Scylla runs on 64-bit Linux. The following operating system releases are supported:
|CentOS/RHEL||7.2 and above|
|Ubuntu||14.04 *, 16.04|
|Debian||8.6 and above (minor releases)|
* Supported in Scylla 3.0 and below. Not supported in Scylla 3.1 and 2019.1 and above
** Supported in Scylla 2.3 and above
Ubuntu 14 is not supported in future versions of Scylla Open Source 3.1 and Scylla Eneterprise 2019.1 and above. This is because Ubuntu has decided to EOL version 14. For more details refer to Ubuntu Release page.
For a more detailed list with recommendations refer to Operating System (OS) Support Guide.
Scylla requires a fix to the XFS append introduced in kernel 3.15 (back-ported to 3.10 in RHEL/CentOS). Scylla will not run with earlier kernel versions. Details in Scylla issue 885.
It’s recommended to have a balanced setup. If there are only 4-8 lcores, large disks or 10Gbps networking may not needed. This works in the opposite direction as well. Scylla can be used in many types of installation environments. Each one has its own recommended hardware requirements. The three use cases most often used with their requirements include:
|Test, minimal||4||2 GB||Single plain SSD||1 Gbps|
|Production||20 cores - 2 socket, 10 cores each||128 GB||RAID-0, 4 SSDs, 1-5 TBs||10 Gbps|
|Analytics, heavy duty||28 cores - 2 socket, 14 cores each||256 GB - 1 TB||NVMe, 10 TB||10-56 Gbps|
Scylla tries to maximize the resource usage of all system components. The shard-per-core approach allows linear scale-up with the number of cores. As you have more cores, it makes sense to balance the other resources, from memory to network.
Scylla requires modern Intel CPUs that support the SSE4.2 instruction set and will not boot without it.
In terms of the number of cores, any number will work since Scylla scales up with the number of cores. A practical approach is to use a large number of cores as long as the hardware price remains reasonable. Between 20-60 logical cores (including hyperthreading) is a recommended number. However any number will fit. When using virtual machines, containers, or the public cloud, remember that each virtual CPU is mapped to a single logical core, or hyperthread. Allow Scylla to run independently without any additional CPU intensive tasks on the same server/cores as Scylla.
The more memory available, the better Scylla performs, as Scylla uses all of available memory for caching. The wider the rows are in the schema, the more memory will be required. 64 GB-256 GB is the recommended range for a medium to high workload. Memory requirements are calculated based on the number of logical cores you are using in your system. A logical core (lcore) is a hyperthreaded core on a hyperthreaded system, or a physical core on a system without hyperthreading.
- Recommended size: 16 GB or 2GB per lcore (whichever is higher)
- Maximum: 1 TiB per lcore, up to 256 lcores
- For test environments: 1 GB or 256 MiB per lcore (whichever is higher)
- For production environments: 4 GB or 0.5 GB per lcore (whichever is higher)
We highly recommend SSD and local disks. Scylla is built for a large volume of data and large storage per node. The rule of thumb is using 30:1 Disk/RAM ratio, for example, 30 TB of storage requires 1 TB of RAM. When there are multiple drives, we recommend a RAID-0 setup and a replication factor of 3 within the local datacenter (RF=3).
HDDs are supported but may become a bottleneck. Some workloads may work with HDDs, especially if they play nice and minimize random seeks. An example of an HDD-friendly workload is a write-mostly (98% writes) workload, with minimal random reads. If you use HDDs, try to allocate a separate disk for the commit log (not needed with SSDs).
We highly recommend EC2 I3 instances—High I/O. This family includes the High Storage Instances that provide very fast SSD-backed instance storage optimized for very high random I/O performance, and provide high IOPS at a low cost. We recommend on using enhanced networking that exposes the physical network cards to the VM.
i3 instances are designed for I/O intensive workloads and equipped with super-efficient NVMe SSD storage, it can deliver up to 3.3 Million IOPS. An i3 instance is great for low latency and high throughput, comapred to the i2 instances, the i3 instance provides storage that it’s less expensive and denser along with the ability to deliver substantially more IOPS and more network bandwidth per CPU core.
|Model||vCPU||Mem (GB)||Storage (NVMe SSD)|
|i3.metal New in version 2.3||72 *||512||8 x 1.9 NVMe SSD|
* i3.metal provides 72 logical processors on 36 physical cores
Source: EC2 Instance Types
More on using Scylla with i3.metal vs i3.16xlarge
Pick a zone where Haswell CPUs are found. Local SSD performance offers, according to Google, less than 1 ms of latency and up to 680,000 read IOPS and 360,000 write IOPS. The CentOS 7.x image with NVMe disk interface is recommended. (More info)
|Model||vCPU||Mem (GB)||Storage (GB)|
|n1-standard-8||8||30||eight 375 GB partitions for 3 TB|
|n1-standard-16||16||60||eight 375 GB partitions for 3 TB|
|n1-standard-32||32||120||eight 375 GB partitions for 3 TB|
|n1-himem-16||16||104||eight 375 GB partitions for 3 TB|
|n1-himem-32||32||208||eight 375 GB partitions for 3 TB|