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Vedha - Dev
Vedha - Dev

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The Circular Dependency That Silently Felled Our App (And How I Fixed It)

#architecture #devjournal #javascript #node

It started with a ghost in the machine. A cryptic AssertionError that would randomly crash our Node.js application in its most critical workflow: processing Shopify orders. The error message itself was a red herring, pointing a finger at our Application Insights monitoring service.

AssertionError [ERR_ASSERTION]: context not currently entered; can't exit.
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This was maddening. The error suggested a problem with our logging and monitoring, not our business logic. We spent hours digging into the Application Insights setup, checking configurations, and ensuring it was initialized correctly. But everything looked fine. The bug remained, an intermittent ghost that haunted our production logs. What made it particularly insidious was that the application didn't crash on startup, a common tell-tale sign of circular dependencies. This initial stability was due to lazy loading mechanisms (getters and setters) that cleverly delayed the full resolution of dependencies. The error only reared its head under specific conditions: when API calls exceeded a certain threshold, typically above 20 concurrent requests. This load-dependent nature made the issue incredibly hard to detect and reproduce in development.

The Hunt for the Real Culprit

After sinking too much time into the Application Insights rabbit hole, we took a step back. An error like this, related to "context," often points to an issue with how asynchronous operations are being tracked. When async/await chains get tangled, especially under heavy load, the context can be lost, and a library like Application Insights, which relies on that context to trace a request from start to finish, can be the first to complain. The error wasn't the problem; it was a symptom exacerbated by high concurrency.

The true problem had to be hiding within the order processing logic itself—a complex series of asynchronous steps involving database calls, API requests, and real-time updates.

Our investigation led us to a key orchestrator: ShopifyOrdersService. This service was responsible for the end-to-end processing of an incoming order webhook. A simplified version of its logic looked something like this:

  1. Receive order data.
  2. Find or create a customer record.
  3. Award points or achievements for the purchase.
  4. Update the user's status, VIP tier, etc.
  5. Queue notifications.

The error seemed to trigger around step 2, specifically when calling a method in our UserService.

The "Aha!" Moment: A Vicious Cycle

As we mapped out the call stack, we uncovered the architectural flaw. It wasn't a single line of code, but a toxic relationship between our services.

Here’s what was happening:

  1. ShopifyOrdersService received an order and called UserService to find or create a user.
  2. UserService, upon creating a new user, had a responsibility to award them their first "Welcome" achievement. To do this, it called into the UserCompletedGameService.
  3. UserCompletedGameService would then calculate points, check for VIP tier bonuses, and update the user's state. To do that, it needed access to user information and VIP tier logic... so it called back into UserService.

The dependency chain looked like this:

ShopifyOrdersService → UserService → UserCompletedGameService → UserService

We had a classic circular dependency.

In Node.js, when Module A imports Module B, and Module B imports Module A, the module system has to break the loop. It does this by returning an incomplete, partially initialized version of one of the modules during the import cycle. This can lead to undefined functions or, in our case, something much more subtle: a broken asynchronous context that caused our monitoring library to crash.

The dependency wasn't obvious at first glance. It was a chain of three services, not a direct two-way loop, which made it harder to spot during code reviews.

The Fix: Breaking the Cycle

The solution was to untangle this chain by enforcing a clear architectural pattern: orchestration over nested delegation. A service's responsibilities had become blurred. UserService had no business knowing about game actions.

The fix was conceptually simple but powerful:

  1. Remove the dependency from UserService to UserCompletedGameService. UserService should only be responsible for user-related data (CRUD operations, profile management, etc.). It should not trigger game logic.
  2. Elevate the responsibility to the orchestrator. The ShopifyOrdersService, which was already managing the overall workflow, was the correct place to manage the sequence of events.

The new, corrected flow became:

  1. ShopifyOrdersService calls UserService to get or create the user.
  2. ShopifyOrdersService takes the user data from that call.
  3. ShopifyOrdersService then calls UserCompletedGameService, passing it the necessary user data to process the achievement or points.

Old, Broken Flow:
ShopifyOrders → Users → Game → Users

New, Corrected Flow:
ShopifyOrders → Users
ShopifyOrders → Game

The services no longer depended on each other in a circle. They became peer services, both called by a single, higher-level orchestrator. The change immediately stabilized the application. The ghost in the machine was gone.

Lessons Learned

This experience was a powerful reminder of a few key software engineering principles:

  1. Single Responsibility Principle: Keep your services focused. UserService was doing too much, which led to the tangled dependency.
  2. Beware of Deeply Nested Logic: A long chain of awaits that cross multiple service boundaries can be a code smell. It often indicates that responsibilities are not clearly separated.
  3. Circular Dependencies are Silent Killers (Especially with Lazy Loading): They don't always cause an immediate startup error. In our case, lazy loading mechanisms (getters/setters) initially hid the circular dependency, preventing a crash on application start. This meant the issue only manifested as bizarre, intermittent runtime bugs under load, making diagnosis significantly harder.
  4. Concurrency Exposes Hidden Flaws: The fact that the error only appeared with more than 20 concurrent API calls highlights how performance and load testing are crucial for uncovering subtle context management issues and race conditions that might not be apparent during typical development or lower load.
  5. Symptoms vs. Root Cause: Always dig deeper than the surface error. The Application Insights error was merely a messenger; the real problem lay in the underlying architectural flaw.

In the end, a cryptic error message led us on a debugging journey that uncovered a fundamental flaw in our architecture. Fixing it not only resolved the bug but also made our entire system more robust, predictable, and easier to maintain.

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