Amazon CloudWatch provides near real-time visibility into infrastructure and application performance through detailed metrics and logs. For example, it gives you insights into the performance of Lambda functions, enabling you to identify and resolve issues quickly.

AWS Identity and Access Management (IAM) lets you grant granular and least-privilege permissions so that users only have access to the specific resources they need. API Gateway enhances security for backend services and data by providing authentication and access control through API keys, helping you restrict access to your APIs and limit API rates using throttling. It also provides access logs and implementation logs to give you visibility into API usage and help you identify security issues.

AWS IoT Core enables reliable bidirectional communication between IoT-connected airport assets and AWS services. It can handle a high volume of messages from many assets and reliably route those messages to AWS for downstream processing and connecting. It also helps you reliably collect and process telemetry IoT data from your airport assets. AWS IoT Core scales to support any number of devices without compromising on reliability, and the built-in retries facilitate reliable communication at scale. Additionally, AWS IoT Greengrass core devices can continue to operate locally if disconnected from the AWS Cloud.

DynamoDB provides fast, predictable performance by spreading data across multiple Availability Zones. It offers single-digit latency at scale, so you can build highly responsive applications with predictable performance at any scale, and provision the throughput capacity you need without having to overprovision for peak usage.

Amazon S3 provides cost-effective storage for any amount of data at scale. Its object life-cycle management and storage tiering reduce costs by automatically transitioning less frequently accessed data to more affordable tiers, such as Amazon S3 Standard-Infrequent Access (S3 Standard-IA) or Amazon S3 Glacier storage classes. This minimizes the overall storage expenses of your architecture at scale.

AWS IoT Greengrass enables local compute, messaging, device shadow, and ML inference capabilities on edge devices. Performing compute and inference locally is more energy efficient than sending large amounts of data back and forth between local devices and the AWS Cloud. By reducing the need to transmit data to AWS for analysis, you can save network bandwidth and energy consumption and reduce the overall carbon footprint of your workloads.