Plan workload deployment to GKE

In this lesson, you’ll learn how to plan workload deployment and manage resources on a Google Kubernetes Engine (GKE) cluster. We’ll cover the four primary workload types—stateless, stateful, batch, and daemons—and compare imperative versus declarative management approaches.

To deploy and manage containerized applications on GKE, you define controller objects in YAML files and apply them with kubectl or via the Kubernetes API.

GKE supports several workload types, including stateless applications, stateful applications, batch jobs, and daemons.

Stateless Applications

Stateless applications do not persist data internally; all session state is managed by clients or external services. They’re ideal for horizontal scaling and rolling updates.

• Examples:
  • NGINX
  • Apache Tomcat
  • Other web servers
• Primary object: Deployment

Pods under a Deployment are interchangeable and ephemeral, allowing you to scale out or update without data loss.

Stateful Applications

Stateful applications require persistent storage to retain data across restarts and replicas. Use PersistentVolumes and PersistentVolumeClaims for durable storage.

• Examples:
  • MongoDB
  • Apache ZooKeeper
• Primary object: StatefulSet

StatefulSet pods maintain unique network identities and stable storage. Updates and scaling follow a strict, ordered process.

Batch Jobs

Batch jobs run to completion and are well suited for parallel, finite tasks.

• Examples:
  • Sending notification emails
  • Video rendering
  • Complex numerical computations
• Primary object: Job

A Job runs Pods until they succeed, with controls for total completions and maximum parallelism.

Daemons

Daemon workloads run continuously on selected nodes to provide cluster-wide services.

• Examples:
  • Fluentd (log collection)
  • Monitoring agents
• Primary object: DaemonSet

A DaemonSet ensures one Pod per node (or per label selector), making it perfect for node-level background tasks.

Imperative vs. Declarative Management

GKE offers both imperative and declarative methods for managing workload objects:

• Imperative Commands
  Use one-off kubectl run, kubectl create, or kubectl delete commands for quick changes and immediate feedback.

• Declarative Object Configuration
  Store complete resource definitions in YAML and apply them with kubectl apply. Keep these files in version control for an audit trail.

• Directory-Based Declarative Configuration
  Organize YAML files in directories and run kubectl apply --recursive to apply updates across many resources. This scales well for large projects.

References

• Kubernetes Basics
• GKE Documentation
• kubectl Cheat Sheet