Ensuring Database Consistency with Automated Validation: A Guide with New Relic

Welcome back to Part 2 of our guide on ensuring database consistency with automated validation. In Part 1, we explored the importance of database consistency and began setting up an automated validation process to ensure data accuracy between MySQL and Snowflake. We covered setting up Python, securely connecting to both databases, and preparing for the row count validation.

With these foundational connections in place, we’re now ready to complete our setup by implementing validation checks, logging results in New Relic, and configuring alerts and dashboards for real-time monitoring of data consistency.

Implementing Row Count Validation

The validation process involves retrieving row counts from both databases to ensure data consistency. Here’s a function that connects to Snowflake, retrieves the row count, and returns it:

def snowflake_validation(table_name):
    connection = snowflake.connector.connect(
        user=USER,
        account=ACCOUNT,
        database=DATABASE,
        schema=SCHEMA,
        role=ROLE,
        warehouse=WAREHOUSE,
        private_key=private_key_bytes
    )
    query = f"SELECT COUNT(*) AS row_count FROM {DATABASE}.{SCHEMA}.{table_name.upper()};"
    cursor = connection.cursor()
    cursor.execute(query)
    return cursor.fetchone()[0]  # Row count

You can create similar functions for both MySQL and Snowflake to perform the row count comparison automatically.

Logging Results to New Relic

The New Relic Python agent allows you to log custom events, like row count comparisons, for real-time monitoring. By recording these events, you can easily visualize database consistency checks, set alerts, and monitor discrepancies directly in your New Relic dashboard. Here’s an example:

newrelic.agent.record_custom_event(
    "RowCountComparison",
    {
        "table_name": table,
        "mysql_row_count": mysql_row_count,
        "snowflake_row_count": snowflake_row_count,
        "result": result_match
    },
    application=application
)

This setup enables you to view the data directly in New Relic’s APM dashboard.

Viewing Data in New Relic

Once logged in to New Relic:

1. Navigate to APM > Events > Custom Events.

2. Use a query like SELECT * FROM RowCountComparison SINCE 1 hour ago to see recent row count validations.

Setting Up Alerts and Dashboards

1. Alerts: In Alerts & AI, create a policy that triggers notifications if discrepancies are detected. This way, your team can respond quickly to any consistency issues.

2. Dashboards: Use New Relic’s NRQL queries to visualize row count comparisons over time, making it easy to track consistency across databases.

Conclusion

Automating database consistency validation with New Relic provides a powerful tool for maintaining data reliability. With secure connections, real-time alerts, and a proactive monitoring setup, you can ensure that your data remains accurate across platforms.

This concludes our two-part guide on database consistency validation. Stay tuned for more posts in the Data Pipeline Best Practices and Solutions series!