The HDF Group appoints Dana Robinson as Director of Engineering

Dana Robinson has been appointed as the new Director of Engineering at The HDF Group. Dana started at The HDF Group in 2009 as a software engineer until stepping into the role of interim Director of Engineering in April 2022. As the Director of Engineering, Dana will lead the team of software engineers and shape the […]

HSDS Streaming

Highly Scalable Data Service principal architect John Readey covers an update to the Highly Scalable Data Service. The max request size limit per HTTP request no longer applies with the latest HSDS update. In the new version large requests are streamed back to the client as the bytes are fetched from storage. Regardless of the size of the read request, the amount of memory used by the service is limited and clients will start to see bytes coming back while the server is still processing the tail chunks in the selection. The same applies for write operations—the service will fetch some bytes from the connection, update the storage, and fetch more bytes until the entire request is complete. Learn more about this update, plus check out John’s benchmark results using a couple of different MacBook Pros and his new DevOne laptop.

HSDS Docker Images

The Highly Scalable Data Service (HSDS) runs as a set of containers in Docker (or pods in Kubernetes) and like all things Docker, each container instance is created based on a container image file. Unlike say, a library binary, the container image includes all the dependent libraries needed for the container to run. In this blog post, HSDS senior architect John Readey explains how to get HSDS running in a Docker container or Kubernetes pod, and gives some tips and tricks to ensure everything runs smoothly for you. 

Deep Dive: HSDS Container Types

HSDS (Highly Scalable Data Service) is described as a “containerized” service, but how are these containers organized to create the service?

2022 HDF5 Release Schedule

Interim Engineering Director Dana Robinson talks about The HDF Group’s upcoming release schedule. As some of you may already have noticed, we now post the current HDF5 release schedule in the README.md document in the project’s root on GitHub. I’ll update this as circumstances change so it always reflects our current thinking.

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