What data for this category looks like
Data for this category primarily comes from logging systems, Trace platforms, Metrics systems, and application SDKs. It is maintained by SREs, platform engineers, and developer productivity teams. Daily supporting documentation includes logging collection specifications, link tracing instructions, metric dictionaries, and dashboard configuration records. Data updates occur daily or per version iteration. Data fields include log timestamps, service identifiers, error codes, trace IDs, call latency, QPS, memory usage, and more. Some fields follow internal standardization rules. Units include milliseconds, count, GB, and other standard units.
What constraints these characteristics impose during deployment and upgrade
The data sources for this category are scattered and update frequently. During deployment, connection parameters for multiple data source types must be configured simultaneously to prevent cross-system connection failures. There are many supporting documents for daily maintenance. Before deployment, mapping rules between logging fields and the knowledge base must be synchronized and reviewed to ensure internal ticket Q&A matches correct context information. Data updates occur daily or per version iteration. During upgrades, compatibility between existing configurations and the new version must be verified in advance to avoid query exceptions caused by field rule changes. Additionally, the requirement for standardized collection fields means additional field mapping logic must be configured during deployment to ensure query accuracy for subsequent operations on-call.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 30-50 connections | Adapt to the concurrent query load of the logging platform, avoid database connection pool overflow |
MONGODB_URI | Fill in the replica set connection address for log aggregation storage | Adapt to the massive log data added daily, ensure query stability |
REDIS_URL | Configure as the authenticated internal cache service address, set cache validity to 1800 seconds | Cache temporary query results for link tracing, reduce repeated request pressure on the logging system |
PG_URL | Point to the relational database storing metric dictionaries and dashboard configurations, enable SSL encryption | Ensure transmission security for sensitive operations and maintenance configurations |
FE_DOMAIN | Set to the domain name of the internal operations and maintenance portal | Ensure that the jump path for internal ticket Q&A points to a compliant operations and maintenance workbench |
STORAGE_S3_ENDPOINT | Fill in the endpoint address of the internal object storage service, such as http://s3.internal.corp:9000 | Store log query export files and dashboard snapshots |
Three common mistakes
- A connection failure error appears when accessing the knowledge base after an upgrade. The cause is that the connection configuration for
MONGODB_URIand the log storage cluster was not synchronized and updated, resulting in failure to read the log data source. - An empty model stream response is returned when calling built-in tools. The cause is that the cache validity period for
REDIS_URLwas not configured correctly, resulting in failure to properly cache and transmit link tracing data. - An SQL permission error appears after restarting the Docker container. The cause is that the database connection authentication parameters for
PG_URLwere not retained, causing authentication credentials to be lost after container restart.
How to confirm configurations are correctly set
- Run the built-in health check script for FastGPT v4.17.0 to verify whether the connection status of
MONGODB_URI,PG_URL, andREDIS_URLis normal. - Upload a test log data entry, trigger a log query via internal ticket Q&A, and confirm that the returned results include the expected service name and error code fields.
- Access the operations and maintenance portal bound to
FE_DOMAIN, click the knowledge base jump link, and confirm that the page loads without errors. - Generate a dashboard configuration record, and verify whether files are properly written to storage via
STORAGE_S3_ENDPOINT.
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.