When you hit 70% CPU or memory utilization level on a server or a virtual machine that is running your solution, it’s probably time to think about what your next option would be.
The obvious solution is to upgrade your server configuration to get more CPU power, memory or storage.
Server sizing estimate based on forecasted future workloads is always prone to error and could increase your operational costs significantly. Moreover, you would incur not only the upgrade costs, you’ll have to pay for the upgrade, during the upgrade the system will be unavailable. This may not be acceptable to your customers if you have promised a high availability to your customers.
Cloud computing offers you many options for elastically scale your resources in response to variations in workload.
e.g. Azure Auto Scaled VM allows you to horizontally expand the number of VMs. As an when the application workload increases above the set trigger point, Azure adds VMs to handle the additional workload. The added VMs are removed when workload decreases. This allows your application to scale on demand while delivering optimal performance and maintain your high availability promise to your customers. And with the Azure Pay-per-use model, you only pay for the time the additional VMs were used.
Cloud technology can help you ensure availability, performance, scalability and security of your systems but it could be challenging exercise when your primary focus is on delivering value to your customers without affecting the current service levels.
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