Production Checklist

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This page provides important recommendations for production deployments of CockroachDB.

Topology

When planning your deployment, it's important to carefully review and choose the topology patterns that best meet your latency and resiliency requirements. This is especially crucial for multi-region deployments.

Also keep in mind some basic topology recommendations:

• Run each node on a separate machine. Since CockroachDB replicates across nodes, running more than one node per machine increases the risk of data loss if a machine fails. Likewise, if a machine has multiple disks or SSDs, run one node with multiple --store flags and not one node per disk. For more details about stores, see Start a Node.

• When starting each node, use the --locality flag to describe the node's location, for example, --locality=region=west,zone=us-west-1. The key-value pairs should be ordered from most to least inclusive, and the keys and order of key-value pairs must be the same on all nodes.

• When deploying in a single availability zone:

  • To be able to tolerate the failure of any 1 node, use at least 3 nodes with the .default 3-way replication factor. In this case, if 1 node fails, each range retains 2 of its 3 replicas, a majority.
  • To be able to tolerate 2 simultaneous node failures, use at least 5 nodes and increase the .default replication factor for user data to 5. The replication factor for important internal data is 5 by default, so no adjustments are needed for internal data. In this case, if 2 nodes fail at the same time, each range retains 3 of its 5 replicas, a majority.

• When deploying across multiple availability zones:

  • To be able to tolerate the failure of 1 entire AZ in a region, use at least 3 AZs per region and set --locality on each node to spread data evenly across regions and AZs. In this case, if 1 AZ goes offline, the 2 remaining AZs retain a majority of replicas.
  • To be able to tolerate the failure of 1 entire region, use at least 3 regions.

Hardware

Basic hardware recommendations

Nodes should have sufficient CPU, RAM, network, and storage capacity to handle your workload. It's important to test and tune your hardware setup before deploying to production.

CPU and memory

• At a bare minimum, each node should have 2 vCPUs and 2 GB of RAM. More data, complex workloads, higher concurrency, and faster performance require additional resources.

  Warning:

  Avoid "burstable" or "shared-core" virtual machines that limit the load on CPU resources.

• To optimize for throughput, use larger nodes, up to 32 vCPUs. Based on internal testing results, 32 vCPUs is the sweet spot for OLTP workloads. For RAM, aim for a ratio of 2 GB per vCPU.

  To increase throughput further, add more nodes to the cluster instead of increasing node size.

• To optimize for resiliency, use many smaller nodes (e.g., 4 vCPUs per node) instead of fewer larger ones. Recovery from a failed node is faster when data is spread across more nodes.

• In all cases, make sure nodes are uniform to ensure consistent SQL performance.

Storage

• The recommended Linux filesystem is ext4.

• Avoid using shared storage such as NFS, CIFS, and CEPH storage.

• For the best performance results, use SSD or NVMe devices. The recommended volume size is 300-500 GB.

  Monitor IOPS for higher service times. If they exceed 1-5 ms, you will need to add more devices or expand the cluster to reduce the disk latency. To monitor IOPS, use tools such as iostat (part of sysstat).

• To calculate IOPS, use sysbench. If IOPS decrease, add more nodes to your cluster to increase IOPS.

• Place a ballast file in each node's storage directory. In the unlikely case that a node runs out of disk space and shuts down, you can delete the ballast file to free up enough space to be able to restart the node.

• Use zone configs to increase the replication factor from 3 (the default) to 5 (across at least 5 nodes).

  This is especially recommended if you are using local disks with no RAID protection rather than a cloud provider's network-attached disks that are often replicated under the hood, because local disks have a greater risk of failure. You can do this for the entire cluster or for specific databases, tables, or rows (enterprise-only).

• The optimal configuration for striping more than one device is RAID 10. RAID 0 and 1 are also acceptable from a performance perspective.

Cloud-specific recommendations

Cockroach Labs recommends the following cloud-specific configurations based on our own internal testing. Before using configurations not recommended here, be sure to test them exhaustively.

AWS

• Use m (general purpose) or c (compute-optimized) instances.

  For example, Cockroach Labs has used c5d.4xlarge (16 vCPUs and 32 GiB of RAM per instance, EBS) for internal testing. Note that the instance type depends on whether EBS is used or not. If you're using EBS, use a c5 instance.

  Warning:

  Do not use "burstable" t instances, which limit the load on CPU resources.

• Use c5 instances with EBS as a primary AWS configuration. To simulate bare-metal deployments, use c5d with SSD Instance Store volumes.

  Provisioned IOPS SSD-backed (io1) EBS volumes need to have IOPS provisioned, which can be very expensive. Cheaper gp2 volumes can be used instead, if your performance needs are less demanding. Allocating more disk space than you will use can improve performance of gp2 volumes.

Azure

• Use compute-optimized F-series VMs. For example, Cockroach Labs has used Standard_F16s_v2 VMs (16 vCPUs and 32 GiB of RAM per VM) for internal testing.

  Warning:

  Do not use "burstable" B-series VMs, which limit the load on CPU resources. Also, Cockroach Labs has experienced data corruption issues on A-series VMs and irregular disk performance on D-series VMs, so we recommend avoiding those as well.

• Use Premium Storage or local SSD storage with a Linux filesystem such as ext4 (not the Windows ntfs filesystem). Note that the size of a Premium Storage disk affects its IOPS.

• If you choose local SSD storage, on reboot, the VM can come back with the ntfs filesystem. Be sure your automation monitors for this and reformats the disk to the Linux filesystem you chose initially.

Digital Ocean

• Use any droplets except standard droplets with only 1 GB of RAM, which is below our minimum requirement. All Digital Ocean droplets use SSD storage.

GCP

• Use n1-standard or n1-highcpu predefined VMs, or custom VMs.

  For example, Cockroach Labs has used n1-standard-16 (16 vCPUs and 60 GB of RAM per VM, local SSD) for performance benchmarking. We have also found benefits in using the Skylake platform.

  Warning:

  Do not use f1 or g1 shared-core machines, which limit the load on CPU resources.

• Use Local SSDs or SSD persistent disks. Note that the IOPS of SSD persistent disks depends both on the disk size and number of vCPUs on the machine.

• nobarrier can be used with SSDs, but only if it has battery-backed write cache. Without one, data can be corrupted in the event of a crash.

  Cockroach Labs conducts most of our internal performance tests using nobarrier to demonstrate the best possible performance, but understand that not all use cases can support this option.

Security

An insecure cluster comes with serious risks:

• Your cluster is open to any client that can access any node's IP addresses.
• Any user, even root, can log in without providing a password.
• Any user, connecting as root, can read or write any data in your cluster.
• There is no network encryption or authentication, and thus no confidentiality.

Therefore, to deploy CockroachDB in production, it is strongly recommended to use TLS certificates to authenticate the identity of nodes and clients and to encrypt in-flight data between nodes and clients. You can use either the built-in cockroach cert commands or openssl commands to generate security certificates for your deployment. Regardless of which option you choose, you'll need the following files:

• A certificate authority (CA) certificate and key, used to sign all of the other certificates.
• A separate certificate and key for each node in your deployment, with the common name node.

• A separate certificate and key for each client and user you want to connect to your nodes, with the common name set to the username. The default user is root.

  Alternatively, CockroachDB supports password authentication, although we typically recommend using client certificates instead.

For more information, see the Security Overview.

Networking

Networking flags

When starting a node, two main flags are used to control its network connections:

• --listen-addr determines which address(es) to listen on for connections from other nodes and clients.
• --advertise-addr determines which address to tell other nodes to use.

The effect depends on how these two flags are used in combination:

Cluster on a single network

When running a cluster on a single network, the setup depends on whether the network is private. In a private network, machines have addresses restricted to the network, not accessible to the public internet. Using these addresses is more secure and usually provides lower latency than public addresses.

Cluster spanning multiple networks

When running a cluster across multiple networks, the setup depends on whether nodes can reach each other across the networks.

Load balancing

Each CockroachDB node is an equally suitable SQL gateway to a cluster, but to ensure client performance and reliability, it's important to use load balancing:

• Performance: Load balancers spread client traffic across nodes. This prevents any one node from being overwhelmed by requests and improves overall cluster performance (queries per second).

• Reliability: Load balancers decouple client health from the health of a single CockroachDB node. To ensure that traffic is not directed to failed nodes or nodes that are not ready to receive requests, load balancers should use CockroachDB's readiness health check.

  Tip:

  With a single load balancer, client connections are resilient to node failure, but the load balancer itself is a point of failure. It's therefore best to make load balancing resilient as well by using multiple load balancing instances, with a mechanism like floating IPs or DNS to select load balancers for clients.

For guidance on load balancing, see the tutorial for your deployment environment:

Connection pooling

Multiple active connections to the database enable efficient use of the available database resources. However, creating new authenticated connections to the database is CPU and memory-intensive and also adds to the latency since the application has to wait for database to authenticate the connection.

Connection pooling helps resolve this dilemma by creating a set of authenticated connections that can be reused to connect to the database. To determine the size of the maximum connection pool, our recommendation is to start your testing with a pool size of (core_count * 2) + ssd_count), where core_count is the total number of cores in the cluster, and ssd_count is the total number of SSDs in the cluster. The optimal pool size will vary based on your workload and application, and may be smaller than that.

In addition to setting a maximum connection pool size, the idle connection pool size must also be set. Our recommendation is to set the idle connection pool size equal to the maximum pool size. While this uses more application server memory, this allows there to be many connections when concurrency is high, without having to dial a new connection for every new operation.

Monitoring and alerting

Despite CockroachDB's various built-in safeguards against failure, it is critical to actively monitor the overall health and performance of a cluster running in production and to create alerting rules that promptly send notifications when there are events that require investigation or intervention.

For details about available monitoring options and the most important events and metrics to alert on, see Monitoring and Alerting.

Clock synchronization

CockroachDB requires moderate levels of clock synchronization to preserve data consistency. For this reason, when a node detects that its clock is out of sync with at least half of the other nodes in the cluster by 80% of the maximum offset allowed (500ms by default), it spontaneously shuts down. While serializable consistency is maintained regardless of clock skew, skew outside the configured clock offset bounds can result in violations of single-key linearizability between causally dependent transactions. It's therefore important to prevent clocks from drifting too far by running NTP or other clock synchronization software on each node.

The one rare case to note is when a node's clock suddenly jumps beyond the maximum offset before the node detects it. Although extremely unlikely, this could occur, for example, when running CockroachDB inside a VM and the VM hypervisor decides to migrate the VM to different hardware with a different time. In this case, there can be a small window of time between when the node's clock becomes unsynchronized and when the node spontaneously shuts down. During this window, it would be possible for a client to read stale data and write data derived from stale reads. To protect against this, we recommend using the server.clock.forward_jump_check_enabled and server.clock.persist_upper_bound_interval cluster settings.

Considerations

When setting up clock synchronization:

• All nodes in the cluster must be synced to the same time source, or to different sources that implement leap second smearing in the same way. For example, Google and Amazon have time sources that are compatible with each other (they implement leap second smearing in the same way), but are incompatible with the default NTP pool (which does not implement leap second smearing).
• For nodes running in AWS, we recommend Amazon Time Sync Service. For nodes running in GCP, we recommend Google's internal NTP service. For nodes running elsewhere, we recommend Google Public NTP. Note that the Google and Amazon time services can be mixed with each other, but they cannot be mixed with other time services (unless you have verified leap second behavior). Either all of your nodes should use the Google and Amazon services, or none of them should.
• If you do not want to use the Google or Amazon time sources, you can use chrony and enable client-side leap smearing, unless the time source you're using already does server-side smearing. In most cases, we recommend the Google Public NTP time source because it handles smearing the leap second. If you use a different NTP time source that doesn't smear the leap second, you must configure client-side smearing manually and do so in the same way on each machine.
• Do not run more than one clock sync service on VMs where cockroach is running.

Tutorials

For guidance on synchronizing clocks, see the tutorial for your deployment environment:

Cache and SQL memory size

By default, each node's cache size and temporary SQL memory size is 128MiB respectively. These defaults were chosen to facilitate development and testing, where users are likely to run multiple CockroachDB nodes on a single computer. When running a production cluster with one node per host, however, it's recommended to increase these values:

• Increasing a node's cache size will improve the node's read performance.
• Increasing a node's SQL memory size will increase the number of simultaneous client connections it allows (the 128MiB default allows a maximum of 6200 simultaneous connections) as well as the node's capacity for in-memory processing of rows when using ORDER BY, GROUP BY, DISTINCT, joins, and window functions.

To manually increase a node's cache size and SQL memory size, start the node using the --cache and --max-sql-memory flags:

$ cockroach start --cache=.25 --max-sql-memory=.25 <other start flags>

Dependencies

The CockroachDB binary for Linux depends on the following libraries:

These libraries are found by default on nearly all Linux distributions, with Alpine as the notable exception, but it's nevertheless important to confirm that they are installed and kept up-to-date. For the time zone data in particular, it's important for all nodes to have the same version; when updating the library, do so as quickly as possible across all nodes.

File descriptors limit

CockroachDB can use a large number of open file descriptors, often more than is available by default. Therefore, please note the following recommendations.

For each CockroachDB node:

• At a minimum, the file descriptors limit must be 1956 (1700 per store plus 256 for networking). If the limit is below this threshold, the node will not start.
• It is recommended to set the file descriptors limit to unlimited; otherwise, the recommended limit is at least 15000 (10000 per store plus 5000 for networking). This higher limit ensures performance and accommodates cluster growth.
• When the file descriptors limit is not high enough to allocate the recommended amounts, CockroachDB allocates 10000 per store and the rest for networking; if this would result in networking getting less than 256, CockroachDB instead allocates 256 for networking and evenly splits the rest across stores.

Increase the file descriptors limit

Attributions

This section, "File Descriptors Limit", is in part derivative of the chapter Open File Limits From the Riak LV 2.1.4 documentation, used under Creative Commons Attribution 3.0 Unported License.

Orchestration / Kubernetes

When running CockroachDB on Kubernetes, making the following minimal customizations will result in better, more reliable performance:

• Use SSDs instead of traditional HDDs.
• Configure CPU and memory resource requests and limits.

For more information and additional customization suggestions, see our full detailed guide to CockroachDB Performance on Kubernetes.

Transaction Retries

When several transactions are trying to modify the same underlying data concurrently, they may experience contention that leads to transaction retries. In order to avoid failures in production, your application should be engineered to handle transaction retries using client-side retry handling.

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