인프라·DevOps 스킬

Configure Cloud Logging within one Google Cloud project. Set storage locations, retention periods, routing rules, and viewing permissions; create metrics from logs; and adjust stored volume through exclusions or sampling, which retains only a portion of entries.

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• Set regional log storage and retention periods
• Restrict access to sensitive logs
• Count specific errors with logs-based metrics

Deploy and manage applications on Cloud Run using source code or container images. Choose services for web requests, jobs for tasks that finish, or worker pools for continuous background processing, with guidance on execution settings and deployment failures.

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• Deploy a web application from source code or a container
• Create and run batch jobs with parallel tasks
• Deploy continuous queue-processing workers

Investigate failing or slow BigQuery jobs and unexpected cost increases. Compare execution details and resource usage with a normal baseline to isolate bottlenecks, identify likely causes, and determine practical remediation steps.

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• Investigate failed or slow BigQuery jobs
• Locate bottlenecks in execution stages
• Diagnose sudden increases in query or capacity costs

Investigate 403 and 500 errors in Google Cloud Gemini Enterprise Agent Platform. Examine logs, registered destinations, agent identities, and authorization policies to produce a diagnostic report with evidence, recommended fixes, and verification steps.

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• Investigating 403 errors when an agent calls an external API
• Diagnosing Agent Runtime 500 errors involving Model Armor
• Checking registration and permissions for failing MCP connections

Find relevant Google Cloud monitoring metrics for a service or resource. Retrieves current metric definitions through the API, filters them by the requested concepts, and presents selected metrics with their names, data types, units, and monitored resources.

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• Find CPU metrics for Compute Engine
• Identify Cloud Storage write throughput and request metrics
• Check metric data types and units

Design Google Cloud infrastructure with Terraform, validate it locally, and assess the planned changes for security, cost, and reliability. The skill then imports templates into Application Design Center, deploys them, investigates failures, and checks the deployed services.

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• Designing and locally validating Terraform for GCP
• Assessing infrastructure plans before deployment
• Importing and deploying Application Design Center templates

Build Cloud Monitoring requests from metric definitions and resource details. Generate JSON parameters, filters, and aggregation settings for retrieving time series data, then validate the request against the live API.

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• Build JSON requests to retrieve monitoring data
• Filter metrics for specific VMs or databases
• Set aggregation intervals and resource grouping

Generate Terraform alerts for Cloud Run services, jobs, and worker pools using PromQL, a monitoring query language. Monitor errors, latency, resource usage, job failures, and queue delays, with configurable thresholds and explanations of when each alert triggers.

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• Monitor Cloud Run service errors and latency
• Detect failed batch job executions
• Monitor worker pool backlogs and message age

Turn Cloud Monitoring metric definitions and resource filters into validated PromQL queries, a language for querying monitoring data. Choose suitable aggregation functions, preserve supplied resource names, and format queries for use in Cloud Monitoring.

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• Convert Cloud Monitoring metric definitions into PromQL
• Filter monitoring queries to specific resources
• Choose aggregations that match metric types

Guides migration from Google AI Studio’s Gemini API to Gemini Enterprise Agent Platform on Google Cloud, covering billing, access permissions, authentication, and connection settings for SDKs and supported agent tools.

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• Moving a Gemini application to Google Cloud
• Using Google Cloud credits for Gemini API calls
• Unifying agent authentication and billing

Use this design reference when planning centrally managed rules for outbound network traffic from a sandbox, an isolated execution environment. It covers design and acceptance gates, but does not itself enforce network restrictions.

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• Planning centrally managed sandbox outbound network rules
• Reviewing acceptance gates before implementation
• Consulting the gateway reference before adding network controls

Guide a Kortix production release from choosing a version and writing release notes to testing on staging, merging the release pull request, and verifying production. Diagnose blocked promotions and direct fixes back to the dev branch.

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• Choose a version number for a Kortix release
• Promote dev through staging to production
• Investigate a blocked release

Preserve lessons from production incidents and near misses in a timestamped ledger. Consult relevant entries before database or release changes, and record each new lesson with a concrete rule and a test or automated check.

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• Review incident lessons before database changes
• Check past release failures before deployment
• Record lessons after resolving an incident

Roll back Kortix production to a previously released version using existing builds. Covers frontend and backend rollback, database compatibility checks, prevention of unintended frontend rebuilds, and returning to the latest version through a later release.

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• Restore a previous release after a production incident
• Check database compatibility before a rollback
• Prevent frontend rebuilds from overwriting a rollback

Investigate Sentry alerts using Datadog logs and recent GitHub changes, then post an initial diagnosis with a severity assessment. Notify the on-call team when severity reaches the configured threshold or the investigation remains inconclusive, without changing monitored systems.

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• Investigate new and unresolved Sentry alerts
• Compare failures with logs and recent deployments
• Notify on-call staff for severe or inconclusive alerts

Draft incident postmortems by aligning channel updates, GitHub deploys and merges, and Datadog spikes. It opens a review PR with a correlated timeline, proposed causes, and candidate follow-up actions for humans to confirm.

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• Drafting a postmortem after an incident is resolved
• Comparing incident events with deploys and metric spikes
• Extending a draft when new evidence appears

Manage encrypted API secrets across local, development, staging, and production profiles with dotenvx and Dotenv Armor. Covers storing and rotating credentials, sharing decryption keys, selecting runtime environments, and checking profile consistency with deployed AWS Secrets Manager settings.

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• Store an API key in an encrypted environment profile
• Switch local execution between backend environments
• Share or rotate decryption keys

Build and operate websites, internal tools, APIs, and databases on Kortix Apps using its CLI or SDK. Covers deployment, sign-in, scaling, persistent storage that survives updates, snapshots, and restoring earlier application releases.

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• Publish a static website or single-page app
• Build an internal CRM with team sign-in
• Create an API or database backend

Monitor daily AWS spending by service and account, compare it with historical baselines, and send Slack alerts with cost differences and likely causes. Known planned increases are excluded, and cloud resources remain unchanged.

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• Detecting unusual increases in daily AWS spending
• Investigating cost spikes by service and account
• Excluding planned or seasonal spending increases

Review new and spiking Sentry errors, rank their impact, and check for existing GitHub issues. Create triage issues for the highest-impact untracked errors and post a Slack summary, while leaving Sentry error states and assignments unchanged.

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• Review new and spiking errors every hour
• Avoid duplicate GitHub issues for Sentry errors
• Create issues with stack traces and impact details

Publish a built website or web app and provide a shareable URL through Kortix Apps, Cloudflare, or Vercel. Check the running build, security, external service requirements, and data storage limits before deploying with the user's explicit approval.

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• Sharing a temporary demo of a static website
• Deploying an app with Kortix sign-in
• Publishing a framework app or container on Vercel

Check AWS S3 buckets and IAM roles against documented compliance rules. Identify public exposure, missing tags, and overly broad permissions, trace changes through audit logs, and prepare remediation requests for human review without applying fixes.

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• Running daily checks for AWS policy violations
• Reviewing bucket exposure, tags, and role permissions
• Tracing who changed a resource and when

Evaluate a machine learning GPU cluster during a cloud trial or acceptance test. Measure GPU computing performance, communication within and between machines, and local and shared storage, then compile the results into a dated Markdown report.

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• Evaluating trial GPU machines from a cloud provider
• Running acceptance tests for a GPU cluster
• Measuring GPU performance under load from neighboring GPUs

Get guidance for installing A0 CLI on Windows, macOS, or Linux and connecting it to Agent Zero for local file and host tool access. Troubleshoot installation, instance discovery, and connection errors step by step.

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• Installing A0 CLI on a personal computer
• Connecting Agent Zero to local files and host tools
• Entering the correct URL when discovery fails