Customer challenges
Our client needed a robust, scalable, and secure mechanism to monitor all backend processes and API activity, with the goal of capturing detailed logs of every API interaction and forwarding them to an external analytics API for further processing. The challenge was not only in capturing this data but also ensuring real-time visibility, secure delivery, and minimal operational overhead. A key hurdle involved handling the high volume and velocity of API traffic—real-time logging had to be achieved without impacting system performance.
Additionally, the external API required token-based authentication, which introduced an operational bottleneck, as each transmission would otherwise require a new token request, increasing latency and the risk of failure due to token expiry. The client also required a system that supported agile development workflows, CI/CD-based deployment, and secure access controls to ensure efficient collaboration between development and operations teams. The entire solution had to be reliable, extensible, and scalable for future growth.
Solutions
We architected a fully-managed, scalable log pipeline with AWS services and token management:
To meet these challenges, we architected and implemented a cloud-native, serverless pipeline using fully managed AWS services to ensure scale, performance, and security. The core focus was to build a system that would monitor all backend activity, process the logs efficiently, and deliver them securely to an external client-defined API.
The solution begins at the Amazon API Gateway, where all API calls are intercepted, and detailed logging is enabled. Both request and response logs are pushed to Amazon CloudWatch, where they are organized into log groups. A CloudWatch Subscription Filter continuously listens to these log groups and streams the log data in real time to Amazon Kinesis Data Firehose—a service designed for high-volume streaming and buffering of data.
The log data then triggers a custom-built AWS Lambda function, which aggregates the logs every minute or upon reaching a 1 MB threshold. This function parses and formats the raw logs into structured JSON, ensuring consistent, readable, and analyzable outputs. Before forwarding the logs to the external API, the function retrieves an authentication token from AWS Systems Manager Parameter Store, where the token is cached to avoid unnecessary authentication API calls. If the token has expired, the Lambda function refreshes it seamlessly and updates the Parameter Store with the new token and timestamp.
This authentication management ensures the system is both secure and efficient, eliminating delays caused by redundant token requests. Logs are then transmitted to the external endpoint with the latest valid token in the request header.
To facilitate collaborative development, we provisioned AWS Cloud9 as a centralized cloud-based development environment, while AWS CodeCommit serves as the version-controlled code repository. The complete infrastructure stack—including IAM roles, Lambda functions, logging configurations, and streaming logic—is codified and deployed using AWS CloudFormation, allowing for consistent, automated, and replicable deployments across environments.
This architecture not only met the client’s real-time monitoring and delivery needs but also laid a solid foundation for scaling observability, automating incident response, and integrating with more advanced analytics tools in the future.
AWS services used
Results
The result was a fast, secure, and reusable monitoring system with minimal ops overhead:
Centralized and scalable logging mechanism for APIs.
Near real-time visibility into API traffic and behavior.
Automated token management using Parameter Store
Reduced troubleshooting time with structured and aggregated logs
Fully managed and reusable infrastructure using CloudFormation.
Secure, event-driven architecture with minimal manual intervention.
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