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# A Practitioners Guide to GitOps - Introduction, Principles and Implementation

Still relying on manual CLI commands to manage infrastructure? Learn to eliminate configuration drift and automate pull-based deployments using declarative GitOps principles and Keptn.

- **Speakers:** Thomas Schütz
- **Event:** WeAreDevelopers LIVE
- **Published:** April 6, 2022
- **Duration:** 45:58
- **URL:** https://www.wearedevelopers.com/videos/372-a-practitioners-guide-to-gitops-introduction-principles-and-implementation

## Summary

The transition from imperative infrastructure management—relying on manual shell scripts and CLI commands that cause configuration drift and lack security—to declarative GitOps principles is becoming essential for reliable software delivery. GitOps centers on defining the desired state of infrastructure and configurations declaratively within a Git repository. According to CNCF principles, this single source of truth is pulled automatically by continuous reconciliation controllers, ensuring immutability, enabling peer-reviewed pull requests, and automating test validations before deployment.

Implementing this methodology requires translating intent into manageable automation, heavily relying on tools like custom resource definitions (CRDs) within Kubernetes ecosystems. The Keptn project, a CNCF control plane for continuous delivery and automated operations, exemplifies this shift. Initially reliant on imperative pipelines, Keptn now leverages continuous reconciliation and CRDs to template projects, manage service stages, and orchestrate the entire deployment lifecycle. This enables operators to encapsulate monitoring configurations (using Dynatrace, Prometheus, or Datadog), quality gates, and automated remediation completely as code.

By abstracting the execution layer, developers only need to declare the target state without learning complex CLI commands, offloading the reconciliation process to automated operators. Orchestrating established tooling—such as Argo or Flux—via a higher-level control plane like Keptn standardizes pipelines across teams and drastically reduces the time needed to onboard new services. Ultimately, adopting automated pull-based deployments eliminates manual cluster interventions, ensuring that environments accurately and securely reflect their version-controlled architecture.

**Keywords:** imperative vs declarative configuration, continuous reconciliation controllers, kubernetes custom resource definitions, application lifecycle orchestration, pull-based deployment automation, infrastructure configuration drift, CNCF gitops principles, keptn control plane, service level objectives, automated quality gate evaluation, remediation workflows configuration, argo and flux integration, single source of truth deployment, declarative infrastructure state

## Chapters

1. **Understanding the drawbacks of imperative infrastructure commands** (00:00) — Manual scripting and imperative commands lead to fragile, outdated, and complex delivery processes.
1. **Simplifying infrastructure state with declarative configuration models** (03:49) — How declaring a target state separates deployment intention from infrastructure execution details.
1. **Security and stability risks of manual declarative configurations** (06:07) — Executing configurations from local machines causes state drift and lacks automated testing workflows.
1. **Core principles and prerequisites of robust GitOps workflows** (08:21) — Establishing Git as the single source of truth for immutable, automatically-reconciled infrastructure states.
1. **Architecting continuous reconciliation loops with Kubernetes controllers** (15:00) — How automated operators continuously compare and reconcile declared target states against the underlying system.
1. **Managing application lifecycles with the Keptn control plane** (21:56) — Using Keptn as a distributed control plane enables continuous delivery, testing, and automated remediation.
1. **Implementing declarative GitOps workflows using Keptn custom resources** (24:46) — Updating manual pipelines to utilize declarative custom resource definitions and Kubernetes operators.
1. **Demonstrating automated deployment sequences via Git repositories** (27:59) — Deploying and testing application changes by syncing custom resources with continuous delivery pipelines.
1. **Comparing Keptn orchestration capabilities against alternative software operators** (33:49) — Comparing GitOps orchestration models against other continuous delivery operators and observability platforms.

## Related Moments

- [Core principles and prerequisites of GitOps implementations](https://www.wearedevelopers.com/videos/370-practical-tips-and-tricks-for-ci-cd-success) (from "Practical tips and tricks for CI/CD success")
- [Introduction to GitOps and the Argo CD presentation](https://www.wearedevelopers.com/videos/108-get-ready-for-operations-by-pull-requests) (from "Get ready for operations by pull requests")
- [Understanding principles and benefits of the GitOps workflow](https://www.wearedevelopers.com/videos/852-securing-secrets-in-the-gitops-era) (from "Securing secrets in the GitOps Era")
- [Defining the core principles of declarative infrastructure and GitOps](https://www.wearedevelopers.com/videos/815-gitops-for-the-people) (from "GitOps for the people")
- [Defining GitOps and declarative infrastructure management](https://www.wearedevelopers.com/videos/547-how-to-gitops-your-cluster-with-flux) (from "How to GitOps your cluster with Flux")
- [Exploring the core benefits of adopting GitOps](https://www.wearedevelopers.com/videos/547-how-to-gitops-your-cluster-with-flux) (from "How to GitOps your cluster with Flux")

## Related Articles

- [Stop Googling Git Commands. Start Actually Learning Git.](https://www.wearedevelopers.com/magazine/730-stop-googling-git-commands-start-actually-learning-git)
- [Learning Kubernetes made easy with KubeCampus](https://www.wearedevelopers.com/magazine/348-learning-kubernetes-made-easy-with-kubecampus)
- [How we Build The Software of Tomorrow](https://www.wearedevelopers.com/magazine/120-how-we-build-the-software-of-tomorrow)
- [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production)

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