Data characteristics for this category
Data for this category typically originates from pressure testing platforms, APM monitoring systems, database slow logs, and production traffic baselines. Updates occur once per month or alongside major version releases. Daily deliverables include pressure testing plans, capacity evaluation reports, pressure testing data records, and optimization suggestion sheets. Common data fields include throughput rate, average latency, peak resource utilization, and concurrent connection count. Corresponding units are requests per second, milliseconds, percentage, and count.
Constraints on database and operations workflows
Scattered, multi-source data requires unified connection via configuration items such as PG_URL and MONGODB_URI. This ensures normal pulling and storage of pressure testing data from all sources. Fixed update cadence requires regular validation of database connection validity. This prevents pressure testing data loss from expired configurations. Clear document field standards require operations teams to store pressure testing results according to specifications. This enables rapid identification of database bottlenecks during subsequent retrospectives. Pressure testing model design is resource-intensive and time-consuming. Sufficient database connection pool resources must be reserved to avoid business disruption from exhausted connections during testing.
Configuration settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
PG_URL | Standard connection string for local PostgreSQL instances | Connect to core business databases for storing pressure testing data and retrospective logs |
MONGODB_URI | Replica set connection string with at least 2 node addresses | Ensure high availability of pressure testing data storage and avoid single-point failures |
DB_MAX_LINK | 800–1200 connections | Match connection demands for pressure testing concurrent peaks and prevent connection pool exhaustion |
REDIS_URL | Cluster connection address with password authentication | Cache pressure testing intermediate results and traffic baseline data to improve retrospective efficiency |
| Database slow log collection switch | Enable and retain logs for 7 days | Facilitate identification of database execution bottlenecks during online fault retrospectives |
Three common configuration errors
- Symptom:
connection refusederror and 503 status code during pressure testing. Cause:DB_MAX_LINKis not configured per requirements. The connection pool size is insufficient to support pressure testing concurrent volume, leading to exhausted database connections. - Symptom: Empty database-related fields in capacity evaluation reports. Cause:
PG_URLorMONGODB_URIis not correctly configured. Original pressure testing platform data cannot be pulled, leading to missing retrospective data. - Symptom: Pressure testing data fails to load after offline upgrade of FastGPT v4.17.0. Cause: Database images and data directories were not backed up in advance. Configuration files were overwritten during the upgrade, leading to lost database connection configurations.
How to confirm configurations are properly set
- Execute basic pressure testing scripts, then check connection logs for each database configuration item to confirm no connection failure prompts.
- Review pressure testing data record documents and verify fields match the preset pressure testing plan to ensure normal data writing.
- Simulate online peak traffic and confirm that APM monitoring and database slow logs can collect corresponding data normally.
- Trigger capacity evaluation report generation and confirm all database-related fields in the report contain valid data.
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.