Gcp Cloud Monitoring Comprehensive Observability Slo Strategy

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Your enterprise operates a distributed microservices architecture deployed across Compute Engine virtual machines, Google Kubernetes Engine (GKE) clusters, and Cloud Run services located in multiple Google Cloud projects. You need to implement a centralized observability strategy in Google Cloud Monitoring to collect and aggregate metrics, logs, and distributed traces from both infrastructure and applications to track Service-Level Objectives (SLOs) and application key performance indicators (KPIs) through unified dashboards.

Which strategy aligns with Google Cloud recommended best practices?

Configure VPC Packet Mirroring across all Virtual Private Clouds to capture network traffic for metrics, create log exclusion filters to drop non-error logs, and export raw unaligned time-series data to BigQuery every minute for real-time dashboarding.

Instrument services with OpenTelemetry to export OTLP metrics and traces; deploy the Ops Agent on Compute Engine with OTLP/Prometheus receivers, enable Google Cloud Managed Service for Prometheus on GKE, configure a central scoping project with a multi-project metrics scope, and build custom Cloud Monitoring dashboards combining metric widgets, log-based metrics, and trace data.

Instrument applications using direct vendor-specific Cloud Monitoring API client libraries, maintain separate individual scoping projects for each workload, and rely exclusively on predefined Google Services dashboards for SLO tracking.

Install standalone OpenTelemetry Collector instances on every VM while disabling the Ops Agent, deploy custom Prometheus servers in every GKE cluster with Cloud Storage log sinks, and write custom Cloud Functions to poll the Cloud Monitoring API for dashboard updates.

Professional Cloud DevOps Engineer

Gcp Cloud Monitoring Comprehensive Observability Slo Strategy

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