Using OpenStack Swift for Extreme Data Durability
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Openstack Swift is a very powerful object storage that is used in several of the largest object storage deployments around the globe. It ensures a very high level of data durability and can withstand epic disasters if setup in the right way.
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Using OpenStack Swift for Extreme Data Durability
- 1. Using OpenStack Swift for extreme data durability Florent Flament, Cloudwatt Christian Schwede, eNovance OpenStack Summit Paris, November 2014
- 2. Intro - Cloudwatt ● Florent Flament ● Dev & Fireman @ Cloudwatt ● Fixing & tuning of OpenStack (Cinder, Keystone, Nova, Swift) ● Email: florent.flament@cloudwatt.com ● IRC: florentflament on #openstack-dev (Freenode) ● Twitter: @florentflament_ ● Blogs: http://dev.cloudwatt.com / http://www.florentflament.com
- 3. Intro - eNovance ● Christian Schwede ● Developer @ eNovance / Red Hat ● Mostly working on Swift, testing, automation and developer tools ● Swift Core ● IRC: cschwede in #openstack-swift ● christian@enovance.com / cschwede@redhat.com ● Twitter: @cschwede_de
- 4. Architecture
- 5. Proxy Node Proxy Node Network Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk
- 6. Proxy Node Proxy Node Network Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Zone 0 Zone 1 Zone 2
- 7. Proxy Node Proxy Node Network Zone 0 Zone 1 Region 0 (⅔ of the data) Zone 2 Region 1 (⅓ of the data) Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Zone 0 Disk Disk Disk
- 8. The Ring
- 9. Ring : the Map of data ● One file per type of data. Ring files map each copy of a data to a physical device through partitions. ● An object’s partition number is computed from the hash of the object’s name. ● A Ring file is: a (replica, partition) to device ID table, a devices table and a number of hash bits. ● Visualize a Ring: https://github.com/victorlin/swiftsense
- 10. Concrete example of Ring Replica & Partition to Device ID table Devices table 0 1 2 3 0 1 2 3 1 2 3 0 1 2 3 0 2 3 0 1 2 3 0 1 Partition number 0 1 2 Replica number 0 1 2 3 4 5 6 7 ID Host Port Device 0 192.168.0.10 6000 sdb1 1 192.168.0.10 6000 sdc1 2 192.168.0.11 6000 sdb1 3 192.168.0.11 6000 sdc1 Bit count (partition power) = 3 → 23 = 8 partitions
- 11. Storage policies ● Included in the Juno release (Swift > 2.0.0) ● Applied on a per-container basis ● Flexibility to use multiple rings, for example: ○ Basic: 2 replicas on spinning disks, single datacenter ○ Strong: 3 replicas in three different datacenters around the globe ○ Fast: 3 replicas on SSDs and much more powerful proxies
- 13. Object durability ● Disk failures: pd ~ 2-5% per year ● Unrecoverable bit read errors: pb = 10-15 ⋅ 8 ⋅ objectsize Failure Failure Failure 3 replicas 2 replicas 1 replica Data loss Replication Replication Replication ● Durability in the range of 10-11 nines with 3 replicas (99.99999999%) ● http://enovance.github.io/swift-durability-calculator/
- 14. Recover from a disk failure Set failed device weight to 0, rebalance, push new ring Failed
- 15. Object availability & durability Zone 0 Zone 1 Region 0 (⅔ of the data) Zone 2 Region 1 (⅓ of the data) Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Disk Zone 0 Disk Disk Disk
- 16. Maintenance
- 17. Maintainability by Simplicity ● Standalone `swift-ring-builder` tool to manipulate the Ring ○ Uses `builders` files to keep architectural information on the cluster ○ Smartly assigns partitions to devices ○ Generates Ring files easily checked ● Processes on Swift nodes focus on ensuring that files are stored uncorrupted at the appropriate location
- 18. Splitting a running Swift Cluster ● Ensuring no data is lost ○ Move only 1 replica at a time ○ Small steps to limit the impact ○ Check for data corruption ○ Check data location ○ Rollback in case of failure ● Limiting the impact on performance ○ Availability of cluster resources ○ Load incurred by cluster being split ○ Small steps to limit the impact ○ Control nodes accessed by users Natively available in Swift
- 19. Splitting a running Swift Cluster ● Ensuring no data is lost ○ Move only 1 replica at a time ○ Small steps to limit the impact ○ Check for data corruption ○ Check data location ○ Rollback in case of failure ● Limiting the impact on performance ○ Availability of cluster resources ○ Load incurred by cluster being split ○ Small steps to limit the impact ○ Control nodes accessed by users Small steps New in Swift 2.2 !!
- 20. Adding a new region Add a new region smoothly by limiting the amount of data moved ● really possible since Swift 2.2 ● Final weight in new region should be at least ⅓ of the total cluster weight Example of process: 1. Add devices to new region with a very low weight 2. Increase devices’ weights to store 5% of data in the new region 3. Progressively increase by steps of 5% the amount of data in the new region More details: http://www.florentflament.com/blog/splitting-swift-cluster.html
- 22. Erasure coding ● Coming real soon now ● Instead of N copies of each object: ○ apply EC to object, split into multiple fragments, for example 14 ○ store them on different disks/nodes ○ objects can be rebuild from 10 fragments ■ Tolerates loss of 4 fragments ● higher durability ■ Only ~ 40% overhead (compared to 200%) ● much cheaper
- 23. Durability calculation ● More detailed calculation ○ Number of disks, servers, partitions ● Add erasure coding ● Include in Swift documentation? ● Community effort ○ Discussion started last Swift hackathon ■ NTT, Swiftstack, IBM, Seagate, Red Hat / eNovance ○ Ad-Hoc session on Thursday/Friday - join us!
- 24. Summary ● High availability, even if large parts of the cluster are not accessible ● Automatic failure correction ensures high durability, and depending on your cluster configuration excels known industry standards ● Swift 2.2 (Juno release) ○ Even smoother and predictable cluster upgrades ○ Storage Policies allow fine grained data placement control ● Erasure Coding increase durability even more while lowering costs