Technical Talks

You'll learn how to leverage AWS Lambda with Amazon Kinesis to architect scalable, high throughput pipelines that handle use cases like in-line process or data manipulation.

Use AWS Step Functions to easily coordinate multiple AWS Lambda functions and microservices as a series of steps using visual workflows.

You'll learn how to run risk and pricing scenario calculations against large datasets in shorter timeframes and at lower cost with serverless architecture.

Learn how to run code closer to your end users with edge computing for 1.) lower latency to respond to viewer requests, 2.) reduced load on origin servers, 3.) automatic scaling. 

You'll learn how to use AWS Lambda with Amazon Kinesis to analyze streaming data in real-time and store results in a managed NoSQL database such as Amazon DynamoDB.

You'll learn common design patterns for big data processing, how they map to AWS Lambda, and how to leverage Machine Learning to derive better insights from the data.

We’ll demonstrate step-by-step how you can use AWS Lambda to easily build and run your first Slack bot – all without the need to provision and manage servers.

Learn the foundations for how you can build highly scalable APIs for backends running on server-based or container-based applications and serverless applications.

You'll learn how to use AWS Lambda permissions. set up authentication and authorization for Amazon API Gateway with Amazon Cognito.

We cover how to use Amazon Cognito identity pools and user pools with API Gateway, Lambda, and IAM, and how to integrate with social identify providers.

We'll dive deep into how to leverage new features of DynamoDB in serverless applications, followed by a real-world use case from CapitalOne.

We will show you how to achieve flexibility and agility by combining microservices and serverless technologies.

We'll intoduce four re-usable serverless patterns for web apps, stream processing, batch processing, and automation.

We'll discuss how to pich the right database technology and connect your app to databases like Amazon RDS, Amazon Aurora, and Amazon DynamoDB.

We'll deep dive into advanced capabilities of API Gateway that enable you to build large scale data ingesting applications and dynamic websites.

This is an advanced session in which we discuss architectural best practices, optimizations, and handy little cheat codes to build high-scale, serverless applications.

You'll learn how to route end users to the appropriate region to achieve optimal latency and availability. 

Learn common deployment patterns such as CI/CD, traffic shifting , automatically roll out and test new versions, and how to perform canary releases with API Gateway.

Learn advanced techniques for AWS SAM at scale, including dynamic template capabilities of SAM, deployment preferences and policy templates, and how to debug locally.

Using Chalice, we will show you how to author a Restful service, and deploy the application to multiple stages using AWS CodePipline and AWS CodeBuild and SAM.

Learn to use AWS X-Ray to perform distributed tracing on AWS Lambda and serverless applications so you can debug and troubleshoot performance issues.

Learn the basics of the AWS Serverless Application Model (AWS SAM) which is an open source specification which defines simplified syntax for expressing serverless resources.

 We'll share best practices for locally testing and then deploying your Lambda application using the AWS Serverless Application Model (AWS SAM) and AWS SAM Local.

We'll discuss how you can use CI/CD tooling from AWS CodePipeline and AWS CodeBuild to build an automated development workflow for your serverless app.