analyze customer feedback with respect to DevOps performance.

#7 Repository Speed

It represents the pull request time period over a 30-day horizon. Ideally, the average pull request time must sit between zero days to two weeks. 

Generally, DevOps teams handle multiple repositories, and the repository speed indicates the effectiveness of the code reviewing framework and the efforts put in by the team.

#8 Code Coverage

Code coverage is an important metric as it helps keep track of the percentage of the code covered by the software testing regime. 

However, it should be understood that the code coverage should not be confused as a marker of quality as testing consumes significant resources.

The DevOps teams must strategize code coverage optimally to ensure that the testing suite is both effective and efficient in order to fulfill the intent behind measuring this metric.

#9 Mean Time Between Failures

This is a powerful metric to understand the overall quality of the code and points out the components that require refactoring.

This metric, too, shall not be taken at face value; it is a reflection of how different software tasks interact with each other, how well the team gels with each other’s work regime, and the overall synergy in the team.

#10 Flakiness

Flakiness can be an effective indicator of customer experience as it represents the reliability of the overall CI/CD platform.

High flakiness is an indicator of mismanaged CI/CD activities, processes, and failure to recover promptly- random failures due to ambiguous reasons.

Wrap Up

Unlike popular perception about DevOps, implementing it doesn’t translate to increased scalability- it remains an approach to software development.

The DevOps metrics discussed herein are vital signs to monitor to ensure that your team is on track and that the product is in good health.

Keeping a tab of these metrics will also give you clarity when scaling your team and processes, as DevOps is comparatively less tractable, especially for teams that have recently implemented it.

Trusted by the top corporations, Talent500 has an ever-growing pool of DevOps opportunities. Join Talent500 today.

Also, you may go through our ultimate guide on exploring DevOps jobs as a software engineer.