strategy

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Published: Apr 6, 2015 License: Apache-2.0 Imports: 7 Imported by: 0

README


page_title: Docker Swarm strategies page_description: Swarm strategies page_keywords: docker, swarm, clustering, strategies

Strategies

The Docker Swarm scheduler features multiple strategies for ranking nodes. The strategy you choose determines how Swarm computes ranking. When you run a new container, Swarm chooses to place it on the node with the highest computed ranking for your chosen strategy.

To choose a ranking strategy, pass the --strategy flag and a strategy value to the swarm manage command. Swarm currently supports these values:

  • spread
  • binpack
  • random

The spread and binpack strategies compute rank according to a node's available CPU, its RAM, and the number of containers it is running. The random strategy uses no computation. It selects a node at random and is primarily intended for debugging.

Your goal in choosing a strategy is to best optimize your swarm according to your company's needs.

Under the spread strategy, Swarm optimizes for the node with the least number of running containers. The binpack strategy causes Swarm to optimize for the container which is most packed. The random strategy, like it sounds, chooses nodes at random regardless of their available CPU or RAM.

Using the spread strategy results in containers spread thinly over many machines. The advantage of this strategy is that if a node goes down you only loose a few containers.

The binpack strategy avoids fragmentation because it leaves room for bigger containers on unused machines. The strategic advantage of binpack is that you use fewer machines as Swarm tries to pack as many containers as it can on a node.

If you do not specify a --strategy Swarm uses spread by default.

Spread strategy example

In this example, your swarm is using the spread strategy which optimizes for nodes that have the fewest containers. In this swarm, both node-1 and node-2 have 2G of RAM, 2 CPUs, and neither node is running a container. Under this strategy node-1 and node-2 have the same ranking.

When you run a new container, the system chooses node-1 at random from the swarm of two equally ranked nodes:

$ docker run -d -P -m 1G --name db mysql
f8b693db9cd6

$ docker ps
CONTAINER ID        IMAGE               COMMAND             CREATED                  STATUS              PORTS                           NODE        NAMES
f8b693db9cd6        mysql:latest        "mysqld"            Less than a second ago   running             192.168.0.42:49178->3306/tcp    node-1      db

Now, we start another container and ask for 1G of RAM again.

$ docker run -d -P -m 1G --name frontend nginx
963841b138d8

$ docker ps
CONTAINER ID        IMAGE               COMMAND             CREATED                  STATUS              PORTS                           NODE        NAMES
963841b138d8        nginx:latest        "nginx"             Less than a second ago   running             192.168.0.42:49177->80/tcp      node-2      frontend
f8b693db9cd6        mysql:latest        "mysqld"            Up About a minute        running             192.168.0.42:49178->3306/tcp    node-1      db

The container frontend was started on node-2 because it was the node the least packed already. If two nodes have the same amount of available RAM and CPUs, the spread strategy prefers the node with least containers running.

BinPack strategy example

In this example, let's says that both node-1 and node-2 have 2G of RAM and neither is running a container. Again, the nodes are equal. When you run a new container, the system chooses node-1 at random from the swarm:

$ docker run -d -P -m 1G --name db mysql
f8b693db9cd6

$ docker ps
CONTAINER ID        IMAGE               COMMAND             CREATED                  STATUS              PORTS                           NODE        NAMES
f8b693db9cd6        mysql:latest        "mysqld"            Less than a second ago   running             192.168.0.42:49178->3306/tcp    node-1      db

Now, you start another container, asking for 1G of RAM again.

$ docker run -d -P -m 1G --name frontend nginx
963841b138d8

$ docker ps
CONTAINER ID        IMAGE               COMMAND             CREATED                  STATUS              PORTS                           NODE        NAMES
963841b138d8        nginx:latest        "nginx"             Less than a second ago   running             192.168.0.42:49177->80/tcp      node-1      frontend
f8b693db9cd6        mysql:latest        "mysqld"            Up About a minute        running             192.168.0.42:49178->3306/tcp    node-1      db

The system starts the new frontend container on node-1 because it was the node the most packed already. This allows us to start a container requiring 2G of RAM on node-2.

If two nodes have the same amount of available RAM and CPUs, the binpack strategy prefers the node with most containers running.

Docker Swarm documentation index

Documentation

Index

Constants

This section is empty.

Variables

View Source
var (

	// ErrNotSupported is exported
	ErrNotSupported = errors.New("strategy not supported")
	// ErrNoResourcesAvailable is exported
	ErrNoResourcesAvailable = errors.New("no resources available to schedule container")
)

Functions

func List added in v0.2.0

func List() []string

List returns the names of all the available strategies

Types

type BinpackPlacementStrategy added in v0.2.0

type BinpackPlacementStrategy struct {
}

BinpackPlacementStrategy is exported

func (*BinpackPlacementStrategy) Initialize added in v0.2.0

func (p *BinpackPlacementStrategy) Initialize() error

Initialize is exported

func (*BinpackPlacementStrategy) Name added in v0.2.0

func (p *BinpackPlacementStrategy) Name() string

Name returns the name of the strategy

func (*BinpackPlacementStrategy) PlaceContainer added in v0.2.0

func (p *BinpackPlacementStrategy) PlaceContainer(config *dockerclient.ContainerConfig, nodes []cluster.Node) (cluster.Node, error)

PlaceContainer is exported

type PlacementStrategy

type PlacementStrategy interface {
	Name() string

	Initialize() error
	// Given a container configuration and a set of nodes, select the target
	// node where the container should be scheduled.
	PlaceContainer(config *dockerclient.ContainerConfig, nodes []cluster.Node) (cluster.Node, error)
}

PlacementStrategy is exported

func New

func New(name string) (PlacementStrategy, error)

New is exported

type RandomPlacementStrategy

type RandomPlacementStrategy struct{}

RandomPlacementStrategy randomly places the container into the cluster.

func (*RandomPlacementStrategy) Initialize

func (p *RandomPlacementStrategy) Initialize() error

Initialize is exported

func (*RandomPlacementStrategy) Name added in v0.2.0

func (p *RandomPlacementStrategy) Name() string

Name returns the name of the strategy

func (*RandomPlacementStrategy) PlaceContainer

func (p *RandomPlacementStrategy) PlaceContainer(config *dockerclient.ContainerConfig, nodes []cluster.Node) (cluster.Node, error)

PlaceContainer is exported

type SpreadPlacementStrategy added in v0.2.0

type SpreadPlacementStrategy struct {
}

SpreadPlacementStrategy is exported

func (*SpreadPlacementStrategy) Initialize added in v0.2.0

func (p *SpreadPlacementStrategy) Initialize() error

Initialize is exported

func (*SpreadPlacementStrategy) Name added in v0.2.0

func (p *SpreadPlacementStrategy) Name() string

Name returns the name of the strategy

func (*SpreadPlacementStrategy) PlaceContainer added in v0.2.0

func (p *SpreadPlacementStrategy) PlaceContainer(config *dockerclient.ContainerConfig, nodes []cluster.Node) (cluster.Node, error)

PlaceContainer is exported

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