How to integrate Datadog with OpenReplay and see backend errors alongside session recordings.

1. Generate Datadog API Key & Application Key

Go to Datadog > Integrations > APIs and generate the API Key, or use the existing one.

Datadog API Key

On the same page, click on Application Keys and generate a new application key.

Datadog Application Key

2. Enable Integration in OpenReplay

Paste your API Key and Application Key in Datadog in OpenReplay dashboard under 'Preferences > Integration'.

Datadog Integration in OpenReplay

3. Propagate openReplaySessionToken

To link a Datadog event with the recorded user session, a unique token has to be propagated from your frontend to your backend on each request you want to track. This can be done using a custom HTTP header. In the below example, we use the fetch function to send that header.

const headers = {
Accept: 'application/json',
'Content-Type': 'application/json',
if (tracker.getSessionToken()) { // or window.OpenReplay instead of tracker if you're using the snippet
headers['X-OpenReplay-SessionToken'] = tracker.getSessionToken(); // Inject openReplaySessionToken
fetch('', {

In order for OpenReplay to associate a Datadog log entry with the recorded user session, a unique token has to be propagated to each backend error you wish to track.

Below is an example in Python using Monkey Patching.

import sys
import traceback
old_tb = traceback.print_exception
old_f = sys.stdout
old_e = sys.stderr
class F:
def write(self, x):
if OPENREPLAY_SESSION_TOKEN is not None and x != '\n':
old_f.write(f"[openReplaySessionToken={OPENREPLAY_SESSION_TOKEN}] {x}")
def flush(self):
def tb_print_exception(etype, value, tb, limit=None, file=None, chain=True):
value = type(value)(f"[openReplaySessionToken={OPENREPLAY_SESSION_TOKEN}] " + str(value))
old_tb(etype, value, tb, limit, file, chain)
traceback.print_exception = tb_print_exception
sys.stderr = F()

The name of the tag openReplaySessionToken is case sensitive.


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