Elasticsearch6.4專題之4:Bootstrap Checks

Bootstrap Checks

Development vs. production mode

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.

Single-node discovery

We recognize that some users need to bind transport to an external interface for testing their usage of the transport client. For this situation, we provide the discovery type single-node (configure it by setting discovery.type to single-node); in this situation, a node will elect itself master and will not join a cluster with any other node.

Forcing the bootstrap checks

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 (set this in Setting JVM options, or by adding -Des.enforce.bootstrap.checks=true to the environment variable ES_JAVA_OPTS). 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

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 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.

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 /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 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.

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 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.

Early-access check

The OpenJDK project provides early-access snapshots of upcoming releases. These releases are not suitable for production. The early-access check detects these early-access snapshots. To pass this check, you must start Elasticsearch on a release build of the JVM.

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.

All permission check

The all permission check ensures that the security policy used during bootstrap does not grant the java.security.AllPermission to Elasticsearch. Running with the all permission granted is equivalent to disabling the security manager.