What the data for this category looks like
Data for IT service desk employee service desks comes primarily from internal network IT help tickets submitted by employees, hardware equipment repair requests, software license activation requests, permission configuration change requests, and similar items. Employees submit tickets in real time, and operation logs are synced on a scheduled basis. Each data entry includes fields such as unique ticket identifier, submitter department and employee ID, problem category, priority, processing status, response duration, resolution result, and more. Field types include strings, enumeration values, and timestamps. Response duration and processing time are measured in seconds. Attachment size is measured in MB. Ticket numbers follow a fixed string format.
What constraints these characteristics impose during deployment and upgrade
IT service desks store core data in internal network environments. Data transmission and storage security must be ensured, so deployments must prioritize databases and storage services accessible within the internal network. High volumes of concurrent ticket submissions and queries generate large numbers of database connection requests. Connection pool parameters must be configured appropriately to avoid resource exhaustion. Data fields include sensitive employee IDs and department information. During upgrades, data leakage must be prevented, and ongoing ticket processing must not be interrupted. A gray upgrade strategy must be used. Reference only; verify against the target FastGPT release and deployment documentation.
How to set configurations
| Config Item | Recommended Value | Basis for This Value |
|---|---|---|
MONGODB_URI | Internal MongoDB cluster address, formatted as mongodb://internal account:internal password@internal host:port/service desk database | Stores core IT service desk data such as ticket history, operation logs, employee service conversation records, etc. Internal network connectivity is required to ensure data security |
REDIS_URL | Internal Redis cluster address, default port 6379 | Caches ticket status and user session information, reduces pressure from frequent database queries, and improves service response speed |
DB_MAX_LINK | 200–300 connections | Adapts to connection demands from high concurrent ticket submissions and queries for IT service desks, prevents service interruptions caused by exhausted connections |
STORAGE_S3_ENDPOINT | Internal object storage endpoint address, such as http://internal storage host:9000 | Stores ticket attachments, operation log files, etc., complies with security requirements for internal network data storage |
FE_DOMAIN | Internal domain name or internal IP:frontend port | Configures the frontend access address for employees to access the employee service desk page within the internal network |
Three common misconfigurations
- Issue: The upgrade script returns a
connection refusederror after execution. Cause:MONGODB_URIwas not configured correctly, and the correct address and authentication information for the internal MongoDB were not specified. - Issue: Memory usage remains consistently high after the service starts, even on 64GB systems, and performance lags. Cause: The
DB_MAX_LINKparameter was not adjusted, and the default connection count is too high, causing the database connection pool to occupy large amounts of memory. - Issue: Searching ticket history returns empty results. Cause:
REDIS_URLwas not configured, causing session cache failure and preventing association of user history ticket submissions.
How to confirm configurations are complete
- Run a database connection test command to verify connectivity for the
MONGODB_URIandPG_URLconfigurations, confirm there are no timeout or authentication failure prompts. - Submit a test ticket, fill in basic information and submit, check if the frontend page loads the ticket list normally, verify that the
FE_DOMAINconfiguration takes effect. - View the Redis monitoring dashboard, confirm that the cache service configured via
REDIS_URLis running normally, and there are no connection exceptions or out-of-memory prompts. - After adjusting the
DB_MAX_LINKparameter, simulate high concurrent ticket submission requests, verify that no connection exhaustion errors occur.
The values provided are common starting points, and should be evaluated 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.