Chapter 2. Considerations and recommendations

An important aspect of a cloud storage solution is that storage clusters can run out of IOPS due to network latency, and other factors. Also, the storage cluster can run out of throughput due to bandwidth constraints long before the storage clusters run out of storage capacity. This means that the network hardware configuration must support the chosen workloads to meet price versus performance requirements.

Storage administrators prefer that a storage cluster recovers as quickly as possible. Carefully consider bandwidth requirements for the storage cluster network, be mindful of network link oversubscription, and segregate the intra-cluster traffic from the client-to-cluster traffic. Also consider that network performance is increasingly important when considering the use of Solid State Disks (SSD), flash, NVMe, and other high performing storage devices.

Ceph supports a public network and a storage cluster network. The public network handles client traffic and communication with Ceph Monitors. The storage cluster network handles Ceph OSD heartbeats, replication, backfilling, and recovery traffic. At a minimum, a single 10 GB Ethernet link should be used for storage hardware, and you can add additional 10 GB Ethernet links for connectivity and throughput.

In the case of a drive failure, replicating 1 TB of data across a 1 GB Ethernet network takes 3 hours, and 3 TB takes 9 hours. Using 3 TB is the typical drive configuration. By contrast, with a 10 GB Ethernet network, the replication times would be 20 minutes and 1 hour. Remember that when a Ceph OSD fails, the storage cluster recovers by replicating the data it contained to other OSDs within the same failure domain and device class as the failed OSD.

The failure of a larger domain such as a rack means that the storage cluster utilizes considerably more bandwidth. When building a storage cluster consisting of multiple racks, which is common for large storage implementations, consider utilizing as much network bandwidth between switches in a "fat tree" design for optimal performance. A typical 10 GB Ethernet switch has 48 10 GB ports and four 40 GB ports. Use the 40 GB ports on the spine for maximum throughput. Alternatively, consider aggregating unused 10 GB ports with QSFP+ and SFP+ cables into more 40 GB ports to connect to other rack and spine routers. Also, consider using LACP mode 4 to bond network interfaces. Additionally, use jumbo frames, with a maximum transmission unit (MTU) of 9000, especially on the backend or cluster network.

Before installing and testing a Red Hat Ceph Storage cluster, verify the network throughput. Most performance-related problems in Ceph usually begin with a networking issue. Simple network issues like a kinked or bent Cat-6 cable could result in degraded bandwidth. Use a minimum of 10 GB ethernet for the front side network. For large clusters, consider using 40 GB ethernet for the backend or cluster network.

The first consideration for using Red Hat Ceph Storage is developing a storage strategy for the data. A storage strategy is a method of storing data that serves a particular use case. If you need to store volumes and images for a cloud platform like OpenStack, you can choose to store data on faster Serial Attached SCSI (SAS) drives with Solid State Drives (SSD) for journals. By contrast, if you need to store object data for an S3- or Swift-compliant gateway, you can choose to use something more economical, like traditional Serial Advanced Technology Attachment (SATA) drives. Red Hat Ceph Storage can accommodate both scenarios in the same storage cluster, but you need a means of providing the fast storage strategy to the cloud platform, and a means of providing more traditional storage for your object store.

One of the most important steps in a successful Ceph deployment is identifying a price-to-performance profile suitable for the storage cluster’s use case and workload. It is important to choose the right hardware for the use case. For example, choosing IOPS-optimized hardware for a cold storage application increases hardware costs unnecessarily. Whereas, choosing capacity-optimized hardware for its more attractive price point in an IOPS-intensive workload will likely lead to unhappy users complaining about slow performance.

Red Hat Ceph Storage can support multiple storage strategies. Use cases, cost versus benefit performance tradeoffs, and data durability are the primary considerations that help develop a sound storage strategy.

Replication stores one or more redundant copies of the data across failure domains in case of a hardware failure. However, redundant copies of data can become expensive at scale. For example, to store 1 petabyte of data with triple replication would require a cluster with at least 3 petabytes of storage capacity.

Erasure coding stores data as data chunks and coding chunks. In the event of a lost data chunk, erasure coding can recover the lost data chunk with the remaining data chunks and coding chunks. Erasure coding is substantially more economical than replication. For example, using erasure coding with 8 data chunks and 3 coding chunks provides the same redundancy as 3 copies of the data. However, such an encoding scheme uses approximately 1.5x the initial data stored compared to 3x with replication.

The CRUSH algorithm aids this process by ensuring that Ceph stores additional copies or coding chunks in different locations within the storage cluster. This ensures that the failure of a single storage device or host does not lead to a loss of all of the copies or coding chunks necessary to preclude data loss. You can plan a storage strategy with cost versus benefit tradeoffs, and data durability in mind, then present it to a Ceph client as a storage pool.

2.2.1. Colocating Ceph daemons and its advantages

You can colocate containerized Ceph daemons on the same host. Here are the advantages of colocating some of Ceph’s daemons:

• Significantly improves the total cost of ownership (TCO) at small scale.
• Can increase overall performance.
• Reduces the amount of physical hosts for a minimum configuration.
• Better resource utilization.
• Upgrading Red Hat Ceph Storage is easier.

By using containers you can colocate one daemon from the following list with a Ceph OSD daemon (ceph-osd). Additionally, for the Ceph Object Gateway (radosgw), Ceph Metadata Server (ceph-mds), and Grafana, you can colocate it either with a Ceph OSD daemon, plus a daemon from the list below.

• Ceph Metadata Server (ceph-mds)
• Ceph Monitor (ceph-mon)
• Ceph Manager (ceph-mgr)
• NFS Ganesha (nfs-ganesha)
• Ceph Manager (ceph-grafana)

Table 2.1. Daemon Placement Example

Host Name	Daemon	Daemon	Daemon
host1	OSD	Monitor & Manager	Prometheus
host2	OSD	Monitor & Manager	RGW
host3	OSD	Monitor & Manager	RGW
host4	OSD	Metadata Server
host5	OSD	Metadata Server

Note

Because ceph-mon and ceph-mgr work closely together, they are not considered two separate daemons for the purposes of colocation.

Colocating Ceph daemons can be done from the command line interface, by using the --placement option to the ceph orch command, or you can use a service specification YAML file.

Command line Example

[ceph: root@host01 /]# ceph orch apply mon --placement="host1 host2 host3"

Service Specification YAML File Example

service_type: mon
placement:
  hosts:
   - host01
   - host02
   - host03

[ceph: root@host01 /]# ceph orch apply -i mon.yml

Red Hat recommends colocating the Ceph Object Gateway with Ceph OSD containers to increase performance. To achieve the highest performance without incurring additional hardware cost, use two Ceph Object Gateway daemons per host.

Ceph Object Gateway Command line Example

[ceph: root@host01 /]# ceph orch apply rgw example --placement="6 host1 host2 host3"

Ceph Object Gateway Service Specification YAML File Example

service_type: rgw
service_id: example
placement:
  count: 6
  hosts:
   - host01
   - host02
   - host03

[ceph: root@host01 /]# ceph orch apply -i rgw.yml

The diagrams below shows the difference between storage clusters with colocated and non-colocated daemons.

Figure 2.1. Colocated Daemons

Figure 2.2. Non-colocated Daemons

Additional resources

• See the Management of services using the Ceph Orchestrator chapter in the Red Hat Ceph Storage Operations Guide for more details on using the --placement option.
• See the Red Hat Ceph Storage RGW deployment strategies and sizing guidance article for more information.

One of the key benefits of a Ceph storage cluster is the ability to support different types of workloads within the same storage cluster using performance domains. Different hardware configurations can be associated with each performance domain. Storage administrators can deploy storage pools on the appropriate performance domain, providing applications with storage tailored to specific performance and cost profiles. Selecting appropriately sized and optimized servers for these performance domains is an essential aspect of designing a Red Hat Ceph Storage cluster.

To the Ceph client interface that reads and writes data, a Ceph storage cluster appears as a simple pool where the client stores data. However, the storage cluster performs many complex operations in a manner that is completely transparent to the client interface. Ceph clients and Ceph object storage daemons, referred to as Ceph OSDs, or simply OSDs, both use the Controlled Replication Under Scalable Hashing (CRUSH) algorithm for the storage and retrieval of objects. Ceph OSDs can run in containers within the storage cluster.

A CRUSH map describes a topography of cluster resources, and the map exists both on client hosts as well as Ceph Monitor hosts within the cluster. Ceph clients and Ceph OSDs both use the CRUSH map and the CRUSH algorithm. Ceph clients communicate directly with OSDs, eliminating a centralized object lookup and a potential performance bottleneck. With awareness of the CRUSH map and communication with their peers, OSDs can handle replication, backfilling, and recovery—allowing for dynamic failure recovery.

Ceph uses the CRUSH map to implement failure domains. Ceph also uses the CRUSH map to implement performance domains, which simply take the performance profile of the underlying hardware into consideration. The CRUSH map describes how Ceph stores data, and it is implemented as a simple hierarchy, specifically an acyclic graph, and a ruleset. The CRUSH map can support multiple hierarchies to separate one type of hardware performance profile from another. Ceph implements performance domains with device "classes".

For example, you can have these performance domains coexisting in the same Red Hat Ceph Storage cluster:

Figure 2.3. Performance and Failure Domains

Another important aspect of designing a storage cluster is to determine if the storage cluster will be in one data center site or span multiple data center sites. Multi-site storage clusters benefit from geographically distributed failover and disaster recovery, such as long-term power outages, earthquakes, hurricanes, floods or other disasters. Additionally, multi-site storage clusters can have an active-active configuration, which can direct client applications to the closest available storage cluster. This is a good storage strategy for content delivery networks. Consider placing data as close to the client as possible. This is important for throughput-intensive workloads, such as streaming 4k video.

mon_pg_warn_max_per_osd = n

# ceph osd pool create .us-west.rgw.buckets.non-ec 64 64 replicated rgw-service

As a storage administrator, when deploying a Ceph storage cluster and an Object Gateway, typically the Ceph Object Gateway has a default zone group and zone. The Ceph storage cluster will have default pools, which in turn will use a CRUSH map with a default CRUSH hierarchy and a default CRUSH rule.

Production gateways typically use a custom realm, zone group and zone named according to the use and geographic location of the gateways. Additionally, the Ceph storage cluster will have a CRUSH map that has multiple CRUSH hierarchies.

##
# SAS-SSD ROOT DECLARATION
##

root sas-ssd {
  id -1   # do not change unnecessarily
  # weight 0.000
  alg straw
  hash 0  # rjenkins1
  item data2-sas-ssd weight 4.000
  item data1-sas-ssd weight 4.000
  item data0-sas-ssd weight 4.000
}

##
# INDEX ROOT DECLARATION
##

root index {
  id -2    # do not change unnecessarily
  # weight 0.000
  alg straw
  hash 0  # rjenkins1
  item data2-index weight 1.000
  item data1-index weight 1.000
  item data0-index weight 1.000
}

host data2-sas-ssd {
  id -11   # do not change unnecessarily
  # weight 0.000
  alg straw
  hash 0  # rjenkins1
  item osd.0 weight 1.000
  item osd.1 weight 1.000
  item osd.2 weight 1.000
  item osd.3 weight 1.000
}

host data2-index {
  id -21   # do not change unnecessarily
  # weight 0.000
  alg straw
  hash 0  # rjenkins1
  item osd.4 weight 1.000
}

osd_crush_update_on_start = false

[osd.0]
osd crush location = "host=data2-sas-ssd"

[osd.1]
osd crush location = "host=data2-sas-ssd"

[osd.2]
osd crush location = "host=data2-sas-ssd"

[osd.3]
osd crush location = "host=data2-sas-ssd"

[osd.4]
osd crush location = "host=data2-index"

##
# SERVICE RULE DECLARATION
##

rule rgw-service {
 type replicated
 min_size 1
 max_size 10
 step take sas-ssd
 step chooseleaf firstn 0 type rack
 step emit
}

##
# THROUGHPUT RULE DECLARATION
##

rule rgw-throughput {
 type replicated
 min_size 1
 max_size 10
 step take sas-ssd
 step chooseleaf firstn 0 type host
 step emit
}

##
# INDEX RULE DECLARATION
##

rule rgw-index {
 type replicated
 min_size 1
 max_size 10
 step take index
 step chooseleaf firstn 0 type rack
 step emit
}

rule ecpool-86
{
    ...
    step take default class hdd
    step choose indep 4 type host
    step choose indep 4 type osd
    step emit
}

rule ecpool-86
{
    type msr_indep
    ...
    step take default class hdd
    step choosemsr 4 type host
    step choosemsr 4 type osd
    step emit
}

rule ecpool-86
{
    ...
    step take default class hdd
    step choose indep 4 type host
    step choose indep 4 type osd
    step emit
}

rule ecpool-86
{
    type msr_indep
    ...
    step take default class hdd
    step choosemsr 4 type host
    step choosemsr 4 type osd
    step emit
}

A Ceph Object Gateway multi-site configuration requires at least two Red Hat Ceph Storage clusters, and at least two Ceph Object Gateway instances, one for each Red Hat Ceph Storage cluster. Typically, the two Red Hat Ceph Storage clusters will be in geographically separate locations; however, this same multi-site configuration can work on two Red Hat Ceph Storage clusters located at the same physical site.

Multi-site configurations require a primary zone group and a primary zone. Additionally, each zone group requires a primary zone. Zone groups might have one or more secondary zones.

The diagrams below illustrate the possible one, and two realm configurations in multi-site Ceph Object Gateway environments.

Figure 2.4. One Realm

Figure 2.5. Two Realms

Figure 2.6. Two Realms Variant

One of the most important factors in designing a cluster is to determine the storage requirements (sizing). Ceph Storage is designed to scale into petabytes and beyond. The following examples are common sizes for Ceph storage clusters.

Sizing includes current needs and near future needs. Consider the rate at which the gateway client will add new data to the cluster. That can differ from use-case to use-case. For example, recording 4k videos or storing medical images can add significant amounts of data faster than less storage-intensive information, such as financial market data. Additionally, consider that the data durability methods, such as replication versus erasure coding, can have a significant impact on the storage media required.

For additional information on sizing, see the Red Hat Ceph Storage Hardware Guide and its associated links for selecting OSD hardware.

Another important aspect of Ceph’s design, includes storage density. Generally, a storage cluster stores data across at least 10 nodes to ensure reasonable performance when replicating, backfilling, and recovery. If a node fails, with at least 10 nodes in the storage cluster, only 10% of the data has to move to the surviving nodes. If the number of nodes is substantially less, a higher percentage of the data must move to the surviving nodes. Additionally, the full_ratio and near_full_ratio options need to be set to accommodate a node failure to ensure that the storage cluster can write data. For this reason, it is important to consider storage density. Higher storage density is not necessarily a good idea.

Another factor that favors more nodes over higher storage density is erasure coding. When writing an object using erasure coding and using node as the minimum CRUSH failure domain, the Ceph storage cluster will need as many nodes as data and coding chunks. For example, a cluster using k=8, m=3 should have at least 11 nodes so that each data or coding chunk is stored on a separate node.

Hot-swapping is also an important consideration. Most modern servers support drive hot-swapping. However, some hardware configurations require removing more than one drive to replace a drive. Red Hat recommends avoiding such configurations, because they can bring down more Ceph OSDs than required when swapping out failed disks.

Ceph Monitors use rocksdb, which is sensitive to synchronous write latency. Red Hat strongly recommends using SSD disks to store the Ceph Monitor data. Choose SSD disks that have sufficient sequential write and throughput characteristics.

I/O is negatively impacted by both backfilling and recovery operations, leading to poor performance and unhappy end users. To help accommodate I/O demand during a cluster expansion or recovery, set the following options and values in the Ceph Configuration file:

[osd]
osd_max_backfills = 1
osd_recovery_max_active = 1
osd_recovery_op_priority = 1

By default, the ceph-osd daemon caches 500 previous osdmaps. Even with deduplication, the map might consume a lot of memory per daemon. Tuning the cache size in the Ceph configuration might help reduce memory consumption significantly. For example:

[ceph: root@host01 /]# ceph config set global osd_map_message_max 10
[ceph: root@host01 /]# ceph config set osd osd_map_cache_size 20
[ceph: root@host01 /]# ceph config set osd osd_map_share_max_epochs 10
[ceph: root@host01 /]# ceph config set osd osd_pg_epoch_persisted_max_stale 10

For Red Hat Ceph Storage version 3 and later, the ceph-manager daemon handles PG queries, so the cluster map should not impact performance.

By default, Ceph performs light scrubbing daily and deep scrubbing weekly. Light scrubbing checks object sizes and checksums to ensure that PGs are storing the same object data. Over time, disk sectors can go bad irrespective of object sizes and checksums. Deep scrubbing checks an object’s content with that of its replicas to ensure that the actual contents are the same. In this respect, deep scrubbing ensures data integrity in the manner of fsck, but the procedure imposes an I/O penalty on the cluster. Even light scrubbing can impact I/O.

The default settings may allow Ceph OSDs to initiate scrubbing at inopportune times, such as peak operating times or periods with heavy loads. End users may experience latency and poor performance when scrubbing operations conflict with end user operations.

To prevent end users from experiencing poor performance, Ceph provides a number of scrubbing settings that can limit scrubbing to periods with lower loads or during off-peak hours. For details, see the Scrubbing the OSD section in the Red Hat Ceph Storage Configuration Guide.

If the cluster experiences high loads during the day and low loads late at night, consider restricting scrubbing to night time hours. For example:

[osd]
osd_scrub_begin_hour = 23   #23:01H, or 10:01PM.
osd_scrub_end_hour = 6      #06:01H or 6:01AM.

If time constraints aren’t an effective method of determining a scrubbing schedule, consider using the osd_scrub_load_threshold. The default value is 0.5, but it could be modified for low load conditions. For example:

[osd]
osd_scrub_load_threshold = 0.25

To improve scalability, you can edit the value of the objecter_inflight_ops parameter, which specifies the maximum number of unsent I/O requests allowed. This parameter is used for client traffic control.

objecter_inflight_ops = 24576

To improve scalability, you can edit the value of the rgw_thread_pool_size parameter, which is the size of the thread pool. The new beast frontend is not restricted by the thread pool size to accept new connections.

rgw_thread_pool_size = 512

Production Red Hat Ceph Storage clusters generally benefit from tuning the operating system, specifically around limits and memory allocation. Ensure that adjustments are set for all hosts within the storage cluster. You can also open a case with Red Hat support asking for additional guidance.

ceph       soft    nofile     unlimited

USER_NAME       soft    nproc     unlimited

Replace USER_NAME with the name of the non-root user account that runs the Ceph administrative commands.