DevOps is a set of skills that bridges the gap between software development and IT operations. Its goal is to shorten the time it takes to design a system and perform continuous delivery with exceptional software quality.
What Exactly Is DevOps (Culture)?
The terms "Development" and "Operations" are combined to form DevOps. It is a collection of development methods that aims to bring together people, processes, tools, and technology to provide high-quality products to customers swiftly.
The primary purpose of DevOps practices is to improve an organization's capacity to deliver applications and services efficiently and quickly by using automated technologies to bridge the gap between operations and development. DevOps practices allow enterprises to improve and accelerate their development life cycle, delivering more products, features, fixes, and updates while ensuring high quality.
A high level of knowledge and trust exists across teams in a DevOps environment. As a result, teams can experiment and innovate without having to slow down the process. DevOps enhances business flow by bringing teams closer together and allowing them to collaborate in real-time. Overall, embracing the DevOps culture provides technological, cultural, and commercial benefits to businesses. Organizations with higher DevOps maturity consistently outscore on the four key software performance metrics.
Source: Puppet State of DevOps Report, 2021
Metrics for Increasing Productivity with DevOps
To be successful with DevOps, teams employ a variety of tools. DevOps metrics are critical for improving and creating a higher-quality software delivery process.
Here are some of the more critical DevOps metrics for teams:
1. Deployment Frequency
It is critical to promote and maintain an ambitious advantage to provide updates, new functionalities, and superior quality & technical efficiency improvements. The ability to increase delivery intensity contributes to increased flexibility and better adherence to changing customer obligations.
The goal should be to allow for smaller deployments as often as possible. Software testing and deployment are much more comfortable when deployments are smaller.
2. Deployment Time
This metric determines the time required to complete a deployment. Even though it may appear insignificant at first, measuring deployment time is one of DevOps metrics indicating potential problems.
For example, if deployment takes an hour, there must be a problem. As a result, it is preferable to concentrate on smaller but more frequent deployments.
3. Deployment Size
This metric is used to keep track of the number of stories, feature requests, and bug fixes that are being deployed to production.
Individual work item counts may vary greatly depending on their size. You could also keep track of how many story points or days of development work are deployed.
4. Customer Tickets
A good customer experience is critical to the product's survival. Increased sales volumes result from satisfied customers and good customer service.
As a result, customer tickets reflect the level of customer satisfaction, which in turn reflects the quality of the DevOps processes. The lower the number, the higher the service quality.
5. Automated Tests Pass Percentage (%)
To increase velocity, it is strongly advised that every team extensively use the unit and functional testing. Because DevOps is heavily reliant on automation, tracking the automated tests' performance is an essential DevOps metric.
It's helpful to know how frequently code changes because your automated tests to fail.
6. Defect Escape Rate
Do you know how many software bugs are discovered in production versus QA? If you want to ship code quickly, you must be confident that you can detect software bugs before they reach production.
Your defect escape rate is an excellent DevOps metric for tracking how frequently those defects go into production.
7. Costs
Although the cloud is a great way to cut infrastructure costs, some unanticipated errors and events can cost a lot of money. As a result, you should focus on capturing and reducing unnecessary expenses.
Visualizing your spending sources can help you understand the actions that cost you the most money. The ideal scenario for saving money would be to use a tool that can automate sleep cycles and wake-up environments only when they are required.
8. Frequent Failed Deployments
We hope it never happens, but how frequently do your deployments cause outages or significant problems for your users? You never want to reverse a failed deployment, but you should always plan for it.
If you have issues with failed deployments, keep an eye on this metric over time.
9. Detection Time
Although reducing or even eliminating failed changes is the best approach, detecting faults as soon as they occur is critical. The time it takes to identify the fault will determine whether current response efforts are appropriate.
Long detection time may result in constraints that disrupt the entire workflow. Setting up robust application monitoring can aid in better understanding of “detection time”.
10. Error Rates
It is critical to monitor error rates within the application. They are not only an indicator of quality issues but also of ongoing performance and uptime issues. Best practices for handling exceptions are critical for good software.
- Bugs:Identify new exceptions thrown in your code following a deployment.
- Production issues:Capture issues like Socket Connection timeout, Database connection timeout, Query timeouts, etc.
11. Application Usage & Traffic
You may want to see if the number of transactions or users accessing your system appears normal after deployment.
Something could be wrong if there is suddenly no traffic or a massive spike in traffic. There are numerous monitoring tools available to provide this information.
12. Application Performance
Look for performance issues, unknown bugs, and other problems before deploying. You should also observe changes in the overall program output both during and after the deployment.
Following a release, it is common to notice changes in the use of specific SQL queries, web server calls, and other requirements. You can detect them by using monitoring tools that display the changes precisely.
13. Mean Time to Recovery (MTTR)
MTTR is a success metric that assesses the enterprise's ability to solve problems. Analyzing the impact on business and customer experience creates the perspective required to comprehend and prioritize concerns thoroughly.
MTTR calculates the total response time from failure to resolution and indicates whether clients have lost control, experienced delays, or abandoned the system. Improving MTTR reduces the impact of these issues while maintaining user satisfaction.
Reducing MTTR is critical and can be achieved through practical application management tools that can detect problems quickly, and efficiently execute patches.
Summary
The metrics listed above will help us figure out what to track and improve if you want to take DevOps to the next level. DevOps accelerates developer involvement in the deployment and monitoring of applications.
Our approach to DevOps is to unite technology, process, metrics & culture in our pursuit to deliver faster & higher-quality software products. Some key elements of our approach are:
- Implement full suite of DevOps best practices & metrics
- Integrate security & compliance into pipelines through DevSecOps
- Deploy optimal DevOps toolchain to minimize overlap, conflict & functionality gaps
- Augment toolchain with Release Orchestration & Performance Monitoring tools
- Architect self-service platform for developers, tailored to the needs of the organization
Join Us at Encora
Are you a developer or engineer looking to make an impact on the world through technology? Visit Encora careers to join a passionate community of innovators and receive unmatched opportunities for professional development and benefits.
Fast-growing tech companies partner with Encora to outsource product development and drive growth. Visit Encora.com to learn more about our remote teams and augmented teams innovating in cloud enablement, big data, QA, AI, DevOps, and more
Resource List
- Miteva, Sara. “13 DevOps Metrics for Increased Productivity.” Dzone.Com, 30 Oct. 2020, http://www.dzone.com/articles/13-devops-metrics-for-increased-productivity
- “How DevOps Increase Productivity?” Super, May 2021, http://www.techasoft.com/post/how-devops-increase-productivity
