In this chapter, we discussed the Lambda pattern at a conceptual level as well as in detail. I walked through an example implementation with serverless technologies to calculate average cryptocurrency prices for different time slices. Our example application was fed by a simple script that receives data from the GDAX WebSocket API. This data producer script published data to a single AWS Kinesis stream, which, in turn, triggered a series of events, ultimately resulting in real-time updates to DynamoDB and triggering batch jobs to calculate historical views of the minute, hourly, and daily average prices for multiple cryptocurrencies.
I discussed when the Lambda pattern may be appropriate and the types of data for which it's well suited. We talked through various systems and services that one may leverage when building a lambda architecture using serverless technologies. I introduced AWS Kinesis and AWS Kinesis Firehose, which are streaming systems you may leverage for real-time applications...