Red Hat Insights Resource Optimization is released

In this post:

• We announced the public beta of the Resource Optimization service last summer and have taken your feedback to enhance Resource Optimization in several areas. The service is now  generally available for our Red Hat Enterprise Linux (RHEL) customers.

• Resource Optimization provides actionable information based on data collected from your systems over 24 hours. 

• Resource Optimization currently supports RHEL 7.7+ and RHEL 8 hosts running on AWS. Give it a try and let us know your feedback.

Last summer we released the public beta of the Resource Optimization service. During public beta, we received a lot of feedback from customers, which we used to enhance Resource Optimization in several areas. We are now announcing that this service is generally available for our Red Hat Enterprise Linux (RHEL) customers.

Overview

Insights provides a single, consistent service for analyzing Red Hat products running on public cloud, hybrid cloud and on-premise infrastructures. Insights analyzes platforms and applications to predict issues, recommend actions, and track costs so enterprises can better manage their workloads. The Resource Optimization service aims to help existing and new Red Hat Enterprise Linux customers who need to grasp control over their public cloud spending.

It might be that the workload on your RHEL system is not as resource-heavy as it was expected, and thus a smaller instance is still perfectly suitable for your needs. Or, it might be that you’re constantly hitting the limits of your system and the service would deserve a larger system. Or, your host might be most of the time idle and, in that case, you might consider scheduling downtime for the system or optimize it in a different way. Or, maybe your instance is fine on average but suffering from peaks. 

In all of those cases, the Resource Optimization service can provide concrete and actionable suggestions to you.

Right-size your RHEL public cloud instances

Running your workloads in the public cloud requires estimating the instance size and monitoring the actual usage. More often than not, estimations become a game of guessing and resizing whenever the application is not working properly or the bill is too high. How do you select the most efficient instance type in a world where increasing memory may also require modifying CPU or disk? 

The Resource Optimization service looks at several metrics of your workload—CPU, memory, disk input/output—and compares these metrics to capacity allocation information provided by the public cloud provider. On RHEL 8 systems, Kernel Pressure Stall Information can optionally be enabled on the client systems to gather granular details and catch cases where resource utilization is fine on average but the system is suffering from occasional bottlenecks.

Using data from the last 24 hours, the Resource Optimization service considers each resource parameter in several distinct ways, thereby providing actionable data. These changes enable better resource allocation and help you to save money on your public cloud investment by recommending the right size of public cloud system for your use case. 

How to start using Resource Optimization

The Resource Optimization service relies on the Performance Co-Pilot (PCP), which is an open source monitoring software available on your RHEL host, to gather metrics and the Red Hat Insights client for Red Hat Enterprise Linux (insights-client) to connect to the Red Hat Hybrid Cloud Console and submit data. 

Our documentation describes the steps to enable and configure PCP and insights-client, or you can use the convenient Ansible playbooks we provide to simplify the configuration. Once you have configured a host, it will show up in Red Hat Insights immediately. Up to 24 hours may be required to receive enough data and show the first results of the Insights rightsizing analysis. You can access the results of the analysis from the Resource Optimization service on the Red Hat Hybrid Cloud Console.

Figure 1 - Resource Optimization example

Once the initial set of metrics is uploaded, you will see your configured systems in this service. In Figure 1, there are 11 instances of RHEL 8 hosts on Amazon Web Services (AWS). Resource Optimization service is telling you that six of the systems are idle, four of them were recently registered and are still waiting for data to be sent to Insights, and one of the systems is suffering a potentially problematic condition: pressure. By clicking on the system name, you can see more details as well as recommendations to address each condition.

Figure 2 - Suggestions example

We love your feedback

If you used Resource Optimization in public beta, you may notice the visible part of the application has changed completely: colors, columns, all registered systems are shown all the time, language, etc. Internally, the logic has also been rewritten from scratch to be able to provide concrete suggestions such as, “it seems your t3a.medium instance on AWS region us-east-2 does not have enough memory, you should consider moving from t3a.medium (0.0376 USD/hour) to either m5a.large (0.0658 USD/hour) or t3a.large (0.0752 USD/hour).” 

Like the other Insights services, Resource Optimization is included in your RHEL subscription. Resource Optimization currently supports RHEL 7.7+ and RHEL 8 hosts running on AWS. Azure, which was part of the public beta, will be re-added in the future.

In the future, we plan to add more public cloud providers as well as new metrics that will allow Red Hat to recommend more efficient ways of running your workloads in public clouds and eventually even show savings you might make by changing your system size and consumption model. 

Additionally, we are considering further capabilities, such as considering bursting allowances, forecasting usage of public cloud systems and providing you with detailed reporting to spot any kind of unexpected and unwanted behaviors. 

Any suggestion about the Resource Optimization service can be sent to us using the Feedback button inside of Insights–you can see it in Figure 1 on the lower right-hand side of the page. Please be sure to check this out and give Resource Optimization a try soon!