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.

1. Argo Rollouts
Advanced Deployment
Strategies for Kubernetes
Riya

2. Lack of etiquette and manners is a huge turn off.
KnolX Etiquettes
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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o Gradually shifts a portion of user traffic to a newer version of the application.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