What this category of data looks like
This category of data primarily originates from pressure testing platforms, APM monitoring systems, database slow logs, and production traffic baselines. Four types of documents are produced on a regular basis: pressure testing plans, capacity assessment reports, pressure testing data records, and optimization suggestion sheets. Data is updated monthly or when major versions are released. Core fields include throughput rate, latency threshold, resource usage, and bottleneck node identifiers. Common units are requests per second, milliseconds, and node names. Data collection covers the entire performance testing workflow. It requires associating baseline parameters from both test and production environments to support review and optimization of capacity conclusions.
What constraints do these characteristics impose on the database and operations workflow
The data characteristics of this category impose multiple constraints on the database and operations workflow. Unified database connection configuration is required to support multi-source data access. This must accommodate interface formats from pressure testing platforms, APM monitoring tools, slow logs, and other sources to avoid format conflicts during data collection. Dynamic update frequencies require a configurable refreshable caching mechanism. This ensures the latest production baselines and pressure testing data are used during capacity assessments. Storage requirements for multiple document types require targeted table structure design. This must adapt to step-by-step descriptions of pressure testing plans, time-series metrics for pressure testing data, and associated node information for optimization suggestions. Additionally, errors during performance testing directly impact business stability. Current limiting and fault tolerance mechanisms must be configured for the database link. This prevents production environment anomalies caused by overload from pressure testing traffic.
How to configure the settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
MONGODB_URI | mongodb://username:password@host:port/perf_data?authSource=admin | Stores pressure testing data records and optimization suggestion sheets. Specifies a dedicated business database to isolate business data |
PG_URL | postgresql://username:password@host:port/perf_report?sslmode=require | Stores structured pressure testing plans and capacity assessment reports. Enables SSL to secure data transmission |
DB_MAX_LINK | 20–50 connections | Adapts to concurrent pressure testing scenarios. Prevents database resource exhaustion from excessive connection counts |
REDIS_URL | redis://:password@host:port/0 | Caches production traffic baselines and real-time pressure testing metrics. Reduces overhead from high-frequency database queries |
| Slow log collection threshold | 500 milliseconds | Identifies database slow queries during pressure testing scenarios to support bottleneck metric analysis |
| Connection timeout period | 600 seconds | Prevents task interruptions from network fluctuations during pressure testing data retrieval |
Three common configuration mistakes
- Symptom: When executing the startup command in a local development environment, the console displays a database connection timeout error, and the development service cannot start. Cause: The
MONGODB_URIparameter is not configured correctly. The entered address does not include valid authentication information or the target database name, resulting in a rejected connection request. - Symptom: In performance testing operational reports, the token consumption statistics for database queries deviate from actual API call token consumption. Cause: Cache hits and misses for database queries are not distinguished, leading to duplicate statistics or missed token consumption entries.
- Symptom: Oracle databases cannot be connected as pressure testing data sources during performance testing. Cause: FastGPT v4.17.0 only supports MongoDB, PostgreSQL, and Redis database connections. No Oracle driver package is integrated.
How to confirm configurations are properly set up
- Verify that database connection configuration items follow the standard URL specifications for their respective databases. A local database client can be used to test connection validity.
- Review pressure testing data import logs to confirm whether new pressure testing records can be successfully written to the corresponding database tables.
- Check the active status of cache configurations. Confirm that production baseline data is refreshed to the cache on schedule to avoid reading outdated data.
- Simulate concurrent requests under a pressure testing scenario. Check that database connection counts stay within the preset range and no connection limit exceeded errors occur.
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.