Your company has an application deployed on Anthos clusters (formerly Anthos GKE) that is running multiple microservices.
The cluster has both Anthos Service Mesh and Anthos Config Management configured.
End users inform you that the application is responding very slowly.
You want to identify the microservice that is causing the delay.
What should you do?
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A. B. C. D.A.
The best answer for this question is A. Use the Service Mesh visualization in the Cloud Console to inspect the telemetry between the microservices.
When an application is running slowly, it is important to identify the root cause of the issue so that it can be addressed. In this scenario, the application is running on Anthos clusters that have both Anthos Service Mesh and Anthos Config Management configured. The first step to identify the microservice causing the delay is to use the Service Mesh visualization in the Cloud Console to inspect the telemetry between the microservices.
Anthos Service Mesh provides a way to observe and control the communication between microservices in a Kubernetes environment. By using the Service Mesh visualization in the Cloud Console, you can see the telemetry data for each microservice and identify any latency or errors that may be occurring. The Service Mesh visualization provides a graphical representation of the communication between microservices, showing the traffic and latency for each request.
To use the Service Mesh visualization, you will need to have Anthos Service Mesh installed and configured in your Anthos cluster. Once you have done that, you can access the Service Mesh visualization in the Cloud Console by navigating to the Anthos Service Mesh page and selecting the appropriate cluster and namespace.
In the Service Mesh visualization, you can select a specific microservice and view its telemetry data, including request latency and errors. By analyzing the telemetry data, you can identify the microservice that is causing the delay and take steps to address the issue.
Option B, using Anthos Config Management to create a ClusterSelector and inspecting the configurations of filtered workloads, may be useful for identifying configuration issues that could be causing the delay, but it may not provide insights into the root cause of the issue.
Option C, using Anthos Config Management to create a namespaceSelector and inspecting the configurations of filtered workloads, is similar to Option B, but focuses on a specific namespace rather than the entire cluster.
Option D, reinstalling Istio using the default Istio profile in order to collect request latency and evaluate telemetry data, is not necessary as Anthos Service Mesh already provides the required telemetry data. Additionally, reinstalling Istio may cause service disruption and should only be done as a last resort.