Kubernetes Cost Optimisation: Practical Ways to Cut Your Cluster Bill
Why Kubernetes clusters waste money and the practical steps — right-sizing, autoscaling, spot capacity and visibility — that…
Serverless vs Containers in 2026: How to Choose
A practical comparison of serverless functions and container platforms for modern applications: cost, scaling, cold starts, portability and operations.
Two deployment models dominate modern cloud applications: serverless (functions and fully managed services) and containers (Docker images on Kubernetes or managed container services). Each shines in different situations.
Serverless strengths
- No servers to manage or patch
- Scales automatically from zero
- Pay only for what you use — ideal for spiky or low traffic
- Fast to build event-driven workflows
Serverless trade-offs
- Cold starts can add latency for some runtimes
- Execution time and resource limits
- Costs can exceed containers at high, steady load
- Vendor-specific services reduce portability
Container strengths
- Run almost anything, with full control over the runtime
- Predictable performance for steady workloads
- Portable across clouds and on-premise
- Mature ecosystem for complex systems
Container trade-offs
- More operational work, especially with Kubernetes
- You pay for capacity even when idle
- Requires more DevOps expertise
A practical decision guide
| Situation | Better fit |
|---|---|
| New MVP with uncertain traffic | Serverless |
| Background jobs and event processing | Serverless |
| Steady, high-throughput APIs | Containers |
| Long-running or GPU workloads | Containers |
| Strict portability requirements | Containers |
The middle ground
Managed container services that scale to zero blur the lines, offering container flexibility with serverless-like operations. For many teams, they are now the default starting point.
Do not forget the data layer
Managed databases, queues and storage matter as much as compute choice.
See our cloud services.
