Reports
Supabase Reports provide comprehensive observability for your project through dedicated monitoring dashboards that visualize key metrics across your database, auth, storage, realtime, and API systems. Each report offers self-debugging tools to gain actionable insights for optimizing performance and troubleshooting issues.
Reports are only available for projects hosted on the Supabase Cloud platform and are not available for self-hosted instances.
Using reports
Reports can be filtered by time range to focus your analysis on specific periods. Available time ranges are gated by your organization's plan, with higher-tier plans providing access to longer historical periods.
| Time Range | Free | Pro | Team | Enterprise |
|---|---|---|---|---|
| Last 10 minutes | ✅ | ✅ | ✅ | ✅ |
| Last 30 minutes | ✅ | ✅ | ✅ | ✅ |
| Last 60 minutes | ✅ | ✅ | ✅ | ✅ |
| Last 3 hours | ✅ | ✅ | ✅ | ✅ |
| Last 24 hours | ✅ | ✅ | ✅ | ✅ |
| Last 7 days | ❌ | ✅ | ✅ | ✅ |
| Last 14 days | ❌ | ❌ | ✅ | ✅ |
| Last 28 days | ❌ | ❌ | ✅ | ✅ |
Database
The Database report provides the most comprehensive view into your Postgres instance's health and performance characteristics. These charts help you identify performance bottlenecks, resource constraints, and optimization opportunities at a glance.
The following charts are available for Free and Pro plans:
| Chart | Available Plans | Description | Key Insights |
|---|---|---|---|
| Memory usage | Free, Pro | RAM usage percentage by the database | Memory pressure and resource utilization |
| CPU usage | Free, Pro | Average CPU usage percentage | CPU-intensive query identification |
| Disk IOPS | Free, Pro | Read/write operations per second with limits | IO bottleneck detection and workload analysis |
| Database connections | Free, Pro | Number of pooler connections to the database | Connection pool monitoring |
| Shared Pooler connections | All | Client connections to the shared pooler | Shared pooler usage patterns |
| Dedicated Pooler connections | All | Client connections to PgBouncer | Dedicated pooler connection monitoring |
Advanced Telemetry
The following charts provide a more advanced and detailed view of your database performance and are available only for Teams and Enterprise plans.
Memory usage
| Component | Description |
|---|---|
| Used | RAM actively used by Postgres and the operating system |
| Cache + buffers | Memory used for page cache and Postgres buffers |
| Free | Available unallocated memory |
How it helps debug issues:
| Issue | Description |
|---|---|
| Memory pressure detection | Identify when free memory is consistently low |
| Cache effectiveness monitoring | Monitor cache performance for query optimization |
| Memory leak detection | Detect inefficient memory usage patterns |
Actions you can take:
| Action | Description |
|---|---|
| Upgrade compute size | Increase available memory resources |
| Optimize queries | Reduce memory consumption of expensive queries |
| Tune Postgres configuration | Improve memory management settings |
| Implement application caching | Add query result caching to reduce memory load |
CPU usage
| Category | Description |
|---|---|
| System | CPU time for kernel operations |
| User | CPU time for database queries and user processes |
| IOWait | CPU time waiting for disk/network IO |
| IRQs | CPU time handling interrupts |
| Other | CPU time for miscellaneous tasks |
How it helps debug issues:
| Issue | Description |
|---|---|
| CPU-intensive query identification | Identify expensive queries when User CPU is high |
| IO bottleneck detection | Detect disk/network issues when IOWait is elevated |
| System overhead monitoring | Monitor resource contention and kernel overhead |
Actions you can take:
| Action | Description |
|---|---|
| Optimize CPU-intensive queries | Target queries causing high User CPU usage |
| Address IO bottlenecks | Resolve disk/network issues when IOWait is high |
| Upgrade compute size | Increase available CPU capacity |
| Implement proper indexing | Use query optimization techniques |
Disk input/output operations per second (IOPS)
This chart displays read and write IOPS with a reference line showing your compute size's maximum IOPS capacity.
How it helps debug issues:
| Issue | Description |
|---|---|
| Disk IO bottleneck identification | Identify when disk IO becomes a performance constraint |
| Workload pattern analysis | Distinguish between read-heavy vs write-heavy operations |
| Performance correlation | Spot disk activity spikes that correlate with performance issues |
Actions you can take:
| Action | Description |
|---|---|
| Optimize indexing | Reduce high read IOPS through better query indexing |
| Consider read replicas | Distribute read-heavy workloads across multiple instances |
| Batch write operations | Reduce write IOPS by grouping database writes |
| Upgrade compute size | Increase IOPS limits with larger compute instances |
Disk IO Usage
This chart displays the percentage of your allocated IOPS (Input/Output Operations Per Second) currently being used.
How it helps debug issues:
| Issue | Description |
|---|---|
| IOPS limit monitoring | Identify when approaching your allocated IOPS capacity |
| Performance correlation | Correlate high IO usage with application performance issues |
| Operation impact assessment | Monitor how database operations affect disk performance |
Actions you can take:
| Action | Description |
|---|---|
| Optimize disk-intensive queries | Reduce queries that perform excessive reads/writes |
| Add strategic indexes | Reduce sequential scans with appropriate indexing |
| Upgrade compute size | Increase IOPS limits with larger compute instances |
| Review database design | Optimize schema and query patterns for efficiency |
Disk size
| Component | Description |
|---|---|
| Database | Space used by your actual database data (tables, indexes) |
| WAL | Space used by Write-Ahead Logging |
| System | Reserved space for system operations |
How it helps debug issues:
| Issue | Description |
|---|---|
| Space consumption monitoring | Track disk usage trends over time |
| Growth pattern identification | Identify rapid growth requiring attention |
| Capacity planning | Plan upgrades before hitting storage limits |
Actions you can take:
| Action | Description |
|---|---|
| Run VACUUM operations | Reclaim dead tuple space and optimize storage |
| Analyze large tables | Use CLI commands like table-sizes to identify optimization targets |
| Implement data archival | Archive historical data to reduce active storage needs |
| Upgrade disk size | Increase storage capacity when approaching limits |
Database connections
| Connection Type | Description |
|---|---|
| Postgres | Direct connections from your application |
| PostgREST | Connections from the PostgREST API layer |
| Reserved | Administrative connections for Supabase services |
| Auth | Connections from Supabase Auth service |
| Storage | Connections from Supabase Storage service |
| Other roles | Miscellaneous database connections |
How it helps debug issues:
| Issue | Description |
|---|---|
| Connection pool exhaustion | Identify when approaching maximum connection limits |
| Connection leak detection | Spot applications not properly closing connections |
| Service distribution monitoring | Monitor connection usage across different Supabase services |
Actions you can take:
| Action | Description |
|---|---|
| Upgrade compute size | Increase maximum connection limits |
| Implement connection pooling | Optimize connection management for high direct connection usage |
| Review application code | Ensure proper connection handling and cleanup |
Auth
The Auth report focuses on user authentication patterns and behaviors within your Supabase project.
| Chart | Description | Key Insights |
|---|---|---|
| Active Users | Count of unique users performing auth actions | User engagement and retention patterns |
| Sign In Attempts by Type | Breakdown of authentication methods used | Password vs OAuth vs magic link preferences |
| Sign Ups | Total new user registrations | Growth trends and onboarding funnel performance |
| Auth Errors | Error rates grouped by status code | Authentication friction and security issues |
| Password Reset Requests | Volume of password recovery attempts | User experience pain points |
Storage
The Storage report provides visibility into how your Supabase Storage is being utilized, including request patterns, performance characteristics, and caching effectiveness.
| Chart | Description | Key Insights |
|---|---|---|
| Total Requests | Overall request volume to Storage | Traffic patterns and usage trends |
| Response Speed | Average response time for storage requests | Performance bottlenecks and optimization opportunities |
| Network Traffic | Ingress and egress bandwidth usage | Data transfer costs and CDN effectiveness |
| Request Caching | Cache hit rates and miss patterns | CDN performance and cost optimization |
| Top Routes | Most frequently accessed storage paths | Popular content and usage patterns |
Realtime
The Realtime report tracks WebSocket connections, channel activity, and real-time event patterns in your Supabase project.
| Chart | Description | Key Insights |
|---|---|---|
| Realtime Connections | Active WebSocket connections over time | Concurrent user activity and connection stability |
| Channel Events | Breakdown of broadcast, Postgres changes, and presence events | Real-time feature usage patterns |
| Rate of Channel Joins | Frequency of new channel subscriptions | User engagement with real-time features |
| Total Requests | HTTP requests to Realtime endpoints | API usage alongside WebSocket activity |
| Response Speed | Performance of Realtime API endpoints | Infrastructure optimization opportunities |
Edge Functions
The Edge Functions report provides insights into serverless function performance, execution patterns, and regional distribution across Supabase's global edge network.
| Chart | Description | Key Insights |
|---|---|---|
| Execution Status Codes | Function response codes and error rates | Function reliability and error patterns |
| Execution Time | Average function duration and performance | Performance optimization opportunities |
| Invocations by Region | Geographic distribution of function calls | Global usage patterns and latency optimization |
API gateway
The API Gateway report analyzes traffic patterns and performance characteristics of requests flowing through your Supabase project's API layer.
| Chart | Description | Key Insights |
|---|---|---|
| Total Requests | Overall API request volume | Traffic patterns and growth trends |
| Response Errors | Error rates with 4XX and 5XX status codes | API reliability and user experience issues |
| Response Speed | Average API response times | Performance bottlenecks and optimization targets |
| Network Traffic | Request and response bandwidth usage | Data transfer patterns and cost implications |
| Top Routes | Most frequently accessed API endpoints | Usage patterns and optimization priorities |