Lambda facilitates seamless deployment and debugging through infrastructure-as-code (IaC) tools like an AWS Cloud Development Kit (AWS CDK). Lambda also offloads the burden of infrastructure management, handling all maintenance, security patches, and monitoring for functions. For example, it works with API Gateway to supply Amazon CloudWatch metrics on workflow elements like video analytics inferencing and message postprocessing. Using these logs and metrics from Lambda functions, your developers can more easily troubleshoot errors and performance bottlenecks.

API Gateway acts as a proxy between the client and backend services, providing a protection layer when you invoke category services through an outbound API. This enables you to control access and implement security measures. Additionally, AWS IoT Core provides secure communication, authentication, authorization, and data protection mechanisms for edge devices. This helps it maintain the confidentiality, integrity, and availability of data exchanged between Internet of Things (IoT) devices and AWS, enabling secure and reliable edge computing operations. Finally, you can seamlessly integrate API Gateway and AWS IoT Core with AWS Identity and Access Management (IAM) so that you can control access to resources and data according to the principle of least privilege.

This Guidance uses AWS Regional services like Lambda, Amazon Bedrock, Amazon S3, and DynamoDB, which use Availability Zones and static stability to achieve high availability. As managed services, Lambda and Amazon Bedrock provide retry and automatic scaling features. Additionally, Amazon S3 and DynamoDB are designed for high reliability, minimizing the risk of losing videos and prompts in the case of a failure.

Kinesis Video Streams enables IP cameras to directly connect to the cloud, streamlining edge-to-cloud video processing in near real time. Additionally, Amazon Bedrock enables your developers to leverage LLMs for video analysis, using APIs to invoke and run inferences.

Lambda bills per millisecond of resource use, so you can run video ingestion, analytics, and message postprocessing without paying for idle compute. Additionally, Amazon S3 and DynamoDB offer a low total cost of ownership for storing and retrieving prompts, video data, and images. Finally, Amazon Bedrock enables you to use LLMs without the need to host or manage your own LLM servers. It also provides a cost-effective API-based approach for invoking inferences, charging based on the number of input and output tokens used.

This Guidance invokes services like Lambda, API Gateway, and Amazon Bedrock only when there is a user query, minimizing resource overprovisioning. As serverless services, Lambda and API Gateway consume only the resources and energy required to support the workload. Additionally, as a managed service, Amazon Bedrock removes the need for you to host dedicated servers for LLMs. As a result, you can avoid the significant energy consumption associated with running such resource-intensive models.