See the getting started page for more information about downloading, building, and deploying Mesos.
See our community page for more details.
In this document we refer to Mesos applications as “frameworks”.
See one of the example framework schedulers in MESOS_HOME/src/examples/ to
get an idea of what a Mesos framework scheduler and executor in the language
of your choice looks like. RENDLER
provides example framework implementations in C++, Go, Haskell, Java, Python
and Scala.
If you are writing a scheduler against Mesos 1.0 or newer, it is recommended to use the new HTTP API to talk to Mesos.
If your framework needs to talk to Mesos 0.28.0 or older, or you have not updated to the
HTTP API, you can write the scheduler in C++, Java/Scala, or Python.
Your framework scheduler should inherit from the Scheduler class
(see: C++,
Java,
Python). Your scheduler should create a SchedulerDriver (which will mediate
communication between your scheduler and the Mesos master) and then call SchedulerDriver.run()
(see: C++,
Java,
Python).
How to build Mesos frameworks that are highly available in the face of failures is discussed in a separate document.
When implementing a scheduler, it’s important to adhere to the following guidelines in order to ensure that the scheduler can run in a scalable manner alongside other schedulers in the same Mesos cluster:
Suppress: The scheduler must stay in a suppressed state whenever it has
no additional tasks to launch or offer operations to perform. This ensures
that Mesos can more efficiently offer resources to those frameworks that do
have work to perform.Decline resources using a large timeout: when declining an offer, use a
large Filters.refuse_seconds timeout (e.g. 1 hour). This ensures that Mesos
will have time to try offering the resources to other scheduler before trying
the same scheduler again. However, if the scheduler is unable to eventually
enter a SUPPRESSed state, and it has new workloads to run after having declined,
it should consider REVIVEing if it is not receiving sufficient resources for
some time.REVIVE frequently: REVIVEing clears all filters, and therefore
if REVIVE occurs frequently it is similar to always declining with a very
short timeout (violation of guideline (3)).FrameworkInfo.offer_filters: This allows the scheduler to specify
global offer filters (Decline filters, on the other hand, are per-agent).
Currently supported is OfferFilters.min_allocatable_resources which acts as
an override of the cluster level --min_allocatable_resources master flag for
each of the scheduler’s roles. Keeping the FrameworkInfo.offer_filters
up-to-date with the minimum desired offer shape for each role will ensure that
the sccheduler gets a better chance to receive offers sized with sufficient
resources.SUBSCRIBE/UPDATE_FRAMEWORK
calls so that the framework role’s quota is not consumed by offers that the
scheduler will have to decline anyway based on agent attributes.
See MESOS-10161
and scheduler.proto
for more details.Operationally, the following can be done to ensure that schedulers get the resources they need when co-existing with other schedulers:
--min_allocatable_resources flag should be set
(e.g. --min_allocatable_resources=cpus:0.1,mem:32:disk:32) to prevent offers
that are missing cpu, memory, or disk
(see MESOS-8935).--role_sorter=random
and --framework_sorter=random (see
MESOS-8936).See the Offer Starvation Design Document in MESOS-3202 for more information about the pitfalls and future plans for running multiple schedulers.
Mesos provides a simple executor that can execute shell commands and Docker containers on behalf of the framework scheduler; enough functionality for a wide variety of framework requirements.
Any scheduler can make use of the Mesos command executor by filling in the
optional CommandInfo member of the TaskInfo protobuf message.
message TaskInfo {
...
optional CommandInfo command = 7;
...
}
The Mesos slave will fill in the rest of the ExecutorInfo for you when tasks
are specified this way.
Note that the agent will derive an ExecutorInfo from the TaskInfo and
additionally copy fields (e.g., Labels) from TaskInfo into the new
ExecutorInfo. This ExecutorInfo is only visible on the agent.
Since Mesos 1.1, a new built-in default executor (experimental) is available that can execute a group of tasks. Just like the command executor the tasks can be shell commands or Docker containers.
The current semantics of the default executor are as folows:
– Task group is an atomic unit of deployment of a scheduler onto the default executor.
– The default executor can run one or more task groups (since Mesos 1.2) and each task group can be launched by the scheduler at different points in time.
– All task groups' tasks are launched as nested containers underneath the executor container.
– Task containers and executor container share resources like cpu, memory, network and volumes.
– Each task can have its own separate root file system (e.g., Docker image).
– There is no resource isolation between different tasks or task groups within an executor. Tasks' resources are added to the executor container.
– If any of the tasks exits with a non-zero exit code or killed by the scheduler, all the tasks in the task group are killed automatically. The default executor commits suicide if there are no active task groups.
Once the default executor is considered stable, the command executor will be deprecated in favor of it.
Any scheduler can make use of the Mesos default executor by setting ExecutorInfo.type
to DEFAULT when launching a group of tasks using the LAUNCH_GROUP offer operation.
If DEFAULT executor is explicitly specified when using LAUNCH offer operation, command
executor is used instead of the default executor. This might change in the future when the default
executor gets support for handling LAUNCH operation.
message ExecutorInfo {
...
optional Type type = 15;
...
}
If your framework has special requirements, you might want to provide your own Executor implementation. For example, you may not want a 1:1 relationship between tasks and processes.
If you are writing an executor against Mesos 1.0 or newer, it is recommended to use the new HTTP API to talk to Mesos.
If writing against Mesos 0.28.0 or older, your framework executor must inherit
from the Executor class (see (see: C++,
Java,
Python). It must override the launchTask() method. You can use
the $MESOS_HOME environment variable inside of your executor to determine where
Mesos is running from. Your executor should create an ExecutorDriver (which will
mediate communication between your executor and the Mesos agent) and then call
ExecutorDriver.run()
(see: C++,
Java,
Python).
After creating your custom executor, you need to make it available to all slaves in the cluster.
One way to distribute your framework executor is to let the
Mesos fetcher download it on-demand when your scheduler launches
tasks on that slave. ExecutorInfo is a Protocol Buffer Message class (defined
in include/mesos/mesos.proto), and it contains a field of type CommandInfo.
CommandInfo allows schedulers to specify, among other things, a number of
resources as URIs. These resources are fetched to a sandbox directory on the
slave before attempting to execute the ExecutorInfo command. Several URI
schemes are supported, including HTTP, FTP, HDFS, and S3 (e.g. see
src/examples/java/TestFramework.java for an example of this).
Alternatively, you can pass the frameworks_home configuration option
(defaults to: MESOS_HOME/frameworks) to your mesos-slave daemons when you
launch them to specify where your framework executors are stored (e.g. on an
NFS mount that is available to all slaves), then use a relative path in
CommandInfo.uris, and the slave will prepend the value of frameworks_home
to the relative path provided.
Once you are sure that your executors are available to the mesos-slaves, you should be able to run your scheduler, which will register with the Mesos master, and start receiving resource offers!
Labels can be found in the FrameworkInfo, TaskInfo, DiscoveryInfo and
TaskStatus messages; framework and module writers can use Labels to tag and
pass unstructured information around Mesos. Labels are free-form key-value pairs
supplied by the framework scheduler or label decorator hooks. Below is the
protobuf definitions of labels:
optional Labels labels = 11;
/**
* Collection of labels.
*/
message Labels {
repeated Label labels = 1;
}
/**
* Key, value pair used to store free form user-data.
*/
message Label {
required string key = 1;
optional string value = 2;
}
Labels are not interpreted by Mesos itself, but will be made available over
master and slave state endpoints. Further more, the executor and scheduler can
introspect labels on the TaskInfo and TaskStatus programmatically.
Below is an example of how two label pairs ("environment": "prod" and
"bananas": "apples") can be fetched from the master state endpoint.
$ curl http://master/state.json
...
{
"executor_id": "default",
"framework_id": "20150312-120017-16777343-5050-39028-0000",
"id": "3",
"labels": [
{
"key": "environment",
"value": "prod"
},
{
"key": "bananas",
"value": "apples"
}
],
"name": "Task 3",
"slave_id": "20150312-115625-16777343-5050-38751-S0",
"state": "TASK_FINISHED",
...
},
When your framework registers an executor or launches a task, it can provide additional information for service discovery. This information is stored by the Mesos master along with other imporant information such as the slave currently running the task. A service discovery system can programmatically retrieve this information in order to set up DNS entries, configure proxies, or update any consistent store used for service discovery in a Mesos cluster that runs multiple frameworks and multiple tasks.
The optional DiscoveryInfo message for TaskInfo and ExecutorInfo is
declared in MESOS_HOME/include/mesos/mesos.proto
message DiscoveryInfo {
enum Visibility {
FRAMEWORK = 0;
CLUSTER = 1;
EXTERNAL = 2;
}
required Visibility visibility = 1;
optional string name = 2;
optional string environment = 3;
optional string location = 4;
optional string version = 5;
optional Ports ports = 6;
optional Labels labels = 7;
}
Visibility is the key parameter that instructs the service discovery system
whether a service should be discoverable. We currently differentiate between
three cases:
Many service discovery systems provide additional features that manage the
visibility of services (e.g., ACLs in proxy based systems, security extensions
to DNS, VLAN or subnet selection). It is not the intended use of the visibility
field to manage such features. When a service discovery system retrieves the
task or executor information from the master, it can decide how to handle tasks
without DiscoveryInfo. For instance, tasks may be made non discoverable to
other frameworks (equivalent to visibility=FRAMEWORK) or discoverable to all
frameworks (equivalent to visibility=CLUSTER).
The name field is a string that provides the service discovery system
with the name under which the task is discoverable. The typical use of the name
field will be to provide a valid hostname. If name is not provided, it is up to
the service discovery system to create a name for the task based on the name
field in taskInfo or other information.
The environment, location, and version fields provide first class support
for common attributes used to differentiate between similar services in large
deployments. The environment may receive values such as PROD/QA/DEV, the
location field may receive values like EAST-US/WEST-US/EUROPE/AMEA, and the
version field may receive values like v2.0/v0.9. The exact use of these fields
is up to the service discovery system.
The ports field allows the framework to identify the ports a task listens to
and explicitly name the functionality they represent and the layer-4 protocol
they use (TCP, UDP, or other). For example, a Cassandra task will define ports
like "7000,Cluster,TCP", "7001,SSL,TCP", "9160,Thrift,TCP",
"9042,Native,TCP", and "7199,JMX,TCP". It is up to the service discovery
system to use these names and protocol in appropriate ways, potentially
combining them with the name field in DiscoveryInfo.
The labels field allows a framework to pass arbitrary labels to the service
discovery system in the form of key/value pairs. Note that anything passed
through this field is not guaranteed to be supported moving forward.
Nevertheless, this field provides extensibility. Common uses of this field will
allow us to identify use cases that require first class support.
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