Intermittent Error 500 on First Access – Works After Multiple Refreshes

André Costa, Just checking in to see if you had got a chance to see the previous response by Amira Bedhiafi. If the answer helped (pointed, you in the right direction) > please click Accept Answer - it will benefit the community to find the answers quickly.

Just to clarify, are you leveraging Azure App Service WebApp?

Adding to Amira's response, based on my understanding of your issue description, that the issue consistently occurs on the initial access or after some idle time, but after 2-3 refreshes, the page loads without any issues, and the app works fine moving forward.

To isolate the issue if it's happening at WebApp end or Database end and fetch more details about the issue, you may try these:

For App Service Webapp, enable Always On: From Azure Portal – Your WebApp > Configuration blade (> General settings).

When Always On isn't turned on (default), the app is unloaded after 20 minutes without any incoming requests. The unloaded app can cause high latency for new requests because of its warm-up time. When Always On is turned on, the front-end load balancer sends a GET request to the application root every five minutes. The continuous ping prevents the app from being unloaded.

You may leverage App Service diagnostics from Azure Portal> Navigate to your App Service app in the Azure Portal. (screenshot below). https://learn.microsoft.com/azure/app-service/overview-diagnostics

If you haven't done this already, As suggested, you may check the connection pool settings in your Flask app, and double check if it's configured to maintain a persistent connection to the database.
Also, you to isolate further, try increasing the timeout value for the connection pool.

Kindly let us know how it goes, I'll follow-up with you further.

This kind of intermittent 500 Internal Server Error after a period of inactivity is commonly related to how connections are managed between your Flask application and the Azure SQL Database.

1. Connection Pool Timeout:

• Issue: SQLAlchemy creates a connection pool to maintain multiple connections to the database. After a period of inactivity, the connections in the pool may time out or get closed due to inactivity, causing the first access to fail.
• Solution:
  • You can configure the connection pool to be more persistent by adjusting parameters like pool_pre_ping, pool_recycle, and pool_timeout. These help ensure the connection is alive when requested and not stale.
  • Example in SQLAlchemy:

    
           engine = create_engine(
    
               'mssql+pyodbc://<connection_string>',
    
               pool_pre_ping=True,
    
               pool_recycle=3600,  # recycle connections every hour
    
               pool_timeout=30,     # wait 30 seconds for a connection
    
           )
    
    

2. Idle Connection Termination:

• Issue: Azure SQL Database might close idle connections after some time, leading to the 500 error on the first request after inactivity. This may also result from how your ODBC driver interacts with Azure SQL.
• Solution:
  • Implement a retry logic that catches this kind of error and retries the database connection. SQLAlchemy supports retry logic in queries, which can help in scenarios where the initial connection fails but subsequent attempts succeed.
  • Add logic to reconnect automatically when the connection has been terminated.

3. Azure SQL Scaling/Cold Start:

• Issue: Azure SQL Database can take some time to "wake up" after periods of inactivity, especially if you are using a serverless or scaled-down SKU. The first query after a period of inactivity might incur some latency as the database becomes available.
• Solution:
  • Use Azure SQL Serverless with appropriate auto-pause and scaling settings, or consider moving to a higher SKU if performance is a concern.
  • Alternatively, set up a keep-alive query that runs periodically (e.g., every few minutes) to keep the database connection warm.

4. ODBC Driver/Network Latency:

• Issue: While the ODBC Driver version is up to date, there could still be network latency issues that cause the first connection attempt to time out.
• Solution:
  • Ensure that TCP KeepAlive is enabled, which helps maintain a more consistent connection.
  • Use the retry_attempts and retry_backoff settings in your connection string to mitigate initial timeouts.

5. Application Timeout:

• Issue: The timeout may be on the Flask application side, where the app doesn’t wait long enough for the database connection to succeed.
• Solution: Check Flask timeout settings (like request_timeout) and SQLAlchemy’s timeout configuration to ensure sufficient time is provided for the database to respond, especially after idle periods.

6. Database Connection Handling in Flask:

• Issue: Flask might not be managing the lifecycle of the database connections properly, leading to dropped connections.
• Solution: Use SQLAlchemy's scoped_session to ensure connections are properly managed across multiple requests.

    
    from sqlalchemy.orm import scoped_session, sessionmaker
    
    session_factory = sessionmaker(bind=engine)
    
    Session = scoped_session(session_factory)