DataDog's Dd-trace-py Bug: Runtime Error During Iteration

Hey guys, let's dive into a pesky bug we've been wrestling with involving DataDog's dd-trace-py library. Specifically, we're hitting a RuntimeError: dictionary changed size during iteration error. This is a real head-scratcher, especially when you're dealing with concurrent operations and, in our case, a ThreadPoolExecutor. Let's break down the issue, the environment where it's popping up, and how we're experiencing it. This is a pretty common problem, so if you're experiencing it too, don't worry, you're not alone!

The Nitty-Gritty: The Error and the Context

So, the core problem is a RuntimeError that stems from a dictionary changing size while it's being iterated over. This typically happens when you're modifying a dictionary (adding, removing, or changing items) while you're looping through it. In a single-threaded environment, this usually isn't a problem, as you have control over the flow. However, in concurrent scenarios, such as when using a ThreadPoolExecutor, multiple threads can potentially access and modify the same dictionary simultaneously. This race condition can lead to the dictionary changing size mid-iteration, which the Python interpreter flags as an error to prevent inconsistent behavior.

We're seeing this error specifically within our code, which involves numerous concurrent calls to generate spans using the dd-trace-py library. Our application is heavily dependent on this library for tracing and monitoring purposes, which makes this bug particularly critical. It's essentially breaking our ability to track and understand our application's performance accurately. This is why we need to sort it out as soon as possible. The traceback often doesn't give a lot of help in these cases, and the error happens because the internal state of a dictionary changes during an iteration. This is a very common scenario that can be difficult to debug.

The error started showing up after we upgraded from version 3.16.2 of the library to version 3.18.0. This indicates that the problem might be related to changes introduced in the more recent versions of dd-trace-py. It's worth noting that we have been using the dd-trace-py library with Django, as the two are designed to work together to automatically create spans for common operations like HTTP requests and database queries. This is another area to think about when troubleshooting a bug. Upgrading a library like ddtrace can sometimes expose vulnerabilities that you didn't even know existed.

Technical Details and Environment

For those of you who want to get your hands dirty, the issue seems to be tied to concurrent operations involving the creation of spans. Spans are the fundamental building blocks of tracing, representing individual units of work within a distributed system. The ThreadPoolExecutor is a part of Python's concurrent.futures module. It's designed to run tasks in parallel using a pool of worker threads. This is where the concurrency comes into play. The ThreadPoolExecutor is super handy for tasks like making multiple API calls, processing data in parallel, or, as in our case, creating spans.

We're running Python 3.13.3, pip version 25.3, and we're using Django 5.2.8 and psycopg2 2.9.11 alongside ddtrace==3.18.0. We're also using a bunch of other packages, but we've narrowed it down to these as the most relevant. The Operating System isn't specified, but it's unlikely to be the root cause of this particular issue, though you should always consider the platform when debugging. This environment information is super critical when you're working on a bug, because you need to ensure you're on the same version.

Diving Deeper: Reproduction, Error Logs, and Libraries

Unfortunately, we don't have a simple, isolated snippet of code (reproduction code) to share that directly replicates the error. This is common when dealing with complex concurrent issues, since it's hard to narrow down and reproduce without a lot of effort. This is one of the hardest parts of debugging. The error is quite intermittent and appears to be triggered under specific load conditions. It usually involves multiple threads trying to interact with the internal data structures of dd-trace-py simultaneously.

We also lack detailed error logs beyond the standard RuntimeError traceback, making it a bit tougher to pinpoint the exact location of the problem within the dd-trace-py library. The RuntimeError itself is a general indication of the issue, but it does not tell you specifically which part of the code is the problem.

As mentioned before, the key libraries in use are django==5.2.8, psycopg2==2.9.11, and ddtrace==3.18.0. These versions are crucial for context, since incompatibilities or specific behaviors within these libraries could be playing a role. It's important to remember that the combination of these libraries is critical. The bug might not happen if the versions were different.

Investigating the Problem

One of the first things we did was to review the changes between dd-trace-py versions 3.16.2 and 3.18.0. This can give us an idea of what code was modified, and which code could be the source of the problem.

Next, we're digging into the internal workings of dd-trace-py, particularly the parts of the code that handle span creation and the interaction with the ThreadPoolExecutor. This requires a good understanding of how tracing libraries work, including span context management, propagation, and the mechanisms used to ensure thread safety. This could mean using a debugger, adding logging statements, or even modifying the library code temporarily to understand what's happening.

We'll also have to examine how dd-trace-py manages the data structures used to store span information, and how it handles concurrent access to these data structures. A common cause of such errors is the improper synchronization of access to shared resources. In a multi-threaded environment, you need to use synchronization primitives like locks or mutexes to prevent concurrent modification of shared data. Without these, you are bound to run into errors.

Potential Solutions and Workarounds

Since we're still in the investigation phase, we don't have a definitive solution yet. However, based on our understanding of the problem and the nature of the error, we're considering a few potential solutions:

1. Synchronization Mechanisms: Implementing proper locking or other synchronization mechanisms within dd-trace-py to protect the dictionary being iterated over. This involves identifying the specific parts of the code that are causing the race condition and ensuring that only one thread can modify the dictionary at a time. This would probably be the best, because it would fix the problem at the root.
2. Code Review: Carefully reviewing the changes in the library between versions 3.16.2 and 3.18.0, focusing on the code related to span creation and thread management. This could help uncover any obvious issues, such as missing locks or incorrect thread handling. Make sure you get multiple developers to review it.
3. Rollback: As a temporary workaround, rolling back to version 3.16.2 of dd-trace-py. This is not a long-term solution, as it means missing out on potential bug fixes or improvements in later versions. However, it can restore functionality and stability while we investigate the root cause of the problem.
4. Workaround: Exploring alternative ways to create spans or reduce the level of concurrency. This might involve batching span creation, using a different threading model, or carefully limiting the number of concurrent operations. This would be a good way to mitigate the issue.

We will keep you updated on our findings and any progress we make in resolving this issue. Stay tuned for more updates!