Right-sizing of Nodes in the Cloud

Info

Right-sizing of nodes in the cloud is important to save costs and resources (energy & embodied carbon).

πŸ”— References

KubeCon 2024 – Saving the Planet One Cluster at a Time - Operationalising Sustainability in Kubernetes

better: fewer nodes (bigger instances)

The Often Overlooked Consideration for Energy-Efficient Computing? Node Sizing. | by Brendan Kamp | Nov, 2023 | The Green Coder

Smaller doesn’t always mean less. While the flexibility and initial budget-friendliness of using smaller nodes are tempting, they easily lead to higher energy use, lower utilisation, and spiraling inefficiencies.

While this is not a call to just go for the biggest machines available to us, for now, the quickest way for earth-conscious IT practitioners to help reduce carbon emissions is to revisit our node size calculations in the past and see if we might be better off altering our machines to better reflect the value that we are creating.

AWS Cost Management – Right Sizing

Right sizing is the process of matching instance types and sizes to your workload performance and capacity requirements at the lowest possible cost. It’s also the process of looking at deployed instances and identifying opportunities to eliminate or downsize without compromising capacity or other requirements, which results in lower costs.

AWS Well-Architected Framework:

amazonwebservices.2023.sustainabilitypillaraws (pg. 65)

SUS05-BP01 Use the minimum amount of hardware to meet your needs

Use the minimum amount of hardware for your workload to efficiently meet your business needs.

Common anti-patterns:

  • You do not monitor resource utilization.
  • You have resources with a low utilization level in your architecture.
  • You do not review the utilization of static hardware to determine if it should be resized.
  • You do not set hardware utilization goals for your compute infrastructure based on business KPIs.

Benefits of establishing this best practice:
Rightsizing your cloud resources helps to reduce a workload’s environmental impact, save money, and maintain performance benchmarks.