In-depth performance metrics are an essential component of cloud migration strategies. They’ll help you make the right choice for several critical cloud decisions, from calculating cloud TCO, to prioritizing applications for migration, and to right-sizing your cloud for performance-cost optimization. In fact, companies that migrate to the cloud without the right performance metrics and analyses typically spend 48% more than they need to.
The performance metrics organizations need to collect and analyze include:
- Peak CPU Utilization
- Allocated and Peak RAM usage
- Observed Storage On-Premises (capacity and current occupancy)
- Disc IOPS and Bandwidth
- Usage Patterns (how often compute and storage resources are on, idle, and unused)
These performance metrics enable companies to make the following 5 key decisions to inform their cloud migration strategies:
- Calculate Cloud TCO: An on-premises to cloud “like-to-like” comparison (what cloud costs would be if you migrated workloads without right-sizing) will not yield a correct cloud TCO - in fact, many times it will be too high. Detailed performance metrics can help you see what resources you actually need in the cloud so that you can accurately calculate cloud TCO based on right-sizing--and avoid the mistake of acting on an inaccurate calculation.
- Identify Best Compute and Storage Options for Each Workload: All three public clouds offer a variety of compute and storage options. The only way to identify the optimal compute and storage options for each workload you’re migrating is to analyze the current performance profile of each. This analysis, along with predictive analytics, will allow you to find matching compute and storage configurations in the cloud that will ensure you meet that workload’s performance requirements.
- Calculate TCO of Each Workload: The performance profile of each workload informs usage and which instances to move to, which enables you calculate the cost of the workload in the cloud. By understanding the TCO of each workload before migrating, companies can accurately forecast costs and ensure they stay within budget at each phase of their migration.
- Determine Migration Order: Having a thorough understanding of performance metrics for each workload can help organizations identify which applications use the most or least CPU resources. The machines consuming the least resources should be migrated in initial phases to reduce risk in the event there are issues, and those that consume more should be moved in later phases.
- Select Workloads Eligible for Migration: Migrating to the cloud isn’t the right choice for every application, but performance metrics can help you weigh your options and determine whether there are suitable options for each workload in the cloud. Performance analysis can help companies find options in the cloud that enable them to match on-premises performance—but sometimes there aren’t good options in the cloud. A workload might have a performance profile in which available compute and storage options won’t enable cost-performance optimization.
Automating Performance Collection and Analysis
Not only are manual attempts to gather and analyze performance metrics extremely time-consuming, but they're also prone to error. Organizations that undertake a manual approach to performance analysis often end up either paying for more than they need or finding themselves in a scenario where they don’t have enough capacity to meet a sudden demand. When it comes to planning cloud migrations, automating the collection and analysis of performane metrics significantly improves the speed and accuracy of your cloud decision-making.
For instance, it’s essential to collect performance metrics at frequent intervals over long periods of time so that performance profiles include the true peaks and valleys of usage instead of an average. The “averaging” approach that many companies use will cause them to over- or under-provision their resources instead of right-sizing their cloud. Doing this manually is extremely challenging, if not impossible.
At Cloudamize, our analytics platform collects performance data at 5-minute intervals to ensure that your performance profile includes peaks and valleys. It then compares each workload’s on-premises performance profile against the millions of possible cloud options to find the optimal compute and storage options to migrate to. The platform can predict the performance of workloads in the cloud and recommends the compute and storage options that will meet performance requirements at the lowest cost. The precision at which this is all done begins with the automated performance analysis.
There is simply no way to plan your migration accurately without using in-depth performance metrics and analysis. Collecting and analyzing these metrics using automation will significantly improve the ease and speed of migration planning and execution.