Understanding your current DevOps maturity stage, which can be anywhere from on-prem/manual to AI-augmented, is a crucial step towards upgrading your IT infrastructure.
In this article, we also cover actionable steps to level up your cloud-based DevOps using DuploCloud’s automation platform and AI Help Desk.
Key Takeaways
- DevOps maturity follows an upward path. It goes from stage 1 (Manual, On-Site) to Stage 4 (AI-powered operations).
- To move from one stage to the next, you must know your current stage. It's best to move slowly through each stage. Don't try to make jumps that are too big.
- The gap between stages 1 and 4 is huge. Think of it like traveling from New York to Paris. Stage 1 is like sailing on an 18th-century ship. Stage 4 is like flying first class in a modern private jet.
Why DevOps Maturity Matters with Complex Infrastructure
Today's technology keeps changing faster than ever. This is why Infrastructure as Code (IaC) is becoming so popular. But even IaC isn't perfect. Organizations using it need more help than they think.
With technology infrastructure, what worked five years ago might now slow your organization down.
Infrastructure includes many things. It covers container systems and serverless computing. It also includes multi-cloud strategies and AI-driven operations. Managing infrastructure is too complex for just one or two IT team members.
DevOps maturity means improving your processes, culture, and technology step by step. The goal is to deliver value faster with better security and reliability. It's not just about using the latest tech trends and hoping they help IT work better.
IT teams that can't move forward on the maturity curve face problems:
- They get stuck doing too much manual work
- They struggle with too much technical debt
- They watch more agile competitors gain advantages
If you're a CIO or CTO, you need to know where you are on this journey. You also need a clear plan for moving forward. This helps you build infrastructure that helps business growth instead of limiting it.
Here are the four most common stages of DevOps maturity. Can you figure out where your organization fits?
The 4 stages of DevOps maturity
Stage 1: Manual, or On-Site (On-prem)
At this stage, you have a traditional IT setup. There's very little automation. Failure rates are high. Teams don't understand or use agile DevOps methods much. Here are the most common traits:
- Infrastructure gets managed through manual processes and internal knowledge. There's limited documentation, standard procedures, and measurements.
- Teams rely too much on physical, on-site servers. They use very little cloud-based storage.
- New software or hardware updates happen rarely. They're high-risk and often cause problems. Leaders prefer to leave things alone. ("If it ain't broke, don't fix it" is common thinking, even when it holds the whole organization back).
- IT team members focus on narrow areas. There's limited teamwork or knowledge sharing across functions.
Because of this, IT teams face these main problems:
- Slow time-to-market: New features and fixes take weeks or months to deploy. They often fail or don't work as planned.
- High error rates: Manual processes create inconsistent environments and frequent outages. Even worse, they create unrealized cybersecurity risks and breaches.
- Scalability bottlenecks: Adding capacity requires major planning and manual work. It's hard to implement.
- Compliance challenges: Following security and regulatory rules takes too much time. It gets done imperfectly and can cause cybersecurity failures.
Why does automation matter?
At this stage, automation isn't just better - it's necessary for operations.
Organizations stuck with manual processes face rising operational costs and higher risks. For these reasons, organizations usually try to move from manual/on-site to the cloud. But they do it in one big piece.
Stage 2: Cloud monolith
At this stage, a leap forward has been made, and these are the most common characteristics:
- Infrastructure has been migrated to cloud providers (like Amazon Web Services (AWS), Google Cloud Partner (GCP), and Microsoft’s Azure), but it maintains legacy architectural patterns.
- Unfortunately, there’s still a limited use of cloud-native services and capabilities
- Deployments may be automated, but environments are still looked after as if they’re on-prem servers.
- Some use of configuration management tools, but with inconsistent implementation.
- Even at this stage, the good news is that you can benefit from fully automated cloud migrations with DupoCloud, with much more consistent and long-term results.
Advantages over Stage 1:
- Better hardware reliability (like 99.999% uptime, and much more secure). Maintenance costs almost disappear. They get replaced with flexible, cloud-based storage costs.
- Basic flexibility and pay-as-you-go cost models (perfect for app-based businesses).
- Cloud providers include better disaster recovery and cybersecurity features.
Main pain points:
- Infrastructure in a silo: Large, complex, monolithic applications don't use cloud advantages very well. This causes technical debt even after escaping on-site problems.
- Limited flexibility: Deployment cycles stay slow and risky. This happens because infrastructure still runs like it's on-site. Cloud technology isn't being used well.
- Cost optimization gaps: Without proper cloud-native design, costs can jump unexpectedly. This especially happens if app use increases.
Either out of necessity or through a dedicated digital transformation project, cloud monoliths can and will be replaced with Infrastructure as Code (IaC). This uses Terraform and Kubernetes.
Stage 3: Upgraded with Infrastructure as Code (IaC)
At this stage, infrastructure should be light years ahead of stage 1 and even 2. The characteristics are:
- Infrastructure managed using code-based tools like Terraform, AWS CloudFormation, or Pulumi.
- Containerization, microservices, and orchestration with Kubernetes or similar platforms
- Comprehensive CI/CD pipelines with automated testing and deployment
- Observability is just as integral within a mature DevOps tech stack, and you can gain this at this stage.
Advantages over Stage 2:
- Reproducible environments: Infrastructure can be consistently deployed across development, staging, and production. Much easier to manage.
- Version control: Infrastructure changes are tracked, reviewed, and can be rolled back (impossible in previous stages).
- Enhanced security: Security and regulatory policies can be implemented in code, and automatically enforced and monitored.
Beyond IaC is AI and machine learning (ML), augmenting and enhancing IaC operations and your entire infrastructure tech stack. AI solutions make it easier to accelerate your DevOps maturity curve.
Stage 4: AI/ML-Augmented IaC operations
The characteristics of this stage:
- Machine learning (ML) models predict and prevent infrastructure issues before they impact users and the business.
- Automated remediation handles common operational tasks without human intervention. DevOps automation makes everyone’s workload easier.
- AI-powered capacity planning and cost optimization.
- Intelligent security monitoring with automated threat response.
- Natural language interfaces for infrastructure management and troubleshooting.
AI-powered infrastructure operations with human expert oversight means:
- Predictive scaling: AI tools analyze usage patterns and automatically adjust resources before demand peaks.
- Anomaly detection: Unusual patterns are detected that might indicate security threats or performance issues.
- Intelligent alerting: AIs prioritize notifications based on business impact, security, and context, like the number of support tickets about a specific issue.
- Automated healing: AI systems automatically detect and remediate common issues without human intervention.
- Continuous optimization: AIs continuously analyze performance and cost metrics to suggest improvements.
Closing Thoughts: Assess Your Current Stage
Ready to accelerate your DevOps maturity journey?
The first step is understanding exactly where you are today. Once you’ve done that, you can create a customized roadmap for how to accelerate continued mature development.
Your infrastructure should enable innovation, not constrain it.
Organizations that proactively evolve their DevOps practices don't just improve their operational efficiency; they create sustainable competitive advantages that compound over time.
Assess your DevOps maturity stage: Book a maturity mapping session with DuploCloud.
Our DevOps infrastructure experts will:
- Conduct a comprehensive assessment of your current DevOps practices and infrastructure.
- Identify specific pain points and bottlenecks limiting your organization's agility;
- Create a customized advancement plan with clear milestones and success metrics.
- Demonstrate how DuploCloud's platform can accelerate your progression through each maturity stage, no matter where you’ve started from.
Don't let infrastructure complexity hold back your innovation. Schedule your maturity mapping session today and discover how to unlock your team's full potential.
DevOps Maturity Curve FAQs
How long does it typically take to advance from one maturity stage to the next?
DevOps maturity evolution timeline varies significantly based on organization size, existing tech stack, any technical debt, and available resources. However, with the right platform and approach:
- Manual to cloud monolith: 3-6 months for most applications
- Cloud monolith to IaC: 6-12 months for comprehensive modernization
- IaC to AI-augmented: 3-6 months for initial AI integration, with ongoing optimization and iterations.
DuploCloud's automation and templates can reduce these timelines by 40% to 60%, compared to building everything from scratch or attempting a transition manually.
Can we skip stages in the maturity curve?
It might be tempting to jump directly to advanced stages. However, each level builds critical foundational capabilities. Organizations that skip stages often face:
- Higher failure rates due to missing foundational practices;
- Increased technical debt that becomes expensive to resolve later.
- No buy-in or understanding from the C-suite of what the IT team is doing;
- Budget overruns and the potential for the whole project failing;
- Team knowledge gaps that limit long-term success;
However, with cutting-edge tech platforms like DuploCloud, this can help you progress through each stage more rapidly and cost-effectively, with fewer risks.
