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#

Decision Criteria#

The choice comes down to four questions:

Comparing Serverless Platforms#

Choosing a serverless platform is not about which one is “best.” Each platform makes different tradeoffs around cold start latency, execution limits, pricing granularity, and ecosystem integration. The right choice depends on what you are building, what cloud you already use, and which constraints matter most.

This framework compares the four major serverless compute platforms as of early 2026: AWS Lambda, Google Cloud Run, Azure Functions, and Cloudflare Workers.

Choosing a Service Mesh#

A service mesh moves networking concerns – mutual TLS, traffic routing, retries, circuit breaking, observability – out of application code and into the infrastructure layer. Every pod gets a proxy that handles these concerns transparently. The control plane configures all proxies across the cluster.

The decision is not just “which mesh” but “do you need one at all.”

Do You Actually Need a Service Mesh?#

Many teams adopt a mesh prematurely. Before evaluating options, identify which specific problems you are trying to solve:

EKS vs AKS vs GKE: Choosing a Managed Kubernetes Provider#

All three major managed Kubernetes services run certified, conformant Kubernetes. The differences lie in networking models, identity integration, node management, upgrade experience, cost, and ecosystem strengths. Your choice should be driven by where the rest of your infrastructure lives, your team’s existing expertise, and specific feature requirements.

Feature Comparison#

Control Plane#

GKE has the most polished upgrade experience. Release channels (Rapid, Regular, Stable) provide automatic upgrades with configurable maintenance windows. Surge upgrades handle node pools with minimal disruption. Google invented Kubernetes, and GKE reflects that pedigree in control plane operations.

Managed Kubernetes vs Self-Managed#

The fundamental tradeoff is straightforward: managed Kubernetes trades control for reduced operational burden, while self-managed Kubernetes gives you full control at the cost of owning everything – etcd, certificates, upgrades, high availability, and recovery.

This decision has cascading effects on team structure, hiring, on-call burden, and long-term maintenance cost. Choose deliberately.

Managed Kubernetes (EKS, AKS, GKE)#

The cloud provider runs the control plane: API server, etcd, controller manager, scheduler. They handle patching, scaling, and high availability for these components. You manage worker nodes and workloads.