Mar 26, 2025
Damian Szewczyk
7 minutesTo successfully embrace DevOps and unlock its full potential, organisations must see it not merely as a methodology but as an ongoing journey of improvement. Achieving full DevOps maturity rarely happens overnight. Instead, teams typically advance through different levels, each bringing greater efficiency, automation, and collaboration. Progressing towards the highest level requires a clear understanding of the company’s current state and a strategic approach to refining processes.
This article explores the five levels of DevOps maturity, outlining the essential tools and practices at each stage while highlighting common pitfalls to avoid.
The journey from fundamental DevOps adoption to full automation is known as the DevOps Maturity Model. The Maturity Model is a framework that encompasses 5 phases and requires a structured and strategic approach to reach phase 5.
Before teams establish powerful communication and effective continuous deployment of their software, they have to start with the gradual adoption of current DevOps practices. The process begins with assessing the organisation’s current maturity level to identify its capabilities, limitations, and areas for improvement. This process of measuring DevOps maturity in the company can bring valuable insights.
From there, the focus should be on implementing the right tools and best practices suited to each stage of development. Along the way, businesses must tackle common obstacles such as cultural resistance, inconsistent automation, and lack of visibility. Overcoming these challenges is crucial for the smooth and effective transition towards full DevOps maturity, unlocking greater efficiency, collaboration, and innovation.
Level 1 of DevOps maturity, known as the Initial or Ad Hoc DevOps stage, is where companies have yet to adopt DevOps and establish a structured framework. Software development and operations teams continue to work in silos, as seen in traditional IT setups. Automation is minimal, with most deployment and testing processes still handled manually, leading to inefficiencies and slow progress.
At this stage, organisations often struggle with slow software delivery, frequent deployment failures, and poor coordination due to a lack of effective communication and collaboration between teams. These challenges create bottlenecks that hinder innovation and agility, making it difficult to meet evolving business demands.
Progressing to the next stage requires basic DevOps implementation. To start their DevOps journey, companies should place a key focus on teamwork between development and operations teams. Implementing foundational tools such as Jenkins for basic CI/CD automation, Git for version control, and Slack for real-time cross-team communication can help organisations build a more structured and efficient DevOps environment.
DevOps maturity Level 2, known as the Managed stage, is defined by the introduction of fundamental automation. Focusing on communication is gradually becoming a natural part of the culture. At this point, teams typically use continuous integration and delivery (CI/CD) pipelines to automate builds and tests and may have partially adopted version control systems like Git. However, manual interventions are still common, preventing using the full potential of DevOps.
During this phase, teams often struggle with limited visibility into deployment status, making it difficult to track and troubleshoot issues effectively. Since automation is still in its early stages, many essential workflows remain inconsistent, and the reliance on manual approvals increases the risk of failures and delays. Further fostering the culture of collaboration and communication is crucial to progress to the next stages of DevOps maturity.
To move forward, teams should focus on expanding CI/CD automation and minimising manual processes. This is the ideal stage to optimise their software and introduce Infrastructure as Code (IaC) tools like Terraform to manage infrastructure efficiently. Additionally, incorporating Nagios for basic monitoring and leveraging GitHub Actions or CircleCI can help streamline testing and deployments, achieving a smoother and more reliable workflow.
Level 3, known as Defined or Standardised DevOps, marks a significant step towards DevOps maturity. At this stage, organisations have well-defined and standardised practices. They leverage fully automated CI/CD pipelines, adopted Infrastructure as Code (IaC) tools for programmatic infrastructure management, and unified the monitoring, logging, and deployment tools and processes. Around this phase, DevOps are also likely to start the adoption of Kubernetes.
These advancements help teams release software faster and more reliably, with fewer errors and failures, while also fostering stronger collaboration between development and operations.
Although Level 3 teams are already enjoying significant improvements, they can further optimise their DevOps practices by extending automation across all areas, including testing, security, and infrastructure. To progress, companies should integrate configuration management tools like Ansible and Puppet, ensuring consistency across environments. Additionally, establishing a unified DevOps culture across all teams is crucial for sustaining long-term efficiency and innovation.
Phase 4, known as Measured or Data-Driven DevOps, represents teams that have established effective observability and monitoring practices while also automating security testing. A key advancement at this stage is the shift to data-driven decision-making for deployments and performance optimisation.
These improvements due to the embracement of more benefits of DevOps ensure greater consistency in software deliveries, strengthen software resilience against attacks, improve compliance, and help proactively detect and resolve issues, further boosting system stability.
After reaching a high level of maturity, Level 4 teams can still refine their DevOps practices by leveraging even more advanced tools.
Security automation can be extended beyond continuous testing to include compliance checks and policy enforcement using tools like Checkov, following the Policy as Code approach. AI-driven insights can further optimise capacity planning and performance, with tools like Prometheus and Grafana, while Google’s Four Keys platform helps track DORA metrics to enhance software delivery performance.
Level 5 or the Optimised DevOps stage represents the pinnacle of DevOps maturity, where AI/ML-driven automation significantly boosts efficiency through predictive scaling and anomaly detection.
Tools like Datadog’s Machine Learning and AWS Forecast predict infrastructure requirements, while self-service DevOps platforms such as Spinnaker and ArgoCD empower developers to manage deployments autonomously.
Continuous experimentation and feedback loops foster ongoing improvements, with security shifting left via proactive vulnerability scanning tools like Snyk.
Service meshes like Istio streamline the management of microservices, ensuring scalability, reliability, and smooth operations at the enterprise level.
The mature phase of the complex DevOps journey delivers substantial benefits. By refining their toolkit and constructing a scalable, secure, and resilient infrastructure, DevOps teams achieve maximum efficiency with minimal manual intervention. This not only boosts developer productivity but also fosters innovation and allows room for growth.
At the highest level of DevOps maturity, maintaining excellence becomes crucial. This involves embracing emerging tools and trends while fostering a culture of continuous learning.
However, DevOps teams must be discerning about which innovations to adopt. Not all trendy modern tools and technologies live up to their promises, and some may result in wasted resources or introduce security vulnerabilities.
As automation increases, teams should avoid over-relying on NoOps and continue to prioritise operational expertise.
Moreover, DevOps should be mindful of potential trade-offs when accelerating production and deployment. For instance, while speed is critical, maintaining thorough documentation may become more difficult but remains essential.
To reach full DevOps maturity, teams should first identify the areas of improvement in their work, and evaluate their current state of software development and delivery processes to build a strong foundation based on agile methodologies and the DevOps framework. The transformation journey of establishing and enhancing DevOps processes will require a lot of effort, but the benefits of turning into successful DevOps are worth the hard work.
Progressing to the highest level of the model has a profound impact on organisations, as it unlocks the full potential of DevOps principles for maximum efficiency, innovation, and productivity. With the adoption of AI-driven automation and predictive scaling, mature DevOps can perform their work efficiently with minimal manual intervention, achieving faster delivery cycles. At this stage, the system has significantly higher reliability and ability to scale operations. However, achieving this level of maturity is just the beginning.
To sustain continuous improvement, enterprises should consider adopting emerging tools and technologies that align with their goals. It is crucial to foster a culture of continuous learning and experimentation, ensuring that teams remain adaptable and capable of tackling newly emerging challenges. While automation is essential, relying too much on NoOps should be avoided. DevOps still requires both development and operational expertise, regardless of the level of automation.
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