Cloud, CI/CD, monitoring, and deployment (6.8K skills)
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.
Turn plain-language requests into Cloud Logging queries for Google Cloud. Generate service-specific filters to find errors, investigate issues, or review audit logs using LQL, the language used to search these logs.
Learn Cloud Build fundamentals and set up a basic build trigger for source code changes. Covers project preparation, configuration files, manual trigger runs, and checking build history and logs in Google Cloud.
Choose a Google Cloud database by clarifying data needs, workload, and scale. The skill explains its recommendation and prepares validated Terraform configurations or provisioning scripts for review before infrastructure changes are made.
Create and administer AlloyDB for PostgreSQL databases, including clusters, instances, backups, secure connections, and access permissions. It also covers command-line operations, infrastructure configuration, and MCP tools that let agents automate database tasks.
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.
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.
Deploy Model Garden models to Agent Platform endpoints, the addresses used for model requests. Check supported hardware and estimated hourly costs, inspect deployment progress, test predictions, and remove deployed resources after use.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Find Agent Zero plugins that match a task, compare candidates and their requirements, and manage installation, updates, settings, activation, and removal. It also supports security scans and checks the resulting plugin state through framework management APIs.