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To follow one request across orders-api and catalog-api, give it a request ID, pass that same ID in an x-request-id header, and include it in each service’s JSON log entries. Then search for the ID in Light Cloud’s Logs tabs to see the related events together.
This tutorial is the final installment of Light Cloud’s “Microservices on Light Cloud” series. It starts with the Bean There project from Parts 1–5 and uses Python for orders-api, JavaScript for catalog-api, and Light Cloud’s Logs tab. The tutorial was published September 29, 2026; its workflow demonstrates request correlation in that platform, not a replacement for a full distributed tracing system. See Light Cloud’s Microservices Part 6 tutorial.
What the request ID does
A request ID is a shared label for log entries produced while handling one request. In this example, orders-api receives a request, calls catalog-api, and includes the same ID in both services’ logs. The ID also goes back to the caller in the response header, so it can be used to look up the request later.
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Where the ID should come from
For this sample, a request may already include an ID. For production use, the tutorial recommends that the first service create it when needed; a browser should not choose the ID. The caller can get the ID from the response header or from the first log entry.
Prerequisites and deployment
Use the Bean There project from Parts 1–5. You need Git and a terminal with curl; on PowerShell 7 for Windows, use curl.exe. The tutorial identifies the part-6 tag in the tutorial-microservices repository. Both APIs change in this part, so redeploy orders-api and catalog-api before testing. The tutorial’s curl commands use placeholder deployment hosts; replace them with the endpoint for your own deployment.
Record the same fields in both services
Write one JSON object per line and include severity, service, requestId, and message. The shared field names and the shared request ID make it possible to search both services for the same request. Light Cloud’s Logs tab reads the severity field to set the log level and enable level filtering.
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orders-api: serialize a log record as JSON, print it, and flush the output. - JavaScript in
catalog-api: serialize one log record as JSON and write it to the console.
Use the service’s own name in service, the propagated value in requestId, and an appropriate level such as a warning for a failed product lookup. Keeping the shape consistent is more important here than making the messages identical.
Follow a successful order across both services
- Send an order request to the deployed
orders-apiusing the tutorial’s curl example, substituting your deployment host for the placeholder hostname. - Capture its request ID. Read the
x-request-idresponse header, or use the first log entry if you are examining a request already made. - Search the ID in
orders-api. Open its Logs tab in Light Cloud and search the exact request ID. - Search the same ID in
catalog-api. Open that service’s Logs tab and search the identical value, not a newly generated ID.
For the sample successful order, the related entries include messages such as “placing order,” “order placed,” and “reserved stock.” Their timestamps and shared request ID help show the request’s path between services.
Find the logs for a failed order
The tutorial’s failure case submits an order for a product that does not exist. The response is 404 Product not found, and the application records a warning. Light Cloud marks 4xx HTTP request logs as WARNING in its interface; this behavior describes Light Cloud’s Logs tab, not all logging systems.
- In the Logs tab, select a warnings-and-above filter to narrow the entries.
- Open the warning entry associated with the failed order and inspect its request ID.
- Search that ID in the
catalog-apiLogs tab to locate the related service entry.
This approach works whether you already know the request ID or first need to find a failure by its severity. A severity filter helps locate candidate events; the request ID then connects the relevant entries across services.
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What this workflow does—and does not—cover
This is a practical request-correlation pattern for the two APIs in the Bean There tutorial. It establishes how to create or retain an ID, forward it between these services, log it as JSON, and find matching entries in Light Cloud. The tutorial does not establish how to propagate context through asynchronous messages or provide broader production distributed-tracing guidance, so do not treat this logging setup as a complete tracing design.
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