Beavers are extremely cool. Being Canadian, I never gave them very much thought until the youtube algorithm one day had me watching a documentary about them, that lead to me searching out another documentary to watch about them because they're so fascinating.
1. If you are building APIs and using Lambda functions as targets from an API Gateway API, look into libraries like serverless-wsgi (Python) or wai-handler-hal (Haskell) that translate between API Gateway request/response payloads and some kind of ecosystem-native representation. Then as long as you're writing code where all state gets persisted outside of the request/response cycle, you can develop locally as if you were writing for a more normal deploy environment.
2. Look into the lambda runtime interface emulator ( https://github.com/aws/aws-lambda-runtime-interface-emulator... ). This lets you send invoke requests to a fake listener and locally test the lambda more easily. While the emulator is provided in the AWS container base images, you don't need to run it inside a container if you're deploying with zip files. (AWS-provided container images automatically enable the emulator if not running in a lambda runtime environment, and using docker for port remapping, which is nice but not at all required.)
3. Get really good at capturing all requests to external services, and mocking them out for local testing. Whether this is done with free monads, effect systems, or by routing everything through gateway classes will depend on your language and library choices.
Because I don't think a lot of people know about it, I'll mention pelias here. If you have 16 GB RAM and 600 GB of disk, you can have a free, open source, pre-populated geo database that covers the entire planet.
Pelias does geocoding (turns addresses, POIs, and administrative regions into coordinates), reverse geocoding (given coordinates, finds nearby POIs, addresses, neighborhood, city, county, state, country), full-text search, and autocompletion. You can also import CSV to use your own custom data.
I run it on an extra PC, where it powers about 20 twitter bots that turn lat/lon coordinates of aircraft into descriptions like "flying over Silver Lake, Los Angeles, 0.5 miles from Circus Liquor."
I led the storage engine prototyping for Kinesis in 2012 (the best time in my career so far).
Kinesis uses Chain Replication, a dead simple fault tolerante storage algorithm: machines formed a chain, data flow from head to tail in one direction, writes always start at head, and read at tail, new nodes always join at tail, but nodes can be kicked out at any position.
The membership management of chain node is done through a paxos-based consensus service like chubby or zookeeper. Allan [2] (the best engineer I personally worked with so far, way better than anyone I encountered) wrote that system. The Java code quality shows itself after the first glance. Not mentioning the humbleness and openness in sharing his knowledge during early design meetings.
I am not sure what protocol is actually used now. But I would be surprised it's different, given the protocol's simplicity and performance.
https://www.youtube.com/watch?v=PLyBZ1mdg2c https://www.youtube.com/watch?v=N15sLwRCmnc