What the data for this category looks like
The data for internal office and employee services in new energy development mainly comes from equipment inspection logs of wind power and photovoltaic projects, project progress ledgers, employee attendance and reimbursement documents, and operation work orders. The data update rhythm falls into three categories: real-time (equipment inspection records), daily (project progress updates), and monthly (operation report generation). A single document’s structure includes fields such as unique equipment identifier, inspection time, abnormal parameters (such as voltage, current), project number, and approval node status. Each field has a dedicated unit: for example, voltage uses kV, power generation uses MWh, and inspection duration uses minutes.
What constraints these characteristics impose on deployment and upgrade
The data volume of new energy development projects continues to grow as projects expand. Sufficient database and storage resources must be reserved during deployment to avoid service lag caused by concurrent reads or insufficient storage. Data fields include dedicated units and specific formats. Original parsing rules must be retained during upgrades to prevent office data failure from incorrect field mapping. Data from multiple sources has significant format differences. Unified preprocessing rules must be configured before deployment to ensure consistent parsing across different document types. Internal office data involves project privacy and employee information. Private storage and access restrictions must be configured during deployment to avoid public network leakage risks.
How to configure the settings
| Configuration Item | Recommended Setting | Rationale for This Setting |
|---|---|---|
DB_MAX_LINK | 20–30 connections | Adapts to the concurrent reading demand of multiple device logs in new energy development, avoids service interruptions caused by exhausted connections |
MONGODB_URI | Local private cluster connection string | Stores massive equipment inspection data and employee office documents, ensures data privacy |
REDIS_URL | Local cache service address | Accelerates response speed of commonly used employee office interfaces (such as approval query, project progress) |
FE_DOMAIN | Enterprise intranet domain name | Limits access scope, adapts to the network isolation requirements of central state-owned enterprises |
STORAGE_S3_ENDPOINT | Enterprise private storage service address | Stores large files such as inspection reports, project documents, avoids public network transmission risks |
FILE_TOKEN_KEY | Custom high-strength random string | Encrypts file upload tokens, prevents unauthorized access to internal office files |
Three common misconfigurations
Reference only; verify against the target FastGPT release and deployment documentation.
- A
permission denied while trying to connect toerror occurs during local deployment. Cause: The FastGPT process is not granted access permissions for the corresponding database and storage services, or the port is blocked by the system firewall. - Files cannot be located in storage after upload in private deployment. Cause:
STORAGE_S3_ENDPOINTor the local storage path is not configured correctly, causing files to not be stored according to preset rules during upload.
How to confirm the configuration is complete
- Access the configured
FE_DOMAIN, confirm that the FastGPT front-end page loads normally, and there are no browser compatibility errors. - Perform a database connection test, confirm that the services configured via
MONGODB_URIandREDIS_URLcan establish normal connections, with no timeout or permission errors. - Upload a PDF of a new energy project inspection report, confirm that the file can be uploaded normally and the corresponding file can be found in the corresponding storage service.
- Initiate a query related to employee services (such as approval progress query), confirm that the interface response speed meets expectations.
The values given 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 2026-09-28.