In today’s cloud-driven landscape, businesses across various industries use virtual machine (VM) services from major cloud providers like AWS EC2, Azure VM, and GCP Compute Engine to leverage their power and flexibility. These services provide the foundational infrastructure for running diverse workloads and applications in the cloud. However, to get the most out of these services, organisations must prioritise cost optimisation.

This blog post will provide you with a comprehensive checklist to ensure maximum cost savings on VM services. This guide will equip you with the essential knowledge to optimise your VM costs effectively.

1. Identifying Underutilised VMs
Utilise AWS CloudWatch, Azure Monitor and GCP Compute Engine Monitor to analyse performance metrics and usage patterns, enabling cost optimisation through downsizing or terminating underutilised VMs.

2. Deleting Unused VMs - Eliminating Wasteful Expenses
Regularly assess and decommission unnecessary VMs to minimise wasteful expenses and optimise cost efficiency.

3. Leveraging Reservations - Cost Savings for Long-Term Workloads
Maximise cost savings by identifying suitable workloads and implementing effective reservation strategies for long-term usage.

4. Spot Instances
Explore Spot Instances (AWS), Spot VMs (Azure), and Preemptible VMs (GCP) to identify non-critical workloads and strategically leverage them for optimised cost savings.

5. Optimising Storage Costs - Tackling Unattached Volumes
Unattached volumes can significantly impact costs. Efficiently review and manage storage volumes, removing or detaching unattached ones to reduce expenses.

6. Minimising Idle Costs - Maximising IP Address Efficiency
Understanding the cost implications of unattached IP addresses and actively managing their allocation to optimise costs. Regularly reviewing and releasing unattached IPs ensures efficient utilisation of resources.

7. Opting for Burstable VMs - Efficiently Handling Workload Spikes
Introducing burstable instances like AWS T3 and Azure B-series for optimised performance and cost balance during workload fluctuations.

8. Scheduling Dev/Non-Prod Instances - Optimising Usage and Costs
Maximise efficiency in dev/non-production environments by scheduling instances during active periods and reducing costs by pausing or shutting down instances during idle periods.

9. Rightsizing Your VMs - Matching Workloads, Saving Costs
Evaluate resource requirements, identify over provisioned instances, and optimise VM sizes to align with workload demands, resulting in cost savings.

10. Auto Scaling
Maximise resource utilisation and cost efficiency by leveraging AWS Auto Scaling Groups for automated, demand-based scaling.

By implementing these strategies, organisations can achieve substantial cost savings and optimise their cloud investments. Start implementing these best practices today and take control of your VM costs for a more efficient and cost-effective.