Kubernetes for Developers

Kubernetes for Developers
brief contents
contents
preface
acknowledgments
about this book
Who should read the book
How this book is organized
About the code
liveBook discussion forum
Additional online resources
about the author
about the cover illustration
Part 1—Getting started with Kubernetes
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
1.2.4 When (not) to use Kubernetes
Summary
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 multistage 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
Summary
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 Imperative 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
Summary
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 Re-create strategy
4.2.3 Blue/green strategy
4.2.4 Choosing a rollout strategy
Summary
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
Summary
Part 2—Going to production
6 Scaling up
6.1 Scaling Pods and nodes
6.2 Horizontal Pod autoscaling
6.2.1 External metrics
6.3 Node autoscaling and 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 tasks
Summary
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 Securing connections with TLS
Summary
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 Co-locating interdependent Pods
8.2.3 Avoiding certain Pods
8.3 Debugging placement problems
8.3.1 Placement rules don’t appear to work
8.3.2 Pods are pending
Summary
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 multirole StatefulSet
9.3 Migrating/recovering disks
9.4 Generic ephemeral volume for scratch space
Summary
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 CronJobs
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
Summary
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
11.3.2 Continuous deployment with Cloud Build
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
Summary
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
12.5.2 Balancing security with compatibility
12.6 Role-based access control
12.7 Next steps
12.7.1 Network policies
12.7.2 Container isolation
12.7.3 Cluster hardening
Summary
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