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docs: fix stale links to the Metrics guide after move to /telemetry (#46816)
## I have read the [CONTRIBUTING.md](https://github.com/supabase/supabase/blob/master/CONTRIBUTING.md) file. YES ## What kind of change does this PR introduce? Docs update (stale internal links / dead anchors). ## What is the current behavior? The Metrics guide moved from `/docs/guides/platform/metrics` to `/docs/guides/telemetry/metrics` and was split into sub-pages, but 15 internal links across the docs still use the old path: 1. **Redirect chain** — non-anchored links to `/docs/guides/platform/metrics` only resolve via a two-hop permanent redirect (`platform/metrics` → `monitoring-troubleshooting/metrics` → `telemetry/metrics`, in `apps/www/lib/redirects.js`). 2. **Dead anchors** — `#accessing-the-metrics-endpoint` and `#deploying-supabase-grafana` no longer exist on the restructured page, so those links currently land at the top of the page instead of the intended section. ## What is the new behavior? - Non-anchored links now point directly at the canonical `/docs/guides/telemetry/metrics` (relative links use `../telemetry/metrics`), avoiding the redirect chain. - `#accessing-the-metrics-endpoint` links → `/docs/guides/telemetry/metrics` (the Metrics API endpoint access content lives on that page). - `#deploying-supabase-grafana` links → `/docs/guides/telemetry/metrics/grafana-self-hosted`, the page that now holds the Prometheus/Grafana installation instructions those links referenced. 15 files changed, links only — no content changes. ## Additional context Pure documentation link cleanup. Affected files include several guides (`database/connection-management`, `database/inspect`, `platform/performance`, `platform/read-replicas`) and troubleshooting entries that reference the Metrics/Grafana setup guide.
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@@ -51,7 +51,7 @@ For more details on using these monitoring charts, see the [Reports guide](/docs
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#### Grafana Dashboard
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Supabase offers a Grafana Dashboard that records and visualizes over 200 project metrics, including connections. For setup instructions, check the [metrics docs](/docs/guides/platform/metrics).
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Supabase offers a Grafana Dashboard that records and visualizes over 200 project metrics, including connections. For setup instructions, check the [metrics docs](/docs/guides/telemetry/metrics).
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Its "Client Connections" graph displays connections for both Supavisor and Postgres
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@@ -262,4 +262,4 @@ Using the query plan analyzer to optimize your queries is a large topic, with a
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- [Postgres Wiki.](https://wiki.postgresql.org/wiki/Using_EXPLAIN)
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- [Enterprise DB.](https://www.enterprisedb.com/blog/postgresql-query-optimization-performance-tuning-with-explain-analyze)
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You can pair the information available from `pg_stat_statements` with the detailed system metrics available [via your metrics endpoint](../platform/metrics) to better understand the behavior of your DB and the queries you're executing against it.
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You can pair the information available from `pg_stat_statements` with the detailed system metrics available [via your metrics endpoint](../telemetry/metrics) to better understand the behavior of your DB and the queries you're executing against it.
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@@ -29,7 +29,7 @@ In such a scenario, you can consider:
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### Configuring clients to use fewer connections
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You can use the [pg_stat_activity](https://www.postgresql.org/docs/current/monitoring-stats.html#MONITORING-PG-STAT-ACTIVITY-VIEW) view to debug which clients are holding open connections on your DB. `pg_stat_activity` only exposes information on direct connections to the database. Information on the number of connections to Supavisor is available [via the metrics endpoint](../platform/metrics).
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You can use the [pg_stat_activity](https://www.postgresql.org/docs/current/monitoring-stats.html#MONITORING-PG-STAT-ACTIVITY-VIEW) view to debug which clients are holding open connections on your DB. `pg_stat_activity` only exposes information on direct connections to the database. Information on the number of connections to Supavisor is available [via the metrics endpoint](../telemetry/metrics).
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Depending on the clients involved, you might be able to configure them to work with fewer connections (e.g. by imposing a limit on the maximum number of connections they're allowed to use), or shift specific workloads to connect via [Supavisor](/docs/guides/database/connecting-to-postgres#connection-pooler) instead. Transient workflows, which can quickly scale up and down in response to traffic (e.g. serverless functions), can especially benefit from using a connection pooler rather than connecting to the DB directly.
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@@ -151,7 +151,7 @@ For API logs, logs can originate from the API Load Balancer as well. The upstrea
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Observability and metrics for Read Replicas are available on the Supabase Dashboard. Resource utilization for a specific Read Replica can be viewed on the [Database Reports page](/dashboard/project/_/observability/database) by toggling for `Source`. Likewise, metrics on API requests going through either a Read Replica or Load Balancer API endpoint are also available on the dashboard through the [API Reports page](/dashboard/project/_/observability/api-overview)
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We recommend ingesting your [project's metrics](/docs/guides/platform/metrics#accessing-the-metrics-endpoint) into your own environment. If you have an existing ingestion pipeline set up for your project, you can [update it](https://github.com/supabase/supabase-grafana?tab=readme-ov-file#read-replica-support) to additionally ingest metrics from your Read Replicas.
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We recommend ingesting your [project's metrics](/docs/guides/telemetry/metrics) into your own environment. If you have an existing ingestion pipeline set up for your project, you can [update it](https://github.com/supabase/supabase-grafana?tab=readme-ov-file#read-replica-support) to additionally ingest metrics from your Read Replicas.
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### Centralized configuration management
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@@ -129,7 +129,7 @@ There is no single threshold to indicate when you should address replication lag
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<Admonition type="tip">
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If you are already ingesting your [project's metrics](/docs/guides/platform/metrics#accessing-the-metrics-endpoint) into your own environment, you can also keep track of replication lag and set alarms with the `physical_replication_lag_physical_replica_lag_seconds` metric.
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If you are already ingesting your [project's metrics](/docs/guides/telemetry/metrics) into your own environment, you can also keep track of replication lag and set alarms with the `physical_replication_lag_physical_replica_lag_seconds` metric.
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</Admonition>
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@@ -25,7 +25,7 @@ Running out of Disk IO Budget means that your instance is using more disk than i
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To check your Disk IO Budget on the Supabase Platform, head over to [Database Health in the Observability section](/dashboard/project/_/observability/database).
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It is also possible to monitor your resources and set up alerts using Prometheus/Grafana. With Grafana you will be able to pinpoint potential causes and see more fine-grained metrics like how much of your RAM is used for caching and your Swap usage. Read the [Metrics Guide](/docs/guides/platform/metrics) to learn more.
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It is also possible to monitor your resources and set up alerts using Prometheus/Grafana. With Grafana you will be able to pinpoint potential causes and see more fine-grained metrics like how much of your RAM is used for caching and your Swap usage. Read the [Metrics Guide](/docs/guides/telemetry/metrics) to learn more.
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## Common reasons for high disk IO usage
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@@ -31,7 +31,7 @@ High RAM usage could come with a range of issues:
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To check your RAM usage on the Supabase Platform, head over to [Database Health in the Observability section](/dashboard/project/_/observability/database).
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It is also possible to monitor your resources and set up alerts using Prometheus/Grafana. With Grafana you will be able to see how much of your RAM is used for caching and you can track other metrics such as your Swap usage. Read the [Metrics Guide](/docs/guides/platform/metrics) to learn more.
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It is also possible to monitor your resources and set up alerts using Prometheus/Grafana. With Grafana you will be able to see how much of your RAM is used for caching and you can track other metrics such as your Swap usage. Read the [Metrics Guide](/docs/guides/telemetry/metrics) to learn more.
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## Common reasons for high RAM usage
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@@ -33,7 +33,7 @@ High Swap usage can affect your database performance. For example, you might see
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## Monitor your swap
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You can monitor your resources and set up alerts using Prometheus/Grafana. See the [metrics guide](/docs/guides/platform/metrics) for more information.
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You can monitor your resources and set up alerts using Prometheus/Grafana. See the [metrics guide](/docs/guides/telemetry/metrics) for more information.
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An [example repository](https://github.com/supabase/supabase-grafana) to ingest metrics and visualize them with Grafana is provided in the linked guide, where we maintain a [list of the exported metrics](https://github.com/supabase/supabase-grafana/blob/main/docs/metrics.md).
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@@ -25,7 +25,7 @@ You can check your CPU usage directly on the Supabase Platform. For this go to d
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It is also possible to monitor your resources and set up alerts using Prometheus/Grafana. You can find a guide for this [here](/docs/guides/platform/metrics).
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It is also possible to monitor your resources and set up alerts using Prometheus/Grafana. You can find a guide for this [here](/docs/guides/telemetry/metrics).
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## Common reasons for high CPU usage
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@@ -7,6 +7,6 @@ keywords = [ "metrics", "grafana", "monitoring" ]
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database_id = "da2d95e5-abc5-47c8-8389-1554d12abf91"
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---
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To monitor real-time metrics of your database, like CPU, EBS, active database connections, and memory usage, you can deploy a Grafana Dashboard. Check our [GitHub repo](https://github.com/supabase/supabase-grafana) for setup instructions for local or free [Fly.io](http://fly.io/) deployments. Refer to our concise [documentation](/docs/guides/platform/metrics) to learn more about the metrics endpoint.
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To monitor real-time metrics of your database, like CPU, EBS, active database connections, and memory usage, you can deploy a Grafana Dashboard. Check our [GitHub repo](https://github.com/supabase/supabase-grafana) for setup instructions for local or free [Fly.io](http://fly.io/) deployments. Refer to our concise [documentation](/docs/guides/telemetry/metrics) to learn more about the metrics endpoint.
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While the [Dashboard's Reports Page](/dashboard/project/_/observability) displays some metric data, it provides hourly averages, not real-time by the second data. However, it offers query metrics, which the Grafana Dashboard does not include.
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@@ -7,7 +7,7 @@ keywords = [ "io", "disk", "database", "grafana" ]
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database_id = "0056cd40-df04-4045-bbfb-c245cb15b85d"
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---
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> [Supabase Grafana Installation Guide](/docs/guides/platform/metrics#deploying-supabase-grafana)
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> [Supabase Grafana Installation Guide](/docs/guides/telemetry/metrics/grafana-self-hosted)
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There are two primary values that matter for IO:
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@@ -19,7 +19,7 @@ _Visual of Grafana Dashboard_
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It can be run locally within Docker. Alternatively, you can deploy it to fly.io or Grafana Cloud, which are better for long-term data collection.
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Installation instructions can be found in it the [metrics docs ](/docs/guides/platform/metrics#deploying-supabase-grafana)
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Installation instructions can be found in it the [metrics docs ](/docs/guides/telemetry/metrics/grafana-self-hosted)
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## Observing connections
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@@ -23,7 +23,7 @@ Supabase has an [open-source Grafana Repo](https://github.com/supabase/supabase-
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_Visual of Grafana Dashboard_
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It can be run locally within Docker or can be deployed for free to fly.io. Installation instructions can be found in [Supabase's metrics docs](/docs/guides/platform/metrics#deploying-supabase-grafana)
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It can be run locally within Docker or can be deployed for free to fly.io. Installation instructions can be found in [Supabase's metrics docs](/docs/guides/telemetry/metrics/grafana-self-hosted)
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## Query optimization through indexes
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@@ -7,7 +7,7 @@ date_created = "2024-06-05"
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database_id = "179d70f3-1e26-4346-9ee8-d340fad382a3"
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---
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> [Supabase Grafana Installation Guide](/docs/guides/platform/metrics#deploying-supabase-grafana)
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> [Supabase Grafana Installation Guide](/docs/guides/telemetry/metrics/grafana-self-hosted)
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Here are examples of unhealthy memory usage:
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@@ -159,7 +159,7 @@ As a rule of thumb, if you're using the DB REST API or multiple app-based "user+
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Connection usage can be monitored with a Supabase Grafana Dashboard. It provides realtime visibility of over 200 database metrics, such as graphs of CPU, EBS, and active direct/pooler connections. It can be extremely useful for monitoring and debugging instances.
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You can check our [GitHub repo](https://github.com/supabase/supabase-grafana) for setup instructions for local deployments or free cloud deployments on [Fly.io](http://fly.io/). Refer to Supabase [documentation](/docs/guides/platform/metrics) to learn more about the metrics endpoint.
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You can check our [GitHub repo](https://github.com/supabase/supabase-grafana) for setup instructions for local deployments or free cloud deployments on [Fly.io](http://fly.io/). Refer to Supabase [documentation](/docs/guides/telemetry/metrics) to learn more about the metrics endpoint.
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### **Can Supavisor really support a million connections?**
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