As an experiment I have put together a simple, actor-based customer appender for log4net which allows you to publish your log messages into a configured Kinesis stream. You can then have another cluster of machines to fetch the data from the stream and do whatever processing or aggregation you like to do.
The implementation is done in F# in 100 lines of code, and as you can see is very simple, easy to reason with, fully asynchronous and thread-safe.
Once you have pushed your log messages into the stream, you’ll need to use the AWSSDK to fetch the data and process them. For Java, there’s a client application which takes care of most of the heavy lifting – e.g. tracking your progress, handling failovers and load balancing. Unfortunately, at the time of writing, there’s no equivalent of such client application in the current version of the .Net AWSSDK.
So to help make it easier for us .Net folks to build real-time data processing applications on top of Amazon Kinesis, I had started a Rx-based .Net client library called ReactoKinesiX (I really wanted to get RX into the name!), more details to follow.
I think the introduction of Kinesis is very exciting and opens up many possibilities, and at the current pricing model it also represents a very cost effective alternative to some of the other competing and more polished services out there.
I’m an AWS Serverless Hero and the author of Production-Ready Serverless. I have run production workload at scale in AWS for nearly 10 years and I have been an architect or principal engineer with a variety of industries ranging from banking, e-commerce, sports streaming to mobile gaming. I currently work as an independent consultant focused on AWS and serverless.
Come learn about operational BEST PRACTICES for AWS Lambda: CI/CD, testing & debugging functions locally, logging, monitoring, distributed tracing, canary deployments, config management, authentication & authorization, VPC, security, error handling, and more.
Here is a complete list of all my posts on serverless and AWS Lambda. In the meantime, here are a few of my most popular blog posts.
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