Choosing Kubernetes Workload Types: Deployment vs StatefulSet vs DaemonSet vs Job

Choosing Kubernetes Workload Types#

Kubernetes provides several workload controllers, each designed for a specific class of application behavior. Choosing the wrong one leads to data loss, unnecessary complexity, or workloads that fight the platform instead of leveraging it. This guide walks through the decision criteria and tradeoffs for each type.

The Workload Types at a Glance#

Workload Type Lifecycle Pod Identity Scaling Model Storage Model Typical Use
Deployment Long-running Interchangeable Horizontal replicas Shared or none Web servers, APIs, stateless microservices
StatefulSet Long-running Stable, ordered Ordered horizontal Per-pod persistent Databases, message queues, distributed consensus
DaemonSet Long-running One per node Tied to node count Node-local Log collectors, monitoring agents, network plugins
Job Run to completion Disposable Parallel completions Ephemeral Batch processing, migrations, one-time tasks
CronJob Scheduled Disposable Per-schedule run Ephemeral Periodic backups, cleanup, scheduled reports
ReplicaSet Long-running Interchangeable Horizontal replicas Shared or none Almost never used directly

Decision Criteria#

The choice comes down to four questions:

DaemonSets: Node-Level Workloads, System Agents, and Update Strategies

DaemonSets#

A DaemonSet ensures that a copy of a pod runs on every node in the cluster – or on a selected subset of nodes. When a new node joins the cluster, the DaemonSet controller automatically schedules a pod on it. When a node is removed, the pod is garbage collected.

This is the right abstraction for infrastructure that needs to run everywhere: log collectors, monitoring agents, network plugins, storage drivers, and security tooling.