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emmanuela Opurum
emmanuela Opurum

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๐—”๐—บ๐—ฎ๐˜‡๐—ผ๐—ป ๐—–๐—ผ๐—ป๐—ป๐—ฒ๐—ฐ๐˜ ๐—–๐—ผ๐—ป๐˜๐—ฎ๐—ฐ๐˜ ๐—–๐—ฒ๐—ป๐˜๐—ฒ๐—ฟ ๐—ผ๐—ป ๐—ฎ ๐Ÿฏโ€‘๐—ง๐—ถ๐—ฒ๐—ฟ ๐—”๐—ช๐—ฆ ๐—”๐—ฟ๐—ฐ๐—ต๐—ถ๐˜๐—ฒ๐—ฐ๐˜๐˜‚๐—ฟ๐—ฒ

I designed an architecture that blends a modern 3โ€‘tier web application with a fully integrated Amazon Connect contact center. The goal was to create a seamless support experience where authenticated users can reach an agent instantly, and the agent receives full customer context the moment the call arrives.

The user journey begins on a web application delivered through Amazon CloudFront and S3. Authentication is handled by Amazon Cognito, which issues a secure JWT token that unlocks the full application experience, including access to support.
All authenticated requests flow through Amazon API Gateway, which validates the token before routing traffic to the application layer running on AWS Fargate behind an Application Load Balancer. The application interacts with DynamoDB for user profiles and S3 for transactional or historical data, keeping the environment scalable, resilient, and fully managed.

When a user selects โ€œContact Support,โ€ a Lambda function is triggered behind the scenes. This function calls Amazon Connect APIs to initiate a contact, route the user to an available agent, and pass along the customer context automatically. Thereโ€™s no need for IVR menus, the system already knows who the user is and what account theyโ€™re coming from.
Inside Amazon Connect, additional Lambda functions retrieve customer information from CRM. This data is surfaced directly in the agent workspace, giving the agent everything they need to assist the customer quickly and effectively. Once the interaction ends, the session is logged for analytics and compliance.

All call recordings and transcripts are stored in Amazon S3, with a lifecycle policy that automatically transitions data after 60 days into S3 Intelligentโ€‘Tiering Flexible Retrieval to optimize longโ€‘term storage costs. Analytics teams can query this data using Amazon Athena and build dashboards in Amazon QuickSight to uncover trends, customer behaviour, and agent performance insights.

This architecture brings together identity, application logic, customer context, and realโ€‘time support into one cohesive flow. Itโ€™s a strong example of how AWS services can be combined to deliver a modern, intelligent, and efficient customer support experience.

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