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Storage tiering and erasure coding in Ceph (SCaLE13x)

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Ceph is designed around the assumption that all components of the system (disks, hosts, networks) can fail, and has traditionally leveraged replication to provide data durability and reliability. The CRUSH placement algorithm is used to allow failure domains to be defined across hosts, racks, rows, or datacenters, depending on the deployment scale and requirements.

Recent releases have added support for erasure coding, which can provide much higher data durability and lower storage overheads. However, in practice erasure codes have different performance characteristics than traditional replication and, under some workloads, come at some expense. At the same time, we have introduced a storage tiering infrastructure and cache pools that allow alternate hardware backends (like high-end flash) to be leveraged for active data sets while cold data are transparently migrated to slower backends. The combination of these two features enables a surprisingly broad range of new applications and deployment configurations.

This talk will cover a few Ceph fundamentals, discuss the new tiering and erasure coding features, and then discuss a variety of ways that the new capabilities can be leveraged.

Published in: Software

Storage tiering and erasure coding in Ceph (SCaLE13x)

  1. 1. ERASURE CODING AND CACHE TIERING SAGE WEIL – SCALE13X - 2015.02.22
  2. 2. 2 AGENDA ● Ceph architectural overview ● RADOS background ● Cache tiering ● Erasure coding ● Project status, roadmap
  3. 3. ARCHITECTURE
  4. 4. 4 CEPH MOTIVATING PRINCIPLES ● All components must scale horizontally ● There can be no single point of failure ● The solution must be hardware agnostic ● Should use commodity hardware ● Self-manage whenever possible ● Open source (LGPL) ● Move beyond legacy approaches – Client/cluster instead of client/server – Ad hoc HA
  5. 5. 5 CEPH COMPONENTS RGW A web services gateway for object storage, compatible with S3 and Swift LIBRADOS A library allowing apps to directly access RADOS (C, C++, Java, Python, Ruby, PHP) RADOS A software-based, reliable, autonomous, distributed object store comprised of self-healing, self-managing, intelligent storage nodes and lightweight monitors RBD A reliable, fully- distributed block device with cloud platform integration CEPHFS A distributed file system with POSIX semantics and scale- out metadata management APP HOST/VM CLIENT
  6. 6. ROBUST SERVICES BUILT ON RADOS
  7. 7. 7 ARCHITECTURAL COMPONENTS RGW A web services gateway for object storage, compatible with S3 and Swift LIBRADOS A library allowing apps to directly access RADOS (C, C++, Java, Python, Ruby, PHP) RADOS A software-based, reliable, autonomous, distributed object store comprised of self-healing, self-managing, intelligent storage nodes and lightweight monitors RBD A reliable, fully- distributed block device with cloud platform integration CEPHFS A distributed file system with POSIX semantics and scale- out metadata management APP HOST/VM CLIENT
  8. 8. 8 THE RADOS GATEWAY M M M RADOS CLUSTER RADOSGW LIBRADOS socket RADOSGW LIBRADOS APPLICATION APPLICATION REST
  9. 9. 9 MULTI-SITE OBJECT STORAGE WEB APPLICATION APP SERVER CEPH OBJECT GATEWAY (RGW) CEPH STORAGE CLUSTER (US-EAST) WEB APPLICATION APP SERVER CEPH OBJECT GATEWAY (RGW) CEPH STORAGE CLUSTER (EU-WEST)
  10. 10. 11 RADOSGW MAKES RADOS WEBBY RADOSGW:  REST-based object storage proxy  Uses RADOS to store objects ● Stripes large RESTful objects across many RADOS objects  API supports buckets, accounts  Usage accounting for billing  Compatible with S3 and Swift applications
  11. 11. 12 ARCHITECTURAL COMPONENTS RGW A web services gateway for object storage, compatible with S3 and Swift LIBRADOS A library allowing apps to directly access RADOS (C, C++, Java, Python, Ruby, PHP) RADOS A software-based, reliable, autonomous, distributed object store comprised of self-healing, self-managing, intelligent storage nodes and lightweight monitors RBD A reliable, fully- distributed block device with cloud platform integration CEPHFS A distributed file system with POSIX semantics and scale- out metadata management APP HOST/VM CLIENT
  12. 12. 13 STORING VIRTUAL DISKS M M RADOS CLUSTER HYPERVISOR LIBRBD VM
  13. 13. 14 KERNEL MODULE M M RADOS CLUSTER LINUX HOST KRBD
  14. 14. 15 RBD FEATURES ● Stripe images across entire cluster (pool) ● Read-only snapshots ● Copy-on-write clones ● Broad integration – Qemu – Linux kernel – iSCSI (STGT, LIO) – OpenStack, CloudStack, Nebula, Ganeti, Proxmox ● Incremental backup (relative to snapshots)
  15. 15. 16 ARCHITECTURAL COMPONENTS RGW A web services gateway for object storage, compatible with S3 and Swift LIBRADOS A library allowing apps to directly access RADOS (C, C++, Java, Python, Ruby, PHP) RADOS A software-based, reliable, autonomous, distributed object store comprised of self-healing, self-managing, intelligent storage nodes and lightweight monitors RBD A reliable, fully- distributed block device with cloud platform integration CEPHFS A distributed file system with POSIX semantics and scale- out metadata management APP HOST/VM CLIENT
  16. 16. 17 SEPARATE METADATA SERVER LINUX HOST M M M RADOS CLUSTER KERNEL MODULE datametadata 01 10
  17. 17. 18 SCALABLE METADATA SERVERS METADATA SERVER  Manages metadata for a POSIX-compliant shared filesystem  Directory hierarchy  File metadata (owner, timestamps, mode, etc.)  Snapshots on any directory  Clients stripe file data in RADOS  MDS not in data path  MDS stores metadata in RADOS  Dynamic MDS cluster scales to 10s or 100s  Only required for shared filesystem
  18. 18. RADOS
  19. 19. 20 ARCHITECTURAL COMPONENTS RGW A web services gateway for object storage, compatible with S3 and Swift LIBRADOS A library allowing apps to directly access RADOS (C, C++, Java, Python, Ruby, PHP) RADOS A software-based, reliable, autonomous, distributed object store comprised of self-healing, self-managing, intelligent storage nodes and lightweight monitors RBD A reliable, fully- distributed block device with cloud platform integration CEPHFS A distributed file system with POSIX semantics and scale- out metadata management APP HOST/VM CLIENT
  20. 20. 21 RADOS ● Flat object namespace within each pool ● Rich object API (librados) – Bytes, attributes, key/value data – Partial overwrite of existing data (mutable objects) – Single-object compound operations – RADOS classes (stored procedures) ● Strong consistency (CP system) ● Infrastructure aware, dynamic topology ● Hash-based placement (CRUSH) ● Direct client to server data path
  21. 21. 22 RADOS CLUSTER APPLICATION M M M M M RADOS CLUSTER
  22. 22. 23 RADOS COMPONENTS OSDs:  10s to 1000s in a cluster  One per disk (or one per SSD, RAID group…)  Serve stored objects to clients  Intelligently peer for replication & recovery Monitors:  Maintain cluster membership and state  Provide consensus for distributed decision- making  Small, odd number (e.g., 5)  Not part of data path M
  23. 23. 24 OBJECT STORAGE DAEMONS FS DISK OSD DISK OSD FS DISK OSD FS DISK OSD FS xfs btrfs ext4 M M M
  24. 24. DATA PLACEMENT
  25. 25. 26 WHERE DO OBJECTS LIVE? ?? APPLICATION M M M OBJECT
  26. 26. 27 A METADATA SERVER? 1 APPLICATION M M M 2
  27. 27. 28 CALCULATED PLACEMENT FAPPLICATION M M M A-G H-N O-T U-Z
  28. 28. 29 CRUSH CLUSTER OBJECTS 10 01 01 10 10 01 11 01 10 01 01 10 10 01 11 01 1001 0110 10 01 11 01 PLACEMENT GROUPS (PGs)
  29. 29. 30 CRUSH IS A QUICK CALCULATION RADOS CLUSTER OBJECT 10 01 01 10 10 01 11 01 1001 0110 10 01 11 01
  30. 30. 31 CRUSH AVOIDS FAILED DEVICES RADOS CLUSTER OBJECT 10 01 01 10 10 01 11 01 1001 0110 10 01 11 01 10
  31. 31. 32 CRUSH: DECLUSTERED PLACEMENT RADOS CLUSTER 10 01 01 10 10 01 11 0 1 1001 0110 10 01 11 01 32● Each PG independently maps to a pseudorandom set of OSDs ● PGs that map to the same OSD generally have replicas that do not ● When an OSD fails, each PG it stored will generally be re-replicated by a different OSD – Highly parallel recovery – Avoid single-disk recovery bottleneck 10 01
  32. 32. 33 CRUSH: DYNAMIC DATA PLACEMENT CRUSH:  Pseudo-random placement algorithm  Fast calculation, no lookup  Repeatable, deterministic  Statistically uniform distribution  Stable mapping  Limited data migration on change  Rule-based configuration  Infrastructure topology aware  Adjustable replication  Weighted devices (different sizes)
  33. 33. 34 DATA IS ORGANIZED INTO POOLS CLUSTER OBJECTS 10 01 01 10 10 01 11 01 1001 0110 10 01 11 01 POOLS (CONTAINING PGs) 10 01 11 01 10 01 01 10 01 10 10 01 11 01 10 01 10 01 10 11 01 11 01 10 10 01 01 01 10 10 01 01 POOL A POOL B POOL C POOL DOBJECTS OBJECTS OBJECTS
  34. 34. TIERED STORAGE
  35. 35. 36 TWO WAYS TO CACHE ● Within each OSD – Combine SSD and HDD under each OSD – Make localized promote/demote decisions – Leverage existing tools ● dm-cache, bcache, FlashCache ● Variety of caching controllers – We can help with hints ● Cache on separate devices/nodes – Different hardware for different tiers ● Slow nodes for cold data ● High performance nodes for hot data – Add, remove, scale each tier independently ● Unlikely to choose right ratios at procurement time HDD OSD BLOCKDEV SSD FS
  36. 36. 37 TIERED STORAGE APPLICATION CACHE POOL (REPLICATED) BACKING POOL (ERASURE CODED) CEPH STORAGE CLUSTER
  37. 37. 38 RADOS TIERING PRINCIPLES ● Each tier is a RADOS pool – May be replicated or erasure coded ● Tiers are durable – e.g., replicate across SSDs in multiple hosts ● Each tier has its own CRUSH policy – e.g., map cache pool to SSDs devices/hosts only ● librados adapts to tiering topology – Transparently direct requests accordingly ● e.g., to cache – No changes to RBD, RGW, CephFS, etc.
  38. 38. 39 READ (CACHE HIT) CEPH CLIENT CACHE POOL (SSD): WRITEBACK BACKING POOL (HDD) CEPH STORAGE CLUSTER READ READ REPLY
  39. 39. 40 READ (CACHE MISS) CEPH CLIENT CACHE POOL (SSD): WRITEBACK BACKING POOL (HDD) CEPH STORAGE CLUSTER READ READ REPLY PROXY READ
  40. 40. 42 READ (CACHE MISS) CEPH CLIENT CACHE POOL (SSD): WRITEBACK BACKING POOL (HDD) CEPH STORAGE CLUSTER READ PROMOTE READ REPLY
  41. 41. 43 WRITE (HIT) CEPH CLIENT CACHE POOL (SSD): WRITEBACK BACKING POOL (HDD) CEPH STORAGE CLUSTER WRITE ACK
  42. 42. 44 WRITE (MISS) CEPH CLIENT CACHE POOL (SSD): WRITEBACK BACKING POOL (HDD) CEPH STORAGE CLUSTER WRITE ACK PROMOTE
  43. 43. 45 WRITE (MISS) (COMING SOON) CEPH CLIENT CACHE POOL (SSD): WRITEBACK BACKING POOL (HDD) CEPH STORAGE CLUSTER WRITE ACK PROXY WRITE
  44. 44. 46 ESTIMATING TEMPERATURE ● Each PG constructs in-memory bloom filters – Insert records on both read and write – Each filter covers configurable period (e.g., 1 hour) – Tunable false positive probability (e.g., 5%) – Store most recent N periods on disk (e.g., last 24 hours) ● Estimate temperature – Has object been accessed in any of the last N periods? – ...in how many of them? – Informs the flush/evict decision ● Estimate “recency” – How many periods since the object hasn't been accessed? – Informs read miss behavior: proxy vs promote
  45. 45. 47 FLUSH AND/OR EVICT COLD DATA CEPH CLIENT CACHE POOL (SSD): WRITEBACK BACKING POOL (HDD) CEPH STORAGE CLUSTER FLUSH ACK EVICT
  46. 46. 48 TIERING AGENT ● Each PG has an internal tiering agent – Manages PG based on administrator defined policy ● Flush dirty objects – When pool reaches target dirty ratio – Tries to select cold objects – Marks objects clean when they have been written back to the base pool ● Evict (delete) clean objects – Greater “effort” as cache pool approaches target size
  47. 47. 49 CACHE TIER USAGE ● Cache tier should be faster than the base tier ● Cache tier should be replicated (not erasure coded) ● Promote and flush are expensive – Best results when object temperature are skewed ● Most I/O goes to small number of hot objects – Cache should be big enough to capture most of the acting set ● Challenging to benchmark – Need a realistic workload (e.g., not 'dd') to determine how it will perform in practice – Takes a long time to “warm up” the cache
  48. 48. ERASURE CODING
  49. 49. 52 ERASURE CODING OBJECT REPLICATED POOL CEPH STORAGE CLUSTER ERASURE CODED POOL CEPH STORAGE CLUSTER COPY COPY OBJECT 31 2 X Y COPY 4 Full copies of stored objects  Very high durability  3x (200% overhead)  Quicker recovery One copy plus parity  Cost-effective durability  1.5x (50% overhead)  Expensive recovery
  50. 50. 53 ERASURE CODING SHARDS CEPH STORAGE CLUSTER OBJECT Y OSD 3 OSD 2 OSD 1 OSD 4 OSD X OSD ERASURE CODED POOL
  51. 51. 54 ERASURE CODING SHARDS CEPH STORAGE CLUSTER Y OSD 3 OSD 2 OSD 1 OSD 4 OSD X OSD 0 4 8 12 16 1 5 9 13 17 2 6 10 14 18 3 7 9 15 19 A B C D E A' B' C' D' E' ● Variable stripe size (e.g., 4 KB) ● Zero-fill shards (logically) in partial tail stripe
  52. 52. 55 PRIMARY COORDINATES CEPH STORAGE CLUSTER Y OSD 3 OSD 2 OSD 1 OSD 4 OSD X OSD ERASURE CODED POOL
  53. 53. 56 EC READ CEPH STORAGE CLUSTER Y OSD 3 OSD 2 OSD 1 OSD 4 OSD X OSD ERASURE CODED POOL CEPH CLIENT READ
  54. 54. 57 EC READ CEPH STORAGE CLUSTER Y OSD 3 OSD 2 OSD 1 OSD 4 OSD X OSD ERASURE CODED POOL CEPH CLIENT READ READS
  55. 55. 58 EC READ CEPH STORAGE CLUSTER Y OSD 3 OSD 2 OSD 1 OSD 4 OSD X OSD ERASURE CODED POOL CEPH CLIENT READ REPLY
  56. 56. 59 EC WRITE CEPH STORAGE CLUSTER Y OSD 3 OSD 2 OSD 1 OSD 4 OSD X OSD ERASURE CODED POOL CEPH CLIENT WRITE
  57. 57. 60 EC WRITE CEPH STORAGE CLUSTER Y OSD 3 OSD 2 OSD 1 OSD 4 OSD X OSD ERASURE CODED POOL CEPH CLIENT WRITE WRITES
  58. 58. 61 EC WRITE CEPH STORAGE CLUSTER Y OSD 3 OSD 2 OSD 1 OSD 4 OSD X OSD ERASURE CODED POOL CEPH CLIENT WRITE ACK
  59. 59. 62 EC WRITE: DEGRADED CEPH STORAGE CLUSTER Y OSD 3 OSD 2 OSD 1 OSD 4 OSD X OSD ERASURE CODED POOL CEPH CLIENT WRITE WRITES
  60. 60. 63 EC WRITE: PARTIAL FAILURE CEPH STORAGE CLUSTER Y OSD 3 OSD 2 OSD 1 OSD 4 OSD X OSD ERASURE CODED POOL CEPH CLIENT WRITE WRITES
  61. 61. 64 EC WRITE: PARTIAL FAILURE CEPH STORAGE CLUSTER Y OSD 3 OSD 2 OSD 1 OSD 4 OSD X OSD ERASURE CODED POOL CEPH CLIENT B B BA A A
  62. 62. 65 EC RESTRICTIONS ● Overwrite in place will not work in general ● Log and 2PC would increase complexity, latency ● We chose to restrict allowed operations – create – append (on stripe boundary) – remove (keep previous generation of object for some time) ● These operations can all easily be rolled back locally – create → delete – append → truncate – remove → roll back to previous generation ● Object attrs preserved in existing PG logs (they are small) ● Key/value data is not allowed on EC pools
  63. 63. 66 EC WRITE: PARTIAL FAILURE CEPH STORAGE CLUSTER Y OSD 3 OSD 2 OSD 1 OSD 4 OSD X OSD ERASURE CODED POOL CEPH CLIENT B B BA A A
  64. 64. 67 EC WRITE: PARTIAL FAILURE CEPH STORAGE CLUSTER Y OSD 3 OSD 2 OSD 1 OSD 4 OSD X OSD ERASURE CODED POOL CEPH CLIENT A A AA A A
  65. 65. 68 EC RESTRICTIONS ● This is a small subset of allowed librados operations – Notably cannot (over)write any extent ● Coincidentally, unsupported operations are also inefficient for erasure codes – Generally require read/modify/write of affected stripe(s) ● Some can consume EC directly – RGW (no object data update in place) ● Others can combine EC with a cache tier (RBD, CephFS) – Replication for warm/hot data – Erasure coding for cold data – Tiering agent skips objects with key/value data
  66. 66. 69 WHICH ERASURE CODE? ● The EC algorithm and implementation are pluggable – jerasure/gf-complete (free, open, and very fast) – ISA-L (Intel library; optimized for modern Intel procs) – LRC (local recovery code – layers over existing plugins) – SHEC (trades extra storage for recovery efficiency – new from Fujitsu) ● Parameterized – Pick “k” and “m”, stripe size ● OSD handles data path, placement, rollback, etc. ● Erasure plugin handles – Encode and decode math – Given these available shards, which ones should I fetch to satisfy a read? – Given these available shards and these missing shards, which ones should I fetch to recover?
  67. 67. 70 COST OF RECOVERY 1 TB OSD
  68. 68. 71 COST OF RECOVERY 1 TB OSD
  69. 69. 72 COST OF RECOVERY (REPLICATION) 1 TB OSD 1 TB
  70. 70. 73 COST OF RECOVERY (REPLICATION) 1 TB OSD .01 TB .01 TB .01 TB .01 TB ... ... .01 TB .01 TB
  71. 71. 74 COST OF RECOVERY (REPLICATION) 1 TB OSD 1 TB
  72. 72. 75 COST OF RECOVERY (EC) 1 TB OSD 1 TB 1 TB 1 TB 1 TB
  73. 73. 76 LOCAL RECOVERY CODE (LRC) CEPH STORAGE CLUSTER Y OSD 3 OSD 2 OSD 1 OSD 4 OSD X OSD ERASURE CODED POOL A OSD C OSD B OSD OBJECT
  74. 74. 77 BIG THANKS TO ● Ceph – Loic Dachary (CloudWatt, FSF France, Red Hat) – Andreas Peters (CERN) – Sam Just (Inktank / Red Hat) – David Zafman (Inktank / Red Hat) ● jerasure / gf-complete – Jim Plank (University of Tennessee) – Kevin Greenan (Box.com) ● Intel (ISL plugin) ● Fujitsu (SHEC plugin)
  75. 75. ROADMAP
  76. 76. 79 WHAT'S NEXT ● Erasure coding – Allow (optimistic) client reads directly from shards – ARM optimizations for jerasure ● Cache pools – Better agent decisions (when to flush or evict) – Supporting different performance profiles ● e.g., slow / “cheap” flash can read just as fast – Complex topologies ● Multiple readonly cache tiers in multiple sites ● Tiering – Support “redirects” to (very) cold tier below base pool – Enable dynamic spin-down, dedup, and other features
  77. 77. 80 OTHER ONGOING WORK ● Performance optimization (SanDisk, Intel, Mellanox) ● Alternative OSD backends – New backend: hybrid key/value and file system – leveldb, rocksdb, LMDB ● Messenger (network layer) improvements – RDMA support (libxio – Mellanox) – Event-driven TCP implementation (UnitedStack) ● CephFS – Online consistency checking and repair tools – Performance, robustness ● Multi-datacenter RBD, RADOS replication
  78. 78. 81 FOR MORE INFORMATION ● http://ceph.com ● http://github.com/ceph ● http://tracker.ceph.com ● Mailing lists – ceph-users@ceph.com – ceph-devel@vger.kernel.org ● irc.oftc.net – #ceph – #ceph-devel ● Twitter – @ceph
  79. 79. THANK YOU! Sage Weil CEPH PRINCIPAL ARCHITECT sage@redhat.com @liewegas

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