Benthos wants to be part of your Data Engineering toolkit - it’s there as a quick and easy way to set up data pipelines and start streaming data out of A and into B. In contrast to a lot of the tools we’ve talked about on Developer Voices, Benthos seems focussed on cutting development time down to a minimum, so you can quickly configure a new pipeline and test it out, without making a whole sprint of the task. As quick as a quick-and-dirty shell script, without the dirt. 😉
So this week we’re talking to the creator of Benthos, Ashley Jeffs, to hear why he created Benthos, what it can do for you, and what its strengths and weaknesses are. And Jeff’s refreshingly candid about when you should and shouldn’t use it. If you ever need to get data from an HTTP connection into S3, or S3 into Kafka, or Kafka into a flat file, Benthos might just save you a few hours of development.
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Benthos: https://www.benthos.dev/
A list of supported inputs, processors & outputs: https://www.benthos.dev/docs/about#components
All their cute blobfish logos: https://www.benthos.dev/blobfish/
IDML: https://idml.io/
Kris on Twitter: https://twitter.com/krisajenkins
Kris on LinkedIn: https://www.linkedin.com/in/krisjenkins/
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#software #podcast #dataengineering #datascience
