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---
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layout: docs
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page_title: Architecture
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description: Learn about the internal architecture of Nomad.
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---
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# Architecture
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Nomad is a complex system that has many different pieces. To help both users and developers of Nomad
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build a mental model of how it works, this page documents the system architecture.
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~> **Advanced Topic!** This page covers technical details
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of Nomad. You do not need to understand these details to
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effectively use Nomad. The details are documented here for
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those who wish to learn about them without having to go
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spelunking through the source code.
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# Glossary
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Before describing the architecture, we provide a glossary of terms to help
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clarify what is being discussed:
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#### Job
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A Job is a specification provided by users that declares a workload for
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Nomad. A Job is a form of _desired state_; the user is expressing that the
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job should be running, but not where it should be run. The responsibility of
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Nomad is to make sure the _actual state_ matches the user desired state. A
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Job is composed of one or more task groups.
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#### Task Group
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A Task Group is a set of tasks that must be run together. For example, a web
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server may require that a log shipping co-process is always running as well. A
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task group is the unit of scheduling, meaning the entire group must run on the
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same client node and cannot be split.
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#### Driver
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A Driver represents the basic means of executing your **Tasks**. Example
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Drivers include Docker, QEMU, Java, and static binaries.
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#### Task
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A Task is the smallest unit of work in Nomad. Tasks are executed by drivers,
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which allow Nomad to be flexible in the types of tasks it supports. Tasks
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specify their driver, configuration for the driver, constraints, and resources
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required.
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#### Client
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A Nomad client is an agent configured to run and manage tasks using available
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compute resources on a machine. The agent is responsible for registering with
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the servers, watching for any work to be assigned and executing tasks. The
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Nomad agent is a long lived process which interfaces with the servers.
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#### Allocation
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An Allocation is a mapping between a task group in a job and a client node. A
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single job may have hundreds or thousands of task groups, meaning an
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equivalent number of allocations must exist to map the work to client
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machines. Allocations are created by the Nomad servers as part of scheduling
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decisions made during an evaluation.
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#### Evaluation
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Evaluations are the mechanism by which Nomad makes scheduling decisions. When
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either the _desired state_ (jobs) or _actual state_ (clients) changes, Nomad
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creates a new evaluation to determine if any actions must be taken. An
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evaluation may result in changes to allocations if necessary.
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#### Deployment
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Deployments are the mechanism by which Nomad rolls out changes to cluster state
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in a step-by-step fashion. Deployments are only available for Jobs with the type
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`service`. When an Evaluation is processed, the scheduler creates only the
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number of Allocations permitted by the [`update`][] block and the current state
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of the cluster. The Deployment is used to monitor the health of those
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Allocations and emit a new Evaluation for the next step of the update.
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#### Server
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Nomad servers are the brains of the cluster. There is a cluster of servers per
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region and they manage all jobs and clients, run evaluations, and create task
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allocations. The servers replicate data between each other and perform leader
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election to ensure high availability. More information about latency
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requirements for servers can be found in [Network
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Topology](/docs/install/production/requirements#network-topology).
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#### Regions
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Nomad models infrastructure as regions and datacenters. A region will contain
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one or more datacenters. A set of servers joined together will represent a
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single region. Servers federate across regions to make Nomad globally aware.
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#### Datacenters
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Nomad models a datacenter as an abstract grouping of clients within a
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region. Nomad clients are not required to be in the same datacenter as the
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servers they are joined with, but do need to be in the same
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region. Datacenters provide a way to express fault tolerance among jobs as
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well as isolation of infrastructure.
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#### Bin Packing
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Bin Packing is the process of filling bins with items in a way that maximizes
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the utilization of bins. This extends to Nomad, where the clients are "bins"
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and the items are task groups. Nomad optimizes resources by efficiently bin
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packing tasks onto client machines.
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# High-Level Overview
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Looking at only a single region, at a high level Nomad looks like this:
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[![Regional Architecture](/img/nomad-architecture-region.png)](/img/nomad-architecture-region.png)
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Within each region, we have both clients and servers. Servers are responsible for
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accepting jobs from users, managing clients, and [computing task placements](/docs/concepts/scheduling/scheduling).
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Each region may have clients from multiple datacenters, allowing a small number of servers
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to handle very large clusters.
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In some cases, for either availability or scalability, you may need to run multiple
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regions. Nomad supports federating multiple regions together into a single cluster.
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At a high level, this setup looks like this:
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[![Global Architecture](/img/nomad-architecture-global.png)](/img/nomad-architecture-global.png)
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Regions are fully independent from each other, and do not share jobs, clients, or
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state. They are loosely-coupled using a gossip protocol, which allows users to
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submit jobs to any region or query the state of any region transparently. Requests
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are forwarded to the appropriate server to be processed and the results returned.
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Data is _not_ replicated between regions.
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2016-08-26 20:57:43 +00:00
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The servers in each region are all part of a single consensus group. This means
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that they work together to elect a single leader which has extra duties. The leader
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is responsible for processing all queries and transactions. Nomad is optimistically
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concurrent, meaning all servers participate in making scheduling decisions in parallel.
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The leader provides the additional coordination necessary to do this safely and
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to ensure clients are not oversubscribed.
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Each region is expected to have either three or five servers. This strikes a balance
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between availability in the case of failure and performance, as consensus gets
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progressively slower as more servers are added. However, there is no limit to the number
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of clients per region.
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Clients are configured to communicate with their regional servers and communicate
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using remote procedure calls (RPC) to register themselves, send heartbeats for liveness,
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wait for new allocations, and update the status of allocations. A client registers
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with the servers to provide the resources available, attributes, and installed drivers.
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Servers use this information for scheduling decisions and create allocations to assign
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work to clients.
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Users make use of the Nomad CLI or API to submit jobs to the servers. A job represents
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a desired state and provides the set of tasks that should be run. The servers are
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responsible for scheduling the tasks, which is done by finding an optimal placement for
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each task such that resource utilization is maximized while satisfying all constraints
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specified by the job. Resource utilization is maximized by bin packing, in which
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the scheduling tries to make use of all the resources of a machine without
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exhausting any dimension. Job constraints can be used to ensure an application is
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running in an appropriate environment. Constraints can be technical requirements based
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on hardware features such as architecture and availability of GPUs, or software features
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like operating system and kernel version, or they can be business constraints like
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ensuring PCI compliant workloads run on appropriate servers.
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# Getting in Depth
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This has been a brief high-level overview of the architecture of Nomad. There
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are more details available for each of the sub-systems. The [consensus protocol](/docs/concepts/consensus),
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[gossip protocol](/docs/concepts/gossip), and [scheduler design](/docs/concepts/scheduling/scheduling)
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are all documented in more detail.
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For other details, either consult the code, ask in IRC or reach out to the mailing list.
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[`update`]: /docs/job-specification/update
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