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DevOps Maturity Model : Levels, Metrics & Benefits

devops maturity model

With the adoption of modern DevOps practices, organizations are looking for ways to enhance and optimize their software development and delivery processes. To start their DevOps journey, they often turn to a DevOps maturity model to evaluate their current state and foster a continuous improvement culture. 

But what exactly is a DevOps maturity model, and how can it benefit your organization? In this blog post, we’ll delve into the details of DevOps maturity models, explore their levels, and discuss how to measure and implement them effectively.

What we will cover:

  1. What is a DevOps maturity model?
  2. What are the five levels of DevOps maturity?
  3. How to measure DevOps maturity?
  4. Benefits of a DevOps maturity model
  5. How to implement a DevOps maturity model?

What is a DevOps maturity model?

A DevOps maturity model is a framework that helps organizations assess their current level of DevOps adoption and maturity. It allows them to determine how far along they are in their DevOps implementations and benchmark themselves against the best. 

Moreover, it provides a structured path for improvement, empowering teams to navigate through various stages of DevOps implementation by examining the metrics and data points that matter. Understanding DevOps adoption and improvement as a continuous journey, not a destination, is crucial to achieving an organization’s higher levels of DevOps maturity.

By evaluating processes, tools, culture, and automation, organizations can identify areas that need enhancement and develop strategies to advance their DevOps practices. The goal is to achieve higher efficiency, faster delivery, and better collaboration between development and operations teams.

What are the five levels of DevOps maturity?

A DevOps maturity model typically consists of multiple levels, representing incremental stages of DevOps maturity for organizations. The number and naming of levels might vary, but the methodology and general idea stay the same. 

Typically the five DevOps maturity levels include:

  1. Initial
  2. Managed
  3. Defines
  4. Measured
  5. Optimized
DevOps maturity levels

Level 1. Initial

At this stage, DevOps practices are sporadic and unstructured. This model is found in organizations that still operate with old-school processes. 

There is little or no collaboration between development and operations teams, they operate in silos, and methods are mainly manual. This was a standard model in the early 2000s, but organizations are increasingly moving away from this stage.

Level 2. Managed

Organizations at this level have started to adopt DevOps practices in a more organized manner. There is some degree of automation, and teams begin to collaborate, though inconsistently. 

Teams have started to adopt Agile methodologies, but there are no well-defined DevOps practices across the organization. Automation initiatives are based on individuals and best-effort approaches.

Level 3. Defined

DevOps processes are well-defined and standardized across the organization. Automation is becoming the norm, and team collaboration is more consistent and effective. DevOps teams are established, and processes and tools for monitoring and automation are in place.

Level 4. Measured

At this stage, after DevOps processes have been set, organizations actively measure the performance of their DevOps practices. Metrics and KPIs are used to identify areas of improvement, and there is a focus on continuous feedback and optimization. 

Although many DevOps principles have been implemented during this stage, organizations start to realize that they still have far to go to achieve optimal operational benefits.

Level 5. Optimized

Optimized is the highest level of DevOps maturity. Organizations have fully integrated DevOps practices with extensive automation, continuous monitoring, and a culture of constant improvement. 

Development and operations teams work together seamlessly, and processes are highly efficient. When inefficiencies or issues arise, teams have all the information they need and are empowered to quickly change processes, tools, and practices. 

How to measure DevOps maturity?

Measuring DevOps maturity involves evaluating various aspects of your organization’s DevOps practices. The best approach is to use a mix of data-driven metrics and employee anecdotal evidence to measure an organization’s holistic DevOps maturity.

How to measure DevOps Maturity

Metrics and KPIs

Use relevant metrics and KPIs to track performance, assess your stage, and validate progression. At the early stages, track metrics such as:

  • Deployment frequency
  • Lead time
  • Mean time to recovery (MTTR)
  • Mean Time to Failure (MTTF)
  • Change failure rate
  • Developer throughput

As you move to more advanced stages of DevOps maturity, look into more specific metrics such as mean time to resolve pull requests, the proportion of time tickets spent in an ‘active’ versus ‘inactive’ status, and mean time for failed builds. 

Processes and automation

Assess the standardization and efficiency of your development and operations processes. Evaluate the extent of automation in your continuous integration and continuous deployment (CI/CD) pipelines, testing, and deployment. Most metrics that a DevOps maturity model focuses on relate to automation and processes. 

Automating repetitive tasks gives developers more free time to focus on delivering value and innovation. Processes must be standardized and efficient in a well-structured and mature DevOps environment. As well as examining pre-defined metrics and KPIs, you should also conduct user interviews to assess users’ experiences with organizational processes.

Collaboration and culture

You should also track and measure the level of collaboration and communication between technical teams. Consider cultural aspects, such as adopting a DevOps mindset and the level of collaboration and trust within teams. 

Collaboration is a critical aspect of a successful DevOps model, and teams that can work together seamlessly fare better at streamlining their processes and innovating. Unity and teamwork are the backbone of a successful DevOps model.

Read more: Improving DevOps Collaboration: Best Practices & Tips

Benefits of a DevOps maturity model

Implementing a DevOps maturity model offers several benefits.

Continuous improvement and increased efficiency
  • Primarily, it provides a clear path for continuous improvement and optimization of DevOps practices. 
  • It helps identify inefficiencies and areas for automation, leading to faster and more reliable software delivery. 
  • It also guides organizations in developing a strategic roadmap for DevOps implementation and maturity.
Enhanced collaboration Following a well-executed and carefully planned DevOps maturity model fosters close collaboration between dev and ops teams.

As organizations attempt to improve their maturity, team collaboration and communication grow and become fluid.

Better performance measurement A DevOps maturity model allows organizations to track and measure the performance of their DevOps practices, making it easier to identify areas for improvement. 

Having metrics, goals, and success criteria upfront aligns the technical team to a common target.

How to implement a DevOps maturity model?

To implement a DevOps maturity model, follow these steps.

  1. Assess current state.
  2. Define goals and success criteria.
  3. Develop a roadmap to progress to the next stages.
  4. Implement changes and measure progress.
  5. Foster a DevOps and collaboration culture.

1. DevOps maturity assessment

Before you define a model and levels, conduct a thorough assessment of your current DevOps practices, identifying strengths and weaknesses. Document the current state of things and define aspirations.

For example, let’s look at automation, culture, and value stream metrics:

Category Metrics Maturity stages
Automation (CI/CD & infrastructure as code)
  • Deployment frequency: How often code is deployed to production.
  • Mean lead time for changes: Time it takes from code commit to deployment in production.
  • Build and test automation: Percentage of the build and testing processes automated.
  • Automated environment provisioning: Use of Infrastructure as Code (IaC) for automatic provisioning and configuration.
  • Pipeline failure recovery time: Time taken to resolve issues in CI/CD pipelines.
Initial: Manual processes for deployment and testing.

Managed: Partial automation of CI/CD and environment provisioning.

Optimized: Fully automated pipelines, IaC in place.

Culture & collaboration
  • Cross-functional collaboration: Degree of collaboration between development, operations, and other teams (e.g., security, QA).
  • Communication frequency: Use of collaboration tools (e.g., Slack, MS Teams) and frequency of interactions.
  • Feedback loops: How well feedback is integrated from stakeholders (e.g., customers, operations, and other teams).
  • Blame-free environment: Ability to foster a culture where failures are learning opportunities.
Initial: Siloed teams, limited collaboration.

Managed: Periodic collaboration, still role-defined boundaries.

Optimized: Fully collaborative, integrated feedback loops.

Value stream metrics (Business impact)
  • Cycle time: Time taken from idea inception to delivery of business value.
  • Customer feedback frequency: Frequency of collecting feedback from end-users.
  • Business alignment: How well development outcomes are aligned with business goals.
  • Customer satisfaction (CSAT/NPS): Measures of customer happiness with the product.
Initial: Poor alignment between business and development.

Managed: Periodic alignment and feedback collection.

Optimized: Continuous alignment, frequent feedback, and iterative development based on feedback.

2. Define goals and success criteria

Next, establish clear goals. Set up different maturity model levels according to your organization’s needs and precise criteria for reaching each subsequent level.

Score each category (such as automation, security, or collaboration) on a scale of 1–5. To calculate the total score, add the scores and divide by the number of categories to get an average score for overall maturity.

3. Develop a roadmap to progress to the next stages

With a solid understanding of the current situation and the desired outcome, continue by creating a detailed roadmap outlining the steps needed to advance through the maturity levels and the changes necessary to get there. Craft a detailed roadmap to guide you on this process.

4. Implement changes and measure progress

Starting from your current state, implement changes incrementally, focusing on areas with the most significant impact. Continuously measure your progress using relevant metrics and adjust your strategies as needed. Celebrate small wins to keep morale high and provide the teams with a sense of continuous improvement.

5. Foster a DevOps and collaboration culture

Throughout the process, it’s crucial to promote a culture of collaboration, continuous learning and growth, and shared responsibility within your organization. This DevOps culture will guide you as you progress.

How can Spacelift help?

Spacelift is an infrastructure orchestration platform that increases your infrastructure deployment speed without sacrificing control. With Spacelift, you can provision, configure, and govern with one or more automated workflows that orchestrate Terraform, OpenTofu, Terragrunt, Pulumi, CloudFormation, Ansible, and Kubernetes. 

You don’t need to define all the prerequisite steps for installing and configuring the infrastructure tool you are using, nor the deployment and security steps, as they are all available in the default workflow.

With Spacelift, you get:

  • Policies to control what kind of resources engineers can create, what parameters they can have, how many approvals you need for a run, what kind of task you execute, what happens when a pull request is open, and where to send your notifications
  • Stack dependencies to build multi-infrastructure automation workflows with dependencies, having the ability to build a workflow that, for example, generates your ec2 instances using Terraform and combines it with Ansible to configure them
  • Self-service infrastructure via Blueprints, or Spacelift’s Kubernetes operator, enabling your developers to do what matters – developing application code while not sacrificing control
  • Creature comforts such as contexts (reusable containers for your environment variables, files, and hooks), and the ability to run arbitrary code
  • Drift detection and optional remediation

Spacelift was built with DevOps/platform engineers in mind, but it developed to become the go-to platform for software engineers, too, because they can increase their velocity with self-service infrastructure that implements all your organization’s guardrails. It greatly enhances collaboration among engineers, offering them a central location to make infrastructure-related decisions.

If you want to learn more about what you can do with Spacelift, check out this article.

Key points

In this blog post, we analyzed a DevOps maturity model for assessing and improving DevOps practices. We reviewed the framework’s typical maturity levels, each representing a stage of DevOps adoption. 

We discussed measuring DevOps maturity, including processes, automation, collaboration, metrics, and culture. Finally, we looked at a high-level plan and the benefits of implementing a DevOps maturity model according to your organization’s needs.

If you are interested in a product that can orchestrate provisioning, configuration, and governance, across your infrastructure, Spacelift is the answer. Create a free account with Spacelift today, or book a demo with one of our engineers.

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