Introduction to Argo Rollouts Presentation
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This document discusses Argo Rollouts, an advanced open-source Kubernetes controller that enhances deployment strategies such as canary and blue-green deployments. It emphasizes best practices for using these deployments, including feedback submission, punctuality, and minimizing disturbances during sessions. The benefits of Argo Rollouts include reduced deployment risk, incremental updates, and automated rollbacks.
Introduction to Argo Rollouts Presentation
- 1. Argo Rollouts Advanced Deployment Strategies for Kubernetes Riya
- 2. Lack of etiquette and manners is a huge turn off. KnolX Etiquettes Punctuality Join the session 5 minutes prior to the session start time. We start on time and conclude on time! Feedback Make sure to submit a constructive feedback for all sessions as it is very helpful for the presenter. Silent Mode Keep your mobile devices in silent mode, feel free to move out of session in case you need to attend an urgent call. Avoid Disturbance Avoid unwanted chit chat during the session.
- 3. 1. Introduction to Argo Rollouts 2. Key Features 3. Benefits 4. Architecture and Components 5. Workflow of a rollout 6. Difference between ArgoCD and Argo Rollout 7. Demo: Implementing a Canary Deployment 8. Best Practices
- 4. • An advanced open-source Kubernetes controller • A part of the Argo Project under the CNCF • Extends the basic Kubernetes deployment capabilities • Focuses on progressive delivery
- 5. Key Features of Argo Rollout Canary Deployment o Gradually shifts a portion of user traffic to a newer version of the application. Blue-Green Deployment o Runs two versions of the application simultaneously, switches all the traffic to the newer version once it's verified. A/B Testing o Distributes different versions of the application to different user segments to compare performance. § Progressive Delivery o Implements a phased approach to releasing features, using traffic management.
- 6. Benefits Reduced risk during deployment Incremental updates with minimal downtime Automated rollbacks Enables near-instantaneous switchovers Provides insights into user preferences Controlled and incremental feature releases
- 7. Controllers Integrations CRDs Rollout: Defines how a deployment should be performed. Experiment: Defines experiments to run different configurations or versions. Analysis Template: Specifies templates for automated analysis. Rollout Controller: Monitors the status of the rollout and makes decisions Experiment Controller: Useful for scenarios requiring multiple variants of a deployment Analysis Controller: Collects m etrics and determines if the rollout should continue Ingress Controllers: Allows for dynamic traffic splitting and routing Service Meshes: Provides advanced traffic management and observability features Metrics Providers: Provides real-time metrics essential for automated analysis Architecture and Components
- 8. Workflow of a Rollout Rollout CRD Rollout Controller Traffic Management Analysis Controller Metrics Providers (Prometheus, etc.) Ingress/Service Mesh Monitoring/Metrics
- 9. Difference between ArgoCD and ArgoRollout
- 10. DEMO
- 11. Best Practices • Understand and Choose the Right Deployment Strategy • Automate Rollbacks • Implement Health Checks • Progressive Delivery • Monitor Metrics and Logs • Leverage Feature Flags • Automate Testing and Validation • Version Control for Configuration and GitOps