What is GitOps ?
GitOps is a methodology for continuous deployment using a Git repository as the single source of truth. The Git repository is the source of truth for both declarative infrastructure as well as application workloads. This repository serves as a store for infrastructure definitions, embodying the principles of Infrastructure as Code (IaC). To understand more about how IaC underpins such practices, enhancing efficiency and consistency, read my in-depth discussion on Infrastructure as Code . The repository contains the IaC definitions for the Kubernetes resources to be created as YAML manifests or Helm charts. The Git repo is used to store, track and version control changes to these YAML files containing the Kubernetes configuration such as Namespaces, Deployments, Pods, Services, Ingress, DaemonSets, ConfigMaps, Secrets etc. The Git repo stores the desired system state. Changes to the runtime state versus the desired state is managed by examining Git diffs and using Git primitives to roll back and reconcile the live state.
GitOps makes Git the source of truth where you specify the desired state of your entire system. Teams introduce changes to the cluster state or application configuration, through a CI pipeline. These updates/changes are stored in a Git repository as Git Commits and can be versioned. Changes between versions can be compared and rolled back if necessary. Changes are explicit and approved through pull requests. A dedicated GitOps component reads approved changes from the Git repository and applies the changes to the Kubernetes cluster through a CD pipeline. This provides for separation of concerns and also ensures that the Git repository reflects the current state of the cluster irrespective of who made the change and when. Any change to a defined branch will trigger the relevant updates to the cluster. The Git repo acts as a backup in case of catastrophic failures and allows for recovery from scratch.
GitOps as a methodology for managing Kubernetes clusters and applications was initially proposed by Alexis Richardson, co-founder and CEO of Weaveworks in a series of blog posts in 2017. Weaveworks used the GitOps methodology with their Kubernetes environments. The GitOps working group in CNCF is building a GitOps manifesto that standardizes GitOps principles . THis group has participation from Weaveworks, Codefresh, Microsoft and others. While the GitOps principles have been solidified the tooling around GitOps is evolving and improving.
DevOps vs GitOps
DevOps is a well established patterns for delivering cloud native applications. DevOps generally takes a push approach where infrastructure updates are pushed into the runtime environment. This requires a good knowledge and understanding of the various environments and the current state of these environments. In a GitOps model we use the pull approach where the GitOps operator pulls changes based on any updates to the desired state. The GitOps operator is responsible for resolving the state changes and applying them to the runtime environment.
In a DevOps model the application pipelines and the deployment pipelines are disconnected and exclusive. The pipeline to build the runtime environment generally consists of IaC scripts which are run once for a static one time build of the environment. The application pipelines are run multiple times to build and deploy the application to this static runtime environment. In the GitOps model the desired runtime environment is described in the Git repository. Teams make changes to the desired state by creating Git commits. The updated to the desired state are then rolled into the runtime environment by agents which pull in these changes and deploy them automatically.
In the DevOps methodology we use Terraform, Ansible, Helm, Kubectl and other tools to script out the environment. In GitOps we use an autonomous agent(Operator) to perform tasks such as create, delete or update the environment based on the declarative manifest in Git. The operator is responsible for reconciling the environment definition in Git with the current state of the environment. We do not run Kubectl apply or Terraform apply directly on a runtime environment in GitOps.
Principles of GitOps
The principles of GitOps are:
Declarative configuration - The System state is described declaratively. Instead of providing a series of instructions on how to build the infrastructure, applying configurations and deploying the application, we declare the end state of what is needed. Declarative configuration is idempotent and can be run multiple times without any impact to the system consistency.
Version controlled, immutable storage - Git is the source of truth. The desired system state is versioned in Git. Multiple Git branches can be created to apply changes to different environments. A pull-request (PR) based approval process can be used along with gated check in to ensure that only approved changes are deployed to the environment.
Automated delivery - Git is the single place for operations (create, change, delete) performed by autonomous agents. An approved Git commit will result in a new deployment and a Git revert would rollback changes.
Autonomous agents - Software agents known as operators enforce the desired state and alert on drift. These agents monitor the environment and alert for any divergence from the repository. It automatically corrects the divergence.
Closed loop - Delivery of approved system state changes is automated.
Why do GitOps ?
GitOps extends DevOps by taking it’s best practices such as version control, collaboration, continuous deployment and applying these to environment automation through application deployment, configuration, and infrastructure. GitOps allows developers and DevOps teams to version control the infrastructure and ship applications faster.
The key benefits of GitOps are
Standardized workflow - Git as the source of truth improves Developer Experience and ensures easy adoption. Developers are familiar with Git. GitOps applies a consistent development workflow to operations. All operations are performed through Git commands.
Auditability - Tracking both application code & infrastructure definition in Git results in a full audit trail and compliance. GitOps promotes collaboration between development, security and operations using Git as the collaboration tool. Code reviews result in better stability of systems experiencing a high rate of change.
Consistency - Infrastructure as a code results in easier rollback, more consistency, & standardization. Automation provides consistency reducing errors.
Reliabiity - Continuous sync and Configuration drift detection results in reliable environments.
Enhanced Security - Shifting security left to the GitOps operator. Security is also maintained as code. Traceability of who made/approved a change is automatically provided. Changes to the runtime state can only be applied by automated agents. The need for external access to the system through tools like ssh, rdp etc is eliminated. Controls applied on the Git repository control who can make changes to which parts of the system.
Best practices & Common pitfalls in GitOps
In the world of software deployment and infrastructure management, GitOps has emerged as a game-changer, offering unparalleled efficiency and consistency. However, the true power of GitOps can only be harnessed when it’s implemented with a mindful approach towards established best practices and a keen awareness of potential pitfalls.
As we delve deeper into the GitOps paradigm, it’s essential to understand that while tools like Argo CD and Flux simplify complex processes, their effectiveness largely depends on how they are employed. Adopting best practices not only maximizes the benefits of GitOps but also safeguards against common errors that can lead to system failures, security breaches, or operational inefficiencies. In this section we will explore the fundamental best practices that should be the cornerstone of any GitOps implementation. We will also navigate through common pitfalls - the subtle yet impactful missteps that can derail the GitOps process.
Best Practices
Declarative Configuration: Ensure all system states are described declaratively. This approach allows for idempotency and repeatability, reducing errors during deployments.
Version Control and Documentation: Keep all configurations version-controlled in a Git repository. This practice not only facilitates tracking changes but also serves as documentation for your system state.
Automated Delivery and Reconciliation: Utilize automated delivery mechanisms. With tools like Argo CD and Flux, changes in the Git repository should trigger automatic deployments. Also, ensure your system supports automated reconciliation to maintain the desired state.
Continuous Monitoring and Alerting: Set up monitoring and alerting for your deployments. Autonomous agents should be in place to alert on any drift from the declared state and correct it automatically.
Clear Workflow and Policies: Establish a standardized workflow for operations. All operations should be performed through Git commands to ensure consistency and traceability. Adherence to this best practice is not easy as operators can sometimes use
kubectlor other command line tools to quickly fix a critical issue. However non-adherence leads to long term pain that is not easy to resolve.Security and Secret Management: Implement robust security practices. This includes managing secrets effectively and ensuring that changes to the runtime state can only be applied by automated agents.
Role-Based Access Control (RBAC): Use RBAC to control access to the Git repository. Properly implemented RBAC ensures that only authorized personnel can make changes, thereby maintaining the integrity of the system.
Regular Backup and Disaster Recovery Plans: Maintain regular backups of your Git repository and have a disaster recovery plan in place. This ensures quick recovery in case of catastrophic failures.
Multi-cluster and Multi-tenant Capabilities: If working in an environment with multiple clusters or requiring multi-tenancy, choose tools that effectively support these features and configure them accordingly
Common Pitfalls
Overlooking Cluster Drift: Cluster drift occurs when the actual state of the cluster diverges from the state declared in Git. It’s crucial to have mechanisms to detect and reconcile drift.
Inadequate Testing: Neglecting to thoroughly test configurations before applying them can lead to system failures. Implement a robust testing pipeline for all changes.
Complex Configurations: Complex configurations can make the system hard to manage. Strive for simplicity and clarity in your configuration files.
Poor Secret Management: Storing secrets insecurely or not managing them effectively can lead to security vulnerabilities. Utilize secret management tools and ensure they are integrated properly with your GitOps workflow.
Ignoring Backup and Recovery: Not having a backup and recovery plan for your Git repository and Kubernetes cluster can be catastrophic. Regularly backup your configurations and test your recovery procedures.
Ineffective Rollback Strategies: Lack of effective rollback strategies for deployments can cause extended downtimes. Ensure your GitOps setup supports easy and reliable rollbacks.
Neglecting User and Access Management: Failing to properly manage user access to your Git repository can lead to unauthorized changes. Implement strict access controls and audit trails.
Not Utilizing the Full Potential of GitOps Tools: Both Argo CD and Flux have unique features and strengths. Ensure you are utilizing these tools to their full potential to maximize the benefits of GitOps.
GitOps Operators
There are many GitOps operators out there, but the two main ones are Flux and Argo CD . The Flux and Argo CD GitOps operators are designed to work with Kubernetes. If you would like to get started on implementing GitOps using ArgoCD, this blog post is a great way to get started. However, GitOps is not limited to Kubernetes operators alone. Kubestack is a Terraform based GitOps framework. We will look at each of these operators in detail in future posts.
Future trends in GitOps
As we advance further into an era dominated by cloud-native technologies and DevOps practices, GitOps is not just evolving; it’s leading the way in infrastructure and deployment automation. Looking towards the future, several key trends and advancements in tooling are set to shape the landscape of GitOps.
The future of GitOps involves greater support for multi-cloud and cross-platform deployments, enabling seamless management of resources across different cloud providers and platforms. As organizations navigate between cloud and on-premises solutions, GitOps tools that can efficiently bridge this gap will become more prevalent.
With the increasing complexity of deployments, advanced rollback capabilities will become essential in GitOps tools, allowing for quicker and more reliable recovery from failed deployments. Enhanced observability features in GitOps tools will provide deeper insights into deployment processes, infrastructure state, and application performance, facilitating more proactive incident management. To counteract the complexity of managing multiple tools, we’ll see a trend towards the simplification of toolchains and tighter integration between different GitOps components.
The integration of policy-as-code tools with GitOps workflows will become more prominent, ensuring compliance and security configurations are consistently applied across all deployments. GitOps tools will increasingly incorporate automated security scanning within the CI/CD pipeline, shifting security further left in the development process.
The landscape of GitOps is dynamic, and the future promises even more sophisticated, secure, and efficient ways of managing deployments and infrastructure.
Next Steps
As we wrap up our exploration of GitOps, it’s time to put theory into practice. For those ready to take the next steps in implementing GitOps, I invite you to delve into my comprehensive guide on Using ArgoCD for GitOps . This post will walk you through the hands-on application of GitOps principles using ArgoCD, a popular tool in the GitOps ecosystem, helping you transform your understanding into actionable skills.