The monitoring dashboard is a tool that helps you track and analyze a site's performance, specifically for backend code and data operations. Use it to ensure site visitors have the best possible experience by monitoring request performance, identifying issues, and optimizing site code.
The monitoring dashboard helps you:
- Track performance over time: Monitor backend code and data request performance to identify trends and anomalies.
- Monitor storage usage: Keep track of how much storage space database collections are using.
- Detect issues early: Identify when a site isn't performing as expected.
- Troubleshoot problems: Determine whether issues are temporary or ongoing, quota-related, or caused by errors.
Tip: For additional monitoring capabilities, you can also use
Wix Logs to track and store logs from your live site.
The monitoring dashboard has 2 main sections:
The top of the dashboard displays high-level metrics for:
- Backend requests
- Data requests
- Collection storage
Exclamation icons indicate areas that need attention, with links to relevant guidance.
The middle section provides detailed breakdowns across 3 tabs:
Displays information about requests to your backend code from a site's frontend, including:
- HTTP functions: Calls to exposed site APIs
- Web module calls: Frontend calls to backend web methods
- Router hooks: Custom routing logic
Available panels:
- Total requests: Graph showing the number of backend requests over time
- Request durations: Percentile analysis (50th and 95th) of request completion times
- Failed requests: Breakdown of failures by type (RPM throttling, timeouts, errors)
- Top backend functions: Table of functions with the most traffic and their performance metrics
By default, data is aggregated across all backend functions. Use filters to view specific functions and time periods.
Displays information about data operations on your site, including:
- API calls using the Items module
- Content Management System (CMS) operations
- Dynamic page data loading
Available panels:
- Total requests: Graph showing the number of data requests over time
- Request durations: Percentile analysis (50th and 95th) of request completion times
- Failed requests: Breakdown of failures by type (RPM throttling, timeouts, errors)
- Top data requests: Table showing collections and operation types with the most traffic
By default, data is aggregated across all collections. Use filters to view specific collections, operations, and time periods.
Displays storage usage for your site's content collections. Each Wix site has a 10 GB storage quota for collections.
What counts toward the quota:
- Standard content collections
- User-generated content in collections
What doesn't count:
- External database collections
- Wix app collections
- Media files stored separately on your site
- Referenced documents and multimedia
Available panel:
- Collection storage breakdown: Table listing your largest collections with their names, IDs, and storage sizes
Learn more about data feature limitations.
Request duration graphs show two percentile lines:
- 50th percentile (blue line): The median request duration. At any point, 50% of requests took this long or less to complete.
- 95th percentile (turquoise line): The duration of the slowest 5% of requests. At any point, 95% of requests took this long or less to complete.
Use these metrics to identify performance issues and set optimization priorities.
Failed requests can occur for several reasons:
- RPM throttling: Too many requests per minute exceeded rate limits
- Timeouts: Requests took too long to complete (exceeded timeout limits)
- Errors: Code errors or internal Wix errors
Spikes in failed requests indicate issues that need investigation and resolution.
- Monitor regularly: Check the dashboard periodically to catch issues early
- Investigate spikes: Look into unusual increases in requests or failures
- Optimize slow functions: Focus on functions with high 95th percentile durations
- Track storage growth: Monitor collection sizes to avoid hitting quota limits
- Use filters: Narrow down data to specific functions, collections, or time periods for detailed analysis