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Version: v2.x

Export Traces, Metrics and Logs to OpenTelemetry Compliant Receiver from Hasura


Distributed traces track and map journeys of user requests across various services or components which can then be analyzed via observability tools.

Traces are typically used to diagnose or debug which part of your application could potentially be responsible for a failure or error state and to monitor the performance of end-user interactions with your application.

Traces are generated by instrumenting application code. Hasura has instrumented all API queries, mutations and subscriptions with the OpenTelemetry format. These traces can be exported directly from your Hasura instances to your observability tool that supports OpenTelemetry traces. This can be configured in the Settings section of the Hasura Console.

Available Metrics

The available OpenTelemetry metrics are the same as those available via Prometheus.

Configure the OpenTelemetry receiver

Supported from

OpenTelemetry traces are supported for Hasura GraphQL Engine versions v2.18.0 and above on Self-Hosted Enterprise, with support for metrics export added in v2.31.0 and for logs export added in v2.35.0. Also, available to all cloud tiers.

We have deprecated the previous Open Telemetry exporter integration on Hasura Cloud in favor of this native feature, and you can now configure this directly via the Hasura Console's Settings page under the Monitoring & Observability section.

All users are encouraged to migrate to this new integration.

Traces on Hasura Cloud

Hasura Cloud implements sampling on traces. That means only one in every n traces will be sampled and exported (n will be automatically configured based on various parameters during runtime. This can't be manually adjusted).

Go to the Settings tab (⚙) in the console and click on OpenTelemetry Exporter. After adding appropriate values to the parameters, click Update and then toggle the Status button to enable the integration.

OpenTelemetry Configuration


The following parameters are needed to set up the integration with your observability tool:


The OpenTelemetry compliant receiver endpoint. The URL scheme (http or https) determines if SSL(TLS) should be used for the communication. Please check the documentation for your observability tool to determine how to set up an OpenTelemetry endpoint. There may be different endpoints provided for the HTTP and gRPC protocols (gRPC is not supported yet), so ensure that you use the appropriate endpoint for your chosen connection type.

Endpoint Notes

  • Environment variable templating is available for the endpoint URL, e.g. https://{{ENV_VAR}}/v1/traces
  • You may need to append /v1/traces or /v1/metrics to the end of the receiver endpoint URL if the provided URL does not contain this already. This depends on the observability vendor.
  • If you are running Hasura as a Docker container without host networking enabled, and want to connect to a local OpenTelemetry Collector, you may want to use this as the endpoint: http://host.docker.internal:4318/v1/traces.
  • If the https endpoint uses a custom or self-signed CA, add the endpoint to the Insecure TLS Allow List.
OpenTelemetry Port Convention

It is a generally accepted convention that the OpenTelemetry receiver endpoint is exposed on port 4318 for HTTP but can usually be customized. Please check the documentation for your observability tool to determine the port number.

Connection Type

The protocol and transport to be used for the communication with the receiver. Hasura currently only supports the OpenTelemetry Protocol over HTTP (OTLP/HTTP with binary-encoded Protobuf payloads).

Data Type

Selects the type of observability data points to be exported. Traces, Logs and Metrics are the only data types that are currently supported.

Batch Size

Batch size is the maximum number of data points (spans in the context of traces) allowed per export request made to the observability tool. Default size is 512.

Trace Propagations

Trace Propagation implements the mechanism that exchanges context between services and processes. It serializes or deserializes the context object and provides the relevant trace information to be propagated from one service to another. GraphQL Engine supports the following propagation mechanisms:

Trace Propagation support

W3C Trace Context is supported for Hasura GraphQL Engine versions v2.35.0 and above.

B3 propagation is enabled by default. You can enable other protocols in the OpenTelemetry Exporter configuration.

OpenTelemetry Trace Propagation Configuration


Headers are (optionally) added to every request made by Hasura to the observability tool. They are generally Authorization/API keys with the required role/permissions to accept OpenTelemetry data. Please refer to the documentation in your observability tool to understand how required request headers need to be formatted. You can use an environment variable as a header value too. This is important for values which are sensitive.

Apply environment variables first

If you use an environment variable as a header value, please make sure that it's applied to the Hasura Docker container before starting the container.

Example using Console:

OpenTelemetry Header Console Configuration


Resource attributes are (optional) custom tags that are sent alongside observability data in order to identify the entity for which the observability data was recorded. This is usually used to identify sources in a distributed tracing environment and aids in granular filtering and analytics.

Example using Console:

OpenTelemetry Attributes Console Configuration

Your observability tool may expect to receive certain resource attributes in order to provide full functionality; such resource attributes must be set with this parameter. Many, but not all, of these resource attributes will be OpenTelemetry Semantic Conventions.

Hasura automatically sets some resource attributes. The values of such attributes can be overridden by specifying your own value for the attribute using this parameter.

Default resource attributes

Attribute type support

Hasura currently only supports string-valued attributes.

Consuming and visualizing traces

You can utilize your observability tool's UI to visualize and perform further analytics on trace data to monitor, diagnose and troubleshoot your application. Typically, traces and their spans are listed out and selecting a trace shows a flame graph containing a visual representation of where the operation spent its execution time. Below, we provide some examples of how to consume and visualize traces using popular observability tools.


To use Jaeger, simply add this to your docker-compose.yaml:

image: jaegertracing/all-in-one:1.37
restart: always
- 5775:5775/udp
- 6831:6831/udp
- 6832:6832/udp
- 5778:5778
- 4002:16686
- 14250:14250
- 14268:14268
- 14269:14269
- 4317:4317 # OTLP gRPC
- 4318:4318 # OTLP HTTP
- 9411:9411

The image below shows a flame graph in Jaeger where a query took 5.64 milliseconds in total, of which 2.78 milliseconds was the actual Postgres database processing the query.

Flame graph for a trace entry in Jaeger

OpenTelemetry Collector

OpenTelemetry provides the OpenTelemetry Collector that can export OpenTelemetry data to observability tools that do not support native OpenTelemetry ingestion.

To work with such observability tools, Hasura's OpenTelemetry integration can be configured to send OpenTelemetry data to the collector.


This collector should be run in your infrastructure and should be reachable by the Hasura backend that is configured to send the data to it. The list of supported exporter targets can be found in the OpenTelemetry Collector repository.

Connect Logs and Traces

Trace and Span ID are included in the root of the log body. GraphQL Engine follows OpenTelemetry's data model so that OpenTelemetry-compliant services can automatically correlate logs with Traces. However, some services need extra configurations.


Grafana can link Jaeger with log data sources such as Loki, Elasticsearch, Splunk, etc... To do that, you need to configure Trace to logs in Jaeger's data source settings.

Jaeger traces and Loki logs correlation config

In this example, Traces are linked to Loki logs by the traceid. You also can copy the below configuration to the data source file.

- name: Jaeger
type: jaeger
url: http://jaeger:16686/
datasourceUid: 'Loki'
spanStartTimeShift: '1h'
spanEndTimeShift: '-1h'
filterByTraceID: false
filterBySpanID: false
customQuery: true
query: '{exporter="OTLP"} | json | traceid=`$${__span.traceId}`'
timeShiftEnabled: true
spanStartTimeShift: '1h'
spanEndTimeShift: '-1h'

You will see the Logs for this span button enabled when exploring the trace detail.

Jaeger traces and Loki logs correlation


If Datadog can't correlate between traces and logs, you should verify the Trace ID attributes mapping. Read more at the troubleshooting section on Datadog.

Datadog traces and logs correlation


Traces and logs can't correlate together if they are exported to different datasets. Note that Honeycomb will use the attribute as the dataset where logs are exported. Therefore the x-honeycomb-dataset header must be matched with that attribute.

Honeycomb traces and logs correlation