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You’ve probably heard about Red Hat Insights and different services that improve your operational, business and security experience with all Red Hat platforms (if not, I recommend reading the Red Hat Insights blog channel). The analytical information that Insights collects to power these services has a much greater impact than you might think. In this blog post, we’ll give you an overview of where Insights analytics are being used (and you probably didn’t even notice). Although this is very much focused on experience with Red Hat OpenShift, less advanced yet similar capabilities are available for other platforms.

Providing contextual information to our teams 

Let’s talk quickly about the complexity of Red Hat OpenShift. The platform is a Kubernetes (k8s) distribution with many components on top of it, distributed as operators in which a lot of component-operational knowledge is encoded (see OpenShift architecture).  The platform is designed to scale from a handful of machines and applications to host thousands of applications and service millions of users. There’s a complexity that such a platform brings including the flexibility it gives to our customers. With all that, it’s important for us at Red Hat to give you the best experience with our product in any situation, and support the scenarios specific to your business. We do that by analyzing remote health data (telemetry and Insights information) and feeding aggregated information to our support and product teams (More about remote health monitoring).

Red Hat's engineering team is notified when a faulty behavior occurs. We use aggregated and anonymized fleet-level customer information (see our privacy statement for more information) to help provide solutions. Every time a particular combination of signals is detected across the fleet, Insights immediately notifies component engineering owners and provides detailed information about the environment where such a problem occurs. The data we have collected over time allows us to stay one step ahead of potential issues and we can fix them before anyone experiences a problem. 

Improving the support experience

Bugs happen, and when you open a support case, we use the Insights analytics immediately. Even before you open a support case, we offer you potential solutions for problems we see in your cluster. These are Insights Advisor recommendations based on known issues that the Red Hat support team has already solved for other customers. When you encounter a problem, we’ve likely seen it before, and thanks to Insights data, the support team can match your problem with an existing solution.

Another advantage of running your clusters connected to Insights services is that we have direct access to the latest snapshot of your cluster’s analytics data. The support team has a large set of internal checks that helps them narrow down the problem to a set of potential offenders and thus focus on components and configurations that are most likely to be the root cause. Chances are that you don’t have to tell us much more in the support case. We can jump right away on the available data using the results of machine learning-powered analytics to match your issue to a known problem or suggest potential solutions. 

Screenshot of the Red Hat customer support request form

What if you’re new to OpenShift? You’re setting up your infrastructure and working with our customer experience team solution architects to create an architecture that best fits your needs. Insights helps here, too. Our teams use Insights to validate architecture, help your cluster follow best practices and to confirm that there are no potential problems or conflicts. This helps the team give you the best experience with OpenShift from day one. But Insights doesn’t stop there. It helps continuously validate your cluster and prevent potential issues.  A lot of that happens behind the scenes and you won’t notice it. 

Safer and smoother upgrades

The launch of OpenShift 4 brought a completely new experience in cluster upgrades. The whole process takes less effort and helps to confirm that the right components are updated, minimizing downtime. Have you ever wondered how it’s done? Insights is a big part of the whole upgrade experience. The analytics data help us verify that new releases do not bring any issues to the platform. OpenShift automatically rejects upgrade paths whenever there’s any sign of a potential problem and offers your OpenShift instance a combination of updated components that are proven to work. With this approach, we’ve minimized the number of failed upgrades and reduced the risk of downtime in your infrastructure. 

Assisting with day-to-day operations 

Insights analytics is part of the standard operating workflow for every site reliability engineering (SRE) team. They will have access to all the information mentioned above, and can use it to validate upgrades, prevent issues, schedule maintenance, etc. On top of that, teams can also verify workflows to help customers follow best practices for Kubernetes applications and avoid mistakes that would have a performance or availability impact on the platform.

As you can see, on top of the Red Hat Insights services for OpenShift such as Advisor, Cost Management, Subscriptions and recently added a Vulnerability service, there is another use for the analytics data. Most of the time it stays hidden from you, but it brings huge value to our support and product engineering teams and allows us to improve both the product and your experience with Red Hat. 

We are always looking for additional use cases and welcome any feedback that can help improve our products. Please submit your suggestions through the feedback form in the Red Hat Customer Portal.

Sobre los autores

Radek Vokal started with Red Hat in 2004 as a software engineer, later lead team responsible for core Red Hat Enteprirse Linux components and core Kubernetes teams. Currently he is the Senior Manager of Product Management for Insights OpenShift services and is based in Brno, Czech Republic.

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Red Hatter since 2010, Dosek's professional career started with virtualization technologies and transformed via variety of roles at Red Hat through to hybrid cloud. His focus is at improving product experience with assistance of Red Hat Insights.

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