Bootstrap checks
Self Managed
Elasticsearch has bootstrap checks that run at startup to ensure that users have configured all important settings.
These bootstrap checks inspect a variety of Elasticsearch and system settings and compare them to values that are safe for the operation of Elasticsearch. If Elasticsearch is in development mode, any bootstrap checks that fail appear as warnings in the Elasticsearch log. If Elasticsearch is in production mode, any bootstrap checks that fail will cause Elasticsearch to refuse to start.
There are some bootstrap checks that are always enforced to prevent Elasticsearch from running with incompatible settings. These checks are documented individually.
By default, Elasticsearch binds to loopback addresses for HTTP and transport (internal) communication. This is fine for downloading and playing with Elasticsearch as well as everyday development, but it’s useless for production systems. To join a cluster, an Elasticsearch node must be reachable via transport communication. To join a cluster via a non-loopback address, a node must bind transport to a non-loopback address and not be using single-node discovery. Thus, we consider an Elasticsearch node to be in development mode if it can not form a cluster with another machine via a non-loopback address, and is otherwise in production mode if it can join a cluster via non-loopback addresses.
Note that HTTP and transport can be configured independently via http.host and transport.host. This can be useful for configuring a single node to be reachable via HTTP for testing purposes without triggering production mode.
Some users need to bind the transport to an external interface for testing a remote-cluster configuration. For this situation, we provide the discovery type single-node. To enable it, set discovery.type to single-node. In this situation, a node will elect itself master, and will not join a cluster with any other node.
If you are running a single node in production, it is possible to evade the bootstrap checks, either by not binding transport to an external interface, or by binding transport to an external interface and setting the discovery type to single-node. For this situation, you can force execution of the bootstrap checks by setting the system property es.enforce.bootstrap.checks to true in the JVM options. We strongly encourage you to do this if you are in this specific situation. This system property can be used to force execution of the bootstrap checks independent of the node configuration.
Heap size check
By default, Elasticsearch automatically sizes JVM heap based on a node’s roles and total memory. If you manually override the default sizing and start the JVM with different initial and max heap sizes, the JVM may pause as it resizes the heap during system usage. If you enable bootstrap.memory_lock, the JVM locks the initial heap size on startup. If the initial heap size is not equal to the maximum heap size, some JVM heap may not be locked after a resize.
To avoid these issues, start the JVM with an initial heap size equal to the maximum heap size.
File descriptor check
File descriptors are a Unix construct for tracking open "files". In Unix though, everything is a file. For example, "files" could be a physical file, a virtual file (e.g., /proc/loadavg), or network sockets. Elasticsearch requires lots of file descriptors (e.g., every shard is composed of multiple segments and other files, plus connections to other nodes, etc.). This bootstrap check is enforced on OS X and Linux.
To pass the file descriptor check, you might have to configure file descriptors.
Memory lock check
When the JVM does a major garbage collection it touches every page of the heap. If any of those pages are swapped out to disk they will have to be swapped back in to memory. That causes lots of disk thrashing that Elasticsearch would much rather use to service requests. There are several ways to configure a system to disallow swapping. One way is by requesting the JVM to lock the heap in memory through mlockall (Unix) or virtual lock (Windows). This is done via the Elasticsearch setting bootstrap.memory_lock. However, there are cases where this setting can be passed to Elasticsearch but Elasticsearch is not able to lock the heap (e.g., if the elasticsearch user does not have memlock unlimited). The memory lock check verifies that if the bootstrap.memory_lock setting is enabled, that the JVM was successfully able to lock the heap.
To pass the memory lock check, you might have to configure bootstrap.memory_lock.
Maximum number of threads check
Elasticsearch executes requests by breaking the request down into stages and handing those stages off to different thread pool executors. There are different thread pool executors for a variety of tasks within Elasticsearch. Thus, Elasticsearch needs the ability to create a lot of threads. The maximum number of threads check ensures that the Elasticsearch process has the rights to create enough threads under normal use. This check is enforced only on Linux.
If you are on Linux, to pass the maximum number of threads check, you must configure your system to allow the Elasticsearch process the ability to create at least 4096 threads. This can be done via /etc/security/limits.conf using the nproc setting (note that you might have to increase the limits for the root user too).
Max file size check
The segment files that are the components of individual shards and the translog generations that are components of the translog can get large (exceeding multiple gigabytes). On systems where the max size of files that can be created by the Elasticsearch process is limited, this can lead to failed writes. Therefore, the safest option here is that the max file size is unlimited and that is what the max file size bootstrap check enforces.
To pass the max file check, you must configure your system to allow the Elasticsearch process the ability to write files of unlimited size. This can be done via /etc/security/limits.conf using the fsize setting to unlimited (note that you might have to increase the limits for the root user too).
Maximum size virtual memory check
Elasticsearch and Lucene use mmap to great effect to map portions of an index into the Elasticsearch address space. This keeps certain index data off the JVM heap but in memory for blazing fast access. For this to be effective, the Elasticsearch should have unlimited address space. The maximum size virtual memory check enforces that the Elasticsearch process has unlimited address space and is enforced only on Linux.
To pass the maximum size virtual memory check, you must configure your system to allow the Elasticsearch process the ability to have unlimited address space. This can be done via adding <user> - as unlimited to /etc/security/limits.conf. This may require you to increase the limits for the root user too.
Maximum map count check
In addition to unlimited address space, to use mmap effectively, Elasticsearch also requires the ability to create many memory-mapped areas. The maximum map count check checks that the kernel allows a process to have at least 262,144 memory-mapped areas and is enforced on Linux only.
To pass the maximum map count check, you must configure vm.max_map_count via sysctl to be at least 262144.
Alternatively, the maximum map count check is only needed if you are using mmapfs or hybridfs as the store type for your indices. If you do not allow the use of mmap then this bootstrap check will not be enforced.
Client JVM check
There are two different JVMs provided by OpenJDK-derived JVMs: the client JVM and the server JVM. These JVMs use different compilers for producing executable machine code from Java bytecode. The client JVM is tuned for startup time and memory footprint while the server JVM is tuned for maximizing performance. The difference in performance between the two VMs can be substantial. The client JVM check ensures that Elasticsearch is not running inside the client JVM.
To pass the client JVM check, you must start Elasticsearch with the server VM. On modern systems and operating systems, the server VM is the default.
Use serial collector check
There are various garbage collectors for the OpenJDK-derived JVMs targeting different workloads. The serial collector in particular is best suited for single logical CPU machines or extremely small heaps, neither of which are suitable for running Elasticsearch. Using the serial collector with Elasticsearch can be devastating for performance. The serial collector check ensures that Elasticsearch is not configured to run with the serial collector.
To pass the serial collector check, you must not start Elasticsearch with the serial collector (whether it’s from the defaults for the JVM that you’re using, or you’ve explicitly specified it with -XX:+UseSerialGC). Note that the default JVM configuration that ships with Elasticsearch configures Elasticsearch to use the G1GC garbage collector with JDK14 and later versions. For earlier JDK versions, the configuration defaults to the CMS collector.
System call filter check
Elasticsearch installs system call filters of various flavors depending on the operating system (e.g., seccomp on Linux). These system call filters are installed to prevent the ability to execute system calls related to forking as a defense mechanism against arbitrary code execution attacks on Elasticsearch. The system call filter check ensures that if system call filters are enabled, then they were successfully installed.
To pass the system call filter check you must fix any configuration errors on your system that prevented system call filters from installing (check your logs).
OnError and OnOutOfMemoryError checks
The JVM options OnError and OnOutOfMemoryError enable executing arbitrary commands if the JVM encounters a fatal error (OnError) or an OutOfMemoryError (OnOutOfMemoryError). However, by default, Elasticsearch system call filters (seccomp) are enabled and these filters prevent forking. Thus, using OnError or OnOutOfMemoryError and system call filters are incompatible. The OnError and OnOutOfMemoryError checks prevent Elasticsearch from starting if either of these JVM options are used and system call filters are enabled. This check is always enforced.
To pass this check, do not enable OnError nor OnOutOfMemoryError; instead, upgrade to Java 8u92 and use the JVM flag ExitOnOutOfMemoryError. While this does not have the full capabilities of OnError nor OnOutOfMemoryError, arbitrary forking will not be supported with seccomp enabled.
Early-access check
All permission check
Discovery configuration check
By default, when Elasticsearch first starts up it will try and discover other nodes running on the same host. If no elected master can be discovered within a few seconds then Elasticsearch will form a cluster that includes any other nodes that were discovered. It is useful to be able to form this cluster without any extra configuration in development mode, but this is unsuitable for production because it’s possible to form multiple clusters and lose data as a result.
This bootstrap check ensures that discovery is not running with the default configuration. It can be satisfied by setting at least one of the following properties:
discovery.seed_hostsdiscovery.seed_providerscluster.initial_master_nodes
Note that you must remove cluster.initial_master_nodes from the configuration of every node after the cluster has started for the first time. Instead, configure discovery.seed_hosts or discovery.seed_providers. If you do not need any discovery configuration, for instance if running a single-node cluster, set discovery.seed_hosts: [] to disable discovery and satisfy this bootstrap check.
Encrypt sensitive data check
If you use Watcher and have chosen to encrypt sensitive data (by setting xpack.watcher.encrypt_sensitive_data to true), you must also place a key in the secure settings store.
To pass this bootstrap check, you must set the xpack.watcher.encryption_key on each node in the cluster. For more information, see Encrypting sensitive data in Watcher.
PKI realm check
If you use Elasticsearch security features and a Public Key Infrastructure (PKI) realm, you must configure Transport Layer Security (TLS) on your cluster and enable client authentication on the network layers (either transport or http). For more information, see PKI user authentication and Set up basic security plus HTTPS.
To pass this bootstrap check, if a PKI realm is enabled, you must configure TLS and enable client authentication on at least one network communication layer.
Role mappings check
If you authenticate users with realms other than native or file realms, you must create role mappings. These role mappings define which roles are assigned to each user.
If you use files to manage the role mappings, you must configure a YAML file and copy it to each node in the cluster. By default, role mappings are stored in ES_PATH_CONF/role_mapping.yml. Alternatively, you can specify a different role mapping file for each type of realm and specify its location in the elasticsearch.yml file. For more information, see Using role mapping files.
To pass this bootstrap check, the role mapping files must exist and must be valid. The Distinguished Names (DNs) that are listed in the role mappings files must also be valid.
SSL/TLS check
If you enable Elasticsearch security features, unless you have a trial license, you must configure SSL/TLS for internode-communication.
Single-node clusters that use a loopback interface do not have this requirement. For more information, see Start the Elastic Stack with security enabled automatically.
To pass this bootstrap check, you must set up SSL/TLS in your cluster.
Token SSL check
If you use Elasticsearch security features and the built-in token service is enabled, you must configure your cluster to use SSL/TLS for the HTTP interface. HTTPS is required in order to use the token service.
In particular, if xpack.security.authc.token.enabled is set to true in the elasticsearch.yml file, you must also set xpack.security.http.ssl.enabled to true. For more information about these settings, see Security settings and Advanced HTTP settings.
To pass this bootstrap check, you must enable HTTPS or disable the built-in token service.