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gapless-network-data
gapless-network-data contiene 7 skills recopiladas de terrylica, con cobertura ocupacional por repositorio y páginas de detalle dentro del sitio.
Skills en este repositorio
Autonomous setup and management of external service monitoring using UptimeRobot (HTTP endpoint monitoring) and Healthchecks.io (heartbeat/Dead Man's Switch monitoring). Use when setting up monitoring for Cloud Run Jobs, VM services, or investigating monitoring configuration issues. Includes Pushover integration, validated API patterns, and dual-service architecture.
Workflow for acquiring historical Ethereum blockchain data using Google BigQuery free tier. Empirically validated for cost estimation, streaming downloads, and DuckDB integration. Use when planning bulk historical data acquisition or comparing data source options for blockchain network metrics.
Empirical validation workflow for blockchain data collection pipelines before production implementation. Use when validating data sources, testing DuckDB integration, building POC collectors, or verifying complete fetch-to-storage pipelines for blockchain data.
Systematic workflow for researching and validating blockchain RPC providers. Use when evaluating RPC providers for historical data collection, rate limits, archive access, compute unit costs, or timeline estimation for large-scale blockchain data backfills.
Execute chunked historical blockchain data backfills using canonical 1-year pattern. Use when loading multi-year historical data, filling gaps in ClickHouse, or preventing OOM failures on Cloud Run. Keywords chunked_backfill.sh, BigQuery historical, gap filling, memory-safe backfill.
Troubleshoot and manage GCP e2-micro VM running eth-realtime-collector. Use when VM service is down, systemd failures occur, real-time data stream stops, or VM network issues arise. Keywords systemd, journalctl, eth-collector, gcloud compute.
Monitor and troubleshoot dual-pipeline data collection systems on GCP. This skill should be used when checking pipeline health, viewing logs, diagnosing failures, or monitoring long-running operations for data collection workflows. Supports Cloud Run Jobs (batch pipelines) and VM systemd services (real-time streams).