Connect AWS Lambda and Google BigQuery to unlock the power of automation

To trigger an AWS Lambda function when new data is inserted into Google BigQuery, we can use a combination of Google Cloud Functions and Pub/Sub. First, configure a BigQuery dataset to export logs to Pub/Sub. Then, we create a Cloud Function that listens to this Pub/Sub topic for new data events and subsequently triggers the AWS Lambda via an HTTP request using API Gateway.

AWS Lambda does not directly write to Google BigQuery. Instead, we can interact with BigQuery using the Cloud Client Libraries for Python or Node.js in our Lambda function. This requires setting up service account credentials with appropriate permissions that the AWS Lambda can utilize via environment variables.

To allow AWS Lambda access to Google BigQuery, we need a service account key file with roles such as 'BigQuery Data Viewer' and 'BigQuery Job User'. These permissions enable the execution of queries and viewing of datasets. The key file must be securely stored in AWS Secrets Manager or encrypted with KMS, allowing the lambda function to access it at runtime.

Secure communication between AWS Lambda and Google BigQuery is ensured by using HTTPS endpoints through API Gateway when invoking from outside Google's network. Within our application code running in Lambda, employing OAuth 2.0 authentication with Google's API client libraries helps manage secure tokens without constant user intervention.

Direct triggering of an AWS Lambda based on changes in specific tables within BigQuery isn't natively supported. However, setting up alerts or changes logs that produce outputs via Pub/Sub allows our setup with Cloud Functions or external scripts (in VM environments) that communicate and invoke actions on specific changes facilitating triggers indirectly.

Yes, streaming data from various AWS services like S3 or DynamoDB into Google BigQuery is possible using lambda functions as intermediaries. Our approach involves extracting events or records from these services within a lambda execution context and then sending them over HTTP POST requests directly or via secured channels facilitated by API Gateway toward Google's Data Ingestion APIs.

Monitoring errors in such integrations can involve checking logs generated by both systems. Using Amazon CloudWatch allows us to track executions within the lambda environment, while Stackdriver Logging (now part of Operations Suite) gives insights into requests reaching and being processed by Google's infrastructure for anomaly detection.