How to Build a DevOps Implementation Plan in 9 Simple Steps

As a business owner, how often do you question the speed and efficiency of your software development process? Why does it seem like updates take so long to release, even when they’re simple? How can you ship software faster and with fewer bugs while optimizing resources for smoother app development? If these questions have ever crossed your mind, then it’s time to explore a DevOps implementation plan.

DevOps is getting more recognition among companies, and that’s how it looks: the global DevOps market is projected to reach USD 81.1 billion by 2033, with a 19.95% CAGR from 2025 to 2033. By 2027, Gartner predicts that 80% of organizations will integrate DevOps platforms into their development toolchains, up from just 25% in 2023, which means industries will adopt these practices at an increasing rate.

Business owners also reap some benefits of DevOps implementation. According to a Google Cloud report, “the top performers” (the teams that have fully adopted DevOps practices) achieve results far beyond those of the teams that rely heavily on manual processes. The top DevOps teams:

• deploy code 973x more frequently than their lower-performing counterparts,
• achieve 6,570x faster lead times from commit to deploy.

Before diving into DevOps, it’s crucial to take a step back and craft a clear plan. It helps avoid unnecessary spending and cluttered processes, which often happen due to incorrect DevOps adoption. In this article, we’ll explore a structured DevOps implementation plan, outlining the key steps involved, best practices, and the benefits of adopting DevOps for your organization. 

What Is DevOps?

DevOps is a set of practices that unifies development and operations to shorten development cycles and improve the quality of software through automation and collaboration. 

Let’s take a look at key elements of DevOps:

• Automation: Instead of relying on people to repeat the same steps, like running tests, packaging code, and deploying builds, these tasks can be handled by scripts and tools. That’s how teams can avoid errors that would normally creep in during manual work.
• Collaboration: In a traditional workflow, developers write code, then hand it off to operations, and problems often surface too late. DevOps changes this dynamic, since developers and operations staff work together from the start and are on the same page in terms of goals and responsibilities. A developer might define server configurations as code, while operations engineers add monitoring hooks or reliability checks.
• Continuous Integration and Continuous Delivery/Deployment (CI/CD): Continuous Integration means code changes are merged into a central repository, and they trigger tests right away to detect any defects at early stages. Continuous Delivery prepares builds for automatic release. Thus, businesses get frequent updates, quicker user feedback, and higher software quality.
  

What DevOps Is Not

Some may think that DevOps is simply a collection of tools, when in reality it is a cultural approach with specific practices. Now, let’s clear up some common misunderstandings about DevOps: 

• DevOps is not just about tools: Tools by themselves do not change how developers and operations interact, nor do they improve collaboration or shorten release cycles. Docker may simplify container management and Jenkins may automate the build process, but without a cultural shift, those gains remain fragmented and fail to transform the way the entire pipeline operates.
• DevOps is not a one-time initiative: In practice, it represents an ongoing, long-term transformation of how teams think, communicate, and share responsibility. For example, both groups (dev and ops teams) stay involved from the start. Developers define application requirements and infrastructure as code. At the same time, operations staff set up monitoring, scaling rules, and deployment pipelines, so the entire system evolves as a shared effort rather than a chain of disconnected tasks.
• DevOps is not a silver bullet: DevOps doesn’t automatically fix problems like slow release cycles or poor-quality code. It’s a way to address these issues, but only if you commit to continuous improvement, collaboration, and a clear focus on automation.

7 Core DevOps Benefits For Your Business

Accelerated time-to-market

To increase delivery speed and reduce time-to-market, companies should implement DevOps wisely. But why? The reason lies in automation and CI/CD pipelines: you don’t need to wait for manual testing or approvals; every code commit triggers automated builds, test runs, and deployments. This means that features reach production faster, feedback loops shorten, and companies can respond to market demands in weeks or even days.

Reduced development costs and increased ROI

If you implement DevOps, you can save money on development. With Infrastructure as Code and automated pipelines, companies eliminate costly configuration errors and streamline workflows. This reduces both expenses and inefficiencies across development and operations. Moreover, organizations see 30% lower software licensing costs per employee, translating to $8.7 million in total benefits. By cutting shadow IT and retiring redundant tools, DevOps keeps things lean. In addition, companies experienced a 358% ROI over three years, proving that DevOps is the right ally for your market stand.

More frequent deployments

Continuous integration ensures that every change is validated early, while continuous delivery prepares production-ready builds automatically. In practice, this makes daily or even hourly releases possible. Instead of saving up changes for a risky “big bang” deployment, teams ship in smaller, safer batches, which lowers risk and accelerates innovation. This results in 182 times more software deployments after companies adopt DevOps.

Enhanced system reliability

DevOps practices like Infrastructure as Code ensure environments stay consistent across dev, test, and production. You can see it works like: monitoring and alerting tools give insights into problems, and if something goes wrong, rollback mechanisms or canary releases let teams revert quickly. Together, these practices build resilience into the pipeline and help companies achieve 8 times lower change failure rates, so that deployments are far less likely to fail.

Increased software quality

This benefit can be attributed to automated tests that run on every commit, monitoring systems that alert developers in real time, and deployment strategies such as canary or blue-green releases that isolate faulty code before it affects all users. Together, these practices raise overall reliability and ensure higher-quality software reaches customers. 

Increased productivity

You can boost your team’s productivity if you automate repetitive tasks. Automated builds, deployments, and infrastructure provisioning free teams from manual work. Therefore, developers spend more time writing code that adds value, and operations teams focus on scaling and reliability instead of firefighting.

More secure software

DevSecOps embeds checks into the CI/CD pipeline, enabling automatic code scans, compliance policies to apply before deployment, and container images to be validated against known risks. This proactive stance helps detect vulnerabilities early, when fixes are cheap and easy, instead of after an attack, when you face the consequences of damage.

9 Simple Steps For Your DevOps Implementation Plan

With our DevOps services, you can get a DevOps implementation plan that works. From CI/CD pipeline automation and Infrastructure as Code (IaC) to containerization, monitoring, and DevSecOps integration, our team ensures faster releases, higher system reliability, and lower development costs.

The DevOps implementation roadmap below is the same structured approach our specialists use when working with clients who need to implement DevOps. It shows how to build DevOps from scratch, step by step, highlighting common challenges and the outcomes you can expect.

Step 1: Assess your current SDLC

The first step in any DevOps implementation plan is to take a hard look at your current software development lifecycle (SDLC). For this, you need to perform a number of activities:

• Identify all SDLC stages such as coding, testing, release, and maintenance. 
• Evaluate and note down your tools, frameworks, and methods in place (Agile, Waterfall, hybrid). 
• Identify all stakeholders involved in each stage, for example, developers, QA, operations, and product owners. 
• Assess each phase and keep in mind the following questions:
  • Are requirements clear and tracked? 
  • Are version control and code reviews in place? 
  • Is testing automated and integrated into CI/CD? 
  • Is deployment repeatable and automated? 
  • How are incidents monitored and resolved?

Without this baseline, it’s impossible to get the benefits of DevOps implementation later. Our specialists can help you perform all these activities, so you don’t need to tackle them all by yourself.

Step 2: Measure KPIs and define improvement targets

After evaluating your current SDLC, time to pay attention to the KPI. Here, you need to measure the following metrics:

• Deployment frequency (how often new code is released).
• Lead time (time from commit to production).
• Change failure rate (how often deployments fail).
• Mean Time to Recovery (MTTR) after incidents.

Based on the gathered KPI: 

• Set measurable targets that you want to achieve with DevOps, for example, “Reduce lead time by 50% in 6 months” or “Increase deployment frequency by 30% within 3 months.” 
• Ensure targets support your overall business goals, like faster delivery or reduced costs.

Step 3: Build DevOps culture

Create an environment where development and operations work together towards shared goals. Collaboration is key, and culture is where it all starts. 

To complete this step: 

• Assign developers and operations to work on the same product backlog. 
• Set joint performance goals, as both teams should be responsible for uptime, release speed, and customer satisfaction. 
• Run regular retrospectives, which means you need to review issues, identify improvements, and continuously align the teams on shared objectives. 
• Get leadership buy-in and ensure executives back the transformation by providing resources and authority.

Step 4: Shift security left

Security must move into the early stages of development, not wait until production. Shifting security left means that you integrate checks and controls directly into the pipeline, so vulnerabilities are found and fixed before release.

For this step, you need to: 

• Add static application security testing (SAST) to the CI pipeline to flag insecure code at commit. 
• Use dependency and container scanners to catch known vulnerabilities before deployment. 
• Automate compliance policies, so every build enforces security standards by default.
• Manage secrets with HashiCorp Vault, AWS Secrets Manager, or similar tools, but never in code. 
• Provide developers with secure coding guidelines and training to reduce recurring flaws.

Step 5: Choose DevOps tools

Select the tools that will support your DevOps goals. Make sure they integrate with each other and scale with your needs.

At this stage: 

• Assess tool requirements based on your KPIs and improvement targets, choose the right tools for CI/CD, Infrastructure as Code (IaC), monitoring, and security. 
• Make sure the same tools are used across teams to avoid fragmentation (e.g., Jenkins, Docker, Prometheus). 
• Decide whether you will adopt a cloud-first approach or a hybrid model, depending on your current infrastructure and goals.

Step 6: Implement CI/CD

A CI/CD pipeline automates the process of integrating code, running tests, and deploying updates. This speeds up releases and reduces manual errors. 

To set up an effective CI/CD pipeline: 

• Select a tool, for example, Jenkins, GitLab CI, or GitHub Actions based on your needs and current toolset. 
• Ensure unit, integration, and functional tests run automatically whenever code is committed. 
• Define deployment strategies with methods like canary releases or blue-green deployments to reduce risk and roll out changes gradually. 
• Automate infrastructure provisioning with Terraform to ensure environments are consistent, from development to production.

Step 7: Adopt Infrastructure as Code (IaC)

To make environments consistent and scalable, replace manual setup with Infrastructure as Code. This ensures servers, networks, and configurations are defined in code, making them repeatable and easier to manage. 

Here’s what you need to do:

• Pick one IaC toolset (e.g., Terraform, AWS CloudFormation, or Pulumi) and standardize it across all teams.
• Store all infrastructure code in version control so changes can be tracked, reviewed, and rolled back when needed.
• Establish review policies for infrastructure code, just like application code, to avoid security or stability risks.
• Automate environment provisioning to ensure dev, test, and production stay identical.
• Test infrastructure definitions before rollout to catch errors early and prevent misconfigurations from spreading.

Step 8: Use containerization and orchestration

Containerization and orchestration help you eliminate environment inconsistencies and scale applications without adding operational overhead.

The actions to take:

• Standardize application packaging with Docker, creating identical container images for every environment.
• Deploy Kubernetes clusters to manage containers automatically, handling scaling, failover, and service discovery.
• Write deployment manifests (YAML files) and store them in version control for transparency and rollback.
• Integrate Kubernetes with your CI/CD pipeline, so new container images are deployed automatically once tests pass.

This step ensures applications run consistently across dev, test, and production, so that you can scale on demand.

Step 9: Set up monitoring and logging

Monitor the performance and health of your systems in real-time. This ensures you catch issues before they impact customers.

You need to:

• Use Prometheus for metrics collection and Grafana for visualizing data.
• Use Elasticsearch, Logstash, and Kibana to aggregate logs and make them searchable.
• Set up alerts to ensure you receive instant notifications for performance degradation or failures.
  

Thus, if your team needs expert support in implementing DevOps, our DevOps consultants can guide you through all the steps above.

Treat DevOps as a Business Transformation

In every DevOps transformation I’ve managed, the companies that succeed are the ones that measure from the start and standardize as they scale. The first step is always to gather data, such as deployment frequency, lead time, rollback rates, because without hard numbers, you cannot prove progress or identify the real pain points.

Culture comes next, and it only works when development and operations share the same goals. If one team focuses on features shipped and the other on system stability, conflicts never stop. The moment both groups answer for uptime, release speed, and recovery time, collaboration finally takes root.

The real challenge after that is strategy. Tool sprawl is the silent killer of many initiatives, and nothing slows progress like ten teams on ten different platforms. Pick your stack for CI/CD, monitoring, and Infrastructure as Code, and stick to it. Once that foundation is in place, automation delivers real wins, as pipelines cut release times, IaC keeps environments consistent, and Kubernetes handles scaling. But remember: automate bad practices, and you don’t get faster progress, you just make mistakes at the speed of light.

Finally, keep security and improvement at the core. Add security checks to the pipeline so vulnerabilities never slip through, and review KPIs regularly to confirm DevOps is still paying off. Companies that treat these as non-negotiable build a lasting operating model; companies that don’t end up another failed experiment.

Senior DevOps engineer at SoftTeco

Arsen Atoyan

Core DevOps Tools to Consider

CI/CD pipeline automation

For continuous integration and continuous delivery, the most common tools are Jenkins, GitLab CI, and GitHub Actions.

• Jenkins automation gives maximum flexibility with thousands of plugins, though it requires more setup and maintenance.
• GitLab CI integrates code repositories, pipelines, and issue tracking in one platform, which simplifies implementing DevOps across teams.
• GitHub Actions works best if your code already lives in GitHub, offering reusable workflows and marketplace extensions.

Infrastructure as Code (IaC)

Defining infrastructure in code is key to developing a DevOps process from scratch. IaC lets teams define infrastructure in code instead of relying on manual setup. Servers, networks, and cloud resources are created the same way every time, which removes configuration drift and speeds up provisioning. So, IaC reduces errors, supports reproducibility, and enables scaling in minutes.

Popular IaC tools:

• Terraform ensures cloud-agnostic provisioning across AWS, Azure, Google Cloud, and other providers, helps teams keep infrastructure reproducible, and reduces drift or manual errors.
• AWS CloudFormation is a Native AWS option that automates infrastructure, tightly integrated with all AWS services. It’s reliable for teams that run on Amazon’s cloud.
• Pulumi lets developers write infrastructure definitions in familiar languages like Python, TypeScript, or Go.
• Google Cloud Deployment Manager is an IaC tool for managing Google Cloud resources.
• Azure Resource Manager (ARM) templates help automate provisioning and management of Azure environments.

Configuration management

Configuration management keeps systems consistent after they’ve been provisioned. It automates updates, patching, and software deployment across environments, which lets you reduce manual overhead and avoid drift.

Take a look at the popular configuration management tools:

• Ansible offers an agentless, lightweight setup with human-readable YAML playbooks and helps automate configuration management, patching, and software deployment.
• Chef ensures compliance through policy-driven automation and offers stability for enterprises with large, long-running server environments.
• Puppet enforces a consistent infrastructure state across all systems and offers detailed reporting and strong integration with enterprise environments
• SaltStack scales fast, supports event-driven automation, and works well for real-time configuration.

Containerization and orchestration

For any DevOps implementation strategy, Docker and Kubernetes are must-have tools. Here’s how they work:

• Docker packages applications and dependencies into portable, lightweight containers and ensures consistent environments across development, testing, and production.
• Kubernetes orchestrates containers at scale with automated scaling, failover, and service discovery. This tool is essential for managing microservices architectures and reducing deployment risks.

Monitoring and logging

Continuous monitoring and centralized logging tools detect issues before users notice, which directly supports faster recovery and higher system reliability.

Let’s break down their use cases:

• Prometheus collects real-time metrics like CPU, memory, and latency and integrates with alerting systems to notify teams of performance issues early.
• Grafana builds interactive dashboards that visualize data from multiple sources and helps developers and operations teams track application health at a glance.
• ELK Stack (Elasticsearch, Logstash, Kibana) centralizes logs from all services, making them easy to search and analyze. You’ll need it for debugging, incident response, and compliance reporting.

Cloud-native platforms

For organizations that move to the cloud, end-to-end toolchains from major providers help implement DevOps practices:

• Azure DevOps is a platform that includes Pipelines for CI/CD, Repos for version control, Boards for project tracking, and Artifacts for package management.
• AWS DevOps toolchain provides a set of tools that cover the main practices:
  • AWS CodePipeline for CI/CD pipeline automation
  • AWS CodeBuild for build and test automation
  • Amazon CloudWatch for monitoring and logging
• Google Cloud DevOps toolchain offers services that together enable DevOps workflows:
  • Cloud Build, which is CI/CD for building and testing code
  • Cloud Deploy for automated application delivery
  • Operations Suite (formerly Stackdriver) for monitoring, logging, and incident response

DevOps vs. Traditional IT Operations

Many companies still run IT the traditional way, with development and operations working in silos. This approach often creates bottlenecks: developers write code, pass it along, and move on. Operations deploy and maintain systems, often without context on how the code was built. This split creates friction, and releases move slowly, issues bounce between teams, and customers wait longer for fixes. 

But DevOps removes this wall. The table below shows how the two approaches differ in practice:

Final thoughts

At its core, DevOps is not a single tool or a one-time initiative, it is a disciplined operating model. The organizations that succeed with DevOps are the ones that treat it as a business transformation: they measure results, standardize processes, automate with intent, and integrate security at every stage.

The DevOps implementation roadmap you’ve just read about provides a practical framework to move from theory to execution, and these steps are the foundation for sustainable performance. 

Thus, business leaders should remember one rule: automation amplifies both strengths and weaknesses. When processes are clear and measured, automation accelerates value creation. When they are fragmented, automation accelerates inefficiency. The right KPIs, like deployment frequency, lead time, mean time to recovery, and change failure rate, ensure you track real outcomes and protect ROI.