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+---
+title: Context propagation implementation details
+linkTitle: Context propagation
+description: Learn how OBI does context propagation for various languages and frameworks.
+weight: 24
+---
+
+## Introduction
+
+To support distributed tracing for HTTP and other protocols, OBI performs automatic context
+propagation, from incoming to outgoing requests. This context propagation works across protocols, 
+for example, correlation may occur between incoming HTTP request and an outgoing SQL request.
+
+In general, performing context propagation depends on how the application handles hand-off between
+worker threads. In some cases, the worker threads are not actual OS threads, but they can be an 
+abstraction on top of OS threads (e.g. `goroutines`, `coroutines`, `green threads`, `virtual threads`).
+Therefore, it's very difficult to implement a single correct context propagation approach that works
+for all programming languages and frameworks.
+
+OBI implements various approaches to tackle specific programming languages and frameworks, but
+they are by no means complete, and will fail to perform correct correlation in certain scenarios.
+This documents attempts to capture some of the details, and provide guidance on what works and
+what doesn't.
+
+## Implementation details
+
+In this section we'll go over each individual approach that is currently implemented and explain
+the scope.
+
+### Go programming language
+
+The Go threading model is based on `goroutines`, where many `goroutines` map to a single OS thread.
+Therefore, in order to perform correct correlation of incoming to outgoing requests, OBI tracks the
+`goroutines` lifecycle. We attach probes to `runtime.newproc1` and `runtime.goexit1`, to track the
+parent to child `goroutine` relationship, by keeping track the `goroutine` relationships in a 
+in-memory map.
+
+At a time of an outgoing client request, we use the parent to child relationship map, up to a depth of 3,
+to lookup any, still active, incoming request that has launched the outgoing request goroutine.
+
+Special consideration is taken for correct context propagation for `gRPC`, because the 
+outgoing requests are all handled by the so called `loopyWriter`, which is a single goroutine 
+handling the outgoing requests. In this specific scenario, we use the `HTTP2`/`gRPC` stream ID, 
+as a unique key to identify the original request, when it's appended to the write queue when
+`google.golang.org/grpc.(*ClientConn).NewStream` is invoked.
+
+### Node.js
+
+The `Node.js` runtime has an async request queue that is handling all incoming and outgoing requests.
+When an incoming request is handled, any outgoing requests, typically done in async fashion to
+avoid holding up the event loop, are added on the event queue loop as separate requests. To correctly
+propagate context between incoming and outgoing requests, we must know which async operation was 
+scheduled by what other async operation.
+
+Prior to `Node.js` 20 we used to track the async event loop correlation, by injecting probes into
+`EmitAsyncInit` and `AsyncReset`. However, from `Node.js` 20 and onward, more of the runtime 
+handling was rewritten in JavaScript, and the eBPF probe approach misses number of critical correlation
+steps.
+
+To correctly track `Node.js`, OBI injects a small agent that hooks into `serverEmit`, `socketConnect` and
+`socketWrite`. This agent is automatically injected in running processes, through the 
+`Node.js` debugger interface, and it has 0 dependencies. It extracts the incoming and outgoing
+file descriptors for the requests, and it communicates them to the eBPF side by performing a
+fake file operation on `/dev/null`.
+
+The eBPF side tracks the fake file access and establishes an internal in-memory map of 
+incoming to outgoing file descriptor mappings. When an outgoing request happens, OBI looks up
+the `Node.js` map to find the parent file descriptor, which is then matched to an incoming request.
+
+`Node.js` correlation doesn't for for `HTTP2`/`gRPC`.
+
+### nginx
+
+`nginx` has a unique threading model, where number of incoming requests and handled by a 
+custom thread pool of `upstream` handlers. To support `nginx` context propagation, OBI injects
+two probes, a probe in `ngx_http_upstream_init` and a return probe on `ngx_event_connect_peer`.
+
+At the time `ngx_http_upstream_init` is invoked, we start tracking the connection information
+of the incoming request, while when `ngx_event_connect_peer` returns, we create a mapping
+of the incoming request to the outgoing file descriptor. At the time OBI handles the outgoing 
+request, it looks up the outgoing call file descriptor and fetches the connection information
+of the incoming request, managing to correlate both. In a sense, this is very similar to how
+we lookup the information for the `Node.js` event loop.
+
+`nginx` correlation doesn't for for `HTTP2`/`gRPC`.
+
+### Generic approach
+
+The fallback approach of incoming to outgoing request correlation, for the purpose of
+distributed trace context propagation, relies on thread ID correlation. The following
+section outlines all the techniques we currently employ to match the requests by
+thread ID:
+
+1. Same thread. OBI tries to detect if the incoming and outgoing requests are handled
+by the same thread. It detects if multiple current outgoing requests are handled by
+the same thread and marks the correlation information as invalid. This helps us
+prevent incorrect correlation, when the application framework handles multiple 
+connections on the same thread.
+
+2. Thread launches from other threads, through tracking of `sys_clone`. This approach
+is similar to what we do for Go applications, where we track parent to child thread
+relationships based on thread creation. This only helps simple applications that do
+not use thread pools, and may have partial success with applications that have 
+elastic thread pools, enabling the correlation when the thread pool is scaled up.
+
+3. Connect calls or connection live checks on the incoming request. Number of 
+application frameworks perform the initial outgoing request connect on the 
+incoming thread, before they hand-off the work to the outgoing worker thread. In
+case of keep-alive, they peek on the outgoing connection to ensure it hasn't 
+dropped since the last request, which allows us to correlate the outgoing to the
+incoming request by the connection information. Essentially, we use the handling
+of the outgoing connection on the incoming request, as a way of matching the
+incoming to outgoing requests.
+
+This approach works well for single threaded programming languages and frameworks,
+for example `Python` applications that do not use `asyncio`. The OpenJDK internal
+HTTP client and the Apache HTTP client also work, because the outgoing connections
+are 'inspected' on the same thread that handles the incoming request.
+
+The generic correlation doesn't work for `HTTP2`/`gRPC`.
+
+## What doesn't work
+
+- Any reactive programming frameworks.
+- Application frameworks with thread pools that handle the full connection
+lifecycle on the outgoing worker threads. 
+- Application frameworks that handle all incoming traffic on the same thread,
+before handing over the request to be served by a worker thread. An example of this
+the `Puma reactor` used in `Ruby on Rails`.
+- `.net` `async`/`await` create number of complex thread pools that are unpredictable
+in how the work is scheduled.
+
+## Future work
+
+- We have identified an approach that will allow us to track the `Puma reactor` used
+in `Ruby on Rails`, by implementing an in-memory queue at the time the reactor thread
+is scheduling the work on the thread pool.
+
+- There might be a possibility to extend the generic tracking approach by tracking 
+epoll wait and wake in the kernel. For example, it appears that the `Java` `Netty` reactor
+is using epoll directly to ask for a client worker to pick up the next queued request.
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