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In this guide, we’ll dive into the Cloud Operations Suite for Google Kubernetes Engine (GKE) using a construction-site analogy. Just as each contractor on a build site has a specialized role, monitoring and logging act as your supervisors and record-keepers—helping you track progress, detect issues early, and keep your cluster running smoothly.

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Monitoring: Your Dedicated Supervisor

Monitoring in Cloud Operations Suite for GKE is like having a dedicated supervisor on-site. It collects, analyzes, and visualizes data about your cluster’s performance, health, and resource usage. With real-time visibility, you can spot anomalies or potential problems before they escalate.
The image is a slide titled "Cloud Operations for GKE" featuring the Google Cloud Platform logo and icons labeled "Collection," "Analysis," and "Visualize," along with a "Dedicated Supervisor" icon.
Key metrics you can track include:
  • CPU and memory utilization
  • Network traffic (ingress/egress)
  • Application-level statistics (request rates, error rates)
The image is a diagram titled "Cloud Operations for GKE" featuring the Google Cloud Platform logo, a "Dedicated Supervisor" icon, and three data-related icons connected by binary code.
GKE monitoring provides insight into:
  • Node health and resource pressure
  • Pod performance and status
  • Network connectivity and latency
The image is a slide titled "Cloud Operations for GKE" featuring the Google Cloud Platform logo. It highlights features like a dedicated supervisor and real-time visibility for node health, resource usage, and pod performance.
By continuously analyzing these metrics, you can detect issues such as CPU spikes, memory exhaustion, or network bottlenecks before they impact your applications.
The image is a slide titled "Cloud Operations for GKE" featuring the Google Cloud Platform logo and icons representing the detection of performance bottlenecks, resource exhaustion, and application errors.

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Logging: Your Detailed Record

Logging acts like a comprehensive site logbook—capturing every event, error, and warning generated by your GKE cluster, containers, applications, and services. These logs form a chronological record essential for troubleshooting, auditing, and understanding system behavior.
The image is a diagram titled "Cloud Operations for GKE" featuring the Google Cloud Platform logo, with a focus on logging and a chronological record of cluster, container, application, and services running on GKE.
Use cases for log analysis:
  • Trace request flows across microservices
  • Pinpoint root causes during incidents
  • Audit changes and security events
Leverage log-based metrics to create custom dashboards and alerts for application-specific events.

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Seamless Integrations and Defaults

When you provision a new GKE cluster on Google Cloud, Cloud Monitoring and Cloud Logging are enabled by default—providing Kubernetes-native observability out of the box. You can fine-tune which logs and metrics are ingested, ensuring you capture only what you need.
High log and metric retention can increase costs. Use log exclusions and metric filters to manage your budget.
GKE also integrates with Google Cloud Managed Service for Prometheus. This allows you to ingest, monitor, and alert on Prometheus metrics at scale—without managing your own servers.
IntegrationPurposeBenefit
Cloud MonitoringCollects cluster & pod metricsReal-time dashboards and alerting
Cloud LoggingAggregates logs from all sourcesCentralized search, analysis, and archive
Managed Service for PrometheusIngests Prometheus metricsScalable monitoring without self-hosted servers
The image is a diagram titled "GKE Dashboard" showing Prometheus in the center, with "Monitor" and "Alert" on either side, connected by icons.
For detailed installation and configuration steps, refer to the course materials or the official documentation below.

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