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  • YUGABYTEDB CORE
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  • REFERENCE
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> Deploy >

Deployment checklist

Report a doc issue Suggest new content
  • Overview
  • Basics
  • Replication
  • Hardware requirements
    • CPU and RAM
    • Verify support for SSE2
    • Disks
    • Network
    • Default ports reference
  • Clock synchronization
    • Clock skew
    • Clock drift
  • Security checklist
  • Running on public clouds
    • Amazon Web Services (AWS)
    • Google Cloud

Overview

A YugabyteDB cluster consists of two distributed services - the YB-TServer service and the YB-Master service. Since the YB-Master service serves the role of the cluster metadata manager, it should be brought up first followed by the YB-TServer service. In order to bring up these distributed services, the respective servers (YB-Master or YB-TServer) need to be started across different nodes. Below are some considerations and recommendations on starting these services. The deployment configurations section below has detailed steps on how to setup YugabyteDB clusters.

Basics

  • YugabyteDB works on a variety of operating systems. For production workloads, the recommended operating systems are CentOS 7.x and RHEL 7.x.
  • Set the appropriate system limits using ulimit on each node running a YugabyteDB server.
  • Use ntp or chrony to synchronize time among the machines.

Replication

YugabyteDB internally replicates data in a strongly consistent manner using Raft consensus protocol in order to survive node failure without compromising data correctness. The number of copies of the data represents the replication factor. Note that this distributed consensus replication is applied at a per-shard (aka tablet) level similar to Google Spanner.

You would first need to choose a Replication Factor (RF). You would need at least as many machines as the RF, which means 1 machine for RF1, 3 machines for RF3 and so on. Below are some recommendations relating to the RF.

  • The RF should be an odd number to ensure majority consensus can be established during failures.
  • The default replication factor is 3.
    • RF of 3 allows tolerating 1 machine failure.
    • RF of 5 allows tolerating 2 machine failures.
    • More generally, if RF is n, YugabyteDB can survive (n - 1) / 2 failures without compromising correctness or availability of data.
  • Number of YB-Master servers running in a cluster should match RF. Run each server on a separate machine to prevent losing availability on failures. You have to also specify the RF using the --replication_factor when bringing up the YB-Master servers.
  • Number of YB-TServer servers running in the cluster should not be less than the replication factor. Run each server on a separate machine to prevent losing availability on failures.

Note that YugabyteDB works with both hostnames or IP addresses. IP addresses are preferred at this point as they are more extensively tested.

See the yb-master command reference for more information.

Hardware requirements

YugabyteDB is designed to run well on bare-metal machines, virtual machines (VMs), and containers.

CPU and RAM

You should allocate adequate CPU and RAM. YugabyteDB has good defaults for running on a wide range of machines, and has been tested from 2 core to 64 core machines, and up to 200GB RAM.

Minimum requirement

  • 2 cores
  • 2GB RAM

Production requirement

  • 16+ cores
  • 32GB+ RAM
  • Add more CPU (compared to adding more RAM) to improve performance.

Additional considerations

For typical OLTP workloads, YugabyteDB performance improves with more aggregate CPU in the cluster. You can achieve this by using larger nodes or adding more nodes to a cluster. Note that if you do not have enough CPUs, this will show up as higher latencies and eventually dropped requests.

Memory depends on your application query pattern. Writes require memory but only up to a certain point (say 4GB, but if you have a write-heavy workload you may need a little more). Beyond that, more memory generally helps improve the read throughput and latencies by caching data in the internal cache. If you do not have enough memory to fit the read working set, then you will typically experience higher read latencies because data has to be read from disk. Having a faster disk could help in some of these cases.

YugabyteDB explicitly manages a block cache, and doesn't need the entire data set to fit in memory. It does not rely on OS to keep data in its buffers. If you give YugabyteDB sufficient memory data accessed and present in block cache will stay in memory.

Verify support for SSE2

YugabyteDB requires SSE2 instruction set support, which was introduced into Intel chips with the Pentium 4 in 2001 and AMD processors in 2003. Most systems produced in the last several years are equipped with SSE2. YugabyteDB requires this instruction set.

To verify that your system supports SSE2, run the following command:

$ cat /proc/cpuinfo | grep sse2

Disks

  • SSDs (solid state disks) are required.
  • Both local or remote attached storage work with YugabyteDB. Since YugabyteDB internally replicates data for fault tolerance, remote attached storage which does its own additional replication is not a requirement. Local disks often offer better performance at a lower cost.
  • Multi-disk nodes - Do not use RAID across multiple disks. YugabyteDB can natively handle multi-disk nodes (JBOD). - Create a data directory on each of the data disks and specify a comma separated list of those directories to the yb-master and yb-tserver servers via the --fs_data_dirs flag.
  • Mount settings - XFS is the recommended filesystem. - Use the noatime setting when mounting the data drives. - ZFS isn't currently supported and is in the roadmap. - NFS isn't currently supported and is in the roadmap.

YugabyteDB does not require any form of RAID, but runs optimally on a JBOD (just a bunch of disks) setup. It can also leverage multiple disks per node and has been tested beyond 10 TB of storage per node.

Write-heavy applications usually require more disk IOPS (especially if the size of each record is larger), therefore in this case the total IOPS that a disk can support matters. On the read side, if the data does not fit into the cache and data needs to be read from the disk in order to satisfy queries, the disk performance (latency and IOPS) will start to matter.

YugabyteDB uses per-tablet size tiered compaction. Therefore the typical space amplification in YugabyteDB tends to be in the 10-20% range.

Network

Below is a minimal list of default ports (along with the network access required) in order to use YugabyteDB.

  • Each of the nodes in the YugabyteDB cluster must be able to communicate with each other using TCP/IP on the following ports.

    7100 for YB-Master RPC communication
    
    9100 for YB-TServer RPC communication
    
  • In order to view the cluster dashboard, you need to be able to navigate to the following ports on the nodes.

    7000 for viewing the YB-Master Admin UI
    
  • To use the database from the app, the following ports need to be accessible from the app (or CLIs).

    5433 for YSQL
    9042 for YCQL
    6379 for YEDIS
    

Default ports reference

The above deployment uses the various default ports listed here.

Note

For Yugabyte Platform, the SSH port is changed for added security.

Clock synchronization

For YugabyteDB to preserve data consistency, the clock drift and clock skew across different nodes must be bounded. This can be achieved by running clock synchronization software, such as NTP or chrony. Below are some recommendations on how to configure clock synchronization.

Clock skew

Set a safe value for the maximum clock skew flag (--max_clock_skew_usec) for YB-TServers and YB-Masters when starting the YugabyteDB servers. The recommended value is two times the expected maximum clock skew between any two nodes in your deployment.

For example, if the maximum clock skew across nodes is expected to be no more than 250 microseconds, then set the parameter to 500 microseconds (--max_clock_skew_usec=500000).

Clock drift

The maximum clock drift on any node should be bounded to no more than 500 PPM (or parts per million). This means that the clock on any node should drift by no more than 0.5 ms per second. Note that 0.5 ms per second is the standard assumption of clock drift in Linux.

Note

In practice, the clock drift would have to be orders of magnitude higher in order to cause correctness issues.

Security checklist

For a list of best practices, see security checklist.

Running on public clouds

Amazon Web Services (AWS)

  • Use the c5 or i3 instance families.
  • Recommended types are i3.2xlarge, i3.4xlarge, c5.2xlarge, c5.4xlarge
  • For the c5 instance family, use gp2 EBS (SSD) disks that are at least 250GB in size, larger if more IOPS are needed. - The number of IOPS are proportional to the size of the disk. - In our testing, gp2 EBS SSDs provide the best performance for a given cost among the various EBS disk options.
  • Avoid running on t2 instance types. The t2 instance types are burstable instance types. Their baseline performance and ability to burst are governed by CPU Credits, and makes it hard to get steady performance.

Google Cloud

  • Use the n1-highcpu instance family. As a second choice, n1-standard instance family works too.
  • Recommended instance types are n1-highcpu-8 and n1-highcpu-16.
  • Local SSDs are the preferred storage option. - Each local SSD is 375 GB in size, but you can attach up to eight local SSD devices for 3 TB of total local SSD storage space per instance.
  • As a second choice, remote persistent SSDs work well. Make sure the size of these SSDs are at least 250GB in size, larger if more IOPS are needed. - The number of IOPS are proportional to the size of the disk.
  • Avoid running on f1 or g1 machine families. These are burstable, shared core machines that may not deliver steady performance.
  • Overview
  • Basics
  • Replication
  • Hardware requirements
    • CPU and RAM
    • Verify support for SSE2
    • Disks
    • Network
    • Default ports reference
  • Clock synchronization
    • Clock skew
    • Clock drift
  • Security checklist
  • Running on public clouds
    • Amazon Web Services (AWS)
    • Google Cloud
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