2V0-71.23 Question 42
Select 3An organization is running production workloads on Kubernetes clusters managed by VMware Tanzu Kubernetes Grid (TKG). The operations team wants to implement an observability strategy to monitor the health and performance of the clusters and applications. Which components are critical to achieving effective Kubernetes observability?
- A
Logs, metrics, and traces from Kubernetes and application workloads
- B
A centralized logging and monitoring platform that integrates with Kubernetes
- C
Direct access to the Kubernetes API Server for real-time debugging
- D
Dashboards and visualizations to analyze cluster and application performance
- E
Deployment of multiple Kubernetes clusters for redundancy and high availability
Show answer and explanation
Correct answers: A, B, D
Explanation
Effective observability for Kubernetes requires collecting logs, metrics, and traces, using a centralized platform to analyze this data, and leveraging dashboards to gain insights. These components work together to provide a comprehensive view of cluster and application health, enabling proactive issue resolution and performance optimization.
- A. Correct.
Logs, metrics, and traces are the fundamental data sources used in observability for Kubernetes. They provide insights into system behavior, application performance, and issues.
- B. Correct.
A centralized platform is critical as it aggregates data from multiple sources, enabling easier monitoring and troubleshooting across clusters and applications.
- C. Incorrect.
Direct access to the Kubernetes API Server is useful for debugging but is not a requirement for observability. Observability focuses more on metrics, logs, and traces rather than direct API interaction.
- D. Correct.
Dashboards and visualization tools help interpret logs, metrics, and traces effectively, enabling teams to make informed decisions based on the data.
- E. Incorrect.
While deploying multiple clusters improves availability, it is not directly related to observability. Observability focuses on monitoring and understanding the behavior of clusters and applications.