mirror of https://github.com/docker/docs.git
350 lines
18 KiB
Markdown
350 lines
18 KiB
Markdown
---
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advisory: swarm-standalone
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hide_from_sitemap: true
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description: Plan for Swarm in production
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keywords: docker, swarm, scale, voting, application, plan
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title: Plan for Swarm in production
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---
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This article provides guidance to help you plan, deploy, and manage Docker
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Swarm clusters in business critical production environments. The following high
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level topics are covered:
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- [Security](plan-for-production.md#security)
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- [High Availability](plan-for-production.md#high-availability)
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- [Performance](plan-for-production.md#performance)
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- [Cluster ownership](plan-for-production.md#cluster-ownership)
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## Security
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There are many aspects to securing a Docker Swarm cluster. This section covers:
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- Authentication using TLS
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- Network access control
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These topics are not exhaustive. They form part of a wider security architecture
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that includes: security patching, strong password policies, role based access
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control, technologies such as SELinux and AppArmor, strict auditing, and more.
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### Configure Swarm for TLS
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All nodes in a Swarm cluster must bind their Docker Engine daemons to a network
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port. This brings with it all of the usual network related security
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implications such as man-in-the-middle attacks. These risks are compounded when
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the network in question is untrusted such as the internet. To mitigate these
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risks, Swarm and the Engine support Transport Layer Security(TLS) for
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authentication.
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The Engine daemons, including the Swarm manager, that are configured to use TLS
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will only accept commands from Docker Engine clients that sign their
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communications. The Engine and Swarm support external 3rd party Certificate
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Authorities (CA) as well as internal corporate CAs.
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The default Engine and Swarm ports for TLS are:
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- Engine daemon: 2376/tcp
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- Swarm manager: 3376/tcp
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For more information on configuring Swarm for TLS, see the [Overview Docker Swarm with TLS](secure-swarm-tls.md) page.
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### Network access control
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Production networks are complex, and usually locked down so that only allowed
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traffic can flow on the network. The list below shows the network ports and protocols
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that the different components of a Swam cluster listen on. You should use these to
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configure your firewalls and other network access control lists.
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- **Swarm manager.**
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- **Inbound 80/tcp (HTTP)**. This allows `docker pull` commands to work. If you plan to pull images from Docker Hub, you must allow Internet connections through port 80.
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- **Inbound 2375/tcp**. This allows Docker Engine CLI commands direct to the Engine daemon.
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- **Inbound 3375/tcp**. This allows Engine CLI commands to the Swarm manager.
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- **Inbound 22/tcp**. This allows remote management via SSH
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- **Service Discovery**:
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- **Inbound 80/tcp (HTTP)**. This allows `docker pull` commands to work. If you plan to pull images from Docker Hub, you must allow Internet connections through port 80.
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- **Inbound *Discovery service port***. This needs setting to the port that the backend discovery service listens on (consul, etcd, or zookeeper).
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- **Inbound 22/tcp**. This allows remote management via SSH
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- **Swarm nodes**:
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- **Inbound 80/tcp (HTTP)**. This allows `docker pull` commands to work. If you plan to pull images from Docker Hub, you must allow Internet connections through port 80.
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- **Inbound 2375/tcp**. This allows Engine CLI commands direct to the Docker daemon.
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- **Inbound 22/tcp**. This allows remote management via SSH.
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- **Custom, cross-host container networks**:
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- **Inbound 7946/tcp** Allows for discovering other container networks.
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- **Inbound 7946/udp** Allows for discovering other container networks.
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- **Inbound `<store-port>`/tcp** Network key-value store service port.
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- **4789/udp** For the container overlay network.
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- **ESP packets** For encrypted overlay networks.
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If your firewalls and other network devices are connection state aware, they
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will allow responses to established TCP connections. If your devices are not
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state aware, you will need to open up ephemeral ports from 32768-65535. For
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added security you can configure the ephemeral port rules to only allow
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connections from interfaces on known Swarm devices.
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If your Swarm cluster is configured for TLS, replace `2375` with `2376`, and
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`3375` with `3376`.
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The ports listed above are just for Swarm cluster operations such as; cluster
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creation, cluster management, and scheduling of containers against the cluster.
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You may need to open additional network ports for application-related
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communications.
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It is possible for different components of a Swarm cluster to exist on separate
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networks. For example, many organizations operate separate management and
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production networks. Some Docker Engine clients may exist on a management
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network, while Swarm managers, discovery service instances, and nodes might
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exist on one or more production networks. To offset against network failures,
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you can deploy Swarm managers, discovery services, and nodes across multiple
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production networks. In all of these cases you can use the list of ports above
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to assist the work of your network infrastructure teams to efficiently and
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securely configure your network.
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## High Availability (HA)
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All production environments should be highly available, meaning they are
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continuously operational over long periods of time. To achieve high
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availability, an environment must the survive failures of its individual
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component parts.
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The following sections discuss some technologies and best practices that can
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enable you to build resilient, highly-available Swarm clusters. You can then use
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these cluster to run your most demanding production applications and workloads.
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### Swarm manager HA
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The Swarm manager is responsible for accepting all commands coming in to a Swarm
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cluster, and scheduling resources against the cluster. If the Swarm manager
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becomes unavailable, some cluster operations cannot be performed until the Swarm
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manager becomes available again. This is unacceptable in large-scale business
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critical scenarios.
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Swarm provides HA features to mitigate against possible failures of the Swarm
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manager. You can use Swarm's HA feature to configure multiple Swarm managers for
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a single cluster. These Swarm managers operate in an active/passive formation
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with a single Swarm manager being the *primary*, and all others being
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*secondaries*.
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Swarm secondary managers operate as *warm standby's*, meaning they run in the
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background of the primary Swarm manager. The secondary Swarm managers are online
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and accept commands issued to the cluster, just as the primary Swarm manager.
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However, any commands received by the secondaries are forwarded to the primary
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where they are executed. Should the primary Swarm manager fail, a new primary is
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elected from the surviving secondaries.
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When creating HA Swarm managers, you should take care to distribute them over as
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many *failure domains* as possible. A failure domain is a network section that
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can be negatively affected if a critical device or service experiences problems.
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For example, if your cluster is running in the Ireland Region of Amazon Web
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Services (eu-west-1) and you configure three Swarm managers (1 x primary, 2 x
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secondary), you should place one in each availability zone as shown below.
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In this configuration, the Swarm cluster can survive the loss of any two
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availability zones. For your applications to survive such failures, they must be
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architected across as many failure domains as well.
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For Swarm clusters serving high-demand, line-of-business applications, you
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should have 3 or more Swarm managers. This configuration allows you to take one
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manager down for maintenance, suffer an unexpected failure, and still continue
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to manage and operate the cluster.
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### Discovery service HA
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The discovery service is a key component of a Swarm cluster. If the discovery
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service becomes unavailable, this can prevent certain cluster operations. For
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example, without a working discovery service, operations such as adding new
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nodes to the cluster and making queries against the cluster configuration fail.
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This is not acceptable in business critical production environments.
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Swarm supports four backend discovery services:
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- Hosted (not for production use)
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- Consul
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- etcd
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- Zookeeper
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Consul, etcd, and Zookeeper are all suitable for production, and should be
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configured for high availability. You should use each service's existing tools
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and best practices to configure these for HA.
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For Swarm clusters serving high-demand, line-of-business applications, it is
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recommended to have 5 or more discovery service instances. This due to the
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replication/HA technologies they use (such as Paxos/Raft) requiring a strong
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quorum. Having 5 instances allows you to take one down for maintenance, suffer
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an unexpected failure, and still be able to achieve a strong quorum.
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When creating a highly available Swarm discovery service, you should take care
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to distribute each discovery service instance over as many failure domains as
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possible. For example, if your cluster is running in the Ireland Region of
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Amazon Web Services (eu-west-1) and you configure three discovery service
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instances, you should place one in each availability zone.
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The diagram below shows a Swarm cluster configured for HA. It has three Swarm
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managers and three discovery service instances spread over three failure
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domains (availability zones). It also has Swarm nodes balanced across all three
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failure domains. The loss of two availability zones in the configuration shown
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below does not cause the Swarm cluster to go down.
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It is possible to share the same Consul, etcd, or Zookeeper containers between
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the Swarm discovery and Engine container networks. However, for best
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performance and availability you should deploy dedicated instances – a
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discovery instance for Swarm and another for your container networks.
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### Multiple clouds
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You can architect and build Swarm clusters that stretch across multiple cloud
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providers, and even across public cloud and on premises infrastructures. The
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diagram below shows an example Swarm cluster stretched across AWS and Azure.
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While such architectures may appear to provide the ultimate in availability,
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there are several factors to consider. Network latency can be problematic, as
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can partitioning. As such, you should seriously consider technologies that
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provide reliable, high speed, low latency connections into these cloud
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platforms – technologies such as AWS Direct Connect and Azure
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ExpressRoute.
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If you are considering a production deployment across multiple infrastructures
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like this, make sure you have good test coverage over your entire system.
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### Isolated production environments
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It is possible to run multiple environments, such as development, staging, and
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production, on a single Swarm cluster. You accomplish this by tagging Swarm
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nodes and using constraints to filter containers onto nodes tagged as
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`production` or `staging` etc. However, this is not recommended. The recommended
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approach is to air-gap production environments, especially high performance
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business critical production environments.
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For example, many companies not only deploy dedicated isolated infrastructures
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for production – such as networks, storage, compute and other systems.
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They also deploy separate management systems and policies. This results in
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things like users having separate accounts for logging on to production systems
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etc. In these types of environments, it is mandatory to deploy dedicated
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production Swarm clusters that operate on the production hardware infrastructure
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and follow thorough production management, monitoring, audit and other policies.
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### Operating system selection
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You should give careful consideration to the operating system that your Swarm
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infrastructure relies on. This consideration is vital for production
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environments.
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It is not unusual for a company to use one operating system in development
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environments, and a different one in production. A common example of this is to
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use CentOS in development environments, but then to use Red Hat Enterprise Linux
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(RHEL) in production. This decision is often a balance between cost and support.
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CentOS Linux can be downloaded and used for free, but commercial support options
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are few and far between. Whereas RHEL has an associated support and license
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cost, but comes with world class commercial support from Red Hat.
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When choosing the production operating system to use with your Swarm clusters,
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choose one that closely matches what you have used in development and staging
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environments. Although containers abstract much of the underlying OS, some
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features have configuration requirements. For example, to use Docker container
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networking with Docker Engine 1.10 or higher, your host must have a Linux kernel
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that is version 3.10 or higher. Refer to the change logs to understand the
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requirements for a particular version of Docker Engine or Swarm.
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You should also consider procedures and channels for deploying and potentially
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patching your production operating systems.
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## Performance
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Performance is critical in environments that support business critical line of
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business applications. The following sections discuss some technologies and
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best practices that can help you build high performance Swarm clusters.
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### Container networks
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Docker Engine container networks are overlay networks and can be created across
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multiple Engine hosts. For this reason, a container network requires a key-value
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(KV) store to maintain network configuration and state. This KV store can be
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shared in common with the one used by the Swarm cluster discovery service.
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However, for best performance and fault isolation, you should deploy individual
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KV store instances for container networks and Swarm discovery. This is
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especially so in demanding business critical production environments.
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Beginning with Docker Engine 1.9, Docker container networks require specific
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Linux kernel versions. Higher kernel versions are usually preferred, but carry
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an increased risk of instability because of the newness of the kernel. Where
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possible, use a kernel version that is already approved for use in your
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production environment. If you can not use a 3.10 or higher Linux kernel version
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for production, you should begin the process of approving a newer kernel as
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early as possible.
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### Scheduling strategies
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<!-- NIGEL: This reads like an explanation of specific scheduling strategies rather than guidance on which strategy to pick for production or with consideration of a production architecture choice. For example, is spread a problem in a multiple clouds or random not good for XXX type application for YYY reason?
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Or perhaps there is nothing to consider when it comes to scheduling strategy and network / HA architecture, application, os choice etc. that good?
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-->
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Scheduling strategies are how Swarm decides which nodes on a cluster to start
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containers on. Swarm supports the following strategies:
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- spread
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- binpack
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- random (not for production use)
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You can also write your own.
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**Spread** is the default strategy. It attempts to balance the number of
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containers evenly across all nodes in the cluster. This is a good choice for
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high performance clusters, as it spreads container workload across all
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resources in the cluster. These resources include CPU, RAM, storage, and
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network bandwidth.
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If your Swarm nodes are balanced across multiple failure domains, the spread
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strategy evenly balance containers across those failure domains. However,
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spread on its own is not aware of the roles of any of those containers, so has
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no intelligence to spread multiple instances of the same service across failure
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domains. To achieve this you should use tags and constraints.
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The **binpack** strategy runs as many containers as possible on a node,
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effectively filling it up, before scheduling containers on the next node.
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This means that binpack does not use all cluster resources until the cluster
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fills up. As a result, applications running on Swarm clusters that operate the
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binpack strategy might not perform as well as those that operate the spread
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strategy. However, binpack is a good choice for minimizing infrastructure
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requirements and cost. For example, imagine you have a 10-node cluster where
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each node has 16 CPUs and 128GB of RAM. However, your container workload across
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the entire cluster is only using the equivalent of 6 CPUs and 64GB RAM. The
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spread strategy would balance containers across all nodes in the cluster.
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However, the binpack strategy would fit all containers on a single node,
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potentially allowing you turn off the additional nodes and save on cost.
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## Ownership of Swarm clusters
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The question of ownership is vital in production environments. It is therefore
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vital that you consider and agree on all of the following when planning,
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documenting, and deploying your production Swarm clusters.
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- Whose budget does the production Swarm infrastructure come out of?
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- Who owns the accounts that can administer and manage the production Swarm
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cluster?
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- Who is responsible for monitoring the production Swarm infrastructure?
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- Who is responsible for patching and upgrading the production Swarm
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infrastructure?
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- On-call responsibilities and escalation procedures?
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The above is not a complete list, and the answers to the questions will vary
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depending on how your organization's and team's are structured. Some companies
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are along way down the DevOps route, while others are not. Whatever situation
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your company is in, it is important that you factor all of the above into the
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planning, deployment, and ongoing management of your production Swarm clusters.
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## Related information
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* [Try Swarm at scale](swarm_at_scale/index.md)
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* [Swarm and container networks](networking.md)
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* [High availability in Docker Swarm](multi-manager-setup.md)
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* [Docker Data Center](https://www.docker.com/products/docker-datacenter)
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