DAX - speeding/cheapening up Dynamo Db

Amazon DynamoDb comes with its own cache layer DAX or DynamoDB Accelerator. In this post I am going to play around with this feature.

Deploying API Gateway

In the last 2 posts, I have been working on setting up API access to my Dynamo Table through API Gateway. The next step would be to deploy the APIs:

Dynamo Db APIs through API Gateway

In the last post, we setup a GET method for my table through API Gateway. I wanted to go ahead and setup the other methods - DELETE, PUT, POST.

REST + Dynamo = API Gateway

My use case is very straight forward - I have a table and I want to expose CRUD operations on the table - GET, ADD, DELETE, UPDATE.

Playing with ElastiCache - 2

In the previous post we setup a basic Lambda function that wrote to Redis. I updated the function to log some Cloud Watch metrics.

Playing with ElastiCache

I have never used Elastic Cache yet. My caching use cases were solved either via an in memory cache or a hosted cache. I finally got the chance to venture beyond - to cloud caches.

Playing with the Paths of Step functions

AWS Step Functions work by moving from one state to another state. States need a way to communicate with each other - DATA needs to be passed between them

Step Functions - AWS Service Integrations 2

In the previous post we successfully executed dynamo db, sqs and sns interactions directly from step functions. I wanted to try some tweaks to my state machine.

Step Functions - AWS Service Integrations

With all this serverless chatter around Lambda, the next thing was to try and orchestrate these Lambdas with Step Functions. Essentially a Step Function allows you to define the steps to be executed across systems in a visual UI. The interactions, retries, failure conditions and other orchestration behavior (or the flow management) can be done by Step Functions.

Using Lambda To Trigger a State Function

So I took the Hello World Step function example and wanted a Lambda to trigger the execution