--- id: 'reports' title: 'Reports' description: 'Built-in observability for your Supabase project' --- 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 | ❌ | ❌ | ✅ | ✅ | --- <$Show if="billing:all"> ## 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 | {/* supa-mdx-lint-disable-next-line Rule001HeadingCase */} ### Advanced Telemetry The following charts provide a more advanced and detailed view of your database performance and are available only for Team, Enterprise, and Platform plans. ### Memory usage Memory usage chart | 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](/docs/guides/platform/compute-and-disk#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 CPU usage chart | 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](/docs/guides/platform/compute-and-disk) | Increase available CPU capacity | | Implement proper indexing | Use [query optimization](/docs/guides/database/postgres/indexes) techniques | ### Disk input/output operations per second (IOPS) Disk IOPS chart 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](/docs/guides/platform/compute-and-disk) | Increase IOPS limits with larger compute instances | ### Disk throughput Available on Team and Enterprise plans. This chart displays read and write throughput (bytes per second) with a reference line showing your compute size's maximum disk throughput. How it helps debug issues: | Issue | Description | | ------------------------------------ | ------------------------------------------------------- | | Throughput bottleneck identification | Spot when disk bandwidth is saturated | | Workload pattern analysis | Differentiate read-heavy vs write-heavy bandwidth usage | | Performance correlation | Correlate spikes with query performance changes | Actions you can take: | Action | Description | | -------------------------------------------------------------- | ------------------------------------------------------------- | | Optimize query patterns | Reduce large sequential reads/writes | | Tune caching and batching | Minimize repeated disk access and improve throughput headroom | | [Upgrade compute size](/docs/guides/platform/compute-and-disk) | Increase throughput limits for sustained workloads | ### Disk size Disk Size chart | 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](https://www.postgresql.org/docs/current/sql-vacuum.html) 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](/docs/guides/platform/database-size) | Increase storage capacity when approaching limits | ### Database connections Database connections chart | 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](/docs/guides/platform/compute-and-disk#compute-size) | Increase maximum connection limits | | Implement [connection pooling](/docs/guides/database/connecting-to-postgres#shared-pooler) | 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 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 | | Broadcast Events | Broadcast events over time | Real-time feature usage patterns | | Presence Events | Presence events over time | Real-time feature usage patterns | | Postgres Changes Events | Postgres Changes events over time | Real-time feature usage patterns | | Rate of Channel Joins | Frequency of new channel subscriptions | User engagement with real-time features | | Message Payload Size | Median size of message payloads sent | Payload size that is being transmitted | | Broadcast From Database Replication Lag | Median latency between database commit and broadcast when using broadcast from database | Latency to Broadcast from the database | | Read/Write Private Channel Subscription RLS Execution Time | Median time to authorize private channels | `realtime.messages` RLS policies performance | | 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 egress usage | Data transfer patterns and cost implications | | Top Routes | Most frequently accessed API endpoints | Usage patterns and optimization priorities |