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Shouldn't Data Connections Be Easier? (with Ashley Jeffs)

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Manage episode 397408445 series 3476072
Content provided by Kris Jenkins. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Kris Jenkins or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

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.

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/

#software #podcast #dataengineering #datascience

  continue reading

64 episodes

Artwork
iconShare
 
Manage episode 397408445 series 3476072
Content provided by Kris Jenkins. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Kris Jenkins or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

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.

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/

#software #podcast #dataengineering #datascience

  continue reading

64 episodes

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