Kubernetes Security and Observability by Alex Pollitt & Manish Sampat

Author:Alex Pollitt & Manish Sampat [Alex Pollitt]
Language: eng
Format: epub
Publisher: O'Reilly Media, Inc.
Published: 2021-11-01T16:00:00+00:00

Figure 5-2. Components of an observability tool for Kubernetes

Figure 5-2 shows that you need the following components for your observability implementation:

Telemetry Collection

As mentioned, your observability solution needs to collect telemetry data from various sensors in your cluster. It needs to be distributed and Kubernetes-native. It must support sensors across all layers, from L3 to L7. It also needs to collect information about Kubernetes infrastructure (e.g., DNS and API server logs) and Kubernetes activity (these are known as audit logs). As described before, this information must be collected in the context of deployments and services.

Analytics and Visibility

In this layer, the system must provide visualizations that are specific to Kubernetes operations (e.g., service graph, Kubernetes platform view, application views). We will cover some common visualizations that are native to Kubernetes. We recommend you pick a solution that leverages machine learning techniques for baselining and reporting anomalies. Finally, the system needs to support the ability for operators to enable pod-to-pod packet capture (note that this is not the same as enabling packet capture on the host interface, as the pod-level visibility is lost). We will cover this in the next section.

Security and Troubleshooting Applications

The observability system you implement must support distributed tracing as described in the previous section to help troubleshoot applications. We also recommend the use of advanced machine learning techniques to understand Kubernetes cluster behavior and predict performance or security concerns. Please note that this is a new area and there is ongoing innovation in it.

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