Navigate Incident Management Like a Pro: MyFitnessPal's Sr. Director of Engineering Shares Insider Strategies with Lee Atchison
How much time are engineering teams spending on incidents?
Are you trying to set your engineering team free to do their best work? Read our new case study to learn how Blameless can help you do that.

DevOps Tools (All of the Tools Your Team Needs)

Emily Arnott

Wondering about DevOps Tools? We explain the best tools for every step of the DevOps development process.

What are DevOps Tools used for?

DevOps relies on effective tools to help teams manage the entire software development lifecycle. These tools can automate tasks, monitor applications, and facilitate sharing of information between teams.

Why use DevOps tools?

DevOps is a practice that breaks down silos around teams. Rather than development “tossing code over the wall” to operations, all teams collaborate throughout the entire DevOps lifecycle. Many of the benefits that DevOps best practices provide are based on the lifecycle flowing smoothly. Tooling helps reduce the toil of advancing code from stage to stage and makes each stage faster and easier.

Tooling is always an investment. Sometimes there’s a financial cost to purchasing a third party tool. Using open source tools or building in-house tools also requires a commitment of time and energy. You need to weigh the expected benefit of the tool against this initial investment. Think about the choice from a reliability perspective to help quantify this judgment. This will let you estimate the improvement a tool could have for your DevOps lifecycle.

Tooling for each stage of the DevOps lifecycle

The DevOps lifecycle consists of seven major stages:

  1. Development
  2. Integration
  3. Testing
  4. Monitoring
  5. Feedback
  6. Deployment
  7. Operations

This cycle takes a piece of code from developers writing it all the way to it running in the hands of users. Each stage has certain things that need to be completed before the next stage can begin. Some stages, like monitoring and feedback, happen continuously from when they start, rather than ending when the next stage begins. The types of tools used at each stage and the benefits they provide are different. Let’s take a look at them:

Development DevOps Tools

Development tools can take on a number of forms. Task management tools, like Jira, track and assign development projects. If your organization uses a practice like Agile, tools can help manage scrums and sprints. These types of tools are helpful for every stage of the lifecycle, as they track the project as it advances to completion.

Development can also be accelerated by investing in tools like integrated development environments (IDEs). These can make the actual process of writing code easier for developers. However, the usefulness of these tools depends on the type of work being done and the development style of the engineers.

Examples of task management tools: Jira,, Targetprocess

Jira allows you to create new tickets, which you then can track with status boards, calendars, and more. Teams can update the status of tickets asynchronously to keep everyone synched on the status of a project. It can also integrate into project planning methodology, like Agile sprints.

Examples of coding tools: Netbeans, Visual Studio, Lazarus

Visual Studio is an IDE developed by Microsoft. It collects and manages the different files that make up the codebase of the project. It features syntax highlighting and prediction to help make writing code easier. You can also run code from within Visual Studio, which offers debugging features such as line-by-line stepping and variable watching.

Integration DevOps Tools

A major source of toil in the DevOps lifecycle is in managing how new code is committed and integrated into the codebase. If poorly managed, you can run into conflicts, broken builds, and redundant work.

Source code management tools are the answer. These tools ensure that code can only be worked on by people who “check it out”, preventing others from making conflicting changes. They also offer tools to differentiate versions, roll back versions with issues, and more. By implementing these tools, this stage of the lifecycle will take less time and cause fewer problems.

Examples: Git, Beanstalk, Bitbucket

Git is a commonly used open source project that handles merging and changing files, distributing them and controlling access, and version control to ensure builds use the correct version of everything.

Testing DevOps Tools

Testing is a stage of the lifecycle that can cause serious delays. Luckily, a variety of tools can reduce the toil of testing. The goal is to achieve continuous testing, where new code can automatically be put through all the common tests. This allows you to find most issues and progress code without any manual intervention.

Automatic testing tools can look at code from a number of angles. Some parse source code to identify syntax errors that would break in runtime. Others simulate the code running and look for the expected outcome. They can test the code in a variety of settings and configurations to see if anything breaks. No matter how the tool does it, automated testing should prevent many common errors while reducing the time finding them.

Examples: SonarQube, Katalon, Eggplant

Katalon is a testing automation platform that allows you to integrate different environments and conditions into one testing process. It allows flexibility in what you want to test and the conditions in which you test it.

Monitoring DevOps Tools

A major part of DevOps is recording and parsing all the data that comes out of your system. You need to be able to filter out the noise to see what important information emerges. If you can’t understand the health of your system, you can’t see the effects of new code being integrated. This stops the code from progressing further in the DevOps lifecycle.

Monitoring tools make this process much easier. They collect and parse data outputted by the system into easy-to-read dashboards. They highlight abnormalities and can trigger alerts. Once your monitoring tools are set up, they can track the health of the code for the rest of the lifecycle.

Examples: DataDog, Sumologic, Prometheus

Sumo Logic is a monitoring environment that can gather data from a variety of sources, even handling multi-cloud architecture. It can consolidate all the data it collects into centralized, easy-to-read graphs and charts.

Feedback DevOps Tools

Feedback is somewhat like monitoring, where you want to set up tools to support the code for the rest of the lifecycle. Like monitoring, you want to ensure the code is still functioning as intended and notice any abnormalities. Feedback allows for more insights than just the health of the system. You can look at how users are interacting with the code to see where improvements can be made. Even if the code is working, it might not have the intended functions if users aren’t engaging with it as expected.

Feedback tools can gather this data in several ways. Some track user behavior, including how much time was spent on each service area. They can even create heatmaps that show where users are most likely to click on your UI. Others solicit feedback directly to gather user opinions.

Examples: Hotjar, UserReport. Userbrain

Hotjar is a user observation tool that generates heatmaps, user recordings, and other data around how users access your service. It can also offer users surveys to get more targeted feedback.

Deployment DevOps Tools

Once the code is finished, and monitoring and feedback tools are in place to support it, it’s time to deploy. DevOps advocates deploying often, using the principles of continuous integration and deployment. In order to keep up this pace, you’ll need to reduce the time and toil each deployment takes. This means automation and tooling.

The type of deployment tool you’ll want to use depends on the architecture you’re working with. A common way to deploy is through containers, using software like Kubernetes to build and orchestrate each container. Other tools help with other parts of the deployment pipeline, like acting as a server to push deployment. The goal is to automate as many stages of configuration and deployment as possible to enable frequent small iterations.

Examples: Kubernetes, Docker, Jenkins

Kubernetes is a containerizing and orchestrating system. It bundles your code into containers, packages containing everything needed for a single part of your codebase to run in production. Then it allows you to deploy and control these containers.

Operations DevOps Tools

Once the code is in users’ hands, you need to be able to support it when things go wrong. Failure is inevitable in complex changing systems. As your code evolves, operations teams will need to deploy fixes, updates, and rollbacks to keep things working as intended.

To make these responses fast and effective, use operations tools. These tools can help handle changes and incidents in three different stages. First, there’s tools that can help prevent and mitigate incidents by reducing single points of failure, creating backups, or building resources to help respond like runbooks. Next, during incidents, there’s tools that help diagnose problems and execute automated runbooks. Finally, once the incident is over, tools can help you build retrospectives to learn from, making you stronger for future incidents.

Examples: Blameless, PagerDuty, Statuspage

Tools can be a valuable investment to improve your DevOps lifecycle. The important thing is to make the most of them. By reducing time and toil, you’ll free up your engineers to explore deeper insights and decisions based on what your service is telling you. Blameless can help. Our SLIs and SLOs can recontextualize your entire lifecycle into the universal language of reliability

Book a blameless demo
To view the calendar in full page view, click here.