OpenSearch/docs/reference/setup/bootstrap-checks.asciidoc

[[bootstrap-checks]]
== Bootstrap Checks

Collectively, we have a lot of experience with users suffering
unexpected issues because they have not configured
<<important-settings,important settings>>. In previous versions of
Elasticsearch, misconfiguration of some of these settings were logged
as warnings. Understandably, users sometimes miss these log messages.
To ensure that these settings receive the attention that they deserve,
Elasticsearch has bootstrap checks upon startup.

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.

[float]
=== Development vs. production mode

By default, Elasticsearch binds to `localhost` for <<modules-http,HTTP>>
and <<modules-transport,transport (internal)>> communication. This is
fine for downloading and playing with Elasticsearch, and everyday
development but it's useless for production systems. To form a cluster,
Elasticsearch instances must be reachable via transport communication so
they must bind transport to an external interface. Thus, we consider an
Elasticsearch instance to be in development mode if it does not bind
transport to an external interface (the default), and is otherwise in
production mode if it does bind transport to an external interface. Note
that HTTP can be configured independently of transport via
<<modules-http,`http.host`>> and <<modules-transport,`transport.host`>>;
this can be useful for configuring a single instance to be reachable via
HTTP for testing purposes without triggering production mode.

=== Heap size check

If a JVM is started with unequal initial and max heap size, it can be
prone to pauses as the JVM heap is resized during system usage. To avoid
these resize pauses, it's best to start the JVM with the initial heap
size equal to the maximum heap size. Additionally, if
<<bootstrap.memory_lock,`bootstrap.memory_lock`>> is enabled, the JVM will
lock the initial size of the heap on startup. If the initial heap size
is not equal to the maximum heap size, after a resize it will not be the
case that all of the JVM heap is locked in memory. To pass the heap size
check, you must configure the <<heap-size,heap size>>.


=== File descriptor check

File descriptors are a Unix construct for tracking open "files". In Unix
though, https://en.wikipedia.org/wiki/Everything_is_a_file[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,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,`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 <<mlockall,`mlockall`>>.

=== 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 <<modules-threadpool,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 2048 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-size-virtual-memory-check]]
=== 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 `/etc/security/limits.conf` using
the `as` setting to `unlimited` (note that you might have to increase
the limits for the `root` user too).

=== Maximum map count check

Continuing from the previous <<max-size-virtual-memory-check,point>>, 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`.

=== 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. Additionally, Elasticsearch is configured by default to force
the server VM.

=== 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 ship with Elasticsearch configures
Elasticsearch to use 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 either fix any configuration errors on your system that prevented system
call filters from installing (check your logs), or *at your own risk* disable
system call filters by setting `bootstrap.system_call_filter` to `false`.

=== 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.

=== G1GC check

Early versions of the HotSpot JVM that shipped with JDK 8 are known to have
issues that can lead to index corruption when the G1GC collector is enabled.
The versions impacted are those earlier than the version of HotSpot that
shipped with JDK 8u40. The G1GC check detects these early versions of the
HotSpot JVM.