Online Fault Troubleshooting and Post-Incident Review for Incident Response and Fault Handling: Database and Operations

Data for this category originates from monitoring alerts, log platforms, APM tools, and user feedback. Update frequency is real time or following each

What Data for This Category Looks Like

Data for this category originates from monitoring alerts, log platforms, APM tools, and user feedback. Update frequency is real time or following each incident. Daily produced documents include fault tickets, incident timelines, emergency response plans, and fault notifications. Data fields include unique incident identifiers, occurrence timestamps, affected service scopes, stop-loss operation records, preliminary root cause judgments, and notification recipients. Common units are timestamps, service names, and operation descriptions.

Constraints Imposed on Database and Operations Workflows

Diverse data sources require databases to support batch writing and structured storage of multi-format data, to avoid entry delays caused by format incompatibility. Real-time update characteristics require database connection pool configurations to adapt to high-concurrency writing and low-latency query requirements, to avoid data backlog caused by insufficient connections. Fixed but extensible document structures require database schemas to have certain flexibility, while indexes must be created for commonly used query fields to ensure fast retrieval during fault troubleshooting. In addition, the time-sensitive nature of fault handling requires database write operations to have transaction guarantees, to avoid loss of critical records.

How to Configure Settings

Configuration ItemRecommended ValueRationale
MONGODB_URImongodb://admin:securepass@host1:27017,host2:27017/fastgpt_fault?replicaSet=rs0Adapts to multi-node clusters for fault log storage, supports authentication and replica set high availability
PG_URLpostgresql://sre:pass@pg-host:5432/fastgpt_workorder?sslmode=requireSupports transactional storage of fault tickets, ensures data consistency
DB_MAX_LINK60–100Balances concurrent write operations and resource usage, adapts to high-concurrency requirements for real-time incidents
REDIS_URLredis://:redispass@redis-host:6379/1Caches frequently queried incident summaries and emergency response plans, reduces database load
Log retention period30–90 daysBalances storage costs and historical data needs for fault post-incident review

Three Common Misconfiguration Issues

  • Symptom: Cannot pull external monitoring alert data after startup, interface returns 401 status code. Cause: Authentication parameters for MONGODB_URI or external service calls are not configured correctly, leading to permission verification failure.
  • Symptom: Fault ticket data fails to sync and display after upgrading from 4.9.13 to 4.10.1. Cause: Database migration operations are not performed correctly. Differences exist between database table structures of old and new versions, and field mapping and data migration are not completed.
  • Symptom: System reports database connection exhaustion error with prompt "too many connections". Cause: DB_MAX_LINK configuration value is too low, cannot support high-concurrency write requests for real-time incidents.

How to Confirm Configurations Are Correct

  • Run external service interface call tests to confirm that monitoring alerts and user feedback data can be pulled normally. Adjust interface configuration parameters based on returned results.
  • Import simulated fault data into the database, query corresponding records to confirm that data can be stored and retrieved normally. Adjust index configurations based on retrieval speed.
  • View the database connection status panel to confirm that current connection count does not reach the configured DB_MAX_LINK upper limit. Adjust connection pool parameters based on actual concurrent volume.
  • Run the database verification script included in FastGPT v4.17.0 to confirm that database table structures and data mapping relationships between old and new versions are correct.

The values provided are common starting points and should be measured against the reader's own samples.

Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.