Kubernetes for Developers is a hands-on guide to taking your first steps into Kubernetes using the powerful Google Kubernetes Engine service.
Kubernetes for Developers is a clear and practical beginner’s guide that shows you just how easy, flexible, and cost-effective it can be to make the switch to Kubernetes deployment even for small to medium-sized applications.
Kubernetes for Developers is a hands-on guide to taking your first steps into Kubernetes using the powerful Google Kubernetes Engine service. It lays out a map for taking an application, containerizing it, and then deploying it onto Kubernetes. You’ll learn best practice techniques for a stable and long-term Kubernetes deployment, including scaling and capacity planning, saving money by optimizing resource consumption, and tricks to make your day-to-day monitoring easier such as debugging code in the cloud.
Author(s): William Denniss
Publisher: Manning Publications
Year: 2023
Language: English
Pages: 279
Kubernetes for Developers MEAP V14
Copyright
Welcome
Brief contents
Chapter 1: Kubernetes for Application Deployment
1.1 Why Containers?
1.1.1 Container Benefits
1.2 Why Kubernetes?
1.2.1 Composable Building Blocks
1.2.2 Features and Benefits
1.2.3 Kubernetes vs Platforms as a Service (PaaS)
1.2.4 When (not) To Use Kubernetes
1.3 Summary
Chapter 2: Containerizing Apps
2.1 Building Docker Containers
2.1.1 Developer Setup
2.1.2 Running Commands in Docker
2.1.3 Building our own Images
2.1.4 Using Base Images
2.1.5 Adding a Default Command
2.1.6 Adding Dependencies
2.1.7 Compiling Code in Docker
2.1.8 Compiling Code with a Multi-stage Build
2.2 Containerizing a Server Application
2.2.1 Containerizing an Application Server
2.2.2 Debugging
2.3 Using Docker Compose for Local Testing
2.3.1 Mapping Folders Locally
2.3.2 Adding Service Dependencies
2.3.3 Faking External Dependencies
2.4 Summary
Chapter 3: Deploying to Kubernetes
3.1 Kubernetes Architecture
3.1.1 The Kubernetes Cluster
3.1.2 Kubernetes Objects
3.2 Deploying an Application
3.2.1 Creating a Cluster
3.2.2 Uploading your Container
3.2.3 Deploying to Kubernetes
3.2.4 The Podspec
3.2.5 Publishing your Service
3.2.6 Interacting with the Deployment
3.2.7 Updating your Application
3.2.8 Cleaning Up
3.3 Declarative Commands
3.4 Local Kubernetes Environments
3.4.1 Docker Desktop’s Kubernetes Cluster
3.4.2 Minikube
3.4.3 Using your Local Kubernetes Cluster
3.5 Summary
Chapter 4: Automated Operations
4.1 Automated Uptime with Health Checks
4.1.1 Liveness and Readiness Probes
4.1.2 Adding a Readiness Probe
4.1.3 Adding a Liveness Probe
4.1.4 Designing Good Health Checks
4.1.5 Rescheduling Unready Containers
4.1.6 Probe Types
4.2 Updating Live Applications
4.2.1 Rolling Update Strategy
4.2.2 Replacement Strategy
4.2.3 Blue / Green Strategy
4.2.4 Choosing a Rollout Strategy
4.3 Summary
Chapter 5: Resource Management
5.1 Pod Scheduling
5.1.1 Specifying Pod Resources
5.1.2 Quality of Service
5.1.3 Evictions, Priority and Preemption
5.2 Calculating Pod Resources
5.2.1 Setting Memory Requests and Limits
5.2.2 Setting CPU Requests and Limits
5.2.3 Reducing Costs by Overcommitting CPU
5.2.4 Balancing Pod Replicas and Internal Pod Concurrency
5.3 Summary
Chapter 6: Scaling Up
6.1 Scaling Pods and Nodes
6.2 Horizontal Pod Autoscaling
6.2.1 External Metrics
6.3 Node Autoscaling & Capacity Planning
6.3.1 Cluster Autoscaling
6.3.2 Spare Capacity with Cluster Autoscaling
6.4 Building Your App to Scale
6.4.1 Avoiding State
6.4.2 Microservice Architectures
6.4.3 Background Jobs
6.5 Summary
Chapter 7: Internal Services and Load Balancing
7.1 Internal Services
7.1.1 Kubernetes Cluster Networking
7.1.2 Creating an Internal Service
7.1.3 Service Discovery
7.2 Ingress: HTTP(S) Load Balancing
7.2.1 TLS
7.3 Summary
Chapter 8: Node Feature Selection
8.1 Node Feature Selection
8.1.1 Node Selectors
8.1.2 Node Affinity and Anti-Affinity
8.1.3 Tainting Nodes to Prevent Scheduling by Default
8.1.4 Workload Separation
8.2 Placing Pods
8.2.1 Building Highly Available Deployments
8.2.2 Collocating Interdependent Pods
8.2.3 Avoiding Certain Pods
8.3 Debugging Placement Issues
8.4 Summary
Chapter 9: Stateful Applications
9.1 Volumes, Persistent Volumes, Claims and Storage Classes
9.1.1 Volumes
9.1.2 Persistent Volumes and Claims
9.1.3 Storage Classes
9.1.4 Single-pod Stateful Workload Deployments
9.2 StatefulSet
9.2.1 Deploying StatefulSet
9.2.2 Deploying a Multi-Role StatefulSet
9.3 Migrating/Recovering Disks
9.4 Summary
Chapter 10: Background Processing
10.1 Background Processing Queues
10.1.1 Creating a custom task queue
10.1.2 Signal Handling in Worker Pods
10.1.3 Scaling Worker Pods
10.1.4 Open Source Task Queues
10.2 Jobs
10.2.1 Running one-off tasks with Jobs
10.2.2 Scheduling Tasks with Cron Jobs
10.3 Batch task processing with Jobs
10.3.1 Dynamic Queue Processing with Jobs
10.3.2 Static Queue Processing with Jobs
10.4 Liveness Probes for Background Tasks
10.5 Summary
Chapter 11: GitOps: Configuration as Code
11.1 Production and Staging Environments using Namespaces
11.1.1 Deploying to our new namespace
11.1.2 Syncing Mutations from the Cluster
11.2 Configuration as Code the Kubernetes Way
11.3 Rolling Out Safely
11.3.1 Deployment Pipelines
11.4 Secrets
11.4.1 String-based (Password) Secrets
11.4.2 Base64 Encoded Secrets
11.4.3 File-based Secrets
11.4.4 Secrets and GitOps
11.5 Summary
Chapter 12: Securing Kubernetes
12.1 Staying up to date
12.1.1 Cluster and Node Updates
12.1.2 Updating Containers
12.1.3 Handling Disruptions
12.2 Deploying Node Agents with DaemonSet
12.3 Pod Security Context
12.4 Non-Root Containers
12.5 Admission Controllers
12.5.1 Pod Security Admission
12.6 Role-based Access Control (RBAC)
12.7 Summary
