Does it support structured logging formats?

Absolutely, it provides standardized JSON logging schemas to ensure your application logs are easily searchable and parseable by Cloud Logging.

How does this skill help with GCP cost management?

It provides templates for log exclusion filters and sampling strategies to reduce ingestion volume and storage costs in Google Cloud Logging.

Can this skill help me write complex Log Explorer queries?

Yes, it includes pre-built patterns for regex matching, severity filtering, and resource correlation to help you find logs quickly.

When should I use this skill?

Invoke this skill when debugging production issues on GCP, setting up new alert policies, or optimizing your application's observability stack.

GCP Observability & Monitoring

Name: GCP Observability & Monitoring
Author: fcakyon

byfcakyon

•

247

Analytics & Monitoring

Optimizes Google Cloud logging and monitoring with battle-tested patterns for structured logs, advanced filtering, and cost-efficient observability.

About

GCP Observability & Monitoring is a specialized Claude Code skill designed to streamline the management of Google Cloud Platform (GCP) logs, metrics, and traces. It provides developers with ready-to-use patterns for structured JSON logging, complex Log Explorer queries, and multi-condition alert policies. Whether you are debugging production issues, reducing cloud costs via exclusion filters, or establishing a robust observability workflow, this skill guides Claude in implementing GCP-specific best practices to ensure high-performance, cost-effective infrastructure monitoring.

Key Features

Structured JSON logging templates with severity level guidance
247 GitHub stars
Alert policy design patterns to reduce alert fatigue
Advanced Google Cloud Logging query patterns and regex filters
Strategic advice on balancing logs, metrics, and distributed tracing
Log cost optimization through exclusion filters and sampling strategies

Use Cases

Designing cost-effective logging strategies for high-volume Cloud Run services
Implementing structured observability across distributed microservices on GCP
Debugging complex production failures using advanced GCP log filtering

About

Key Features

Structured JSON logging templates with severity level guidance
247 GitHub stars
Alert policy design patterns to reduce alert fatigue
Advanced Google Cloud Logging query patterns and regex filters
Strategic advice on balancing logs, metrics, and distributed tracing
Log cost optimization through exclusion filters and sampling strategies

Use Cases

Designing cost-effective logging strategies for high-volume Cloud Run services
Implementing structured observability across distributed microservices on GCP
Debugging complex production failures using advanced GCP log filtering