gcp-logs

GCP Logs Query Skill When to Use Investigating relayer, validator, or scraper behavior Debugging message processing issues Analyzing operational incidents Looking for specific errors or patterns in agent logs Prerequisites gcloud CLI installed and authenticated Access to abacus-labs-dev GCP project Base Query Templates Relayer (Omniscient) gcloud logging read 'resource.type="k8s_container" AND resource.labels.project_id="abacus-labs-dev" AND resource.labels.location="us-east1-c" AND resource.labels.cluster_name="hyperlane-mainnet" AND resource.labels.namespace_name="mainnet3" AND labels.k8s-pod/app_kubernetes_io/component="relayer" AND labels.k8s-pod/app_kubernetes_io/instance="omniscient-relayer" AND labels.k8s-pod/app_kubernetes_io/name="hyperlane-agent"' --project = abacus-labs-dev --limit = 50 --format = json --freshness = 1d Validator gcloud logging read 'resource.type="k8s_container" AND resource.labels.project_id="abacus-labs-dev" AND resource.labels.location="us-east1-c" AND resource.labels.cluster_name="hyperlane-mainnet" AND resource.labels.namespace_name="mainnet3" AND labels.k8s-pod/app_kubernetes_io/component="validator" AND labels.k8s-pod/app_kubernetes_io/name="hyperlane-agent"' --project = abacus-labs-dev --limit = 50 --format = json --freshness = 1d Scraper gcloud logging read 'resource.type="k8s_container" AND resource.labels.project_id="abacus-labs-dev" AND resource.labels.location="us-east1-c" AND resource.labels.cluster_name="hyperlane-mainnet" AND resource.labels.namespace_name="mainnet3" AND labels.k8s-pod/app_kubernetes_io/component="scraper3" AND labels.k8s-pod/app_kubernetes_io/instance="omniscient-scraper" AND labels.k8s-pod/app_kubernetes_io/name="hyperlane-agent"' --project = abacus-labs-dev --limit = 50 --format = json --freshness = 1d Noise Filtering Add these filters to reduce noisy log lines that consume context without providing value: -jsonPayload.fields.message="Found log(s) in index range" -jsonPayload.fields.message="Dispatching get_public_key" NOT "Instantiated AWS signer" -jsonPayload.fields.message="Ingesting leaf" -jsonPayload.fields.message="Message already marked as processed in DB" -jsonPayload.fields.message="Message destined for self, skipping" -jsonPayload.fields.message="Message has already been delivered, marking as submitted." -jsonPayload.fields.message="Popped OpQueue operations" -jsonPayload.fields.message="Validator returned latest index" -jsonPayload.fields.message="Found signed checkpoint" -jsonPayload.fields.return="Ok(None)" -jsonPayload.fields.message="Fast forwarded current sequence" -jsonPayload.fields.message="Cursor can't make progress, sleeping" -jsonPayload.fields.message="fallback_request" -jsonPayload.fields.message="No message found in DB for leaf index" -jsonPayload.fields.message="Processor working on message" -jsonPayload.fields.message="Message destined for unknown domain, skipping" Progressive Query Strategy (Token Efficiency) Step 1: Fetch Message Field Only First To minimize context consumption, first fetch only the message field: gcloud logging read '[BASE_QUERY] AND "[search_term]"' --project = abacus-labs-dev --limit = 30 --format = 'json(jsonPayload.fields.message,timestamp)' --freshness = 1d This gives you a quick overview without the full log payload. Step 2: Get Full Context for Specific Entries Once you identify interesting log entries, fetch full details: gcloud logging read '[BASE_QUERY] AND "[specific_identifier]"' --project = abacus-labs-dev --limit = 20 --format = json --freshness = 1d Step 3: Extract Specific Fields When you need specific details, use jq or grep to extract: gcloud logging read '[QUERY]' --format = json | jq '.[].jsonPayload.fields.error' Common Query Patterns Search by Message ID gcloud logging read '[BASE_QUERY] AND "0x[MESSAGE_ID]"' --project = abacus-labs-dev --limit = 50 --format = json --freshness = 1d Search for Errors/Warnings gcloud logging read '[BASE_QUERY] AND severity>="WARNING"' --project = abacus-labs-dev --limit = 50 --format = json --freshness = 1d Search by Chain/Domain gcloud logging read '[BASE_QUERY] AND jsonPayload.spans.domain:"[chain_name]"' --project = abacus-labs-dev --limit = 50 --format = json --freshness = 1d Search for Stuck Messages (High Retry Count) gcloud logging read '[BASE_QUERY] AND jsonPayload.fields.num_retries>=5' --project = abacus-labs-dev --limit = 30 --format = json --freshness = 1d Search for Gas Estimation Errors gcloud logging read '[BASE_QUERY] AND "eth_estimateGas"' --project = abacus-labs-dev --limit = 30 --format = json --freshness = 1d Search by App Context gcloud logging read '[BASE_QUERY] AND jsonPayload.fields.app_context:"[APP_CONTEXT]"' --project = abacus-labs-dev --limit = 30 --format = json --freshness = 1d Time Range Options --freshness=1h - Last hour --freshness=1d - Last day --freshness=7d - Last week Or use explicit timestamps in filter: timestamp>="2026-01-27T00:00:00Z" Output Format Options --format=json - Full JSON (verbose, high context) --format='json(jsonPayload.fields.message,timestamp)' - Specific fields only (efficient) --format='value(jsonPayload.fields.message)' - Just values, no structure Key Log Fields to Focus On Field Description jsonPayload.fields.message Main log message jsonPayload.fields.error Error details jsonPayload.spans[].domain Chain involved jsonPayload.fields.num_retries Retry count jsonPayload.fields.operations Pending message details jsonPayload.span.id Message ID in span context Environment Variations Environment Namespace Cluster mainnet3 mainnet3 hyperlane-mainnet testnet4 testnet4 hyperlane-mainnet Tips Always start specific - Search for exact message IDs or error patterns first Use noise filters - The base logs are very noisy; always filter Limit results - Use --limit to avoid overwhelming context Progressive detail - Start with message field only, expand as needed Time bound queries - Use --freshness or timestamp filters Pipe to grep/jq - Post-process large results locally