Troubleshoot Self-Hosted Setup

If you’re having trouble starting or scaling your cluster, this page will help you troubleshoot the issue. To use this guide, it’s important to understand some of CockroachDB’s terminology:

A cluster acts as a single logical database, but is actually made up of many cooperating nodes.
Nodes are single instances of the cockroach binary running on a machine. It’s possible (though atypical) to have multiple nodes running on a single machine.

Cannot run a single-node CockroachDB cluster

Try running:

$ cockroach start-single-node --insecure

If the process exits prematurely, check for the following:

An existing storage directory

When starting a node, the directory you choose to store the data in also contains metadata identifying the cluster the data came from. This causes conflicts when you’ve already started a node on the server, have quit cockroach, and then tried to start another cluster using the same directory. Because the existing directory’s cluster ID doesn’t match the new cluster ID, the node cannot start. Solution: Disassociate the node from the existing directory where you’ve stored CockroachDB data. For example, you can do either of the following:

Choose a different directory to store the CockroachDB data:

$ cockroach start-single-node --store=<new directory --insecure

Remove the existing directory and start the node again:

$ rm -r cockroach-data/

$ cockroach start-single-node --insecure

Toolchain incompatibility

The components of the toolchain might have some incompatibilities that need to be resolved. For example, a few months ago, there was an incompatibility between Xcode 8.3 and Go 1.8 that caused any Go binaries created with that toolchain combination to crash immediately.

Incompatible CPU

If the cockroach process had exit status 132 (SIGILL), it attempted to use an instruction that is not supported by your CPU. Non-release builds of CockroachDB may not be able to run on older hardware platforms than the one used to build them. Release builds should run on any x86-64 CPU.

Default ports already in use

Other services may be running on port 26257 or 8080 (CockroachDB’s default --listen-addr port and --http-addr port respectively). You can either stop those services or start your node with different ports, specified in the . If you change the port, you will need to include the --port=<specified port flag in each subsequent cockroach command or change the COCKROACH_PORT environment variable.

Single-node networking issues

Networking issues might prevent the node from communicating with itself on its hostname. You can control the hostname CockroachDB uses with the . If you change the host, you will need to include --host=<specified host in each subsequent cockroach command.

CockroachDB process hangs when trying to start a node in the background

See

Cannot run SQL statements using built-in SQL client

If the CockroachDB node appeared to , in a separate terminal run:

$ cockroach sql --insecure -e "show databases"

You should see a list of the built-in databases:

  database_name
+---------------+
  defaultdb
  postgres
  system
(3 rows)

If you’re not seeing the output above, check for the following:

connection refused error, which indicates you have not included some flag that you used to start the node. We have additional troubleshooting steps for this error .
The node crashed. To ascertain if the node crashed, run ps | grep cockroach to look for the cockroach process. If you cannot locate the cockroach process (i.e., it crashed), , including the and any errors you received.

Cannot run a multi-node CockroachDB cluster on the same machine

Running multiple nodes on a single host is useful for testing CockroachDB, but it’s not recommended for production deployments. To run a physically distributed cluster in production, see or . Also be sure to review the .

If you are trying to run all nodes on the same machine, you might get the following errors:

Store directory already exists

ERROR: could not cleanup temporary directories from record file: could not lock temporary directory /cockroach-data/cockroach-temp301343769, may still be in use: IO error: While lock file: /cockroach-data/cockroach-temp301343769/TEMP_DIR.LOCK: Resource temporarily unavailable

Explanation: When starting a new node on the same machine, the directory you choose to store the data in also contains metadata identifying the cluster the data came from. This causes conflicts when you’ve already started a node on the server and then tried to start another cluster using the same directory. Solution: Choose a different directory to store the CockroachDB data.

Port already in use

ERROR: cockroach server exited with error: consider changing the port via --listen-addr: listen tcp 127.0.0.1:26257: bind: address already in use

Solution: Change the --port, --http-port flags for each new node that you want to run on the same machine.

Scaling issues

Cannot join a node to an existing CockroachDB cluster

Store directory already exists

When joining a node to a cluster, you might receive one of the following errors:

no resolvers found; use --join to specify a connected node

node belongs to cluster {"cluster hash"} but is attempting to connect to a gossip network for cluster {"another cluster hash"}

Explanation: When starting a node, the directory you choose to store the data in also contains metadata identifying the cluster the data came from. This causes conflicts when you’ve already started a node on the server, have quit the cockroach process, and then tried to join another cluster. Because the existing directory’s cluster ID doesn’t match the new cluster ID, the node cannot join it. Solution: Disassociate the node from the existing directory where you’ve stored CockroachDB data. For example, you can do either of the following:

Choose a different directory to store the CockroachDB data:

$ cockroach start --store=<new directory --join=<cluster host <other flags>

Remove the existing directory and start a node joining the cluster again:

$ rm -r cockroach-data/

$ cockroach start --join=<cluster host:26257 <other flags>

Incorrect `--join` address

If you try to add another node to the cluster, but the --join address is not pointing at any of the existing nodes, then the process will never complete, and you’ll see a continuous stream of warnings like this:

W180817 17:01:56.506968 886 vendor/google.golang.org/grpc/clientconn.go:942 Failed to dial localhost:20000: grpc: the connection is closing; please retry.
W180817 17:01:56.510430 914 vendor/google.golang.org/grpc/clientconn.go:1293 grpc: addrConn.createTransport failed to connect to {localhost:20000 0 <nil>}. Err :connection error: desc = "transport: Error while dialing dial tcp [::1]:20000: connect: connection refused". Reconnecting…

Explanation: These warnings tell you that the node cannot establish a connection with the address specified in the --join flag. Without a connection to the cluster, the node cannot join. Solution: To successfully join the node to the cluster, start the node again, but this time include a correct --join address.

Performance is degraded when adding nodes

Excessive snapshot rebalance and recovery rates

The kv.snapshot_rebalance.max_rate sets the rate limit at which are sent to nodes. This setting can be temporarily increased to expedite replication during an outage or when scaling a cluster up or down. However, if the setting is too high when nodes are added to the cluster, this can cause degraded performance and node crashes. We recommend not increasing this value by more than 2 times its without explicit approval from Cockroach Labs. Explanation: If kv.snapshot_rebalance.max_rate is set too high for the cluster during scaling, this can cause nodes to experience ingestions faster than can keep up, and result in an . Solution: . If compaction has fallen behind and caused an , throttle your workload concurrency to allow to catch up and restore a healthy LSM shape. The number of active connections across all connection pools should not exceed 4 times the number of vCPUs in the cluster by a large amount. A connection is “active” when it is actively executing a query. To monitor active connections, use the . If a node is severely impacted, you can and then decommission the problematic node. By default, the uses a compaction concurrency of 3. If you have sufficient IOPS and CPU headroom, you can consider increasing this setting via the COCKROACH_COMPACTION_CONCURRENCY environment variable. This may help to reshape the LSM more quickly in scenarios; and it can lead to increased overall performance for some workloads. Cockroach Labs strongly recommends testing your workload against non-default values of this setting. After has completed, lower kv.snapshot_rebalance.max_rate to its . As you add nodes to the cluster, slowly increase the value of the cluster setting, if desired. This will control the rate of new ingestions for newly added nodes. Meanwhile, monitor the cluster for unhealthy increases in and . Outside of performing cluster maintenance, return kv.snapshot_rebalance.max_rate to its .

RESET CLUSTER SETTING kv.snapshot_rebalance.max_rate;

Client connection issues

If a client cannot connect to the cluster, check basic network connectivity (ping), port connectivity (telnet), and certificate validity.

Networking issues

Most networking-related issues are caused by one of two issues:

Firewall rules, which require your network administrator to investigate
Inaccessible hostnames on your nodes, which can be controlled with the --listen-addr and --advertise-addr flags on

Solution: To check your networking setup:

Use ping. Every machine you are using as a CockroachDB node should be able to ping every other machine, using the hostnames or IP addresses used in the --join flags (and the --advertise-host flag if you are using it).
If the machines are all pingable, check if you can connect to the appropriate ports. With your CockroachDB nodes still running, log in to each node and use telnet or nc to verify machine to machine connectivity on the desired port. For instance, if you are running CockroachDB on the default port of 26257, run either:

telnet <other-machine> 26257
nc <other-machine> 26257

Both telnet and nc will exit immediately if a connection cannot be established. If you are running in a firewalled environment, the firewall might be blocking traffic to the desired ports even though it is letting ping packets through. To efficiently troubleshoot the issue, it’s important to understand where and why it’s occurring. We recommend checking the following network-related issues:

By default, CockroachDB advertises itself to other nodes using its hostname. If your environment doesn’t support DNS or the hostname is not resolvable, your nodes cannot connect to one another. In these cases, you can:
Change the hostname each node uses to advertises itself with --advertise-addr
Set --listen-addr=<node's IP address if the IP is a valid interface on the machine
Every node in the cluster should be able to ping each other node on the hostnames or IP addresses you use in the --join, --listen-addr, or --advertise-addr flags.
Every node should be able to connect to other nodes on the port you’re using for CockroachDB (26257 by default) through telnet or nc:
telnet <other node host> 26257
nc <other node host> 26257

Again, firewalls or hostname issues can cause any of these steps to fail.

Network partition

If the DB Console

lists any suspect or dead nodes on the or
indicates any suspect nodes on the ,

then you might have a network partition. Explanation: A network partition occurs when two or more nodes are prevented from communicating with each other in one or both directions. A network partition can be caused by a network outage or a configuration problem with the network, such as when allowlisted IP addresses or hostnames change after a node is . In a symmetric partition, node communication is disrupted in both directions. In an asymmetric partition, nodes can communicate in one direction but not the other. CockroachDB protects against asymmetric partitions by converting all asymmetric (uni-directional) network partitions into symmetric (bi-directional) network partitions. This increases cluster resiliency by reducing the number of partition-related failures that can occur. Many temporary symmetric partitions can be recovered from automatically without operator intervention. The effect of a network partition depends on which nodes are partitioned, where the ranges are located, and to a large extent, whether or are defined. A partition that cuts off at least (n-1)/2 replicas from a will cause range unavailability which will cause some data unavailability. If there are no localities or other constraints on where replicas are placed, then a partition of any ( / 2) nodes will likely cause unavailability. With the introduction of , most network partitions between a leaseholder and its followers should heal in a few seconds. Solution: To identify a network partition:

In the DB Console, access the .
In the network matrix, check for nodes with . This indicates that a node cannot communicate with another node, and might indicate a network partition.
Hover over a cell in the matrix to see the connection status and the error message that resulted from the most recent connection attempt.

Authentication issues

Missing certificate

If you try to add a node to a secure cluster without providing the node’s security certificate, you will get the following error:

problem with CA certificate: not found
*
* ERROR: cannot load certificates.
* Check your certificate settings, set --certs-dir, or use --insecure for insecure clusters.
*
* problem with CA certificate: not found
*
Failed running "start"

Explanation: The error tells you that because the cluster is secure, it requires the new node to provide its security certificate in order to join. Solution: To successfully join the node to the cluster, start the node again, but this time include the --certs-dir flag

Certification expiration

If you’re running a secure cluster, be sure to monitor your certificate expiration. If one of the inter-node certificates expires, nodes will no longer be able to communicate which can look like a network partition. To check the certificate expiration date:

.
Click the gear icon on the left-hand navigation bar to access the Advanced Debugging page.
Scroll down to the Even More Advanced Debugging section. Click All Nodes. The Node Diagnostics page appears. Click the certificates for each node and check the expiration date for each certificate in the Valid Until field.

Client password not set

While connecting to a secure cluster as a user, CockroachDB first checks if the client certificate exists in the cert directory. If the client certificate doesn’t exist, it prompts for a password. If password is not set and you press Enter, the connection attempt fails, and the following error is printed to stderr:

Error: pq: invalid password
Failed running "sql"

Solution: To successfully connect to the cluster, you must first either generate a client certificate or create a password for the user.

Clock sync issues

A node’s timezone data has changed

CockroachDB relies on each node’s operating system timezone database to resolve named timezones like America/New_York, and for applying daylight saving rules. This can lead to inconsistent results across a cluster when coercing date/time strings into temporal types. Ensure that each node’s operating system uses the same timezone database. In general, Cockroach Labs recommends that each node has an identical hardware and software configuration. Timezone data is read from the following sources in order of preference:

The ZONEINFO operating system environment variable, if it is set to point to a zoneinfo.zip file such as the one included in Go or to the directory that results from unzipping a zoneinfo.zip.
The operating system’s timezone database, sometimes called tzdata or zoneinfo. The following common locations are searched:
- /usr/share/zoneinfo/
- /usr/share/lib/zoneinfo/
- /usr/lib/locale/TZ/

The Windows operating system’s timezone database is not used by CockroachDB on Windows.

The timezone database that is embedded in Go.

each node if:

The operating system’s timezone database is updated.
Any node’s timezone changes.
The definition of a timezone changes due to government or geopolitical decisions.
The ZONEINFO operating system environment variable is updated or if the file it points to is updated.

Node clocks are not properly synchronized

See the following FAQs:

Capacity planning issues

You may encounter the following issues when your cluster nears 100% resource capacity:

Running CPU at close to 100% utilization with high run queue will result in poor performance.
Running RAM at close to 100% utilization triggers Linux OOM and/or swapping that will result in poor performance or stability issues.
Running storage at 100% capacity causes writes to fail, which in turn can cause various processes to stop.
Running storage at 100% utilization read/write causes poor service time and .
Running network at 100% utilization causes response between databases and client to be poor.

Solution: and navigate to Metrics > Hardware dashboard to monitor the following metrics: Check that adequate capacity was available for the incident:

Type	Time Series	What to look for
RAM capacity	Memory Usage	Any non-zero value
CPU capacity	CPU Percent	Consistent non-zero values
Disk capacity	Available Disk Capacity	Any non-zero value
Disk I/O	Disk Ops In Progress	Zero or occasional single-digit values
Network capacity	Network Bytes Received Network Bytes Sent	Any non-zero value

For minimum provisioning guidelines, see .

Check for resources that are running out of capacity:

Type	Time Series	What to look for
RAM capacity	Memory Usage	Consistently more than 80%
CPU capacity	CPU Percent	Consistently less than 20% in idle (i.e., 80% busy)
Disk capacity	Available Disk Capacity	Consistently less than 20% of the size
Disk I/O	Disk Ops In Progress	Consistent double-digit values
Network capacity	Network Bytes Received Network Bytes Sent	Consistently more than 50% capacity for both

Storage issues

Disks filling up

Like any database system, if you run out of disk space the system will no longer be able to accept writes. Additionally, a CockroachDB node needs a small amount of disk space (a few GiBs to be safe) to perform basic maintenance functionality. For more information about this issue, see:

In rare cases, disk usage can increase on nodes with due to a .

Automatic ballast files

CockroachDB automatically creates an emergency ballast file at . This feature is on by default. Note that the command is still available but deprecated. The ballast file defaults to 1% of total disk capacity or 1 GiB, whichever is smaller. The size of the ballast file may be configured using with a ; this field accepts the same value formats as the size field. In order for the ballast file to be automatically created, the following conditions must be met:

Available disk space is at least four times the configured ballast file size.
Available disk space on the store after creating the ballast file is at least 10 GiB.

During node startup, if available disk space on at least one store is less than or equal to half the ballast file size, the process will exit immediately with the exit code 10, signifying ‘Disk Full’. To allow the node to start, you can manually remove the EMERGENCY_BALLAST file, which is located in the store’s cockroach-data/auxiliary directory as shown below:

cockroach-data
├── ...
├── auxiliary
│   └── EMERGENCY_BALLAST
...

Removing the ballast file will give you a chance to remedy the disk space exhaustion; it will automatically be recreated when there is sufficient disk space.

Different filesystems may treat the ballast file differently. Make sure to test that the file exists, and that space for the file is actually being reserved by the filesystem. For a list of supported filesystems, see the .

Disk stalls

A disk stall is any disk operation that does not terminate in a reasonable amount of time. This usually manifests as write-related system calls such as fsync(2) (aka fdatasync) taking a lot longer than expected (e.g., more than 20 seconds). The mitigation in almost all cases is to with the stalled disk. CockroachDB’s internal disk stall monitoring will attempt to shut down a node when it sees a disk stall that lasts longer than 20 seconds. At that point the node should be restarted by your .

In cloud environments, transient disk stalls are common, often lasting on the order of several seconds. If you deploy a CockroachDB self-hosted cluster in the cloud, we strongly recommend enabling .

Symptoms of disk stalls include:

Bad cluster write performance, usually in the form of a substantial drop in QPS for a given workload.
Node liveness issues.
Messages like the following start appearing in the : disk slowness detected: write to file {path/to/store/*.sst} has been ongoing for {duration}s

Causes of disk stalls include:

Disk operations have slowed due to underprovisioned IOPS. Make sure you are deploying with our and .
Actual hardware-level storage issues that result in slow fsync performance.
In rare cases, operating-system-level configuration of subsystems such as SELinux can slow down system calls such as fsync enough to affect storage engine performance.

CockroachDB’s built-in disk stall detection works as follows:

Every 10 seconds, the CockroachDB storage engine checks the write-ahead log, or WAL. If data has not been synced to disk (via fsync) within that interval, the log message disk stall detected: unable to write to %s within %s %s warning log entry is written to the . If this state continues for 20 seconds or more (configurable with the COCKROACH_ENGINE_MAX_SYNC_DURATION environment variable), the cockroach process is terminated.
Every time the storage engine writes to the main , the engine waits 20 seconds for the write to succeed (configurable with the COCKROACH_LOG_MAX_SYNC_DURATION environment variable). If the write to the log fails, the cockroach process is terminated and the following message is written to stderr / cockroach.log, providing details regarding the type, size, and duration of the ongoing write:
- file write stall detected: %s
During heartbeats, the writes to disk.

If you see messages like the following in the , it is an early sign of severe I/O slowness, and usually means a fatal stall is imminent:

disk slowness detected: write to file {path/to/store/*.sst} has been ongoing for {duration}s

Repeated occurrences of this message usually mean the node is effectively degraded: it will struggle to hold and serve requests, and will degrade the entire cluster generally. Do not raise the stall thresholds to mask hardware issues. Instead, and replace the . If you are considering tuning, refer to (or the corresponding environment variable COCKROACH_ENGINE_MAX_SYNC_DURATION_DEFAULT), but note that increasing these values generally prolongs unavailability rather than fixing the underlying problem. For the purposes of and determining the of a , node health is no longer determined by heartbeating a single “liveness range”; instead it is determined using . However, node heartbeats of a single range are still used to determine:

Whether a node is still a member of a cluster (this is used by ).
Whether a node is dead (in which case ).
How to avoid placing replicas on dead, decommissioning or unhealthy nodes, and to make decisions about lease transfers.

Disk utilization is different across nodes in the cluster

This is expected behavior. CockroachDB uses to spread across the nodes in a cluster. The rebalancing criteria for load-based replica rebalancing do not include the percentage of disk utilized per node. Not all are the same size. The proportions of larger and smaller ranges on each node balance each other out on average, so disk utilization differences across nodes should be relatively small. However, in some cases a majority of the largest (or smallest) ranges are on one node, which will result in imbalanced utilization. Normally that shouldn’t be a problem with . If this imbalance is causing issues, please for guidance you on how to manually rebalance your cluster’s disk usage. Finally, note that although the replica allocator does not rebalance based on disk utilization during normal operation, it does have the following mechanisms to help protect against full disks:

It will avoid moving replicas onto a disk that is more than 92.5% full.
It will start moving replicas off of a disk that is 95% full.

CPU issues

CPU is insufficient for the workload

Issues with CPU most commonly arise when there is insufficient CPU to support the scale of the workload. If the concurrency of your workload significantly exceeds your provisioned CPU, you will encounter a . This is the most common symptom of CPU starvation. Because requires significant CPU to run concurrent worker threads, a lack of CPU resources will eventually cause compaction to fall behind. This leads to and inversion of the log-structured merge (LSM) trees on the . By default, the uses a compaction concurrency of 3. If you have sufficient IOPS and CPU headroom, you can consider increasing this setting via the COCKROACH_COMPACTION_CONCURRENCY environment variable. This may help to reshape the LSM more quickly in scenarios; and it can lead to increased overall performance for some workloads. Cockroach Labs strongly recommends testing your workload against non-default values of this setting. If these issues remain unresolved, affected nodes will eventually become unresponsive. Solution: To diagnose and resolve an excessive workload concurrency issue:

and compare it to your provisioned CPU.
- To prevent issues with workload concurrency, and use for the workload.
, which can be affected over time by CPU starvation.
- If compaction has fallen behind and caused an , throttle your workload concurrency to allow to catch up and restore a healthy LSM shape. The number of active connections across all connection pools should not exceed 4 times the number of vCPUs in the cluster by a large amount. A connection is “active” when it is actively executing a query. To monitor active connections, use the . If a node is severely impacted, you can and then decommission the problematic node. By default, the uses a compaction concurrency of 3. If you have sufficient IOPS and CPU headroom, you can consider increasing this setting via the COCKROACH_COMPACTION_CONCURRENCY environment variable. This may help to reshape the LSM more quickly in scenarios; and it can lead to increased overall performance for some workloads. Cockroach Labs strongly recommends testing your workload against non-default values of this setting.

Memory issues

Suspected memory leak

A CockroachDB node will grow to consume all of the memory allocated for its --cache, . The default cache size is 25% of physical memory, which can be substantial, depending on your machine configuration. For more information, see . CockroachDB memory usage has the following components:

Go allocated memory: Memory allocated by the Go runtime to support query processing and various caches maintained in Go by CockroachDB.
CGo allocated memory: Memory allocated by the C/C++ libraries linked into CockroachDB and primarily concerns the block caches for the ). This is the allocation specified with --cache. The size of CGo allocated memory is usually very close to the configured --cache size.
Overhead: The RSS (resident set size) minus Go/CGo allocated memory.

Solution: To determine Go and CGo allocated memory:

.
Navigate to Metrics > Runtime dashboard, and check the Memory Usage graph.

On hovering over the graph, the values for the following metrics are displayed:

Metric	Description
RSS	Total memory in use by CockroachDB.
Go Allocated	Memory allocated by the Go layer.
Go Total	Total memory managed by the Go layer.
CGo Allocated	Memory allocated by the C layer.
CGo Total	Total memory managed by the C layer.

Expected values for a healthy cluster: Go Allocated will depend on workload but should not exceed by more than 100%. CGo Allocated should not exceed the size and CGo Total should not exceed the size by more than 15%. If you observe values not within the expected range for a healthy cluster, .

Out-of-memory (OOM) crash

When a node exits without logging an error message, the operating system has likely stopped the node due to insufficient memory. CockroachDB attempts to restart nodes after they crash. Nodes that frequently restart following an abrupt process exit may point to an underlying memory issue. Solution: If you :

- To prevent OOM crashes, . If all CockroachDB machines are provisioned and configured correctly, either run the CockroachDB process on another node with sufficient memory, or .

Decommissioning issues

Decommissioning process hangs indefinitely

If the appears to be hung on a node, a message like the following will print to stderr:

possible decommission stall detected
n3 still has replica id 2 for range r1
n3 still has replica id 3 for range r2
n3 still has replica id 2 for range r3
n3 still has replica id 3 for range r4
n3 still has replica id 2 for range r5

Explanation: Before decommissioning a node, you need to make sure other nodes are available to take over the range replicas from the node. If no other nodes are available, the decommission process will hang indefinitely. For more information, see . Solution: Confirm that there are enough nodes with sufficient storage space to take over the replicas from the node you want to remove.

Replication issues

DB Console shows under-replicated/unavailable ranges

When a CockroachDB node dies (or is partitioned) the under-replicated range count will briefly spike while the system recovers. Explanation: CockroachDB uses consensus replication and requires a quorum of the replicas to be available in order to allow both writes and reads to the range. The number of failures that can be tolerated is equal to (Replication factor - 1)/2. Thus CockroachDB requires (n-1)/2 nodes to achieve quorum. For example, with 3x replication, one failure can be tolerated; with 5x replication, two failures, and so on.

Under-replicated Ranges: When a cluster is first initialized, the few default starting ranges have a single replica. As more nodes become available, the cluster replicates these ranges to other nodes until the number of replicas for each range reaches the desired (3 by default). If a range has fewer replicas than the replication factor, the range is said to be “under-replicated”. , if configured, are not counted when calculating replication status.
Unavailable Ranges: If a majority of a range’s replicas are on nodes that are unavailable, then the entire range is unavailable and will be unable to process queries.

Solution: To identify under-replicated/unavailable ranges:

.
On the , check the Replication Status. If the Under-replicated ranges or Unavailable ranges count is non-zero, then you have under-replicated or unavailable ranges in your cluster.
Check for a network partition: On the , if there are nodes in the network matrix with , this may indicate a network partition. If there is no partition and still no upreplication after 5 minutes, then .

Add nodes to the cluster: On the DB Console’s Cluster Overview page, check if any nodes are down. If the number of nodes down is less than (n-1)/2, then that is most probably the cause of the under-replicated/unavailable ranges. Add nodes to the cluster such that the cluster has the required number of nodes to replicate ranges properly. If you still see under-replicated/unavailable ranges on the Cluster Overview page, investigate further:

On the , click Problem Ranges.
In the Connections table, identify the node with the under-replicated/unavailable ranges and click the node ID in the Node column.
To view the Range Report for a range, click on the range number in the Under-replicated (or slow) table or Unavailable table.
On the Range Report page, scroll down to the Simulated Allocator Output section. The table contains an error message which explains the reason for the under-replicated range. Follow the guidance in the message to resolve the issue. If you need help understanding the error or the guidance, . Please be sure to include the full Range Report and error message when you submit the issue.

Check for under-replicated or unavailable data

To see if any data is under-replicated or unavailable in your cluster, follow the steps described in .

Check for replication zone constraint violations

To see if any of your cluster’s are being violated, follow the steps described in Check for critical localities.

Check for critical localities

To see which of your (if any) are critical, follow the steps described in the . A locality is “critical” for a range if all of the nodes in that locality becoming unreachable would cause the range to become unavailable. In other words, the locality contains a majority of the range’s replicas.

Node liveness issues

“Node liveness” refers to whether a node in your cluster has been determined to be “dead” or “alive” by the rest of the cluster. With , node liveness is managed based on liveness rather than through a centralized node liveness range (as in previous versions less than v25.2); this reduces single points of failure and improves resilience to network partitions and other faults. Common reasons for node liveness issues include:

Heavy I/O load on the node. Nodes running CockroachDB v25.2 and later no longer need to update a centralized node liveness record, but heavy I/O can still impact . See also: Capacity planning issues.
A disk stall. This can cause node liveness issues for the same reasons as listed above.
Insufficient CPU for the workload: This can cause nodes to be marked as unresponsive.
Networking issues with the node.

The DB Console provides several ways to check for node liveness issues in your cluster:

For more information about how node liveness works, see .

Impact of node failure is greater than 10 seconds

With , the impact of a node failure is significantly reduced. The dependency on a single node liveness range that existed in versions less than v25.2 has been eliminated. Leader leases use a store-wide failure detection mechanism that ensures that lease transfers occur more efficiently.

Lease Transfer Efficiency: When a node fails, the is expedited due to the decentralized store liveness checks. This process should complete within a few seconds, as there is no longer a dependency on a single node liveness range.
Network or DNS issues cause connection issues between nodes. If there is no live server for the IP address or DNS lookup, connection attempts to a node will not return an immediate error, but will hang . This can cause unavailability and prevent a speedy movement of leases and recovery. CockroachDB avoids contacting unresponsive nodes or DNS during certain performance-critical operations, and the connection issue should generally resolve in 10-30 seconds. However, an attempt to contact an unresponsive node could still occur in other scenarios that are not yet addressed.
A node’s disk stalls. A disk stall on a node can cause write operations to stall indefinitely. Pebble detects most stalls and will terminate the cockroach process after 20 seconds, but there are gaps in its detection. Each lease acquisition attempt on an unresponsive node . However, CockroachDB can still appear to stall as these timeouts are occurring.
Otherwise unresponsive nodes. Internal deadlock due to faulty code, resource exhaustion, OS/hardware issues, and other arbitrary failures can make a node unresponsive.

Solution: If you are experiencing intermittent network or connectivity issues, first temporarily so that nodes phasing in and out do not cause disruption. If a node has become unresponsive without returning an error, so that network requests immediately become hard errors rather than stalling. If you are running a version of CockroachDB that is affected by an issue described here, upgrade to a version that contains the fix for the issue, as described in the preceding list.

Partial availability issues

If your cluster is in a partially-available state due to a recent node or network failure, the internal logging table system.eventlog might be unavailable. This can cause the logging of (e.g., the execution of SQL statements) to the system.eventlog table to fail to complete, contributing to cluster unavailability. If this occurs, you can set the server.eventlog.enabled to false to disable writing notable log events to this table, which may help to recover your cluster. Even with server.eventlog.enabled set to false, notable log events are still sent to configured as usual.

Something else?

If we do not have a solution here, you can try using our other , including:

​Cannot run a single-node CockroachDB cluster

​An existing storage directory

​Toolchain incompatibility

​Incompatible CPU

​Default ports already in use

​Single-node networking issues

​CockroachDB process hangs when trying to start a node in the background

​Cannot run SQL statements using built-in SQL client

​Cannot run a multi-node CockroachDB cluster on the same machine

​Store directory already exists

​Port already in use

​Scaling issues

​Cannot join a node to an existing CockroachDB cluster

Store directory already exists

Incorrect --join address

​Performance is degraded when adding nodes

Excessive snapshot rebalance and recovery rates

​Client connection issues

​Networking issues

​Network partition

​Authentication issues

​Missing certificate

​Certification expiration

​Client password not set

​Clock sync issues

​A node’s timezone data has changed

​Node clocks are not properly synchronized

​Capacity planning issues

​Storage issues

​Disks filling up

Automatic ballast files

​Disk stalls

​Disk utilization is different across nodes in the cluster

​CPU issues

​CPU is insufficient for the workload

​Memory issues

​Suspected memory leak

​Out-of-memory (OOM) crash

​Decommissioning issues

​Decommissioning process hangs indefinitely

​Replication issues

​DB Console shows under-replicated/unavailable ranges

​Check for under-replicated or unavailable data

​Check for replication zone constraint violations

​Check for critical localities

​Node liveness issues

​Impact of node failure is greater than 10 seconds

​Partial availability issues

​Something else?

Cannot run a single-node CockroachDB cluster

An existing storage directory

Toolchain incompatibility

Incompatible CPU

Default ports already in use

Single-node networking issues

CockroachDB process hangs when trying to start a node in the background

Cannot run SQL statements using built-in SQL client

Cannot run a multi-node CockroachDB cluster on the same machine

Store directory already exists

Port already in use

Scaling issues

Cannot join a node to an existing CockroachDB cluster

Incorrect `--join` address

Performance is degraded when adding nodes

Client connection issues

Networking issues

Network partition

Authentication issues

Missing certificate

Certification expiration

Client password not set

Clock sync issues

A node’s timezone data has changed

Node clocks are not properly synchronized

Capacity planning issues

Storage issues

Disks filling up

Disk stalls

Disk utilization is different across nodes in the cluster

CPU issues

CPU is insufficient for the workload

Memory issues

Suspected memory leak

Out-of-memory (OOM) crash

Decommissioning issues

Decommissioning process hangs indefinitely

Replication issues

DB Console shows under-replicated/unavailable ranges

Check for under-replicated or unavailable data

Check for replication zone constraint violations

Check for critical localities

Node liveness issues

Impact of node failure is greater than 10 seconds

Partial availability issues

Something else?