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@multiplayer-app/session-recorder-node
Advanced tools

The Multiplayer Full Stack Session Recorder is a powerful tool that offers deep session replays with insights spanning frontend screens, platform traces, metrics, and logs. It helps your team pinpoint and resolve bugs faster by providing a complete picture of your backend system architecture. No more wasted hours combing through APM data; the Multiplayer Full Stack Session Recorder does it all in one place.
npm i @multiplayer-app/session-recorder-node
# or
yarn add @multiplayer-app/session-recorder-node
Multiplayer Full Stack Session Recorder is built on top of OpenTelemetry.
No problem. You can set it up in a few minutes. If your services don't already use OpenTelemetry, you'll first need to install the OpenTelemetry libraries. Detailed instructions for this can be found in the OpenTelemetry documentation.
You have two primary options for routing your data to Multiplayer:
Direct Exporter: This option involves using the Multiplayer Exporter directly within your services. It's a great choice for new applications or startups because it's simple to set up and doesn't require any additional infrastructure. You can configure it to send all session recording data to Multiplayer while optionally sending a sampled subset of data to your existing observability platform.
OpenTelemetry Collector: For large, scaled platforms, we recommend using an OpenTelemetry Collector. This approach provides more flexibility by having your services send all telemetry to the collector, which then routes specific session recording data to Multiplayer and other data to your existing observability tools.
Send OpenTelemetry data from your services to Multiplayer and optionally other destinations (e.g., OpenTelemetry Collectors, observability platforms, etc.).
This is the quickest way to get started, but consider using an OpenTelemetry Collector (see Option 2 below) if you're scalling or a have a large platform.
import {
SessionRecorderHttpTraceExporter,
SessionRecorderHttpLogsExporter,
SessionRecorderTraceExporterWrapper
SessionRecorderLogsExporterWrapper,
} from "@multiplayer-app/session-recorder-node"
import { OTLPTraceExporter } from "@opentelemetry/exporter-trace-otlp-http"
import { OTLPLogExporter } from "@opentelemetry/exporter-logs-otlp-http"
// set up Multiplayer exporters. Note: GRPC exporters are also available.
// see: `SessionRecorderGrpcTraceExporter` and `SessionRecorderGrpcLogsExporter`
const multiplayerTraceExporter = new SessionRecorderHttpTraceExporter({
apiKey: "MULTIPLAYER_API_KEY", // note: replace with your Multiplayer API key
})
const multiplayerLogExporter = new SessionRecorderHttpLogsExporter({
apiKey: "MULTIPLAYER_API_KEY", // note: replace with your Multiplayer API key
})
// Multiplayer exporter wrappers filter out session recording atrtributes before passing to provided exporter
const traceExporter = new SessionRecorderTraceExporterWrapper(
// add any OTLP trace exporter
new OTLPTraceExporter({
// ...
})
)
const logExporter = new SessionRecorderLogsExporterWrapper(
// add any OTLP log exporter
new OTLPLogExporter({
// ...
})
)
If you're scalling or a have a large platform, consider running a dedicated collector. See the Multiplayer OpenTelemetry collector repository which shows how to configure the standard OpenTelemetry Collector to send data to Multiplayer and optional other destinations.
Add standard OpenTelemetry code to export OTLP data to your collector.
See a basic example below:
import { OTLPTraceExporter } from "@opentelemetry/exporter-trace-otlp-http"
import { OTLPLogExporter } from "@opentelemetry/exporter-logs-otlp-http"
const traceExporter = new OTLPTraceExporter({
url: "http://<OTLP_COLLECTOR_URL>/v1/traces",
headers: {
// ...
}
})
const logExporter = new OTLPLogExporter({
url: "http://<OTLP_COLLECTOR_URL>/v1/logs",
headers: {
// ...
}
})
In addition to sending traces and logs, you need to capture request and response content. We offer two solutions for this:
In-Service Code Capture: You can use our libraries to capture, serialize, and mask request/response and header content directly within your service code. This is an easy way to get started, especially for new projects, as it requires no extra components in your platform.
Multiplayer Proxy: Alternatively, you can run a Multiplayer Proxy to handle this outside of your services. This is ideal for large-scale applications and supports all languages, including those like Java that don't allow for in-service request/response hooks. The proxy can be deployed in various ways, such as an Ingress Proxy, a Sidecar Proxy, or an Embedded Proxy, to best fit your architecture.
The Multiplayer Session Recorder library provides utilities for capturing request, response and header content. See example below:
import {
SessionRecorderHttpInstrumentationHooksNode,
} from "@multiplayer-app/session-recorder-node"
import {
getNodeAutoInstrumentations,
} from "@opentelemetry/auto-instrumentations-node"
import { type Instrumentation } from "@opentelemetry/instrumentation"
export const instrumentations: Instrumentation[] = getNodeAutoInstrumentations({
"@opentelemetry/instrumentation-http": {
enabled: true,
responseHook: SessionRecorderHttpInstrumentationHooksNode.responseHook({
// list of headers to mask in request/response headers
maskHeadersList: ["set-cookie"],
// set the maximum request/response content size (in bytes) that will be captured
// any request/response content greater than size will be not included in session recordings
maxPayloadSizeBytes: 500000,
isMaskBodyEnabled: false,
isMaskHeadersEnabled: true,
}),
requestHook: SessionRecorderHttpInstrumentationHooksNode.requestHook({
maskHeadersList: ["Authorization", "cookie"],
maxPayloadSizeBytes: 500000,
isMaskBodyEnabled: false,
isMaskHeadersEnabled: true,
}),
}
})
The Multiplayer Proxy enables capturing request/response and header content without changing service code. See instructions at the Multiplayer Proxy repository.
The Multiplayer Full Stack Session Recorder can be used inside the CLI apps.
The Multiplayer Time Travel Demo includes an example node.js CLI app.
See an additional example below.
Use the following code below to initialize and run the session recorder.
The example relies on opentelemetry.ts. Copy that file and put it next to quick start code.
// IMPORTANT: set up OpenTelemetry
// for an example see ./examples/cli/src/opentelemetry.ts
// NOTE: for the code below to work copy ./examples/cli/src/opentelemetry.ts to ./opentelemetry.ts
import { idGenerator } from "./opentelemetry"
import { sessionRecorder } from "@multiplayer-app/session-recorder-node"
sessionRecorder.init({
apiKey: "MULTIPLAYER_API_KEY", // note: replace with your Multiplayer API key
traceIdGenerator: idGenerator,
resourceAttributes: {
componentName: "{YOUR_APPLICATION_NAME}",
version: "{YOUR_APPLICATION_VERSION}",
environment: "{YOUR_APPLICATION_ENVIRONMENT}",
}
})
Below is an example showing how to create a session recording in MANUAL mode. Manual session recordings stream and save all the data between calling start and stop.
import { sessionRecorder, SessionType } from "@multiplayer-app/session-recorder-node"
await sessionRecorder.start(
SessionType.MANUAL,
{
name: "This is test session",
sessionAttributes: {
accountId: "1234",
accountName: "Acme Corporation"
}
}
)
// do something here
await sessionRecorder.stop()
Below is an example showing how to create a session in CONTINUOUS mode. Continuous session recordings stream all the data received between calling start and cancel -
but only save a rolling window data (90 seconds by default) when:
save is called; orimport { sessionRecorder, SessionType } from "@multiplayer-app/session-recorder-node"
await sessionRecorder.start(
SessionType.CONTINUOUS,
{
name: "This is test session",
sessionAttributes: {
accountId: "1234",
accountName: "Acme Corporation"
}
}
)
// do something here
await sessionRecorder.save()
// do something here
await sessionRecorder.save()
// do something here
// or cancel
await sessionRecorder.cancel()
Continuous session recordings may also be saved from within any service or component involved in a trace by adding the attributes below to a span:
import { trace, context } from "@opentelemetry/api"
import {
ATTR_MULTIPLAYER_CONTINUOUS_SESSION_AUTO_SAVE,
ATTR_MULTIPLAYER_CONTINUOUS_SESSION_AUTO_SAVE_REASON,
} from "@multiplayer-app/session-recorder-node"
const activeContext = context.active()
const activeSpan = trace.getSpan(activeContext)
activeSpan.setAttribute(ATTR_MULTIPLAYER_CONTINUOUS_SESSION_AUTO_SAVE, true)
activeSpan.setAttribute(ATTR_MULTIPLAYER_CONTINUOUS_SESSION_AUTO_SAVE_REASON, "Some reason")
Use cancel() to end a CONTINUOUS session without saving the final window, or to discard a MANUAL session:
await sessionRecorder.cancel()
checkRemoteContinuousSession() polls the Multiplayer API to check whether a continuous session should be started or stopped remotely. Call it on a schedule (e.g. every 30 seconds) to enable remotely-triggered session recordings:
import { sessionRecorder } from "@multiplayer-app/session-recorder-node"
setInterval(async () => {
await sessionRecorder.checkRemoteContinuousSession({
name: "Remote-controlled session",
sessionAttributes: {
accountId: "1234",
},
})
}, 30000)
Replace the placeholders with your application’s version, name, environment, and API key.
The package includes an Express error handler middleware that automatically captures uncaught errors (HTTP 5xx) as Multiplayer exceptions:
import express from "express"
import { Integrations } from "@multiplayer-app/session-recorder-node"
const app = express()
// ... your routes ...
// Add as the last middleware
app.use(Integrations.express.expressErrorHandler())
You can provide a custom shouldHandleError predicate to control which errors are captured:
app.use(
Integrations.express.expressErrorHandler({
shouldHandleError(error) {
return error.statusCode >= 400
},
})
)
FAQs
Multiplayer Fullstack Session Recorder for Node.js
The npm package @multiplayer-app/session-recorder-node receives a total of 812 weekly downloads. As such, @multiplayer-app/session-recorder-node popularity was classified as not popular.
We found that @multiplayer-app/session-recorder-node demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 5 open source maintainers collaborating on the project.
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