The application performance is good but what about efficiency? Why is the balance of performance and efficiency in your observability strategy important?

Costs are an important piece of all company strategies and can define the success of a project or for an entire company. High performance is important but at what cost?

The most important objective of deploying observability solutions is to improve the reliability, performance and availability of the applications, but how can we guarantee we’re not overutilizing the infrastructure to deliver good performance?

We can find the root cause of the problems using observability, but how can we identify exactly which infrastructure component we need to expand to improve the application performance? And how can we automate the infrastructure changes to do it?

The following example provides an idea on how to pursue performance with efficiency at the same time, contributing to the teams and companies on how to deliver solutions not covering only performance but also using the IT infrastructure efficiently.

To exemplify it we need an application performance management tool (APM) and an application resource management tool (ARM). I will use two IBM solutions to demonstrate it, the IBM® Instana® platform as the APM solution and IBM Turbonomic® software as the ARM solution.

The APM solution will identify the bottlenecks and performance issues, define the service-level objective (SLO), and so on. And the ARM will identify the infrastructure utilization, comparison of cloud vendor prices and so on. The following image shows the application performance using the APM tool and, as you can see, the application is running well, and the latency, error rate and traffic are pretty good:

But let’s go deeper to see if the SLO is being satisfied. That’s why it’s really important to set the SLOs.

As you can see the SLOs are also good but it’s important to emphasize that we had a peak on the graphs and we can identify the problem:

By navigating into Instana analytics, we can identify exactly when it happened:

And by going deeper into the specific transaction, we can see where the problem is:

So, using the Instana platform, we identified the performance problem that’s exactly a query running on a specific host. Is it a resource problem? Not sure yet.

Now, let’s go to the other part of this demonstration, the Turbonomic software.

The Turbonomic software will help us identify two things, the efficiency of the IT resources used by the application and the possibility to size up the IT resources to improve the application’s performance.

First of all, it’s good to show Turbonomic abstracts the Instana data, in other words, how the Turbonomic software is associating the Instana entities.

As you can see in the following image, the application perspective is associated with the business application, endpoints are associated with business transactions, service is associated with service and processes are associated with the application component:

Let’s see the same application now on the Turbonomic software. As you can see in the following image, at the left we have the topology created by the Turbonomic software, since the data centers and infrastructure components through the business application are showing the status of the components in terms of efficiency and performance in yellow, green and red. On the right we can see, for example, some pending actions:

By clicking on the pending actions, we’ll see the complete list of possible improvements on the infrastructure—29 actions—where those actions will help to save 129 Gb of vmem and 20 vCPUs just for this application. Imagine if it was the entire company. By accepting the actions, it can be automatically changed and we’ll have an application with the same performance but using less IT resources:

Related to the performance improvements, the Turbonomic software also recommended some actions as we can see in the following image. The Turbonomic software also gets the SLO from the Instana platform to compare and check when the SLO is violated:

We hope this article helps you define observability strategies, not only concerning performance but also efficiency, allowing you to deliver high-performance and efficient solutions.

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