Stay proactive to maintain peak cloud performance

Performance has to be built into your applications from the start, then maintained and monitored regularly

Stay proactive to maintain peak cloud performance

There is an expectation of performance in the cloud, then there is actual cloud performance. In many cases, they don’t match. Why?

Most platforms, public clouds included, provide good performance at the outset. But over time, databases get bigger, applications grow more complex, and the platforms themselves become harder to manage. The result is much poorer performance.

First, let’s understand the factors in play. Most cloud-based platforms, such as a virtual Linux server, work exactly like the physical server you had down the hall for the last 15 years. If they aren't configured and managed properly, they slow down exactly like your aging PCs and servers.

But most performance issues are caused by applications. Developers don’t focus on performance, hoping that the power of the cloud will provide the extra horsepower. Not only do they implement functionality in inefficient methods that waste computing resources, they also make the apps more complex than needed, again squandering computing resources.

Faster servers and PCs can mask that waste, but it’s still there. It gets worse over time. In other words, developers often engineer poor performance in the applications, and their applications perform poorly whether on a cloud or not.

Here’s what you can do to keep performance strong:

  • Engineer performance into your applications, by considering it in the design and structure of the applications. You need to do that not only for the initial application version but also for the updates and upgrades you make over time.
  • Test for performance, using devops processes and test streams. You must validate performance before deploying applications to the cloud.
  • Give monitoring and management priority after deployment, such as by looking at logs and performance trends. And be able to understand what those signals tell you about possible causes.

Performance has to be proactively designed and managed. When performance is not meeting expectations, chances are you need to make deep code changes, not simply tune here and there. After all, performance is core to the application, so the factors that hinder it are usually core as well.