The Supabase Platform includes a Logs Explorer that allows log tracing and debugging. Log retention is based on your project's pricing plan.
These features are not currently available for self-hosting and local development.
This is on the roadmap and you can follow the progress in the Logflare repository.
Supabase provides a logging interface specific to each product. You can use simple regular expressions for keywords and patterns to search log event messages. You can also export and download the log events matching your query as a spreadsheet.
Logging Postgres Queries#
By default, query logs are disabled for new Supabase projects, as they can reveal metadata about the contents of your database (such as table and column names).
To enable query logs:
- Enable the pgAudit extension.
- Restart your project using the Fast database reboot option.
pgaudit.log(see below). Perform a fast reboot if needed.
- View your query logs under Logs > Postgres Logs.
To enable logging for function calls/do blocks, writes, and DDL statements for a single session, execute the following within the session:
-- temporary single-session config update set pgaudit.log = 'function, write, ddl';
To permanently set a logging configuration (beyond a single session), execute the following, then perform a fast reboot:
-- equivalent permanent config update. alter role postgres set pgaudit.log to 'function, write, ddl';
To reset system-wide settings, execute the following, then perform a fast reboot:
-- resets stored config. alter role postgres reset pgaudit.log
If any permission errors are encountered when executing
alter role postgres ..., it is likely that your project has yet to receive the patch to the latest version of supautils, which is currently being rolled out.
The Logs Explorer exposes logs from each part of the Supabase stack as a separate table that can be queried and joined using SQL.
You can access the following logs from the Sources drop-down:
auth_logs: GoTrue server logs, containing authentication/authorization activity.
edge_logs: Edge network logs, containing request and response metadata retrieved from Cloudflare.
function_edge_logs: Edge network logs for only edge functions, containing network requests and response metadata for each execution.
function_logs: Function internal logs, containing any
consolelogging from within the edge function.
postgres_logs: Postgres database logs, containing statements executed by connected applications.
realtime_logs: Realtime server logs, containing client connection information.
storage_logs: Storage server logs, containing object upload and retrieval information.
Querying with the Logs Explorer#
The Logs Explorer uses BigQuery and supports all available SQL functions and operators.
Timestamp Display and Behavior#
Each log entry is stored with a
timestamp as a
TIMESTAMP data type. Use the appropriate timestamp function to utilize the
timestamp field in a query.
Raw top-level timestamp values are rendered as unix microsecond. To render the timestamps in a human-readable format, use the
DATETIME() function to convert the unix timestamp display into an ISO-8601 timestamp.
-- timestamp column without datetime() select timestamp from .... -- 1664270180000 -- timestamp column with datetime() select datetime(timestamp) from .... -- 2022-09-27T09:17:10.439Z
Each log event stores metadata an array of objects with multiple levels, and can be seen by selecting single log events in the Logs Explorer. To query arrays, use
unnest() on each array field and add it to the query as a join. This allows you to reference the nested objects with an alias and select their individual fields.
For example, to query the edge logs without any joins:
select timestamp, metadata from edge_logs t
metadata key is rendered as an array of objects in the Logs Explorer. In the following diagram, each box represents a nested array of objects:
cross join unnest() to work with the keys nested in the
To query for a nested value, add a join for each array level:
select timestamp, request.method, header.cf_ipcountry from edge_logs t cross join unnest(t.metadata) as metadata cross join unnest(metadata.request) as request cross join unnest(request.headers) as header
This surfaces the following columns available for selection:
This allows you to select the
cf_ipcountry columns. In JS dot notation, the full paths for each selected column are:
LIMIT and Result Row Limitations#
The Logs Explorer has a maximum of 1000 rows per run. Use
LIMIT to optimize your queries by reducing the number of rows returned further.
- Include a filter over timestamp
Querying your entire log history might seem appealing. For Enterprise customers that have a large retention range, you run the risk of timeouts due additional time required to scan the larger dataset.
- Avoid selecting large nested objects. Select individual values instead.
When querying large objects, the columnar storage engine selects each column associated with each nested key, resulting in a large number of columns being selected. This inadvertently impacts the query speed and may result in timeouts or memory errors, especially for projects with a lot of logs.
Instead, select only the values required.
-- ❌ Avoid doing this select datetime(timestamp), m as metadata -- <- metadata contains many nested keys from edge_logs t cross join unnest(t.metadata) as m; -- ✅ Do this select datetime(timestamp), r.method -- <- select only the required values from edge_logs t cross join unnest(t.metadata) as m cross join unnest(m.request) as r
Examples and Templates#
The Logs Explorer includes Templates (available in the Templates tab or the dropdown in the Query tab) to help you get started.
For example, you can enter the following query in the SQL Editor to retrieve each user's IP address:
select datetime(timestamp), h.x_real_ip from edge_logs cross join unnest(metadata) as m cross join unnest(m.request) AS r cross join unnest(r.headers) AS h where h.x_real_ip is not null and r.method = "GET"