What data scientists and data engineers can do with current generation serverless technologies
The O’Reilly Data Show Podcast: Avner Braverman on what’s missing from serverless today and what users should expect in the near future.
Sculpture at the Cass Sculpture Foundation (source: Ben Lorica, used with permission)
In this episode of the Data Show, I spoke with Avner Braverman, co-founder and CEO of Binaris, a startup that aims to bring serverless to web-scale and enterprise applications. This conversation took place shortly after the release of a seminal paper from UC Berkeley (“Cloud Programming Simplified: A Berkeley View on Serverless Computing”), and this paper seeded a lot of our conversation during this episode.
Serverless is clearly on the radar of data engineers and architects. In a recent survey, we found 85% of respondents already had parts of their data infrastructure in one of the public clouds, and 38% were already using at least one of the serverless offerings we listed. As more serverless offerings get rolled out—e.g., things like PyWren that target scientists—I expect these numbers to rise.
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We had a great conversation spanning many topics, including:
- A short history of cloud computing.
- The fundamental differences between serverless and conventional cloud computing.
- The reasons serverless—specifically AWS Lambda—took off so quickly.
- What can data scientists and data engineers do with the current generation serverless offerings.
- What is missing from serverless today and what should users expect in the near future.
Related resources:
- “The evolution and expanding utility of Ray”
- Results of a new survey: “Evolving Data Infrastructure: Tools and Best Practices for Advanced Analytics and AI”
- Eric Jonas on “Building accessible tools for large-scale computation and machine learning”
- “7 data trends on our radar”
- “Handling real-time data operations in the enterprise”
- “Progress for big data in Kubernetes”