Time to market for software companies is critical, especially with your competition fighting every step of the way to make sure they have the first-mover advantage for their product.

Recent reports show that companies that adopt DevOps report a significant reduction in time-to-market for their software and services. Specifically, 49% of companies noted a decrease in their software delivery times.

But simply implementing DevOps without a solid action plan and knowledge of DevOps' best practices won’t guarantee success. Like with anything, there are always unexpected pitfalls that can derail your plans.

So, in this guide, we’ll explore how you can navigate the challenges of implementing DevOps and the best practices you should follow to see the best results.

What is DevOps

DevOps represents a set of practices and cultural values that have been designed to enhance the software development process by fostering collaboration between the development and operations teams. DevOps came about to address the fundamental inefficiencies and dysfunctions between software development (Dev) and IT operations (Ops) teams that were common in the traditional waterfall development model.

The roots of DevOps trace back to the Agile methodology, which emerged in the early 2000s and began shifting the emphasis toward iterative development, regular feedback, and more fluid, cross-functional team structures. Agile practices highlighted the need for more collaboration and quicker iteration cycles, but they often did not extend beyond the development teams to include operations.

Older models and methodologies often led to siloed teams that worked independently, resulting in conflicts, slow production cycles, and a lack of cohesion that could lead to errors and operational issues. The aim of DevOps is to merge Dev and Ops into a single, continuous process that emphasizes collaboration, automation, integration, and communication across the entire application lifecycle.

How Does DevOps Work?

DevOps works by automating and integrating the processes between software development and IT teams. This allows them to build, test, and release software faster and more reliably. DevOps merges software development with IT Ops with the aim of shortening the development life cycle, increasing the frequency of deployment, and ensuring a high rate of software production quality. You can break it down into a few components, each with its own importance.

Continuous Integration is a foundational practice in DevOps where developers frequently merge code changes into a central repository, after which automated builds and tests are run. The primary goals are to find and address bugs more quickly, improve software quality, and reduce the time it takes to validate and release new software updates.

Following CI, Continuous Delivery automates the software release process, allowing DevOps teams to ensure that the software can be reliably released at any time. This practice goes hand in hand with CI, automating further stages of the pipeline to include the release of changes to a staging environment after the build and test stages. It aims to make deployments predictable and schedule them at almost any time with minimal intervention.

For teams that take CD further, Continuous Deployment automates the release of every change that passes the automated tests directly into production, eliminating human intervention in the deployment process. This allows organizations to accelerate the feedback loop with customers, providing rapid iterations based on user feedback.

A reliable DevOps toolchain is essential to support these practices, including tools for managing project builds, automations, deployments, monitoring, and collaboration. Monitoring remains a critical component throughout the DevOps lifecycle. It involves tracking the application’s performance and operational health to ensure reliability and availability.

How To Measure DevOps Success

DORA's 2025 State of AI-assisted Software Development report shows that about 32% of DevOps teams take between one day and one week to go from committed code to production, and 35% take less than one day to restore a service after a failed deployment. Compare that to the 9.4% of DevOps teams that take less than one hour to go from committed code to production and the 21.3% that take less than one hour to restore services after failure.

Louis Cribbins, a software architect with 20+ years building distributed systems, data platforms, and cloud operations, explains what the DORA metrics reveal about an organization’s DevOps. He advises reading the measurements in pairs for more meaning and attributing results to the whole team, not individuals.

Here’s what each metric reveals. If all five look weak, he advises starting with the first one:

• Failed deployment recovery time distribution: This metric describes how long it takes to recover from a deployment that fails. A weak score signals brittle deployment mechanisms. If recovering from a failed deployment takes heroic effort, that's a clear, fundable investment area, and usually the cheapest of the five to improve.
• Deployment frequency: This metric measures how often you deploy to production. A low score signals infrequent releases, where the team can't deploy on any given day. This usually comes from large batch sizes and releases that deviate from what is the norm
• Change lead time: This metric measures how long a change takes to go from committed in version control to running in production. A slow lead time uncovers a process-heavy organization, or one afraid to touch production. If you can only deploy on a constrained schedule, you've also constrained how fast you can fix things, making every incident worse than it needs to be.
• Change fail rate: The metric tracks the ratio of deployments that require immediate intervention. A high rate means the teams missed the issue and the customer found it. To improve this metric, set up a pre-production environment that genuinely resembles production, or provide the capabilities to release changes without exposing them to your customers.
• Deployment rework rate: This metric tracks the ratio of deployments that are unplanned and are caused by a production incident. This is the same validation gap as change fail rate, measured after the fact, the deployments you didn't plan to make.

Common DevOps Tools

DevOps tools automate workflows that continuously integrate and deploy software to production. They work across the eight stages of the DevOps lifecycle:

• Plan: Translate business needs and user feedback into use cases and tickets.
• Code: Set up components to easily automate integration and deployment.
• Build: Fetch code changes. Run automated checks. Produce packages.
• Test: Validate that each change is functional, secure, and performant.
• Release: Move the code into staging and production.
• Deploy: Deliver the packaged code to production.
• Operate: Keep applications in production reliable, secure, and accessible.
• Monitor: Observe the application and infrastructure. Proactively detect issues and understand users’ behavior.

Each tool below is mapped to the lifecycle stages where it plays a primary or supporting role:

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Docker: Docker is a widely used containerization platform that enables developers to package applications into containers. Docker simplifies setting up stable environments across multiple deployments.

Jenkins: Jenkins is a cornerstone tool for Continuous Integration (CI), providing an automation server to support building and testing software projects continuously.

Kubernetes: Kubernetes is an open-source system for automating the deployment, scaling, and management of containerized applications.

Ansible: Ansible is an open-source tool focused on configuration management, application deployment, and task automation.

Terraform: Terraform by HashiCorp enables infrastructure as code (IaC), allowing developers to define and provision infrastructure using a high-level configuration language. It drives cloud migration and transformation and the management of on-premises resources.

Git: Git is a distributed version control system that is fundamental to DevOps workflows. It supports distributed workflows, allowing multiple developers to work on a project simultaneously without interfering with each other.

Prometheus: Prometheus is an open-source monitoring and alerting toolkit originally built at SoundCloud. It has a powerful query language and integrates well with a graphical representation tool like Grafana to visualize and make sense of the monitoring data.

Observability and Reliability

Observability gives DevOps teams a picture of what’s happening inside a system or application. It relies on three pillars:

• Logs: Logs record what system events happened and why. They help DevOps staff diagnose and remediate system errors. After implementing a fix, you can retrigger the events and use the logs to verify the correction.
• Metrics: System metrics reveal performance issues happening over a time interval. Typically, DevOps uses these metrics to identify memory leaks and slow run times.
• Traces: Traces follow a single request’s path as it moves through the components of a system. Team members use traces to understand where and how system events happened by seeing the relationships among those components.

All three pillars feed alerting, so DevOps teams can respond to and fix issues based on their importance. Having a managed DevOps support team that responds to alert signals and not noise is critical.

Why Alert on the Symptoms

If the team ignores valid alerts, it can greatly hurt revenue. Louis Cribbins points to the case of Knight Capital, where the company ignored 97 emails and lost $460 million. Yet having a team respond to every alert a tool generates isn’t the fix either; that’s a fast way to get into debt with your error budget.

Cribbins says, “Alert on symptoms, not on causes.” Here how they compare based on a CPU alert example.

• A cause-based alert fires when the CPU is above 80% for five minutes. That happens during batch jobs, while a cache warms, or when network traffic is healthy. Most of these noisy blips require no action, so they get ignored.
• A symptom-based alert notifies DevOps that development’s "checkout error rate is above 2% for five minutes, affecting real transactions." Developers are being harmed at that instant, unable to contribute their code to the correct branch. The DevOps team can and must do something about it.

Cribbins clarifies, “CPU still matters - it's how you diagnose the problem once you're awake. For a practical guide, see Google's SRE Workbook Chapter 5, "Alerting on SLOs”

Start by defining what “good” means for the service. In the case of the CPU alerts, decide the indicator you measure, target, budget for, and then the alert. This work reduces the risk of ignored alerts and overspending your error budget.

Building Security Into the Pipeline

Shifting security scans left, into the development pipeline, stops bad actors from putting malicious code in the application. This saves a lot of headaches in dealing with multiple failed components and systems, bringing down business operations.

The trick is to have appropriate gating practices in the pipeline that block the bad code, but don’t hinder legitimate development work. Louis Cribbins recommends an organizing principle: “A scan can block a build only if it finishes inside the developer's attention span.” Anything longer will result in engineers bypassing the deployment pipelines to meet deadlines.

Should There Be A Security Override?

Cribbins says every serious checkpoint, such as one at a financial services organization, needs an override, as long as code changes still follow established processes, like requiring two reviewers before anything reaches production. A director or VP has the keys to bypass the scan upon special coding exceptions, reducing the likelihood of DevOps working around it unofficially.

You want one role from a third party to own that fix, advises Cribbins. If you go with some combination of the InfoSec/CISO who owns the policy, the engineering team that owns the scan, or the development team who wrote the code, you risk automating a broken process. There will be lots of activity, but no fix. Plus, in regulated industries like finance and healthcare, it’s illegal for the engineer who wrote a change to approve and release it.

Hire A DevSecOps Engineer

Cribbins advises scanning for these abilities when hiring a DevSecOps engineer, application security engineer, or platform security engineer.

• Can they write the automation? This role builds pipelines, not spreadsheets. Ask for something they've automated end-to-end.
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• Do they triage by exploitability rather than severity score? Give them a scan report with 400 findings and ask what they'd fix first.
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• Do they treat developer friction as their problem? Ask how they'd stop engineers from bypassing a security gate.
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• Can they explain a risk decision to the business owner, why a release is on hold, or why it isn't?

DevOps Best Practices

1. Managing CI/CD Collaboration: CI/CD is a cornerstone of effective DevOps. It helps catch errors early, reduce conflict, and streamline software delivery.
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2. Automate Everything Possible: Automating infrastructure, build, testing, and deployment workflows, where possible, minimizes errors and speeds up processes. Sit down with your DevOps, development, and IT teams to identify which processes can be automated and how to measure their effectiveness.
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3. Embrace Configuration as Code: Managing development infrastructure as code ensures consistent environments, version control, and successful cloud migration and transformation. Collaborate with your teams on what a stable development environment looks like and agree.
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4. Prioritize Continuous Monitoring and Logging: High service quality requires proactively monitoring performance and security. Assign a clear owner from your DevOps, other IT, and development teams for continuous monitoring. That way, deployment problems get addressed before they compound.
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5. Incorporate Security Practices Early (DevSecOps): Minimizing security risks means integrating checks into the development process. Security training that fits your team’s culture and daily workflows reduces risk further.
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6. Use Microservices Architecture: When DevOps adopts microservices for flexible, scalable applications, code deployments can be faster and more manageable. You need clear owners for each microservice and for combining them into business capabilities.
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7. Continually Evaluate and Improve: DevOps relies on continuous development, integration, testing, delivery, feedback, monitoring, and administrative processes to improve. Each phase requires team members to communicate clearly about what they’re doing, their progress, and any blockers.

DevOps Anti-Patterns To Avoid

DevOps anti-patterns lead to friction, burnout, and lost revenue. Yet teams fall into them because attention goes to the loudest issues rather than the most frequent ones, and knowledge concentrates wherever attention already is

• Ticket Tag: An organization has multiple teams (DevOps, dev, ops), and no one knows who owns what when a ticket lands or a component fails. This can happen during a company reorg. Instead, put together a platform team that builds self-service paths, measured on whether other teams can ship without them
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• The Midnight Savior: One person (or a small handful) holds the tribal knowledge of how DevOps works and saves every release. Even at multi-billion-dollar companies, knowledge of a critical process can narrow over time to just two or three people. Instead, rotate who runs the deployment, write the runbook while the savior is still there, and treat "only X can do this" as a defect with an owner.
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• Band-aids on Broken Bones: Effort goes to fixing the biggest failure, not the one that's bleeding. It looks like a team who spent a week fixing a visible error that happened once, while routine errors were pushed aside as background noise. Instead, count failures before funding fixes. Frequency times cost beats whoever escalated loudest.
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• Tools Over Outcomes: You purchased a platform, but the handoffs, approvals, and queues remain unchanged. No one measured beforehand what the tool was expected to approve. Instead, measure first, buy second, and name the number the purchase will improve.
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• Alert Drowning: Each DevOps member gets hundreds of emails that jobs and processes are successful, with the one meaningful message buried in the middle. So the DevOps team ends up ignoring the important alerts, as happened at Knight Capital in 2012. To avoid this, delete every alert that nobody acted on last quarter and confirm successes on a dashboard, not through email.

Big Takeaway

Whether you are just beginning to integrate DevOps principles or refining your approach, continuous learning and adaptation are key.

Every step toward implementing these practices can reduce development times, decrease deployment failures, and enhance service quality.

If you’re seeking guidance on where to start, contact MSH today to set up a consultation.

Frequently Asked Questions

What are the five DORA metrics, and why do they matter?

The five DORA metrics, when viewed in pairs, identify key DevOps team performance and areas for improvement. They consist of:

• Failed deployment recovery time distribution - how long it takes to recover from a deployment that fails
• Deployment frequency - how often you deploy to production
• Change lead time - how long a change takes to go from committed in version control to running in production
• Change fail rate - the ratio of deployments requiring immediate intervention
• Deployment rework rate - unplanned deployments that happen as a result of a production incident.

What are the steps to implement DevOps?

To implement DevOps adopt the continuous processes of the DevOps lifecycle

• Continuous development
• Continuous integration
• Continuous delivery and deployment
• Continuous feedback
• Continuous testing
• Continuous monitoring
• Continuous operations

What is DevOps culture, and why does it come before tools

DevOps culture describes a shared approach to development and IT that quickly deploys applications while managing risks. Having a healthy DevOps culture, with good collaboration, reduces errors and conflict and streamlines software delivery.

What are the benefits of adopting a DevOps process?

DevOps brings collaboration, automation, integration, and communication to the entire application lifecycle. Older models and methodologies often lead to siloed teams working independently and conflicting with one another. Adopting a good DevOps process speeds up production cycles and builds the cohesion needed to keep business applications running with few issues.

What is the difference between Agile and DevOps?

Agile describes a software development methodology to foster more collaboration and quicker iteration cycles. DevOps implements Agile methodologies as a single, continuous process across development and operations.

What are the most common DevOps anti-patterns to avoid

Common anti-patterns include ticket tag, the midnight savior, band-aids on broken bones, tools over outcomes, and alert drowning. They emerge when attention goes to the loudest issues instead of the most frequent ones, and knowledge concentrates wherever that attention goes.