[[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 and publishes to `localhost`. This is fine for downloading and playing with Elasticsearch, and everyday development but it's useless for production systems. For a production installation to be reachable, it must either bind or publish to an external interface. Thus, we consider Elasticsearch to be in development mode if it does not bind nor publish to an external interface (the default), and is otherwise in production mode if it does bind or publish to an external interface. === 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 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`>>. === Minimum master nodes check Elasticsearch uses a single master for managing cluster state but enables there to be multiple master-eligible nodes for high-availability. In the case of a partition, master-eligible nodes on each side of the partition might be elected as the acting master without knowing that there is a master on the side of the partition. This can lead to divergent cluster states potentially leading to data loss when the partition is healed. This is the notion of a split brain and it is the worst thing that can happen to an Elasticsearch cluster. But by configuring <<minimum_master_nodes,`discovery.zen.minimum_master_nodes`>> to be equal to a quorum of master-eligible nodes, it is not possible for the cluster to suffer from split brain because during a network partition there can be at most one side of the partition that contains a quorum of master nodes. The minimum master nodes check enforces that you've set <<minimum_master_nodes,`discovery.zen.minimum_master_nodes`>>. To pass the minimum master nodes check, you must configure <<minimum_master_nodes,`discovery.zen.minimum_master_nodes`>>. NOTE: The minimum master nodes check does not enforce that you've configured <<minimum_master_nodes,`discovery.zen.minimum_master_nodes`>> correctly, only that you have it configured. Elasticsearch does log a warning message if it detects that <<minimum_master_nodes,`discovery.zen.minimum_master_nodes`>> is incorrectly configured based on the number of master-eligible nodes visible in the cluster state. Future versions of Elasticsearch will contain stricter enforcement of <<minimum_master_nodes,`discovery.zen.minimum_master_nodes`>>. === 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 increaes 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. === 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.