The POST /v2/analytics.getRatelimits endpoint runs SQL queries against your
rate limit analytics. Use it from a trusted backend with a root key. Never
expose a root key in browser code.
For the request and response schemas, see the API reference.
Authenticate the request#
Use a root key with one of these permissions:
ratelimit.*.read_analyticsto query every rate limit namespace in the workspaceratelimit.<namespaceId>.read_analyticsto query a specific namespace
Unkey always restricts queries to the root key's workspace. A namespace-scoped
permission also adds a namespace_id filter to every table in the query. You
can grant a root key access to multiple namespaces by adding one scoped
permission for each namespace.
Send a query#
Send a JSON object with a query string. The response uses the same shape as
analytics.getVerifications: meta.requestId identifies the API request, and
data contains an array of result objects.
Queries follow the shared SQL and resource limits described in Query
restrictions. CTEs, subqueries, UNION,
and EXCEPT are supported. Use a namespace_id filter to select one or more
namespaces when the root key has wildcard access:
You can omit this filter. A wildcard root key then queries every namespace in
the workspace, while a namespace-scoped root key returns only data permitted by
its ratelimit.<namespaceId>.read_analytics permissions. A query cannot bypass
these automatic workspace and namespace filters.
Choose a table#
Choose the least granular table that supports the chart or report. Aggregated tables scan fewer rows, while the raw table exposes individual requests and fields such as the applied limit, remaining tokens, and reset time.
| Public table | Granularity | Retention | Best for |
|---|---|---|---|
ratelimits_v1 | Individual request | 1 month | Recent request details and exact request times |
ratelimits_per_minute_v1 | Minute | 7 days | Recent dashboard charts |
ratelimits_per_hour_v1 | Hour | 30 days | Daily and weekly trends |
ratelimits_per_day_v1 | Day | 100 days | Longer reports |
ratelimits_per_month_v1 | Month | 3 years | Long-term trends |
Your workspace retention setting controls the time range that a query can request. If you omit a time filter, Unkey automatically constrains results to your workspace retention range. A query that stays within your workspace quota can request a range beyond a table's retention, but it returns only the rows that remain in that table. For example, a 30-day query against the minute table can contain partial data because that table retains 7 days. Select the hour table when you need the complete 30-day range.
Reference available columns#
The raw table contains one row for each rate limit request. Unkey automatically
filters workspace_id, so you don't need to include it in a query.
| Column | Type | Description |
|---|---|---|
request_id | String | Unique request ID |
time | Int64 | Request time as a Unix timestamp in milliseconds |
workspace_id | String | Workspace ID, automatically filtered |
namespace_id | String | Rate limit namespace ID |
identifier | String | Identifier that was limited |
passed | Bool | Whether the request passed the rate limit |
latency | Float64 | Time spent on the rate limit check in milliseconds |
override_id | String | Applied override ID, when an override matched |
limit | UInt64 | Applied token limit |
remaining | UInt64 | Tokens remaining after the request |
reset_at | Int64 | Reset time as a Unix timestamp in milliseconds |
tokens | UInt64 | Tokens requested |
The minute, hour, day, and month tables contain pre-aggregated rows.
| Column | Type | Description |
|---|---|---|
time | DateTime or Date | Start of the aggregation interval |
workspace_id | String | Workspace ID, automatically filtered |
namespace_id | String | Rate limit namespace ID |
identifier | String | Identifier that was limited |
passed | Int64 | Number of requests that passed the rate limit |
total | Int64 | Number of requests |
total_tokens | Int64 | Number of requested tokens |
passed_tokens | Int64 | Number of tokens from passed requests |
latency_avg | AggregateFunction | State for calculating average latency with avgMerge |
latency_p75 | AggregateFunction | State for calculating p75 latency with quantilesTDigestMerge(0.75) |
latency_p99 | AggregateFunction | State for calculating p99 latency with quantilesTDigestMerge(0.99) |
Use ClickHouse aggregate merge functions when selecting latency from an aggregated table:
Build a zero-filled time series#
Use WITH FILL to return every minute, including intervals without requests.
This query produces passed, blocked, and total metrics for both requests and
tokens, which supports a dashboard chart without client-side gap filling.
Combine multiple identifiers#
Filter with IN and omit identifier from GROUP BY to combine several
identifiers into one result. This example returns daily totals for three
customers.
Paginate an identifier breakdown#
Group by identifier to build a table with usage totals and the last request
time. The secondary identifier sort makes ordering stable when multiple rows
have the same request count. Keep the same ordering while changing OFFSET
for subsequent pages.