Unpredictable AWS Lambda performance when using TypeScript

After deploying my code to AWS Lambda, I noticed a strange issue. When I access the endpoint using Postman, it runs smoothly for the first time. However, upon subsequent attempts, I encounter the following error:

{
    "error": "Validation error"
}

If I redeploy the code, it works once again before breaking. Interestingly, when running locally, this error never occurs.

The problem seems to be related to a specific line of code:

this._repo.save(user)

Although the model gets saved in the database without any issues, the error persists. Has anyone faced a similar issue before? What could possibly be causing this erratic behavior?

Here is the relevant code snippet:

  public signUp(event: APIGatewayEvent): Observable<APIGatewayProxyResult> {
    // Code implementation here...
  }


 private register(event: APIGatewayEvent): Observable<UserInfosModel> {
   // Code implementation here...
  }

Any insights or assistance on this matter would be greatly appreciated. Thank you!

Answer №1

If you encounter this issue, it is likely that your function is not idempotent.

Lambda does not ensure a clean start for functions. It allows for the reuse of the previous execution container along with any old temporary disk space.

Make sure to review your function for any leftover variables in the context space, unclosed streams, unused DBcontexts, or similar issues.

Here is more information on running Lambda code efficiently.

Answer №2

After a bit of searching, I finally discovered the solution to my problem. Utilizing the @Default decorator in sequelize enabled me to automatically generate a unique uuid for each new model. However, upon further investigation, I realized that the generated uuid remained constant within the context. This meant that subsequent inserts would all use the same uuid until a new context was initiated. To address this issue, instead of relying solely on the sequelize-typescript @Default decorator, I opted to implement a beforeCreate hook to manually generate an id for each new model instance. This approach effectively resolved the issue at hand.

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