What you will learn:
How to set up the integration
How to configure log forwarding
The full list of externally-available metrics
Available for Scale plan users, the Neon Datadog integration lets you monitor Neon database performance, resource utilization, and system health directly from Datadog's observability platform.
How it works
The integration enables secure, reliable export of Neon metrics and Postgres logs to Datadog. By configuring the integration with your Datadog API key, Neon automatically sends data from your project to your selected Datadog site.
note
Data is sent for all computes in your Neon project. For example, if you have multiple branches, each with an attached compute, both metrics and logs will be collected and sent for each compute.
Neon metrics
The integration exports a comprehensive set of metrics including:
- Connection counts — Tracks active and idle database connections.
- Database size — Monitors total size of all databases in bytes.
- Replication delay — Measures replication lag in bytes and seconds.
- Compute metrics — Includes CPU and memory usage statistics for your compute.
Postgres logs
Beta
Postgres logs export is in beta and ready to use. We're actively improving it based on feedback from developers like you. Share your experience in our Discord or via the Neon Console.
The Neon Datadog integration can forward Postgres logs to your Datadog account. These logs provide visibility into database activity, errors, and performance. See Export Postgres logs to Datadog for details.
Prerequisites
Before getting started, ensure the following:
- You have a Neon account and project. If not, see Sign up for a Neon account.
- You have a Datadog account and API key.
- You know the region you selected for your Datadog account. Here's how to check: Find your Datadog region
Steps to integrate Datadog with Neon
- In the Neon Console, navigate to the Integrations page in your Neon project.
- Locate the Datadog card and click Add.
- Enter your Datadog API key. You can generate or retrieve Datadog API Keys from your Datadog organization. For instructions, see Datadog API and Application Keys.
- Select the Datadog site that you used when setting up your Datadog account.
- Select what you want to export. You can enable either or both:
- Metrics: System metrics and database statistics (CPU, memory, connections, etc.)
- Postgres logs: Error messages, warnings, connection events, and system notifications
- Click Confirm to complete the integration.
note
You can change these settings later by editing your integration configuration.
Optionally, you can import the Neon-provided JSON configuration file into Datadog, which creates a pre-built dashboard from Neon metrics, similar to the charts available on our Monitoring page. See Import Neon dashboard.
We do not yet provide a pre-built dashboard for Postgres logs, but it's coming soon.
Once the integration is set up, Neon will start sending Neon metrics to Datadog, and you can use these metrics to create custom dashboards and alerts in Datadog.
note
Neon computes only send logs and metrics when they are active. If the Scale to Zero feature is enabled and a compute is suspended due to inactivity, no logs or metrics will be sent during the suspension. This may result in gaps in your Neon logs and metrics in Datadog. If you notice missing data in Datadog, check if your compute is suspended. You can verify a compute's status as Idle or Active on the Branches page in the Neon console, and review Suspend compute events on the System operations tab of the Monitoring page.
Additionally, if you are setting up Neon's Datadog integration for a project with an inactive compute, you'll need to activate the compute before it can send metrics and logs to Datadog. To activate it, simply run a query from the Neon SQL Editor or any connected client on the branch associated with the compute.
Example usage in Datadog
Once integrated, you can create custom dashboards in Datadog by querying the metrics sent from Neon. Use Datadog's Metrics Explorer to search for metrics like neon_connection_counts, neon_db_total_size, and host_cpu_seconds_total. You can also set alerts based on threshold values for critical metrics.
Import the Neon dashboard
As part of the integration, Neon provides a JSON configuration file that you can import into Datadog to start with a pre-built dashboard based on a subset of Neon metrics.
Here's how you can import the dashboard:
-
In the Neon Console, open your Datadog integration from the Integrations page.
-
Scroll to the bottom of the panel and copy the JSON from there.
OR
You can copy the JSON below instead.
-
Next, create a new dashboard in Datadog.
-
Open Configure, select Import dashboard JSON, then paste the Neon-provided configuration JSON.
If any of the computes in your project are active, you should start seeing data in the resulting charts right away. By default, the charts show metrics for all active endpoints in your project. You can filter results to one or more selected endpoints using the endpoint_id variable dropdown selector.
Dashboard JSON
Copy JSON configuration
{
"title": "Single Neon Compute metrics (with dropdown)",
"description": "",
"widgets": [
{
"id": 3831219857468963,
"definition": {
"title": "RAM",
"title_size": "16",
"title_align": "left",
"show_legend": true,
"legend_layout": "auto",
"legend_columns": [
"avg",
"min",
"max",
"value",
"sum"
],
"time": {},
"type": "timeseries",
"requests": [
{
"formulas": [
{
"number_format": {
"unit": {
"type": "canonical_unit",
"unit_name": "byte"
}
},
"alias": "Cached",
"formula": "query3"
},
{
"alias": "Used",
"number_format": {
"unit": {
"type": "canonical_unit",
"unit_name": "byte"
}
},
"formula": "query1 - query2"
}
],
"queries": [
{
"name": "query3",
"data_source": "metrics",
"query": "max:host_memory_cached_bytes{$endpoint_id}"
},
{
"name": "query1",
"data_source": "metrics",
"query": "max:host_memory_total_bytes{$endpoint_id}"
},
{
"name": "query2",
"data_source": "metrics",
"query": "max:host_memory_available_bytes{$endpoint_id}"
}
],
"response_format": "timeseries",
"style": {
"palette": "dog_classic",
"order_by": "values",
"line_type": "solid",
"line_width": "normal"
},
"display_type": "line"
}
]
},
"layout": {
"x": 0,
"y": 0,
"width": 6,
"height": 2
}
},
{
"id": 7296782684811837,
"definition": {
"title": "CPU",
"title_size": "16",
"title_align": "left",
"show_legend": true,
"legend_layout": "auto",
"legend_columns": [
"avg",
"min",
"max",
"value",
"sum"
],
"time": {},
"type": "timeseries",
"requests": [
{
"formulas": [
{
"alias": "Used",
"formula": "per_minute(query1)"
}
],
"queries": [
{
"name": "query1",
"data_source": "metrics",
"query": "max:host_cpu_seconds_total{!mode:idle,$endpoint_id}.as_rate()"
}
],
"response_format": "timeseries",
"style": {
"palette": "dog_classic",
"order_by": "values",
"line_type": "solid",
"line_width": "normal"
},
"display_type": "line"
}
]
},
"layout": {
"x": 6,
"y": 0,
"width": 6,
"height": 2
}
},
{
"id": 7513607855022102,
"definition": {
"title": "Connections",
"title_size": "16",
"title_align": "left",
"show_legend": true,
"legend_layout": "auto",
"legend_columns": [
"avg",
"min",
"max",
"value",
"sum"
],
"type": "timeseries",
"requests": [
{
"formulas": [
{
"alias": "Total",
"formula": "query1"
},
{
"alias": "Active",
"formula": "query2"
},
{
"alias": "Idle",
"formula": "query3"
}
],
"queries": [
{
"name": "query1",
"data_source": "metrics",
"query": "sum:neon_connection_counts{!datname:postgres,$endpoint_id}"
},
{
"name": "query2",
"data_source": "metrics",
"query": "sum:neon_connection_counts{!datname:postgres,state:active ,$endpoint_id}"
},
{
"name": "query3",
"data_source": "metrics",
"query": "sum:neon_connection_counts{!datname:postgres,!state:active,$endpoint_id}"
}
],
"response_format": "timeseries",
"style": {
"palette": "dog_classic",
"order_by": "values",
"line_type": "solid",
"line_width": "normal"
},
"display_type": "line"
}
]
},
"layout": {
"x": 0,
"y": 2,
"width": 6,
"height": 3
}
},
{
"id": 5523349536895199,
"definition": {
"title": "Database size",
"title_size": "16",
"title_align": "left",
"show_legend": true,
"legend_layout": "auto",
"legend_columns": [
"avg",
"min",
"max",
"value",
"sum"
],
"type": "timeseries",
"requests": [
{
"formulas": [
{
"number_format": {
"unit": {
"type": "canonical_unit",
"unit_name": "byte"
}
},
"formula": "query2"
},
{
"number_format": {
"unit": {
"type": "canonical_unit",
"unit_name": "byte"
}
},
"alias": "Size of all databases",
"formula": "query3"
},
{
"alias": "Max size",
"number_format": {
"unit": {
"type": "canonical_unit",
"unit_name": "byte"
}
},
"formula": "query1 * 1024 * 1024"
}
],
"queries": [
{
"name": "query2",
"data_source": "metrics",
"query": "max:neon_pg_stats_userdb{kind:db_size,$endpoint_id} by {datname}"
},
{
"name": "query3",
"data_source": "metrics",
"query": "max:neon_db_total_size{$endpoint_id}"
},
{
"name": "query1",
"data_source": "metrics",
"query": "max:neon_max_cluster_size{$endpoint_id}"
}
],
"response_format": "timeseries",
"style": {
"palette": "dog_classic",
"order_by": "values",
"line_type": "solid",
"line_width": "normal"
},
"display_type": "line"
}
],
"yaxis": {
"include_zero": false,
"scale": "log"
}
},
"layout": {
"x": 6,
"y": 2,
"width": 6,
"height": 3
}
},
{
"id": 1608572645458648,
"definition": {
"title": "Deadlocks",
"title_size": "16",
"title_align": "left",
"show_legend": true,
"legend_layout": "auto",
"legend_columns": [
"avg",
"min",
"max",
"value",
"sum"
],
"type": "timeseries",
"requests": [
{
"formulas": [
{
"alias": "Deadlocks",
"formula": "query1"
}
],
"queries": [
{
"name": "query1",
"data_source": "metrics",
"query": "max:neon_pg_stats_userdb{kind:deadlocks,$endpoint_id} by {datname}"
}
],
"response_format": "timeseries",
"style": {
"palette": "dog_classic",
"order_by": "values",
"line_type": "solid",
"line_width": "normal"
},
"display_type": "line"
}
]
},
"layout": {
"x": 0,
"y": 5,
"width": 6,
"height": 2
}
},
{
"id": 5728659221127513,
"definition": {
"title": "Changed rows",
"title_size": "16",
"title_align": "left",
"show_legend": true,
"legend_layout": "auto",
"legend_columns": [
"avg",
"min",
"max",
"value",
"sum"
],
"type": "timeseries",
"requests": [
{
"formulas": [
{
"alias": "Rows inserted",
"formula": "diff(query1)"
},
{
"alias": "Rows deleted",
"formula": "diff(query2)"
},
{
"alias": "Rows updated",
"formula": "diff(query3)"
}
],
"queries": [
{
"name": "query1",
"data_source": "metrics",
"query": "max:neon_pg_stats_userdb{kind:inserted,$endpoint_id}"
},
{
"name": "query2",
"data_source": "metrics",
"query": "max:neon_pg_stats_userdb{kind:deleted,$endpoint_id}"
},
{
"name": "query3",
"data_source": "metrics",
"query": "max:neon_pg_stats_userdb{kind:updated,$endpoint_id}"
}
],
"response_format": "timeseries",
"style": {
"palette": "dog_classic",
"order_by": "values",
"line_type": "solid",
"line_width": "normal"
},
"display_type": "line"
}
]
},
"layout": {
"x": 6,
"y": 5,
"width": 6,
"height": 2
}
},
{
"id": 630770240665422,
"definition": {
"title": "Local file cache hit rate",
"title_size": "16",
"title_align": "left",
"show_legend": true,
"legend_layout": "auto",
"legend_columns": [
"avg",
"min",
"max",
"value",
"sum"
],
"time": {},
"type": "timeseries",
"requests": [
{
"formulas": [
{
"alias": "Cache hit rate",
"formula": "query1 / (query1 + query2)",
"number_format": {
"unit": {
"type": "canonical_unit",
"unit_name": "fraction"
}
}
}
],
"queries": [
{
"name": "query1",
"data_source": "metrics",
"query": "max:neon_lfc_hits{$endpoint_id}"
},
{
"name": "query2",
"data_source": "metrics",
"query": "max:neon_lfc_misses{$endpoint_id}"
}
],
"response_format": "timeseries",
"style": {
"palette": "dog_classic",
"order_by": "values",
"line_type": "solid",
"line_width": "normal"
},
"display_type": "line"
}
]
},
"layout": {
"x": 0,
"y": 7,
"width": 6,
"height": 3
}
},
{
"id": 2040733022455075,
"definition": {
"title": "Working set size",
"title_size": "16",
"title_align": "left",
"show_legend": true,
"legend_layout": "auto",
"legend_columns": [
"avg",
"min",
"max",
"value",
"sum"
],
"time": {},
"type": "timeseries",
"requests": [
{
"formulas": [
{
"alias": "Local file cache size",
"number_format": {
"unit": {
"type": "canonical_unit",
"unit_name": "byte"
}
},
"formula": "query2"
},
{
"number_format": {
"unit": {
"type": "canonical_unit",
"unit_name": "byte"
}
},
"formula": "8192 * query1"
}
],
"queries": [
{
"name": "query2",
"data_source": "metrics",
"query": "max:neon_lfc_cache_size_limit{$endpoint_id}"
},
{
"name": "query1",
"data_source": "metrics",
"query": "max:neon_lfc_approximate_working_set_size_windows{$endpoint_id} by {duration}"
}
],
"response_format": "timeseries",
"style": {
"palette": "dog_classic",
"order_by": "values",
"line_type": "solid",
"line_width": "normal"
},
"display_type": "line"
}
]
},
"layout": {
"x": 6,
"y": 7,
"width": 6,
"height": 3
}
}
],
"template_variables": [
{
"name": "endpoint_id",
"prefix": "endpoint_id",
"available_values": [],
"default": "*"
},
{
"name": "project_id",
"prefix": "project_id",
"available_values": [],
"default": "*"
},
{
"name": "state",
"prefix": "state",
"available_values": [],
"default": "*"
}
],
"layout_type": "ordered",
"notify_list": [],
"reflow_type": "fixed"
}Available metrics
Neon exports a comprehensive set of metrics including connection counts, database size, replication delay, and compute metrics (CPU and memory usage). For a complete list of all available metrics with detailed descriptions, see the Metrics and logs reference.
Export Postgres logs to Datadog
You can export your Postgres logs from your Neon compute to your Datadog account. These logs provide visibility into database activity, errors, and performance. For detailed information about log fields and technical considerations, see the Metrics and logs reference.
Performance impact
Enabling this feature may result in:
- An increase in compute resource usage for log processing
- Additional network egress for log transmission, which is billed after 100 GB on paid plans
- Associated costs based on log volume in Datadog
Feedback and future improvements
We’re always looking to improve! If you have feature requests or feedback, please let us know via the Feedback form in the Neon Console or on our Discord channel.
Need help?
Join our Discord Server to ask questions or see what others are doing with Neon. For paid plan support options, see Support.