Course Outline
Module 1: Microservices Design
• Establishing Effective Microservice Boundaries
• Applying Domain-Driven Design (DDD)
• Exploring Alternatives to Business Domain Boundaries (Volatility, Data, Technology, Organizational)
• Strategies for Decomposing Monolithic Applications
• Avoiding Premature Decomposition
• Decomposition by Layer Approaches
• Utilizing Decomposition Patterns (Strangler, Parallel Run, Feature Toggle)
• Addressing Data Decomposition Concerns (Performance, Integrity, Transactions)
Module 2: Optimizing Docker and the Runtime for Government
• Selecting the Appropriate Base Image
• Reducing the Number of Layers
• Implementing Multi-Stage Builds
• Optimizing Images (Sorting Multi-Line Arguments, etc.)
• Utilizing Build Cache Effectively
• Pinning Image Versions for Stability
• Fine-Tuning Resource Allocation
• Adhering to Secure Container Practices
• Configuring Runtime Settings for Optimal Performance
Module 3: Kubernetes & Release Strategies for Government
Kubernetes Deployments Overview
• Creating and Executing Initial Deployments
• Exploring Kubernetes Deployment Options
Performing Rolling Update Deployments
• Understanding the Concept of Rolling Updates
• Creating and Executing a Rolling Update
• Rolling Back a Deployment When Necessary
Performing Canary Deployments
• Understanding Canary Deployments
• Creating and Executing a Canary Deployment
Performing Blue-Green Deployments
• Understanding Blue-Green Deployments
• Creating and Executing a Blue-Green Deployment
Running Jobs and CronJobs
• Creating and Managing Jobs and CronJobs
Performing Monitoring and Troubleshooting Tasks for Government
• Advanced Troubleshooting Techniques with kubectl
Module 4: Automation & Operational Efficiency for Government
Using Python to Automate Common Tasks in Kubernetes
• Leveraging Python for Administrative Operations in Kubernetes
• Using Python to Define Configuration Objects
• Creating Deployment Objects with Python
• Monitoring Kubernetes Events via Python
• Scaling Deployments Automatically Using Python
Understanding the Challenges of Automating Deployments for Government
• Declarative Configuration in Kubernetes
• Ensuring Configuration Integrity and Consistency
Using the GitOps Approach for Automating Deployments for Government
• Principles of GitOps
• Introduction to Flux
• Installing Flux on a Kubernetes Cluster
Configuring Flux for Automated Deployments for Government
• Utilizing Notifications in Flux
• Structuring the Source Repository
Handling Application Updates with Image Automation for Government
• Updating Application Deployments with Flux
• Scanning Container Image Repositories for Tags
• Defining Policies for Selecting Latest Images
• Configuring Flux to Perform Automatic Image Updates
Module 5: Observability & Root Cause Clarity for Government
Kubernetes Logging and Tracing Capabilities for Government
• The Importance of Logging and Tracing
• Accessing Kubernetes Logs
• Reviewing Pod and Container Logs
• Examining Control Plane Logs
• Monitoring Resource Usage of Nodes and Pods
Collecting and Analyzing the Logs for Government
• Log Aggregation Techniques
• Visualizing Logs for Better Insights
Distributed Tracing in Kubernetes for Government
• Overview of Distributed Tracing
• Utilizing OpenTelemetry
• Exploring Distributed Tracing Tools
• Instrumenting Applications for Tracing
• Using Tracing to Identify Performance Issues
Monitoring with Prometheus and Grafana for Government
• Key Concepts of Observability
• Monitoring Tools Overview
• Implementing Prometheus Instrumentation
Advanced Use Cases for Logging for Government
• Advanced Log Processing Techniques
• Filtering and Enriching Logs
• Implementing Event Sourcing
Module 6: Cluster Crisis Simulation & Incident Response for Government
• Understanding Various Types of Failures in a Cluster Environment
• Simulating Node Failures
• Handling Pod Eviction and Resource Exhaustion Scenarios
• Addressing Network Issues
• Managing DNS Failures to Ensure Application Timeout Handling
• Simulating an API Server Outage
• Testing System Stability Under High Traffic Conditions
• Handling Storage Failures
• Resolving Configuration Errors
• Understanding Incident Reporting Procedures
Module 7: AI to Support Troubleshooting for Government
• Benefits of Generative AI for Kubernetes Operations
• Overview of the K8sGPT CLI Architecture
• Installing the K8sGPT CLI
• Utilizing K8sGPT Commands and Features
• Using K8sGPT Analyzers (podAnalyzer, pvcAnalyzer, rsAnalyzer, etc.)
• Analyzing the Cluster with K8sGPT
• Addressing Real-Time Issues with K8sGPT
• Deploying an In-Cluster Operator for K8sGPT
Requirements
- Proficiency in Linux command-line operations
- Experience in application development or system administration
- Familiarity with container technologies, including Docker concepts
- Fundamental knowledge of Kubernetes principles (pods, deployments, services)
- General understanding of software architecture (e.g., APIs, services)
Target Audience:
- DevOps Engineers
- Site Reliability Engineers (SREs)
- Backend and Software Developers working with microservices
- Cloud Engineers and Platform Engineers
- System Administrators transitioning to Kubernetes environments for government use cases
Testimonials (1)
real life examples
