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The Amazon Q Business pre-built connectors like Amazon Simple Storage Service (Amazon S3), document retrievers, and upload capabilities streamlined data ingestion and processing, enabling the team to provide swift, accurate responses to both basic and advanced customer queries.
Workshops, conferences, and training sessions serve as platforms for collaboration and knowledge sharing, where the attendees can understand the information being conveyed in real-time and in their preferred language. A serverless, event-driven workflow using Amazon EventBridge and AWS Lambda automates the post-event processing.
The workflow consists of the following steps: A user uploads multiple images into an Amazon Simple Storage Service (Amazon S3) bucket via a Streamlit web application. The DynamoDB update triggers an AWS Lambda function, which starts a Step Functions workflow. The Step Functions workflow runs the following steps for each image: 5.1
The architecture carries out the following steps: Customer reviews can be imported into an Amazon Simple Storage Service (Amazon S3) bucket as JSON objects. This bucket will have event notifications enabled to invoke an AWS Lambda function to process the objects created or updated.
Action groups are a set of APIs and corresponding business logic, whose OpenAPI schema is defined as JSON files stored in Amazon Simple Storage Service (Amazon S3). Each action group can specify one or more API paths, whose business logic is run through the AWS Lambda function associated with the action group.
Event-driven compute with AWS Lambda is a good fit for compute-intensive, on-demand tasks such as document embedding and flexible large language model (LLM) orchestration, and Amazon API Gateway provides an API interface that allows for pluggable frontends and event-driven invocation of the LLMs.
Week One: Local Development and Debugging Workshop. AM, Chase, and Eric kicked off the first week of SSS by sharing the basics of getting started with a tutorial on locally debugging AWS Lambda functions and other serverless resources with Stackery. AWS Lambda: Amazon’s version of serverless functions.
For storage-intensive workloads, AWS Customers will have an opportunity to use smaller instance sizes and still meet EBS-optimized instance performance requirements, thereby saving costs. Athena executes federated queries using Athena Data Source Connectors that run on AWS Lambda. an AWS DeepRacer event.
gcp:project : cicd-workshops. apply ( lambda args : generate_k8_config ( * args )). The docker push command uploads our the newly built Docker image to Docker Hub for storage and retrieval in the future. py - The Pulumi program that defines our stack resources. This is where the IaC magic happens. gcp:region : us-east1.
All of these large media assets are backed by Netlify’s Edge – our robust and redundant cloud storage. Launched Netlify Functions. Read more about this milestone.
After you and your teams have a basic understanding of security on AWS, we strongly recommend reviewing How to approach threat modeling and then leading a threat modeling exercise with your teams starting with the Threat Modeling For Builders Workshop training program.
The Step Functions state machine invokes AWS Lambda functions to get a findings summary and remediation steps through Amazon Bedrock. The workflow invokes a Lambda function and passes the GuardDuty findings details. The Lambda function calls Anthropic’s Claude 3 Sonnet model through Amazon Bedrock APIs with the input request.
Application controller layer (LLM orchestrator Lambda function) The application controller layer is usually vulnerable to risks such as LLM01:2025 Prompt Injection, LLM05:2025 Improper Output Handling, and LLM 02:2025 Sensitive Information Disclosure.
The loan handler AWS Lambda function uses the information in the KYC documents to check the credit score and internal risk score. The notification Lambda function emails information about the loan application to the customer. The Lambda function can be integrated with external credit APIs. Delete the S3 bucket.
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