DevOps—you either master it or explore it. According to the 2021 State of DevOps Report by Puppet, 83% of the organizations surveyed use DevOps practices. Among them, only 18 percent fall into the “Master” category, reaching a high level of DevOps evolution. However, 78 percent tend toward the “Explore” category. They’re stuck in the middle range and have a long way to go in their DevOps journey.
Whether your enterprise is in the middle majority or struggling to reach the small elite, keep reading. This post examines DevOps maturity, starting with the basic principles and levels. Then, it guides you through the key steps to progress to the elite DevOps maturity level.
Basic principles of DevOps
DevOps relies heavily on automation and established best practices to streamline the software development life cycle (SDLC). Its primary goals center on accelerating time-to-value and upholding product quality. It achieves these goals by breaking down silos and improving collaboration across all groups that have a stake in the development outcome.
By following these principles, companies develop technology faster to gain a competitive edge.
Levels of DevOps maturity
The DevOps Research and Assessment (DORA) program—a part of Google Cloud—defines four DevOps maturity levels:
Low maturity. Teams use manual processes that come with a high risk of human error.
Medium maturity. Teams use scripting tools to automate configuration management and aid in reducing human error in manual configuration.
High maturity. Teams use fully automated deployment tools that reduce human error in the deployment process.
Elite maturity. Teams use continuous deployments (continuous integration (CI) and continuous delivery (CD)) and testing to drive changes into production without any human intervention.
Advantages of the elite level of DevOps maturity
Organizations that reach the elite DevOps maturity level continuously improve their applications, pivoting quickly in response to customer demands and competitive threats. The elite level also has the following advantages:
- Anytime assessments of current DevOps ecosystems
- Elevated customer experiences
- Data-driven approaches to root-cause analysis and self-healing applications
- Guardrails for security, compliance, and governance
- Enhanced security through DevSecOps
- Faster solution implementations
- Enriched analytics with actionable insights
These advantages are worthy goals and achievable for enterprises in the middle of the DevOps maturity ladder.
3 steps to achieve the DevOps elite level
To reach the elite DevOps maturity level, enterprises must follow three essential steps.
1. Assess the current level and create objectives
To achieve better results from DevOps, first, identify your current maturity level. Consider the following scenarios.
- Low maturity. At this beginner stage, teams use manual health checks and monitoring, along with basic configuration management.
- Medium maturity. At this middle stage, teams use automated CI/CD, health checks, and monitoring tools.
- High maturity. At this advanced stage, teams shift to DevSecOps, embedding security operations across DevOps processes.
- Elite maturity. At this stage, teams implement zero-touch deployments and AI-driven automation.
Then, define objectives to guide you in moving up each level. All efforts should drive toward elite status. Your enterprise can achieve elite DevOps maturity by continuously improving across the SDLC, adding features and capabilities while reducing bugs that affect quality.
2. Set and push for data-driven goals
Seek specific, data-driven goals in the following DevOps performance categories:
- Deployment frequency. The frequency at which your team deploys code into production.
- Lead time for changes. The time it takes from committing code to running it successfully in production.
- Time to restore service. The average time it takes to restore service.
- Change failure rate. How often deployment failures occur in production that requires immediate remedy.
The following table, based on DORA metrics, shows the outcomes to target in each category when moving across maturity levels. For example, the deployment frequency metric for low maturity might be weekly or monthly, while the frequency at the elite level is multiple deployments in a day.
| DORA METRICS - Aspect of Software Delivery Performance |
Low | Medium | High | Elite |
| Deployment Frequencies (How frequently team deploys the code into production) | Once per week - Once per month | Once per week - Once per month | Once per day | On-Demand (Multiple Deploys per day) |
| Lead Time for Changes (Time it takes to go from code committed to code successfully running in production) | 1 - 6 months | 1 week - 1 month | 1 day - 1 week | <1 hour |
| Time to Restore service (Average time it takes to restore service) | 1 week - 1 month | <1 day | <1 day | <1 hour |
| Change Failure rate (How often deployment failures occur in production that require immediate remedy) | 46 - 60% | 0 - 15% | 0 - 15% | 0 - 15% |
Source: “Are you an Elite DevOps performer? Find out with the Four Keys Project.” Google Cloud. October 2, 2020.
The elite DevOps maturity level might seem out of reach if your enterprise currently has low to medium DevOps maturity. However, you can achieve the elite level by moving up the maturity ladder one step at a time.
3. Strive to achieve outcomes
When working toward your DevOps goals, strive for the following outcomes as they correspond to each level:
- Value stream management. The continuous nature of DevOps converges multiple aspects of development and operations to produce a value stream. Manage this stream to optimize requirements, idea delivery, and other variables for maximum productivity and efficiency. Explore this topic further in the whitepaper Value Stream Mapping Applied to DevSecOps.
- Continuous measurement. The ability to measure software reliability and time-to-market is essential to progressing across the DevOps maturity levels. Therefore, each time, you must quantify and analyze the four DORA metrics along with any other relevant data points. Data analysis can also reveal what’s working well and guide you to areas that need improvement. Learn more in the Telemetry dashboard for SDLC.
- Continuous compliance. Automation is pivotal to high-level DevOps and requires methodologies for always-on compliance, sometimes called policy as code. Develop policies that cover such areas as tool-based planning and reporting, lifecycle traceability, continuous security and testing, and other key components of the CI/CD pipeline.
- Continuous governance. Merge AI-driven insights and recommendations with each outcome to produce a continuous governance engine. Doing so enables elite-level use cases such as the following examples:
- AI-driven demand management
- Change failure prediction
- Change impact assessments
- Customer experience optimization
- Automated incident categorization and routing
- Problem root-cause analysis
- Automated remediation and self-healing
- Capacity forecasting and optimization
Start your journey to elite DevOps maturity
DevOps is more than a methodology for accelerating software engineering. It’s a culture that removes silos and bottlenecks. Reaching the elite DevOps maturity level requires implementation of effective tactics that your organization can reference, scale, and repeat across people, processes, and technologies.
From the first level, you must establish clear goals and seek specific outcomes as you work your way to the elite level. As you complete each level, you’ll gain agility, speed, and a competitive advantage from your DevOps practices, leading you to earn the rewards of the elite maturity level. By following the approach in this post, you’ll go from just exploring DevOps to mastering it.
Don’t wait to get started on your journey to elite DevOps maturity. Count on DevOps experts who can set you on your way.
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Sujatha Sivaraman
Director–Intelligent Engineering Automation in Global Consulting & Technology Solutions
Sujatha Sivaraman is a Director–Intelligent Engineering Automation in Global Consulting & Technology Solutions (GCTS) of Virtusa Consulting Services. She has over 20 years of experience in IT, banking and financial services, manufacturing, project and program management, testing and quality assurance, DevOps, automation, Agile, business analytics, and Lean and Six Sigma practices. Sujatha is a Certified Cloud Practitioner, Six Sigma Black Belt, Scrum Master, PMP, and CFPS Certified professional, and she holds other certifications in ITSM, Machine Learning, Python, and Design Thinking. She has published estimation articles and presented papers in International Software Estimation Colloquium (ISEC), Software Process Improvement Network (SPIN), and International Software and Measurement Analysis (ISMA) forums.