---
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.

<Admonition type="note">

Reports are only available for projects hosted on the Supabase Cloud platform and are not available for self-hosted instances.

</Admonition>

## 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        |

</$Show>

{/* 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

<Image
  alt="Memory usage chart"
  zoomable
  src={{
    dark: '/docs/img/database/reports/memory-usage-chart-dark.png',
    light: '/docs/img/database/reports/memory-usage-chart-light.png',
  }}
/>

| 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

<Image
  alt="CPU usage chart"
  zoomable
  src={{
    dark: '/docs/img/database/reports/cpu-usage-chart-dark.png',
    light: '/docs/img/database/reports/cpu-usage-chart-light.png',
  }}
/>

| 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)

<Image
  alt="Disk IOPS chart"
  zoomable
  src={{
    dark: '/docs/img/database/reports/disk-iops-chart-dark.png',
    light: '/docs/img/database/reports/disk-iops-chart-light.png',
  }}
/>

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

<Image
  alt="Disk Size chart"
  zoomable
  src={{
    dark: '/docs/img/database/reports/disk-size-chart-dark.png',
    light: '/docs/img/database/reports/disk-size-chart-light.png',
  }}
/>

| 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

<Image
  alt="Database connections chart"
  zoomable
  src={{
    dark: '/docs/img/database/reports/db-connections-chart-dark.png',
    light: '/docs/img/database/reports/db-connections-chart-light.png',
  }}
/>

| 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       |
