DevOps tools are rarely chosen in isolation. Most teams end up with a mix of platforms that grew over time – some picked for speed, others for stability, and a few simply because they were already there. What matters is how these tools fit together in real work: building code, shipping changes, watching systems, and fixing things when they break.
This DevOps tools list is meant to set the stage. Instead of jumping straight into feature checklists, it helps frame what these tools are, why teams rely on them, and how they usually show up in day-to-day workflows. Whether you are tightening an existing setup or starting fresh, this overview gives you a grounded place to begin.
1. AppFirst
AppFirst approaches infrastructure from the application side rather than starting with cloud resources or templates. They let developers describe what an app needs – things like compute, databases, networking, and container images – and handle the infrastructure setup behind the scenes. This shifts a lot of work away from Terraform files, cloud specific configuration, and internal platform tooling.
In a DevOps context, AppFirst fits teams that want to reduce friction between development and deployment without building their own infrastructure frameworks. Logging, monitoring, security standards, and auditing are built into the platform, so teams can move changes through environments while keeping visibility and control in one place.
Faits marquants :
- Application defined infrastructure instead of Terraform or CDK
- Journalisation, surveillance et alerte intégrées
- Centralized audit trail for infrastructure changes
- Visibilité des coûts par application et par environnement
- Fonctionne sur AWS, Azure et GCP
- Options de déploiement SaaS et auto-hébergées
Pour qui c'est le mieux :
- Product teams without a dedicated infrastructure group
- Developers tired of managing cloud configuration
- Organizations standardizing infrastructure across teams
- Teams that want guardrails without heavy DevOps tooling
Informations de contact :
- Site web : www.appfirst.dev
2. Git
Git is a distributed version control system that sits at the core of most DevOps workflows. Teams use it to track code changes, manage branches, review work, and coordinate across developers without relying on a central server. Its design makes it suitable for both small projects and large, long-lived codebases.
In DevOps pipelines, Git acts as the source of truth that connects build systems, CI tools, and deployment workflows. Its wide ecosystem of command-line tools, GUIs, and hosting platforms allows teams to adapt it to almost any process, from simple scripts to complex automation chains.
Faits marquants :
- Distributed version control with local and remote workflows
- Fast performance for large repositories
- Works with most CI and deployment tools
- Large ecosystem of hosting services and clients
- Open source with active community support
Pour qui c'est le mieux :
- Development teams of any size
- Projects that require reliable change tracking
- CI and CD pipelines built around source control
- Teams that need flexibility in how workflows are set up
Informations de contact :
- Website: git-scm.com
- E-mail: git+subscribe@vger.kernel.org
3. GitHub
GitHub is a shared workspace where code, collaboration, and automation come together. Teams use it to store repositories, review changes, track issues, and coordinate work around pull requests. It sits at the center of many DevOps workflows, acting as the place where development activity starts and where other tools connect.
Beyond version control, GitHub supports CI workflows, security checks, and team coordination in one environment. Automation through workflows helps teams run tests and deployments close to the code, while built-in collaboration tools keep discussions, reviews, and decisions tied to specific changes rather than scattered across systems.
Faits marquants :
- Source code hosting with pull request based workflows
- CI automation through built-in workflows
- Issue tracking and project organization
- Code review and team collaboration tools
- Integrations with a wide range of DevOps tools
Pour qui c'est le mieux :
- Development teams working in shared repositories
- Teams that rely on pull requests and code reviews
- Projects that connect CI and automation directly to code
- Organizations that want collaboration close to the codebase
Informations de contact :
- Site web : github.com
- Facebook: www.facebook.com/GitHub
- Twitter : x.com/github
- LinkedIn : www.linkedin.com/company/github
- Instagram : www.instagram.com/github
4. GitLab
GitLab takes a more all-in-one approach to DevOps by placing planning, source control, CI, security, and deployment in a single application. Instead of stitching together many tools, teams can work through most of the software lifecycle inside one interface. This can reduce handoffs and make it easier to follow work from idea to release.
In daily use, GitLab often becomes both a coordination layer and an execution layer. Developers plan work, push code, run pipelines, and review results without switching systems. Security and compliance checks are part of the same flow, which helps teams keep visibility without adding extra steps.
Faits marquants :
- Single application covering the full DevOps lifecycle
- Built-in CI pipelines tied directly to repositories
- Planning tools for issues and roadmaps
- Integrated security and compliance checks
- Centralized visibility across code and pipelines
Pour qui c'est le mieux :
- Teams looking to reduce the number of DevOps tools
- Organizations that want planning and delivery in one place
- Projects that need traceability from task to deployment
- Teams comfortable standardizing on a single platform
Informations de contact :
- Site web : about.gitlab.com
- Facebook : www.facebook.com/gitlab
- Twitter : x.com/gitlab
- LinkedIn : www.linkedin.com/company/gitlab-com
5. Bitbucket
Bitbucket focuses on source control and CI while staying closely connected to the Atlassian ecosystem. Teams use it to manage repositories, review code, and run pipelines, often alongside Jira for planning and issue tracking. This tight connection helps link code changes directly to work items.
From a DevOps perspective, Bitbucket works as part of a broader toolchain rather than a standalone system. Pipelines handle builds and deployments, while integrations allow teams to plug in testing, security, and monitoring tools as needed. The setup suits teams that already rely on Atlassian products for collaboration.
Faits marquants :
- Git based repository hosting
- Built-in CI with pipeline support
- Pull request and code review workflows
- Strong integration with Jira and other Atlassian tools
- Flexible permissions and access controls
Pour qui c'est le mieux :
- Teams already using Jira for planning
- Organizations standardizing on Atlassian tools
- Projects that want CI close to version control
- Teams that prefer modular DevOps setups
Informations de contact :
- Site web : bitbucket.org
- Facebook : www.facebook.com/Atlassian
- Twitter : x.com/bitbucket
6. Docker
Docker is used to package applications into containers so they run the same way across local machines, test setups, and production systems. Instead of worrying about differences between environments, teams bundle the app and its dependencies together, which simplifies development and handoffs between stages of the pipeline.
In DevOps workflows, Docker usually sits between development and deployment. Developers build and test containers locally, then reuse the same images in CI pipelines and runtime environments. This reduces guesswork during releases and makes debugging more straightforward when something behaves differently than expected.
Faits marquants :
- Container based application packaging
- Consistent environments from local to production
- Image based workflows for builds and deployments
- Works with CI pipelines and orchestration tools
- Large ecosystem of base images and tooling
Pour qui c'est le mieux :
- Teams deploying applications across multiple environments
- Projects that struggle with environment consistency
- DevOps setups built around containers
- Developers who want simpler local to production workflows
Informations de contact :
- Site web : www.docker.com
- Facebook : www.facebook.com/docker.run
- Twitter : x.com/docker
- LinkedIn : www.linkedin.com/company/docker
- Instagram : www.instagram.com/dockerinc
- Adresse : 3790 El Camino Real # 1052 Palo Alto, CA 94306
- Téléphone : (415) 941-0376
7. Terraform
Terraform is used to define and manage infrastructure through code instead of manual setup. Teams describe resources like servers, networks, and storage in configuration files, then apply those definitions to create or update infrastructure in a repeatable way.
Within DevOps pipelines, Terraform often acts as the layer that turns code changes into infrastructure changes. It fits workflows where infrastructure needs to be versioned, reviewed, and rolled out in a controlled manner, similar to application code. This makes it easier to track changes and coordinate work across teams.
Faits marquants :
- Infrastructure defined using configuration files
- Supports multiple cloud providers and services
- CLI driven workflows for planning and applying changes
- Version control friendly infrastructure management
- Commonly used in CI and automation pipelines
Pour qui c'est le mieux :
- Teams managing cloud infrastructure at scale
- Organizations treating infrastructure like code
- Projects that require repeatable provisioning
- DevOps teams integrating infra changes into CI pipelines
Informations de contact :
- Website: developer.hashicorp.com
- Facebook : www.facebook.com/HashiCorp
- Twitter : x.com/hashicorp
- LinkedIn : www.linkedin.com/company/hashicorp
8. OpenTofu
OpenTofu is an open source infrastructure as code tool designed to work with existing Terraform style configurations. It allows teams to keep their current workflows while using a community driven project that focuses on transparency and long term openness.
In practice, OpenTofu is used much like Terraform in DevOps environments. Teams define infrastructure in code, track changes in version control, and apply updates through automated pipelines. Additional features focus on giving more control during rollouts and protecting infrastructure state.
Faits marquants :
- Open source infrastructure as code tool
- Compatible with existing Terraform workflows
- Community maintained providers and modules
- Command line based planning and apply steps
- Built in support for state protection features
Pour qui c'est le mieux :
- Teams already using Terraform style configs
- Organizations prioritizing open source tooling
- Projects that need infrastructure version control
- DevOps teams managing multi environment setups
Informations de contact :
- Website: opentofu.org
- Twitter: x.com/opentofuorg
9. AWS CloudFormation
AWS CloudFormation is used to define and manage cloud infrastructure using templates. Teams describe resources such as compute, networking, and storage in structured files, then use those templates to create and update environments in a repeatable way. This helps keep infrastructure changes consistent and tied to versioned definitions instead of manual setup.
In a DevOps tools list, CloudFormation usually appears as the infrastructure management layer for teams working inside AWS. It supports workflows where infrastructure updates move alongside application changes, making it easier to review, track, and roll out updates through automated pipelines and controlled processes.
Faits marquants :
- Infrastructure defined through templates
- Automated creation and updates of AWS resources
- Version controlled infrastructure changes
- Integration with CI pipelines and deployment workflows
- Native fit for AWS based environments
Pour qui c'est le mieux :
- Teams running most of their infrastructure on AWS
- Projects managing infrastructure through code
- DevOps workflows that require repeatable provisioning
- Organizations standardizing AWS resource management
Informations de contact :
- Site web : aws.amazon.com
- Facebook : www.facebook.com/amazonwebservices
- Twitter : x.com/awscloud
- LinkedIn : www.linkedin.com/company/amazon-web-services
- Instagram : www.instagram.com/amazonwebservices
10. Chef
Chef focuses on managing system configuration and operational workflows across servers and environments. Teams use it to define how systems should be set up and maintained, then apply those rules consistently across cloud, on-prem, or hybrid setups. This helps reduce manual work and keeps environments aligned as they scale.
Within a DevOps setup, Chef is often used to support configuration, compliance checks, and operational automation. It connects infrastructure and application delivery by ensuring systems stay in the expected state while changes move through development, testing, and production.
Faits marquants :
- Configuration management through code
- Workflow orchestration for operational tasks
- Support for cloud and on-prem environments
- Compliance and audit focused automation
- Integration with existing DevOps toolchains
Pour qui c'est le mieux :
- Teams managing large numbers of servers
- Organizations with compliance driven environments
- DevOps setups needing consistent system configuration
- Projects combining automation with operational control
Informations de contact :
- Site web : www.chef.io
- Facebook : www.facebook.com/getchefdotcom
- Twitter : x.com/chef
- LinkedIn : www.linkedin.com/company/chef-software
- Instagram : www.instagram.com/chef_software
11. Puppet
Puppet is used to automate infrastructure configuration and enforce consistent system states across environments. Teams define desired configurations, and Puppet applies and maintains those settings across servers, networks, and cloud resources. This approach helps reduce drift and keeps systems aligned with operational rules.
In DevOps workflows, Puppet supports ongoing infrastructure reliability rather than one-time provisioning. It is commonly used alongside CI and deployment tools to ensure that systems remain stable, compliant, and predictable as applications and infrastructure evolve.
Faits marquants :
- Desired state configuration management
- Automation across cloud and hybrid environments
- Policy driven infrastructure control
- Continuous enforcement of system settings
- Works alongside CI and deployment tools
Pour qui c'est le mieux :
- Teams managing complex infrastructure setups
- Organizations focused on long-term system stability
- DevOps environments with strict configuration rules
- Projects that need continuous infrastructure control
Informations de contact :
- Site web : www.puppet.com
- Courriel : sales-request@perforce.com
- Adresse : 400 First Avenue North #400 Minneapolis, MN 55401
- Téléphone : +1 612.517.2100
12. Kubernetes
Kubernetes is used to run and manage containerized applications across clusters. It groups containers into logical units, handles scheduling, and keeps services available as workloads change. Teams rely on it to deploy applications, scale them up or down, and manage networking and storage in a consistent way.
In a DevOps tools list, Kubernetes usually sits at the runtime layer. It connects build and deployment processes with real production environments, making it easier to roll out updates, recover from failures, and manage complex systems without handling each container manually.
Faits marquants :
- Orchestration of containerized applications
- Automated rollouts and rollbacks
- Built-in service discovery and load balancing
- Resource based scheduling and scaling
- Works across cloud, on-prem, and hybrid setups
Pour qui c'est le mieux :
- Teams running applications in containers
- Projects that need scalable runtime environments
- DevOps workflows managing multiple services
- Organizations operating across different infrastructures
Informations de contact :
- Site web : kubernetes.io
- Twitter : x.com/kubernetesio
- LinkedIn : www.linkedin.com/company/kubernetes
13. Jenkins
Jenkins is used to automate build, test, and deployment tasks in software projects. Teams set up pipelines that react to code changes, run tests, and prepare releases. Its plugin system allows it to work with many languages, tools, and platforms.
Within a DevOps setup, Jenkins often acts as the glue between version control, testing tools, and deployment targets. It supports workflows where automation needs to be flexible and closely tied to existing systems rather than locked into a single platform.
Faits marquants :
- Pipeline based CI and CD automation
- Large plugin ecosystem
- Distributed build and execution support
- Web based configuration and management
- Integration with most DevOps tools
Pour qui c'est le mieux :
- Teams building custom CI and CD pipelines
- Projects with diverse tooling needs
- DevOps setups that require flexible automation
- Organizations running self-managed CI systems
Informations de contact :
- Site web : www.jenkins.io
- Twitter : x.com/jenkinsci
- LinkedIn : www.linkedin.com/company/jenkins-project
14. Google Cloud
Google Cloud provides infrastructure and services used to build, deploy, and operate applications. Teams use it for compute, storage, networking, and managed services that support modern application development. These services form the foundation for many DevOps workflows.
In a DevOps tools list, Google Cloud appears as the environment where automation, deployments, and monitoring come together. It supports workflows that combine infrastructure management, application delivery, and operational visibility within a single cloud ecosystem.
Faits marquants :
- Cloud infrastructure for application deployment
- Managed services for compute, storage, and networking
- Tooling for application development and operations
- Support for container and Kubernetes based workloads
- Integration with CI and automation workflows
Pour qui c'est le mieux :
- Teams running workloads in the cloud
- Projects needing managed infrastructure services
- DevOps workflows built around cloud platforms
- Organizations combining infrastructure and delivery in one environment
Informations de contact :
- Site web : cloud.google.com
- Twitter : x.com/googlecloud
15. Prométhée
Prometheus is used to collect and work with metrics from applications and infrastructure. Teams instrument their systems to expose metrics, which Prometheus then pulls in and stores as time series data. This makes it possible to observe how services behave over time and spot changes that may signal problems.
In a DevOps tools list, Prometheus usually appears on the monitoring and alerting side. It helps teams understand system health, define alerts based on real behavior, and connect operational data to dashboards and on-call workflows. Its tight fit with container and cloud environments makes it a common companion to orchestration and deployment tools.
Faits marquants :
- Time series based metrics collection
- Query language for filtering and aggregating metrics
- Alerting rules tied to observed behavior
- Integrations with many systems and services
- Designed for container and cloud native setups
Pour qui c'est le mieux :
- Teams that rely on metrics for system visibility
- DevOps workflows with active monitoring needs
- Environments running containers or Kubernetes
- Projects that need flexible alerting logic
Informations de contact :
- Site web : prometheus.io
16. Buildbot
Buildbot is a framework for automating build, test, and release workflows. Teams configure it using Python, which allows them to define jobs, schedules, and execution logic in a very flexible way. It runs tasks across distributed workers and reports results back to developers.
Within a DevOps setup, Buildbot is often used when workflows do not fit neatly into predefined CI patterns. It works well for complex build systems, multi-platform testing, and custom release processes where teams need more control over how automation behaves.
Faits marquants :
- Job scheduling for build, test, and release tasks
- Distributed execution across multiple workers
- Python based configuration and customization
- Supports complex and non-standard workflows
- Detailed status and result reporting
Pour qui c'est le mieux :
- Teams with custom build or release requirements
- Projects spanning multiple platforms or languages
- DevOps setups that need fine-grained control
- Organizations comfortable maintaining CI infrastructure
Informations de contact :
- Website: buildbot.net
17. Bamboo
Bamboo is used to automate build and deployment pipelines, often alongside other Atlassian tools. Teams define stages that take code from build through test and deployment, keeping each step visible and repeatable. It is commonly deployed in environments where teams manage their own infrastructure.
In a DevOps tools list, Bamboo fits into workflows that value traceability between code, issues, and deployments. Its integrations help teams link changes in source control to delivery steps, making it easier to follow how work moves from planning to production.
Faits marquants :
- Build and deployment pipeline automation
- Stage based workflows from code to release
- Integration with version control and issue tracking
- Support for container and cloud deployments
- Self-managed deployment options
Pour qui c'est le mieux :
- Teams using Atlassian tools for planning and code
- Projects that need structured delivery pipelines
- Organizations running self-hosted CI systems
- DevOps workflows focused on traceable releases
Informations de contact :
- Site web : www.atlassian.com
- Adresse : Niveau 6, 341 George Street, Sydney, NSW 2000, Australie
- Téléphone : +61 2 9262 1443 +61 2 9262 1443
18. PagerDuty
PagerDuty is used to manage incidents and coordinate response when systems fail or behave unexpectedly. Teams connect alerts from monitoring and infrastructure tools, route them to the right people, and track incidents from first signal to resolution. The focus is on reducing confusion during outages and making sure issues are acknowledged and handled in a clear order.
In a DevOps tools list, PagerDuty fits into the operational response layer. It connects monitoring, on-call schedules, and communication so teams can react quickly when automation or deployments trigger real world problems. Rather than replacing monitoring or CI tools, it helps teams act on the signals those tools produce.
Faits marquants :
- Incident alerting and on-call scheduling
- Central place to track active incidents
- Integrations with monitoring and infrastructure tools
- Workflow support for incident response and follow-ups
- Shared visibility across engineering and operations
Pour qui c'est le mieux :
- Teams running services that need on-call coverage
- DevOps workflows with real-time alerting needs
- Organizations coordinating response across teams
- Projects where downtime handling is critical
Informations de contact :
- Site web : www.pagerduty.com
- Phone: 1-844-800-3889
- Courriel : sales@pagerduty.com
- Facebook : www.facebook.com/PagerDuty
- Twitter : x.com/pagerduty
- LinkedIn : www.linkedin.com/company/pagerduty
- Instagram : www.instagram.com/pagerduty
19. Datadog
Datadog is used to observe applications and infrastructure through metrics, logs, and traces. Teams install agents or integrations to collect data from services, servers, containers, and cloud resources, then explore that data in a shared interface. This helps them understand how systems behave under load and during changes.
Within a DevOps setup, Datadog usually acts as the visibility layer. It gives developers and operators a common view of performance and health, which supports troubleshooting, release validation, and ongoing improvement. It often works alongside CI, deployment, and incident tools rather than standing alone.
Faits marquants :
- Metrics, logs, and traces in one view
- Broad integrations across infrastructure and apps
- Dashboards for system and service visibility
- Support for cloud and container environments
- Collaboration around shared operational data
Pour qui c'est le mieux :
- Teams needing end-to-end system visibility
- DevOps workflows focused on observability
- Environments with many services or dependencies
- Organizations that want shared operational context
Informations de contact :
- Site web : www.datadoghq.com
- App Store: apps.apple.com/ua/app/datadog/id1391380318
- Google Play: play.google.com/store/apps/details?id=com.datadog.app&pcampaignid=web_share
- Courriel : info@datadoghq.com
- Twitter : x.com/datadoghq
- LinkedIn : www.linkedin.com/company/datadog
- Instagram : www.instagram.com/datadoghq
- Address: 620 8th Ave 45th FloorNew York, NY 10018 USA
- Téléphone : 866 329-4466
20. Argo CD
Argo CD is used to deploy and manage applications in Kubernetes using Git as the source of truth. Teams define the desired state of applications in repositories, and Argo CD keeps running environments aligned with those definitions. Changes flow through Git, making deployments easier to track and review.
In a DevOps tools list, Argo CD sits between version control and runtime environments. It supports workflows where deployment logic is declarative and auditable, and where drift between intended and actual state needs to be visible. This approach helps teams keep deployments predictable as systems grow.
Faits marquants :
- Git-based deployment and configuration management
- Continuous syncing between desired and live state
- Support for common Kubernetes config formats
- Visibility into deployment status and drift
- CLI and API for automation
Pour qui c'est le mieux :
- Teams using Kubernetes in production
- DevOps setups following GitOps practices
- Projects needing clear deployment history
- Organizations managing multiple clusters
Informations de contact :
- Site web : argo-cd.readthedocs.io
Conclusion
A DevOps tools list is never really about the tools alone. What matters more is how they fit together and how well they support the way a team actually works. Some tools help with automation, others with infrastructure, collaboration, or keeping systems stable once they are live. Each one plays a role, but none of them solves everything on its own.
The real value comes from choosing tools that match your workflows, skills, and constraints. For some teams, that means a simple setup that covers the basics. For others, it means a more layered stack that grows over time. There is no single right combination, only tradeoffs that make sense for where you are now and where you are headed. A clear view of what each tool does makes those decisions easier and helps avoid building a stack that looks good on paper but feels heavy in day to day work.
