Ceph: A Reliable And Scalable Distributed Filesystem with Sage Weil - Episode 40

00:00:00
/
00:48:30

July 15th, 2018

48 mins 30 secs

Your Host

About this Episode

Summary

When working with large volumes of data that you need to access in parallel across multiple instances you need a distributed filesystem that will scale with your workload. Even better is when that same system provides multiple paradigms for interacting with the underlying storage. Ceph is a highly available, highly scalable, and performant system that has support for object storage, block storage, and native filesystem access. In this episode Sage Weil, the creator and lead maintainer of the project, discusses how it got started, how it works, and how you can start using it on your infrastructure today. He also explains where it fits in the current landscape of distributed storage and the plans for future improvements.

Preamble

  • Hello and welcome to the Data Engineering Podcast, the show about modern data management
  • When you’re ready to build your next pipeline you’ll need somewhere to deploy it, so check out Linode. With private networking, shared block storage, node balancers, and a 40Gbit network, all controlled by a brand new API you’ve got everything you need to run a bullet-proof data platform. Go to dataengineeringpodcast.com/linode to get a $20 credit and launch a new server in under a minute.
  • Are you struggling to keep up with customer request and letting errors slip into production? Want to try some of the innovative ideas in this podcast but don’t have time? DataKitchen’s DataOps software allows your team to quickly iterate and deploy pipelines of code, models, and data sets while improving quality. Unlike a patchwork of manual operations, DataKitchen makes your team shine by providing an end to end DataOps solution with minimal programming that uses the tools you love. Join the DataOps movement and sign up for the newsletter at datakitchen.io/de today. After that learn more about why you should be doing DataOps by listening to the Head Chef in the Data Kitchen at dataengineeringpodcast.com/datakitchen
  • Go to dataengineeringpodcast.com to subscribe to the show, sign up for the mailing list, read the show notes, and get in touch.
  • Join the community in the new Zulip chat workspace at dataengineeringpodcast.com/chat
  • Your host is Tobias Macey and today I’m interviewing Sage Weil about Ceph, an open source distributed file system that supports block storage, object storage, and a file system interface.

Interview

  • Introduction
  • How did you get involved in the area of data management?
  • Can you start with an overview of what Ceph is?
    • What was the motivation for starting the project?
    • What are some of the most common use cases for Ceph?


  • There are a large variety of distributed file systems. How would you characterize Ceph as it compares to other options (e.g. HDFS, GlusterFS, LionFS, SeaweedFS, etc.)?

  • Given that there is no single point of failure, what mechanisms do you use to mitigate the impact of network partitions?

    • What mechanisms are available to ensure data integrity across the cluster?


  • How is Ceph implemented and how has the design evolved over time?

  • What is required to deploy and manage a Ceph cluster?

    • What are the scaling factors for a cluster?
    • What are the limitations?


  • How does Ceph handle mixed write workloads with either a high volume of small files or a smaller volume of larger files?

  • In services such as S3 the data is segregated from block storage options like EBS or EFS. Since Ceph provides all of those interfaces in one project is it possible to use each of those interfaces to the same data objects in a Ceph cluster?

  • In what situations would you advise someone against using Ceph?

  • What are some of the most interested, unexpected, or challenging aspects of working with Ceph and the community?

  • What are some of the plans that you have for the future of Ceph?

Contact Info

Parting Question

  • From your perspective, what is the biggest gap in the tooling or technology for data management today?

Links

The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA

Support Data Engineering Podcast