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google-cloud-waf-operational-excellence

Review Google Cloud operations and develop guidance for monitoring, incident response, resource sizing, and automated deployments. Use framework-based questions and checklists to identify gaps in production readiness and plan ongoing operational improvements.

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Generates operational guidance for CI/CD deployment pipelines, observability, monitoring, logging, and incident management on Google Cloud based on the design principles and recommendations in the Operational Excellence pillar of the Google Cloud Well-Architected Framework (WAF). Use when the user asks about operations-related topics like capacity management, change management, incident and problem management, configuration management, deployment automation using infrastructure as code (IaC), or operational health checks for Google Cloud workloads.

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Good for

  • Reviewing production readiness
  • Planning monitoring and logging
  • Improving incident response procedures
  • Reviewing deployment automation
  • Checking resource sizing

Files included (1)

  • SKILL.md9.2 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Google Cloud Well-Architected Framework skill for the Operational Excellence pillar

Overview

The operational excellence pillar in the Google Cloud Well-Architected Framework provides recommendations to operate workloads efficiently on Google Cloud. Operational excellence in the cloud involves designing, implementing, and managing cloud solutions that provide value, performance, security, and reliability. The recommendations in this pillar help you to continuously improve and adapt workloads to meet the dynamic and ever-evolving needs in the cloud.

Core principles

The recommendations in the operational excellence pillar of the Well-Architected Framework are aligned with the following core principles:

Relevant Google Cloud products

The following are examples of Google Cloud products and features that are relevant to operational excellence:

  • Observability and monitoring

    • Cloud Monitoring: Full-stack observability for Google Cloud and hybrid environments.
    • Cloud Logging: Real-time log management and analysis at scale.
    • Error Reporting: Aggregates and displays errors for running cloud services.
    • Service Monitoring: Tools for defining and tracking Service Level Objectives (SLOs).
  • Automation and CI/CD

    • Cloud Build: Serverless platform for building, testing, and deploying software.
    • Cloud Deploy: Managed continuous delivery service for GKE, Cloud Run, and GCE.
    • Terraform / Infrastructure Manager: Managed service for Infrastructure as Code (IaC) automation.
    • Artifact Registry: Central repository for managing build artifacts and container images.
  • Resource management and optimization

    • Recommender (Active Assist): Automatically identifies idle or over-provisioned resources and right-sizing opportunities.
    • Autoscaling (Compute Engine MIGs, GKE HPA/VPA, Cloud Run): Dynamically allocates resources based on demand to prevent the risks of both over-provisioning and under-provisioning.
    • Resource Manager: Hierarchical management of resources across organizations, folders, and projects.
  • Incident response

    • Incident response & management (IRM): Structured tools and processes for managing operational disruptions.

Workload assessment questions

Ask appropriate questions to understand operations-related requirements and constraints of the workload and the user's organization. Choose questions from the following list:

  • Operational readiness and performance

    • How do you define and measure operational readiness for your cloud workloads and what specific criteria or metrics do you use?
    • Describe your process for defining, tracking, and achieving SLOs for your critical workloads.
    • How do you ensure that your workloads can seamlessly leverage multiple machine types or families for VMs during capacity constraints?
    • What is your strategy for modernizing your cloud resources to avoid technical debt and availability risks?
  • Incident and problem management

    • Describe your incident management process, including roles, responsibilities, and communication channels.
    • How do you conduct post-incident reviews (PIRs) to identify root causes and implement preventive measures?
  • Resource management and optimization

    • How do you ensure that your cloud resources are right-sized for your workloads, and what tools or techniques do you use?
  • Change automation

    • Describe your change management process, including approval workflows, testing procedures, and deployment strategies.
    • How do you automate deployments, ensure their consistency and manage configuration?
  • Continuous improvement

    • How do you ensure that your cloud operations are continuously adapting to meet evolving business needs and technological advancements?

Validation checklist

Use the following checklist to evaluate the architecture's alignment with operational excellence recommendations:

  • Operational readiness

    • A formal framework or set of criteria exists to assess operational readiness across staffing, processes, tooling, and governance before deployment to production.
    • Service Level Indicators (SLIs) based on user journeys, Service Level Objectives (SLOs), and error budgets are explicitly defined and monitored using Cloud Monitoring.
    • Workloads achieve continuous availability by using automated spillover mapping (via Managed Instance Groups (Flexible MIGs) with mixed-instance templates or GKE Custom Compute Classes) to seamlessly utilize cross-generation machine types across multiple zones in a region.
    • Workloads follow a "Migration-by-Design" strategy that leverages instance flexibility and automated spillover mapping to naturally transition workloads to newer hardware generations (evergreen capacity), decouple workloads from rigid, specific machine types to avoid capacity constraints, and align deployments with Google Cloud's most obtainable physical fleet to minimize availability risks.
  • Incident management

    • Incident response roles (such as an Incident Commander), communication channels, escalation paths, and automated response tasks are clearly defined and documented.
    • A structured, blameless post-incident review (PIR) process is followed for all major incidents to conduct thorough root cause analysis and implement preventive measures.
  • Change automation

    • All infrastructure changes are performed using Infrastructure as Code (IaC) stored in version control (using modern tools like Terraform) to ensure consistency and enable automated deployments.
    • CI/CD pipelines (using Cloud Build for continuous integration and Cloud Deploy for continuous delivery) are integrated with automated testing for all deployment changes.
  • Resource optimization

    • Resource utilization is regularly reviewed, and resources are right-sized using Recommender (Active Assist) and autoscaling to mitigate the risks of over-provisioning and under-provisioning.
  • Culture of improvement

    • The organization uses agile operational practices, iterative workflows, and adaptable operating models.
    • Leadership fosters a culture of continuous improvement, psychological safety, and ongoing learning.
    • Teams periodically review their cloud architecture against business goals, industry trends, and technological advancements.

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