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ARCHITECTING CEPH SOLUTIONS
Brent Compton & Kyle Bader
Red Hat Storage
January 2016
CLUSTER BUILDING BLOCKS
STANDARD SERVERS AND MEDIA (HDD, SSD, PCIE)
STANDARD NICS AND SWITCHES
WORKLOADS
ACCESS
PLATFORM
NETWORK
CEPH STORAGE CLUSTER
CEPH BLOCK & OBJECT CLIENTS
1. Qualify need for scale-out storage
2. Design for target workload IO profile(s)
3. Choose storage access method(s)
4. Identify capacity
5. Determine fault-domain risk tolerance
6. Select data protection method
Target
Cluster
Architecture
CLUSTER DESIGN CONSIDERATIONS
OpenStack Starter
100TB
S
500TB
M
1PB
L
2PB
IOPS
OPTIMIZED
THROUGHPUT
OPTIMIZED
COST-
CAPACITY
OPTIMIZED
TARGET CLUSTER ARCHITECTURE
OpenStack Starter
100TB
S
500TB
M
1PB
L
2PB
IOPS
OPTIMIZED
2-4x PCIe/NVMe slot servers (PCIe)
12x 2.5” SSD bay servers (SAS/SATA)
THROUGHPUT
OPTIMIZED
12-16x 3.5” bay servers
24-36x 3.5” bay
servers
24-36x 3.5” bay
servers
COST-
CAPACITY
OPTIMIZED
60-72x 3.5” bay
servers
BROAD SERVER SIZE TRENDS
OpenStack Starter
100TB
S
500TB
M
1PB
L
2PB
IOPS
OPTIMIZED
• Ceph RBD (block)
• OSDs on all flash media (SATA SSD or PCIe)
• High-bin, dual-socket CPU
• 2x replication w/ backup or 3x replication
• Multiple OSDs per drive (if PCIe)
THROUGHPUT
OPTIMIZED
• Ceph RBD (block) or RGW (object)
• OSDs on HDD media with dedicated SSD write journals (4:1 ratio)
• Mid-bin, dual-socket CPU (single-socket adequate, servers <=12 OSDs)
• 3x replication (RBD/RGW read intensive) or erasure-coded (RGW write-intensive)
• High-bandwidth networking, >10Gb (for servers with >12 OSDs)
COST-
CAPACITY
OPTIMIZED
• Ceph RGW (object)
• OSDs on HDD media (write journals co-located on HDDs)
• Mid-bin, single-socket CPU (dual-socket, servers >12 OSDs)
• Erasure-coded data protection (v. replication)
BROAD SERVER CONFIGURATION TRENDS
Elastic provisioning across storage server cluster
Standardized servers and networking
Petabyte scale: 10s, 100s, or 1000s of servers/cluster
Data HA across ‘islands’ of scale-up storage servers
Performance and capacity scaled independently
Incremental vs. forklift upgrades
STEP 1: QUALIFY NEED FOR SCALE-OUT
STORAGE
Performance vs. ‘cheap-and-deep’?
Performance: throughput vs. IOPS intensive?
Small block vs. large block?
Sequential vs. random IO?
Read vs. write mix?
Latency: absolute vs. consistency targets?
STEP 2: DESIGN FOR TARGET WORKLOADS
DISTRIBUTED FILE* OBJECT BLOCK**
CEPH STORAGE CLUSTER
* Support for CephFS is not yet included in Red Hat Ceph Storage
** RBD supported with replicated data protection only
STEP 3: CHOOSE STORAGE ACCESS METHODS
OpenStack Starter
100TB
S
500TB
M
1PB
L
2PB
IOPS
OPTIMIZED
THROUGHPUT
OPTIMIZED
COST-
CAPACITY
OPTIMIZED
STEP 4: IDENTIFY CAPACITY
How much cluster capacity can you tolerate on one node?
• With fewer nodes in the cluster, performance will be more degraded during recovery
• Each node must devote a greater % of its compute/IO utilization to recovery operations
• With fewer nodes in the cluster, maximum node utilization is limited
• Each node must contribute a greater % of its reserve capacity for backfill/recovery operations
Guidelines:
• Minimum supported (Red Hat Ceph Storage): 3 OSD nodes per cluster
• Minimum recommended (performance cluster): 10 OSD nodes per cluster
• 1 node represents <10% of total cluster capacity
• Minimum recommended (cost/capacity cluster): 7 OSD nodes per cluster
• 1 node represents <15% of total cluster capacity
STEP 5: DETERMINE FAILURE RISK TOLERANCE
STEP 6: SELECT DATA PROTECTION METHOD
Replication
• Data is copied n times and spread onto different disks on different servers
• Clusters can tolerate n-1 disk failures without data loss
• 3 replicas is a popular configuration
Erasure Coding (analogous to network RAID)
• Data is encoded into k chunks with m parity chunks and spread onto different
disks on different servers
• Clusters can tolerate m disk failures without data loss
• 8+3 k+m is a popular configuration
This decision will affect the initial cost of your cluster more than any other.
1. Qualify need for scale-out storage
2. Design for target workload IO profile(s)
3. Choose storage access method(s)
4. Identify capacity
5. Determine fault-domain risk tolerance
6. Select data protection method
Target
Cluster
Architecture
CLUSTER DESIGN CONSIDERATIONS
RESOURCES
Ceph on Supermicro Performance & Sizing Guide
http://www.redhat.com/en/resources/red-hat-ceph-storage-clusters-supermicro-storage-servers
Ceph on Cisco UCS C3160 Whitepaper
http://www.cisco.com/c/en/us/products/collateral/servers-unified-computing/ucs-c-series-rack-
servers/whitepaper-C11-735004.html
Ceph on Scalable Informatics Whitepaper
https://www.scalableinformatics.com/assets/documents/Unison-Ceph-Performance.pdf
RED HAT STORAGE TEST DRIVES
Test drive:
bit.ly/glustertestdrive
Test-drive:
bit.ly/cephtestdrive
Architecting Ceph Solutions

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Architecting Ceph Solutions

  • 1. ARCHITECTING CEPH SOLUTIONS Brent Compton & Kyle Bader Red Hat Storage January 2016
  • 2. CLUSTER BUILDING BLOCKS STANDARD SERVERS AND MEDIA (HDD, SSD, PCIE) STANDARD NICS AND SWITCHES WORKLOADS ACCESS PLATFORM NETWORK CEPH STORAGE CLUSTER CEPH BLOCK & OBJECT CLIENTS
  • 3. 1. Qualify need for scale-out storage 2. Design for target workload IO profile(s) 3. Choose storage access method(s) 4. Identify capacity 5. Determine fault-domain risk tolerance 6. Select data protection method Target Cluster Architecture CLUSTER DESIGN CONSIDERATIONS
  • 5. OpenStack Starter 100TB S 500TB M 1PB L 2PB IOPS OPTIMIZED 2-4x PCIe/NVMe slot servers (PCIe) 12x 2.5” SSD bay servers (SAS/SATA) THROUGHPUT OPTIMIZED 12-16x 3.5” bay servers 24-36x 3.5” bay servers 24-36x 3.5” bay servers COST- CAPACITY OPTIMIZED 60-72x 3.5” bay servers BROAD SERVER SIZE TRENDS
  • 6. OpenStack Starter 100TB S 500TB M 1PB L 2PB IOPS OPTIMIZED • Ceph RBD (block) • OSDs on all flash media (SATA SSD or PCIe) • High-bin, dual-socket CPU • 2x replication w/ backup or 3x replication • Multiple OSDs per drive (if PCIe) THROUGHPUT OPTIMIZED • Ceph RBD (block) or RGW (object) • OSDs on HDD media with dedicated SSD write journals (4:1 ratio) • Mid-bin, dual-socket CPU (single-socket adequate, servers <=12 OSDs) • 3x replication (RBD/RGW read intensive) or erasure-coded (RGW write-intensive) • High-bandwidth networking, >10Gb (for servers with >12 OSDs) COST- CAPACITY OPTIMIZED • Ceph RGW (object) • OSDs on HDD media (write journals co-located on HDDs) • Mid-bin, single-socket CPU (dual-socket, servers >12 OSDs) • Erasure-coded data protection (v. replication) BROAD SERVER CONFIGURATION TRENDS
  • 7. Elastic provisioning across storage server cluster Standardized servers and networking Petabyte scale: 10s, 100s, or 1000s of servers/cluster Data HA across ‘islands’ of scale-up storage servers Performance and capacity scaled independently Incremental vs. forklift upgrades STEP 1: QUALIFY NEED FOR SCALE-OUT STORAGE
  • 8. Performance vs. ‘cheap-and-deep’? Performance: throughput vs. IOPS intensive? Small block vs. large block? Sequential vs. random IO? Read vs. write mix? Latency: absolute vs. consistency targets? STEP 2: DESIGN FOR TARGET WORKLOADS
  • 9. DISTRIBUTED FILE* OBJECT BLOCK** CEPH STORAGE CLUSTER * Support for CephFS is not yet included in Red Hat Ceph Storage ** RBD supported with replicated data protection only STEP 3: CHOOSE STORAGE ACCESS METHODS
  • 11. How much cluster capacity can you tolerate on one node? • With fewer nodes in the cluster, performance will be more degraded during recovery • Each node must devote a greater % of its compute/IO utilization to recovery operations • With fewer nodes in the cluster, maximum node utilization is limited • Each node must contribute a greater % of its reserve capacity for backfill/recovery operations Guidelines: • Minimum supported (Red Hat Ceph Storage): 3 OSD nodes per cluster • Minimum recommended (performance cluster): 10 OSD nodes per cluster • 1 node represents <10% of total cluster capacity • Minimum recommended (cost/capacity cluster): 7 OSD nodes per cluster • 1 node represents <15% of total cluster capacity STEP 5: DETERMINE FAILURE RISK TOLERANCE
  • 12. STEP 6: SELECT DATA PROTECTION METHOD Replication • Data is copied n times and spread onto different disks on different servers • Clusters can tolerate n-1 disk failures without data loss • 3 replicas is a popular configuration Erasure Coding (analogous to network RAID) • Data is encoded into k chunks with m parity chunks and spread onto different disks on different servers • Clusters can tolerate m disk failures without data loss • 8+3 k+m is a popular configuration This decision will affect the initial cost of your cluster more than any other.
  • 13. 1. Qualify need for scale-out storage 2. Design for target workload IO profile(s) 3. Choose storage access method(s) 4. Identify capacity 5. Determine fault-domain risk tolerance 6. Select data protection method Target Cluster Architecture CLUSTER DESIGN CONSIDERATIONS
  • 14. RESOURCES Ceph on Supermicro Performance & Sizing Guide http://www.redhat.com/en/resources/red-hat-ceph-storage-clusters-supermicro-storage-servers Ceph on Cisco UCS C3160 Whitepaper http://www.cisco.com/c/en/us/products/collateral/servers-unified-computing/ucs-c-series-rack- servers/whitepaper-C11-735004.html Ceph on Scalable Informatics Whitepaper https://www.scalableinformatics.com/assets/documents/Unison-Ceph-Performance.pdf
  • 15. RED HAT STORAGE TEST DRIVES Test drive: bit.ly/glustertestdrive Test-drive: bit.ly/cephtestdrive