AWS, Azure, and GCP all have options that enable you to rightsize or scale your cloud environment. But rightsizing in cloud computing isn’t a “set and forget” activity. For continued success, a long-term policy for cloud cost optimization is essential and will ensure the ongoing cost-effectiveness of your enterprise’s cloud.
The potential of cloud resources is huge. Instead of having to wait months to acquire and install new servers, developers can spin up new instances in a matter of seconds. This allows enterprises to embark on exciting new ventures that were previously impossible.
Today, providers offer so many compute instance types that organizations end up using an instance size that is larger than they need. Together with idle resources, overprovisioned instances are the top contributor to public cloud spending waste.
A rightsizing policy will make sure that all future projects and systems are managed in a way that is efficient and cost-effective. And when managed successfully, it can reduce your cloud costs by as much as 36%.
A rightsizing strategy should consider:
One of the dangers of rightsizing is compromising business performance. By understanding the operational expectations of each workload, you can optimize without affecting service.
When you look for rightsizing opportunities, consider batch jobs. They can often take a bit longer to run without any immediate business impact.
To judge realistic operational needs, don’t look at average use, look at spikes. Spikes in usage are where you can achieve major cost savings while ensuring that operational needs are always met.
You’ll need seasonal data to make an accurate assessment. And that will depend on the nature of your application. Some enterprises need to look at monthly trends, while others need to get granular and consider hourly spikes.
You need to be able to see the whole picture. Every instance has four core factors: CPU, memory, disk IOPS, and network speed.
The performance characteristics of the workload include long and short timeframe demands. Are they synchronous, asynchronous, or batch? You need to see exactly how they are being used to identify your opportunities.
Executing your rightsizing measures will require some amount of downtime. So, once opportunities have been identified, you must consider the risk of rightsizing. Complex eco-systems with many dependencies are at a higher risk of disruption than smaller environments.
Your rightsizing strategy needs to consider upstream and downstream dependencies. In complex cloud environments, your rightsizing optimizations mustn’t affect other parts of your ecosystem.
Downsizing capacity may present a risk to the throughput and response time of an application when under peak load. Conversely, changing the memory footprint of a database service may present a stability risk.
To scale this capability and avoid false-positive test results, it is critical to use automated performance test analysis. This will speed the route to optimization and minimize the risk of service-impacting incidents when the optimizations go live.
Rightsizing your workloads is a continuous exercise. The cloud is a dynamic environment, so your rightsizing strategy should be too.
Set monthly review periods to maintain control of your cloud costs.
Your rightsizing strategies must adjust to new offerings and increased cloud usage. Having an effective strategy won’t just make cloud migration easier, but your ongoing optimizations, too.
And the more you rightsize, the fewer optimizations you’ll see, and the more streamlined your cloud environment will be.
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