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From s...@apache.org
Subject [6/7] aurora git commit: Reorganize Documentation
Date Mon, 28 Mar 2016 20:55:47 GMT
http://git-wip-us.apache.org/repos/asf/aurora/blob/f28f41a7/docs/configuration-tutorial.md
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-Aurora Configuration Tutorial
-=============================
-
-How to write Aurora configuration files, including feature descriptions
-and best practices. When writing a configuration file, make use of
-`aurora job inspect`. It takes the same job key and configuration file
-arguments as `aurora job create` or `aurora update start`. It first ensures the
-configuration parses, then outputs it in human-readable form.
-
-You should read this after going through the general [Aurora Tutorial](tutorial.md).
-
-- [Aurora Configuration Tutorial](#user-content-aurora-configuration-tutorial)
-	- [The Basics](#user-content-the-basics)
-		- [Use Bottom-To-Top Object Ordering](#user-content-use-bottom-to-top-object-ordering)
-	- [An Example Configuration File](#user-content-an-example-configuration-file)
-	- [Defining Process Objects](#user-content-defining-process-objects)
-	- [Getting Your Code Into The Sandbox](#user-content-getting-your-code-into-the-sandbox)
-	- [Defining Task Objects](#user-content-defining-task-objects)
-		- [SequentialTask: Running Processes in Parallel or Sequentially](#user-content-sequentialtask-running-processes-in-parallel-or-sequentially)
-		- [SimpleTask](#user-content-simpletask)
-		- [Combining tasks](#user-content-combining-tasks)
-	- [Defining Job Objects](#user-content-defining-job-objects)
-	- [The jobs List](#user-content-the-jobs-list)
-	- [Templating](#user-content-templating)
-		- [Templating 1: Binding in Pystachio](#user-content-templating-1-binding-in-pystachio)
-		- [Structurals in Pystachio / Aurora](#user-content-structurals-in-pystachio--aurora)
-			- [Mustaches Within Structurals](#user-content-mustaches-within-structurals)
-		- [Templating 2: Structurals Are Factories](#user-content-templating-2-structurals-are-factories)
-			- [A Second Way of Templating](#user-content-a-second-way-of-templating)
-		- [Advanced Binding](#user-content-advanced-binding)
-			- [Bind Syntax](#user-content-bind-syntax)
-			- [Binding Complex Objects](#user-content-binding-complex-objects)
-				- [Lists](#user-content-lists)
-				- [Maps](#user-content-maps)
-				- [Structurals](#user-content-structurals)
-		- [Structural Binding](#user-content-structural-binding)
-	- [Configuration File Writing Tips And Best Practices](#user-content-configuration-file-writing-tips-and-best-practices)
-		- [Use As Few .aurora Files As Possible](#user-content-use-as-few-aurora-files-as-possible)
-		- [Avoid Boilerplate](#user-content-avoid-boilerplate)
-		- [Thermos Uses bash, But Thermos Is Not bash](#user-content-thermos-uses-bash-but-thermos-is-not-bash)
-			- [Bad](#user-content-bad)
-			- [Good](#user-content-good)
-		- [Rarely Use Functions In Your Configurations](#user-content-rarely-use-functions-in-your-configurations)
-			- [Bad](#user-content-bad-1)
-			- [Good](#user-content-good-1)
-
-The Basics
-----------
-
-To run a job on Aurora, you must specify a configuration file that tells
-Aurora what it needs to know to schedule the job, what Mesos needs to
-run the tasks the job is made up of, and what Thermos needs to run the
-processes that make up the tasks. This file must have
-a`.aurora` suffix.
-
-A configuration file defines a collection of objects, along with parameter
-values for their attributes. An Aurora configuration file contains the
-following three types of objects:
-
-- Job
-- Task
-- Process
-
-A configuration also specifies a list of `Job` objects assigned
-to the variable `jobs`.
-
-- jobs (list of defined Jobs to run)
-
-The `.aurora` file format is just Python. However, `Job`, `Task`,
-`Process`, and other classes are defined by a type-checked dictionary
-templating library called *Pystachio*, a powerful tool for
-configuration specification and reuse. Pystachio objects are tailored
-via {{}} surrounded templates.
-
-When writing your `.aurora` file, you may use any Pystachio datatypes, as
-well as any objects shown in the [*Aurora+Thermos Configuration
-Reference*](configuration-reference.md), without `import` statements - the
-Aurora config loader injects them automatically. Other than that, an `.aurora`
-file works like any other Python script.
-
-[*Aurora+Thermos Configuration Reference*](configuration-reference.md)
-has a full reference of all Aurora/Thermos defined Pystachio objects.
-
-### Use Bottom-To-Top Object Ordering
-
-A well-structured configuration starts with structural templates (if
-any). Structural templates encapsulate in their attributes all the
-differences between Jobs in the configuration that are not directly
-manipulated at the `Job` level, but typically at the `Process` or `Task`
-level. For example, if certain processes are invoked with slightly
-different settings or input.
-
-After structural templates, define, in order, `Process`es, `Task`s, and
-`Job`s.
-
-Structural template names should be *UpperCamelCased* and their
-instantiations are typically *UPPER\_SNAKE\_CASED*. `Process`, `Task`,
-and `Job` names are typically *lower\_snake\_cased*. Indentation is typically 2
-spaces.
-
-An Example Configuration File
------------------------------
-
-The following is a typical configuration file. Don't worry if there are
-parts you don't understand yet, but you may want to refer back to this
-as you read about its individual parts. Note that names surrounded by
-curly braces {{}} are template variables, which the system replaces with
-bound values for the variables.
-
-    # --- templates here ---
-	class Profile(Struct):
-	  package_version = Default(String, 'live')
-	  java_binary = Default(String, '/usr/lib/jvm/java-1.7.0-openjdk/bin/java')
-	  extra_jvm_options = Default(String, '')
-	  parent_environment = Default(String, 'prod')
-	  parent_serverset = Default(String,
-                                 '/foocorp/service/bird/{{parent_environment}}/bird')
-
-	# --- processes here ---
-	main = Process(
-	  name = 'application',
-	  cmdline = '{{profile.java_binary}} -server -Xmx1792m '
-	            '{{profile.extra_jvm_options}} '
-	            '-jar application.jar '
-	            '-upstreamService {{profile.parent_serverset}}'
-	)
-
-	# --- tasks ---
-	base_task = SequentialTask(
-	  name = 'application',
-	  processes = [
-	    Process(
-	      name = 'fetch',
-	      cmdline = 'curl -O
-                  https://packages.foocorp.com/{{profile.package_version}}/application.jar'),
-	  ]
-	)
-
-        # not always necessary but often useful to have separate task
-        # resource classes
-        staging_task = base_task(resources =
-                         Resources(cpu = 1.0,
-                                   ram = 2048*MB,
-                                   disk = 1*GB))
-	production_task = base_task(resources =
-                            Resources(cpu = 4.0,
-                                      ram = 2560*MB,
-                                      disk = 10*GB))
-
-	# --- job template ---
-	job_template = Job(
-	  name = 'application',
-	  role = 'myteam',
-	  contact = 'myteam-team@foocorp.com',
-	  instances = 20,
-	  service = True,
-	  task = production_task
-	)
-
-	# -- profile instantiations (if any) ---
-	PRODUCTION = Profile()
-	STAGING = Profile(
-	  extra_jvm_options = '-Xloggc:gc.log',
-	  parent_environment = 'staging'
-	)
-
-	# -- job instantiations --
-	jobs = [
-          job_template(cluster = 'cluster1', environment = 'prod')
-	               .bind(profile = PRODUCTION),
-
-          job_template(cluster = 'cluster2', environment = 'prod')
-	                .bind(profile = PRODUCTION),
-
-          job_template(cluster = 'cluster1',
-                        environment = 'staging',
-			service = False,
-			task = staging_task,
-			instances = 2)
-			.bind(profile = STAGING),
-	]
-
-## Defining Process Objects
-
-Processes are handled by the Thermos system. A process is a single
-executable step run as a part of an Aurora task, which consists of a
-bash-executable statement.
-
-The key (and required) `Process` attributes are:
-
--   `name`: Any string which is a valid Unix filename (no slashes,
-    NULLs, or leading periods). The `name` value must be unique relative
-    to other Processes in a `Task`.
--   `cmdline`: A command line run in a bash subshell, so you can use
-    bash scripts. Nothing is supplied for command-line arguments,
-    so `$*` is unspecified.
-
-Many tiny processes make managing configurations more difficult. For
-example, the following is a bad way to define processes.
-
-    copy = Process(
-      name = 'copy',
-      cmdline = 'curl -O https://packages.foocorp.com/app.zip'
-    )
-    unpack = Process(
-      name = 'unpack',
-      cmdline = 'unzip app.zip'
-    )
-    remove = Process(
-      name = 'remove',
-      cmdline = 'rm -f app.zip'
-    )
-    run = Process(
-      name = 'app',
-      cmdline = 'java -jar app.jar'
-    )
-    run_task = Task(
-      processes = [copy, unpack, remove, run],
-      constraints = order(copy, unpack, remove, run)
-    )
-
-Since `cmdline` runs in a bash subshell, you can chain commands
-with `&&` or `||`.
-
-When defining a `Task` that is just a list of Processes run in a
-particular order, use `SequentialTask`, as described in the [*Defining*
-`Task` *Objects*](#Task) section. The following simplifies and combines the
-above multiple `Process` definitions into just two.
-
-    stage = Process(
-      name = 'stage',
-      cmdline = 'curl -O https://packages.foocorp.com/app.zip && '
-                'unzip app.zip && rm -f app.zip')
-
-    run = Process(name = 'app', cmdline = 'java -jar app.jar')
-
-    run_task = SequentialTask(processes = [stage, run])
-
-`Process` also has optional attributes to customize its behaviour. Details can be found in the [*Aurora+Thermos Configuration Reference*](configuration-reference.md#process-objects).
-
-
-## Getting Your Code Into The Sandbox
-
-When using Aurora, you need to get your executable code into its "sandbox", specifically
-the Task sandbox where the code executes for the Processes that make up that Task.
-
-Each Task has a sandbox created when the Task starts and garbage
-collected when it finishes. All of a Task's processes run in its
-sandbox, so processes can share state by using a shared current
-working directory.
-
-Typically, you save this code somewhere. You then need to define a Process
-in your `.aurora` configuration file that fetches the code from that somewhere
-to where the slave can see it. For a public cloud, that can be anywhere public on
-the Internet, such as S3. For a private cloud internal storage, you need to put in
-on an accessible HDFS cluster or similar storage.
-
-The template for this Process is:
-
-    <name> = Process(
-      name = '<name>'
-      cmdline = '<command to copy and extract code archive into current working directory>'
-    )
-
-Note: Be sure the extracted code archive has an executable.
-
-## Defining Task Objects
-
-Tasks are handled by Mesos. A task is a collection of processes that
-runs in a shared sandbox. It's the fundamental unit Aurora uses to
-schedule the datacenter; essentially what Aurora does is find places
-in the cluster to run tasks.
-
-The key (and required) parts of a Task are:
-
--   `name`: A string giving the Task's name. By default, if a Task is
-    not given a name, it inherits the first name in its Process list.
-
--   `processes`: An unordered list of Process objects bound to the Task.
-    The value of the optional `constraints` attribute affects the
-    contents as a whole. Currently, the only constraint, `order`, determines if
-    the processes run in parallel or sequentially.
-
--   `resources`: A `Resource` object defining the Task's resource
-        footprint. A `Resource` object has three attributes:
-        -   `cpu`: A Float, the fractional number of cores the Task
-        requires.
-        -   `ram`: An Integer, RAM bytes the Task requires.
-        -   `disk`: An integer, disk bytes the Task requires.
-
-A basic Task definition looks like:
-
-    Task(
-        name="hello_world",
-        processes=[Process(name = "hello_world", cmdline = "echo hello world")],
-        resources=Resources(cpu = 1.0,
-                            ram = 1*GB,
-                            disk = 1*GB))
-
-A Task has optional attributes to customize its behaviour. Details can be found in the [*Aurora+Thermos Configuration Reference*](configuration-reference.md#task-object)
-
-
-### SequentialTask: Running Processes in Parallel or Sequentially
-
-By default, a Task with several Processes runs them in parallel. There
-are two ways to run Processes sequentially:
-
--   Include an `order` constraint in the Task definition's `constraints`
-    attribute whose arguments specify the processes' run order:
-
-        Task( ... processes=[process1, process2, process3],
-	          constraints = order(process1, process2, process3), ...)
-
--   Use `SequentialTask` instead of `Task`; it automatically runs
-    processes in the order specified in the `processes` attribute. No
-    `constraint` parameter is needed:
-
-        SequentialTask( ... processes=[process1, process2, process3] ...)
-
-### SimpleTask
-
-For quickly creating simple tasks, use the `SimpleTask` helper. It
-creates a basic task from a provided name and command line using a
-default set of resources. For example, in a .`aurora` configuration
-file:
-
-    SimpleTask(name="hello_world", command="echo hello world")
-
-is equivalent to
-
-    Task(name="hello_world",
-         processes=[Process(name = "hello_world", cmdline = "echo hello world")],
-         resources=Resources(cpu = 1.0,
-                             ram = 1*GB,
-                             disk = 1*GB))
-
-The simplest idiomatic Job configuration thus becomes:
-
-    import os
-    hello_world_job = Job(
-      task=SimpleTask(name="hello_world", command="echo hello world"),
-      role=os.getenv('USER'),
-      cluster="cluster1")
-
-When written to `hello_world.aurora`, you invoke it with a simple
-`aurora job create cluster1/$USER/test/hello_world hello_world.aurora`.
-
-### Combining tasks
-
-`Tasks.concat`(synonym,`concat_tasks`) and
-`Tasks.combine`(synonym,`combine_tasks`) merge multiple Task definitions
-into a single Task. It may be easier to define complex Jobs
-as smaller constituent Tasks. But since a Job only includes a single
-Task, the subtasks must be combined before using them in a Job.
-Smaller Tasks can also be reused between Jobs, instead of having to
-repeat their definition for multiple Jobs.
-
-With both methods, the merged Task takes the first Task's name. The
-difference between the two is the result Task's process ordering.
-
--   `Tasks.combine` runs its subtasks' processes in no particular order.
-    The new Task's resource consumption is the sum of all its subtasks'
-    consumption.
-
--   `Tasks.concat` runs its subtasks in the order supplied, with each
-    subtask's processes run serially between tasks. It is analogous to
-    the `order` constraint helper, except at the Task level instead of
-    the Process level. The new Task's resource consumption is the
-    maximum value specified by any subtask for each Resource attribute
-    (cpu, ram and disk).
-
-For example, given the following:
-
-    setup_task = Task(
-      ...
-      processes=[download_interpreter, update_zookeeper],
-      # It is important to note that {{Tasks.concat}} has
-      # no effect on the ordering of the processes within a task;
-      # hence the necessity of the {{order}} statement below
-      # (otherwise, the order in which {{download_interpreter}}
-      # and {{update_zookeeper}} run will be non-deterministic)
-      constraints=order(download_interpreter, update_zookeeper),
-      ...
-    )
-
-    run_task = SequentialTask(
-      ...
-      processes=[download_application, start_application],
-      ...
-    )
-
-    combined_task = Tasks.concat(setup_task, run_task)
-
-The `Tasks.concat` command merges the two Tasks into a single Task and
-ensures all processes in `setup_task` run before the processes
-in `run_task`. Conceptually, the task is reduced to:
-
-    task = Task(
-      ...
-      processes=[download_interpreter, update_zookeeper,
-                 download_application, start_application],
-      constraints=order(download_interpreter, update_zookeeper,
-                        download_application, start_application),
-      ...
-    )
-
-In the case of `Tasks.combine`, the two schedules run in parallel:
-
-    task = Task(
-      ...
-      processes=[download_interpreter, update_zookeeper,
-                 download_application, start_application],
-      constraints=order(download_interpreter, update_zookeeper) +
-                        order(download_application, start_application),
-      ...
-    )
-
-In the latter case, each of the two sequences may operate in parallel.
-Of course, this may not be the intended behavior (for example, if
-the `start_application` Process implicitly relies
-upon `download_interpreter`). Make sure you understand the difference
-between using one or the other.
-
-## Defining Job Objects
-
-A job is a group of identical tasks that Aurora can run in a Mesos cluster.
-
-A `Job` object is defined by the values of several attributes, some
-required and some optional. The required attributes are:
-
--   `task`: Task object to bind to this job. Note that a Job can
-    only take a single Task.
-
--   `role`: Job's role account; in other words, the user account to run
-    the job as on a Mesos cluster machine. A common value is
-    `os.getenv('USER')`; using a Python command to get the user who
-    submits the job request. The other common value is the service
-    account that runs the job, e.g. `www-data`.
-
--   `environment`: Job's environment, typical values
-    are `devel`, `test`, or `prod`.
-
--   `cluster`: Aurora cluster to schedule the job in, defined in
-    `/etc/aurora/clusters.json` or `~/.clusters.json`. You can specify
-    jobs where the only difference is the `cluster`, then at run time
-    only run the Job whose job key includes your desired cluster's name.
-
-You usually see a `name` parameter. By default, `name` inherits its
-value from the Job's associated Task object, but you can override this
-default. For these four parameters, a Job definition might look like:
-
-    foo_job = Job( name = 'foo', cluster = 'cluster1',
-              role = os.getenv('USER'), environment = 'prod',
-              task = foo_task)
-
-In addition to the required attributes, there are several optional
-attributes. Details can be found in the [Aurora+Thermos Configuration Reference](configuration-reference.md#job-objects).
-
-
-## The jobs List
-
-At the end of your `.aurora` file, you need to specify a list of the
-file's defined Jobs. For example, the following exports the jobs `job1`,
-`job2`, and `job3`.
-
-    jobs = [job1, job2, job3]
-
-This allows the aurora client to invoke commands on those jobs, such as
-starting, updating, or killing them.
-
-Templating
-----------
-
-The `.aurora` file format is just Python. However, `Job`, `Task`,
-`Process`, and other classes are defined by a templating library called
-*Pystachio*, a powerful tool for configuration specification and reuse.
-
-[Aurora+Thermos Configuration Reference](configuration-reference.md)
-has a full reference of all Aurora/Thermos defined Pystachio objects.
-
-When writing your `.aurora` file, you may use any Pystachio datatypes, as
-well as any objects shown in the *Aurora+Thermos Configuration
-Reference* without `import` statements - the Aurora config loader
-injects them automatically. Other than that the `.aurora` format
-works like any other Python script.
-
-### Templating 1: Binding in Pystachio
-
-Pystachio uses the visually distinctive {{}} to indicate template
-variables. These are often called "mustache variables" after the
-similarly appearing variables in the Mustache templating system and
-because the curly braces resemble mustaches.
-
-If you are familiar with the Mustache system, templates in Pystachio
-have significant differences. They have no nesting, joining, or
-inheritance semantics. On the other hand, when evaluated, templates
-are evaluated iteratively, so this affords some level of indirection.
-
-Let's start with the simplest template; text with one
-variable, in this case `name`;
-
-    Hello {{name}}
-
-If we evaluate this as is, we'd get back:
-
-    Hello
-
-If a template variable doesn't have a value, when evaluated it's
-replaced with nothing. If we add a binding to give it a value:
-
-    { "name" : "Tom" }
-
-We'd get back:
-
-    Hello Tom
-
-Every Pystachio object has an associated `.bind` method that can bind
-values to {{}} variables. Bindings are not immediately evaluated.
-Instead, they are evaluated only when the interpolated value of the
-object is necessary, e.g. for performing equality or serializing a
-message over the wire.
-
-Objects with and without mustache templated variables behave
-differently:
-
-    >>> Float(1.5)
-    Float(1.5)
-
-    >>> Float('{{x}}.5')
-    Float({{x}}.5)
-
-    >>> Float('{{x}}.5').bind(x = 1)
-    Float(1.5)
-
-    >>> Float('{{x}}.5').bind(x = 1) == Float(1.5)
-    True
-
-    >>> contextual_object = String('{{metavar{{number}}}}').bind(
-    ... metavar1 = "first", metavar2 = "second")
-
-    >>> contextual_object
-    String({{metavar{{number}}}})
-
-    >>> contextual_object.bind(number = 1)
-    String(first)
-
-    >>> contextual_object.bind(number = 2)
-    String(second)
-
-You usually bind simple key to value pairs, but you can also bind three
-other objects: lists, dictionaries, and structurals. These will be
-described in detail later.
-
-### Structurals in Pystachio / Aurora
-
-Most Aurora/Thermos users don't ever (knowingly) interact with `String`,
-`Float`, or `Integer` Pystashio objects directly. Instead they interact
-with derived structural (`Struct`) objects that are collections of
-fundamental and structural objects. The structural object components are
-called *attributes*. Aurora's most used structural objects are `Job`,
-`Task`, and `Process`:
-
-    class Process(Struct):
-      cmdline = Required(String)
-      name = Required(String)
-      max_failures = Default(Integer, 1)
-      daemon = Default(Boolean, False)
-      ephemeral = Default(Boolean, False)
-      min_duration = Default(Integer, 5)
-      final = Default(Boolean, False)
-
-Construct default objects by following the object's type with (). If you
-want an attribute to have a value different from its default, include
-the attribute name and value inside the parentheses.
-
-    >>> Process()
-    Process(daemon=False, max_failures=1, ephemeral=False,
-      min_duration=5, final=False)
-
-Attribute values can be template variables, which then receive specific
-values when creating the object.
-
-    >>> Process(cmdline = 'echo {{message}}')
-    Process(daemon=False, max_failures=1, ephemeral=False, min_duration=5,
-            cmdline=echo {{message}}, final=False)
-
-    >>> Process(cmdline = 'echo {{message}}').bind(message = 'hello world')
-    Process(daemon=False, max_failures=1, ephemeral=False, min_duration=5,
-            cmdline=echo hello world, final=False)
-
-A powerful binding property is that all of an object's children inherit its
-bindings:
-
-    >>> List(Process)([
-    ... Process(name = '{{prefix}}_one'),
-    ... Process(name = '{{prefix}}_two')
-    ... ]).bind(prefix = 'hello')
-    ProcessList(
-      Process(daemon=False, name=hello_one, max_failures=1, ephemeral=False, min_duration=5, final=False),
-      Process(daemon=False, name=hello_two, max_failures=1, ephemeral=False, min_duration=5, final=False)
-      )
-
-Remember that an Aurora Job contains Tasks which contain Processes. A
-Job level binding is inherited by its Tasks and all their Processes.
-Similarly a Task level binding is available to that Task and its
-Processes but is *not* visible at the Job level (inheritance is a
-one-way street.)
-
-#### Mustaches Within Structurals
-
-When you define a `Struct` schema, one powerful, but confusing, feature
-is that all of that structure's attributes are Mustache variables within
-the enclosing scope *once they have been populated*.
-
-For example, when `Process` is defined above, all its attributes such as
-{{`name`}}, {{`cmdline`}}, {{`max_failures`}} etc., are all immediately
-defined as Mustache variables, implicitly bound into the `Process`, and
-inherit all child objects once they are defined.
-
-Thus, you can do the following:
-
-    >>> Process(name = "installer", cmdline = "echo {{name}} is running")
-    Process(daemon=False, name=installer, max_failures=1, ephemeral=False, min_duration=5,
-            cmdline=echo installer is running, final=False)
-
-WARNING: This binding only takes place in one direction. For example,
-the following does NOT work and does not set the `Process` `name`
-attribute's value.
-
-    >>> Process().bind(name = "installer")
-    Process(daemon=False, max_failures=1, ephemeral=False, min_duration=5, final=False)
-
-The following is also not possible and results in an infinite loop that
-attempts to resolve `Process.name`.
-
-    >>> Process(name = '{{name}}').bind(name = 'installer')
-
-Do not confuse Structural attributes with bound Mustache variables.
-Attributes are implicitly converted to Mustache variables but not vice
-versa.
-
-### Templating 2: Structurals Are Factories
-
-#### A Second Way of Templating
-
-A second templating method is both as powerful as the aforementioned and
-often confused with it. This method is due to automatic conversion of
-Struct attributes to Mustache variables as described above.
-
-Suppose you create a Process object:
-
-    >>> p = Process(name = "process_one", cmdline = "echo hello world")
-
-    >>> p
-    Process(daemon=False, name=process_one, max_failures=1, ephemeral=False, min_duration=5,
-            cmdline=echo hello world, final=False)
-
-This `Process` object, "`p`", can be used wherever a `Process` object is
-needed. It can also be reused by changing the value(s) of its
-attribute(s). Here we change its `name` attribute from `process_one` to
-`process_two`.
-
-    >>> p(name = "process_two")
-    Process(daemon=False, name=process_two, max_failures=1, ephemeral=False, min_duration=5,
-            cmdline=echo hello world, final=False)
-
-Template creation is a common use for this technique:
-
-    >>> Daemon = Process(daemon = True)
-    >>> logrotate = Daemon(name = 'logrotate', cmdline = './logrotate conf/logrotate.conf')
-    >>> mysql = Daemon(name = 'mysql', cmdline = 'bin/mysqld --safe-mode')
-
-### Advanced Binding
-
-As described above, `.bind()` binds simple strings or numbers to
-Mustache variables. In addition to Structural types formed by combining
-atomic types, Pystachio has two container types; `List` and `Map` which
-can also be bound via `.bind()`.
-
-#### Bind Syntax
-
-The `bind()` function can take Python dictionaries or `kwargs`
-interchangeably (when "`kwargs`" is in a function definition, `kwargs`
-receives a Python dictionary containing all keyword arguments after the
-formal parameter list).
-
-    >>> String('{{foo}}').bind(foo = 'bar') == String('{{foo}}').bind({'foo': 'bar'})
-    True
-
-Bindings done "closer" to the object in question take precedence:
-
-    >>> p = Process(name = '{{context}}_process')
-    >>> t = Task().bind(context = 'global')
-    >>> t(processes = [p, p.bind(context = 'local')])
-    Task(processes=ProcessList(
-      Process(daemon=False, name=global_process, max_failures=1, ephemeral=False, final=False,
-              min_duration=5),
-      Process(daemon=False, name=local_process, max_failures=1, ephemeral=False, final=False,
-              min_duration=5)
-    ))
-
-#### Binding Complex Objects
-
-##### Lists
-
-    >>> fibonacci = List(Integer)([1, 1, 2, 3, 5, 8, 13])
-    >>> String('{{fib[4]}}').bind(fib = fibonacci)
-    String(5)
-
-##### Maps
-
-    >>> first_names = Map(String, String)({'Kent': 'Clark', 'Wayne': 'Bruce', 'Prince': 'Diana'})
-    >>> String('{{first[Kent]}}').bind(first = first_names)
-    String(Clark)
-
-##### Structurals
-
-    >>> String('{{p.cmdline}}').bind(p = Process(cmdline = "echo hello world"))
-    String(echo hello world)
-
-### Structural Binding
-
-Use structural templates when binding more than two or three individual
-values at the Job or Task level. For fewer than two or three, standard
-key to string binding is sufficient.
-
-Structural binding is a very powerful pattern and is most useful in
-Aurora/Thermos for doing Structural configuration. For example, you can
-define a job profile. The following profile uses `HDFS`, the Hadoop
-Distributed File System, to designate a file's location. `HDFS` does
-not come with Aurora, so you'll need to either install it separately
-or change the way the dataset is designated.
-
-    class Profile(Struct):
-      version = Required(String)
-      environment = Required(String)
-      dataset = Default(String, hdfs://home/aurora/data/{{environment}}')
-
-    PRODUCTION = Profile(version = 'live', environment = 'prod')
-    DEVEL = Profile(version = 'latest',
-                    environment = 'devel',
-                    dataset = 'hdfs://home/aurora/data/test')
-    TEST = Profile(version = 'latest', environment = 'test')
-
-    JOB_TEMPLATE = Job(
-      name = 'application',
-      role = 'myteam',
-      cluster = 'cluster1',
-      environment = '{{profile.environment}}',
-      task = SequentialTask(
-        name = 'task',
-        resources = Resources(cpu = 2, ram = 4*GB, disk = 8*GB),
-        processes = [
-	  Process(name = 'main', cmdline = 'java -jar application.jar -hdfsPath
-                 {{profile.dataset}}')
-        ]
-       )
-     )
-
-    jobs = [
-      JOB_TEMPLATE(instances = 100).bind(profile = PRODUCTION),
-      JOB_TEMPLATE.bind(profile = DEVEL),
-      JOB_TEMPLATE.bind(profile = TEST),
-     ]
-
-In this case, a custom structural "Profile" is created to self-document
-the configuration to some degree. This also allows some schema
-"type-checking", and for default self-substitution, e.g. in
-`Profile.dataset` above.
-
-So rather than a `.bind()` with a half-dozen substituted variables, you
-can bind a single object that has sensible defaults stored in a single
-place.
-
-Configuration File Writing Tips And Best Practices
---------------------------------------------------
-
-### Use As Few .aurora Files As Possible
-
-When creating your `.aurora` configuration, try to keep all versions of
-a particular job within the same `.aurora` file. For example, if you
-have separate jobs for `cluster1`, `cluster1` staging, `cluster1`
-testing, and`cluster2`, keep them as close together as possible.
-
-Constructs shared across multiple jobs owned by your team (e.g.
-team-level defaults or structural templates) can be split into separate
-`.aurora`files and included via the `include` directive.
-
-### Avoid Boilerplate
-
-If you see repetition or find yourself copy and pasting any parts of
-your configuration, it's likely an opportunity for templating. Take the
-example below:
-
-`redundant.aurora` contains:
-
-    download = Process(
-      name = 'download',
-      cmdline = 'wget http://www.python.org/ftp/python/2.7.3/Python-2.7.3.tar.bz2',
-      max_failures = 5,
-      min_duration = 1)
-
-    unpack = Process(
-      name = 'unpack',
-      cmdline = 'rm -rf Python-2.7.3 && tar xzf Python-2.7.3.tar.bz2',
-      max_failures = 5,
-      min_duration = 1)
-
-    build = Process(
-      name = 'build',
-      cmdline = 'pushd Python-2.7.3 && ./configure && make && popd',
-      max_failures = 1)
-
-    email = Process(
-      name = 'email',
-      cmdline = 'echo Success | mail feynman@tmc.com',
-      max_failures = 5,
-      min_duration = 1)
-
-    build_python = Task(
-      name = 'build_python',
-      processes = [download, unpack, build, email],
-      constraints = [Constraint(order = ['download', 'unpack', 'build', 'email'])])
-
-As you'll notice, there's a lot of repetition in the `Process`
-definitions. For example, almost every process sets a `max_failures`
-limit to 5 and a `min_duration` to 1. This is an opportunity for factoring
-into a common process template.
-
-Furthermore, the Python version is repeated everywhere. This can be
-bound via structural templating as described in the [Advanced Binding](#AdvancedBinding)
-section.
-
-`less_redundant.aurora` contains:
-
-    class Python(Struct):
-      version = Required(String)
-      base = Default(String, 'Python-{{version}}')
-      package = Default(String, '{{base}}.tar.bz2')
-
-    ReliableProcess = Process(
-      max_failures = 5,
-      min_duration = 1)
-
-    download = ReliableProcess(
-      name = 'download',
-      cmdline = 'wget http://www.python.org/ftp/python/{{python.version}}/{{python.package}}')
-
-    unpack = ReliableProcess(
-      name = 'unpack',
-      cmdline = 'rm -rf {{python.base}} && tar xzf {{python.package}}')
-
-    build = ReliableProcess(
-      name = 'build',
-      cmdline = 'pushd {{python.base}} && ./configure && make && popd',
-      max_failures = 1)
-
-    email = ReliableProcess(
-      name = 'email',
-      cmdline = 'echo Success | mail {{role}}@foocorp.com')
-
-    build_python = SequentialTask(
-      name = 'build_python',
-      processes = [download, unpack, build, email]).bind(python = Python(version = "2.7.3"))
-
-### Thermos Uses bash, But Thermos Is Not bash
-
-#### Bad
-
-Many tiny Processes makes for harder to manage configurations.
-
-    copy = Process(
-      name = 'copy',
-      cmdline = 'rcp user@my_machine:my_application .'
-     )
-
-     unpack = Process(
-       name = 'unpack',
-       cmdline = 'unzip app.zip'
-     )
-
-     remove = Process(
-       name = 'remove',
-       cmdline = 'rm -f app.zip'
-     )
-
-     run = Process(
-       name = 'app',
-       cmdline = 'java -jar app.jar'
-     )
-
-     run_task = Task(
-       processes = [copy, unpack, remove, run],
-       constraints = order(copy, unpack, remove, run)
-     )
-
-#### Good
-
-Each `cmdline` runs in a bash subshell, so you have the full power of
-bash. Chaining commands with `&&` or `||` is almost always the right
-thing to do.
-
-Also for Tasks that are simply a list of processes that run one after
-another, consider using the `SequentialTask` helper which applies a
-linear ordering constraint for you.
-
-    stage = Process(
-      name = 'stage',
-      cmdline = 'rcp user@my_machine:my_application . && unzip app.zip && rm -f app.zip')
-
-    run = Process(name = 'app', cmdline = 'java -jar app.jar')
-
-    run_task = SequentialTask(processes = [stage, run])
-
-### Rarely Use Functions In Your Configurations
-
-90% of the time you define a function in a `.aurora` file, you're
-probably Doing It Wrong(TM).
-
-#### Bad
-
-    def get_my_task(name, user, cpu, ram, disk):
-      return Task(
-        name = name,
-        user = user,
-        processes = [STAGE_PROCESS, RUN_PROCESS],
-        constraints = order(STAGE_PROCESS, RUN_PROCESS),
-        resources = Resources(cpu = cpu, ram = ram, disk = disk)
-     )
-
-     task_one = get_my_task('task_one', 'feynman', 1.0, 32*MB, 1*GB)
-     task_two = get_my_task('task_two', 'feynman', 2.0, 64*MB, 1*GB)
-
-#### Good
-
-This one is more idiomatic. Forced keyword arguments prevents accidents,
-e.g. constructing a task with "32*MB" when you mean 32MB of ram and not
-disk. Less proliferation of task-construction techniques means
-easier-to-read, quicker-to-understand, and a more composable
-configuration.
-
-    TASK_TEMPLATE = SequentialTask(
-      user = 'wickman',
-      processes = [STAGE_PROCESS, RUN_PROCESS],
-    )
-
-    task_one = TASK_TEMPLATE(
-      name = 'task_one',
-      resources = Resources(cpu = 1.0, ram = 32*MB, disk = 1*GB) )
-
-    task_two = TASK_TEMPLATE(
-      name = 'task_two',
-      resources = Resources(cpu = 2.0, ram = 64*MB, disk = 1*GB)
-    )

http://git-wip-us.apache.org/repos/asf/aurora/blob/f28f41a7/docs/cron-jobs.md
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diff --git a/docs/cron-jobs.md b/docs/cron-jobs.md
deleted file mode 100644
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--- a/docs/cron-jobs.md
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-# Cron Jobs
-
-Aurora supports execution of scheduled jobs on a Mesos cluster using cron-style syntax.
-
-- [Overview](#overview)
-- [Collision Policies](#collision-policies)
-	- [KILL_EXISTING](#kill_existing)
-	- [CANCEL_NEW](#cancel_new)
-- [Failure recovery](#failure-recovery)
-- [Interacting with cron jobs via the Aurora CLI](#interacting-with-cron-jobs-via-the-aurora-cli)
-	- [cron schedule](#cron-schedule)
-	- [cron deschedule](#cron-deschedule)
-	- [cron start](#cron-start)
-	- [job killall, job restart, job kill](#job-killall-job-restart-job-kill)
-- [Technical Note About Syntax](#technical-note-about-syntax)
-- [Caveats](#caveats)
-	- [Failovers](#failovers)
-	- [Collision policy is best-effort](#collision-policy-is-best-effort)
-	- [Timezone Configuration](#timezone-configuration)
-
-## Overview
-
-A job is identified as a cron job by the presence of a
-`cron_schedule` attribute containing a cron-style schedule in the
-[`Job`](configuration-reference.md#job-objects) object. Examples of cron schedules
-include "every 5 minutes" (`*/5 * * * *`), "Fridays at 17:00" (`* 17 * * FRI`), and
-"the 1st and 15th day of the month at 03:00" (`0 3 1,15 *`).
-
-Example (available in the [Vagrant environment](vagrant.md)):
-
-    $ cat /vagrant/examples/job/cron_hello_world.aurora
-    # cron_hello_world.aurora
-    # A cron job that runs every 5 minutes.
-    jobs = [
-      Job(
-        cluster = 'devcluster',
-        role = 'www-data',
-        environment = 'test',
-        name = 'cron_hello_world',
-        cron_schedule = '*/5 * * * *',
-        task = SimpleTask(
-          'cron_hello_world',
-          'echo "Hello world from cron, the time is now $(date --rfc-822)"'),
-      ),
-    ]
-
-## Collision Policies
-
-The `cron_collision_policy` field specifies the scheduler's behavior when a new cron job is
-triggered while an older run hasn't finished. The scheduler has two policies available,
-[KILL_EXISTING](#kill_existing) and [CANCEL_NEW](#cancel_new).
-
-### KILL_EXISTING
-
-The default policy - on a collision the old instances are killed and a instances with the current
-configuration are started.
-
-### CANCEL_NEW
-
-On a collision the new run is cancelled.
-
-Note that the use of this flag is likely a code smell - interrupted cron jobs should be able
-to recover their progress on a subsequent invocation, otherwise they risk having their work queue
-grow faster than they can process it.
-
-## Failure recovery
-
-Unlike with services, which aurora will always re-execute regardless of exit status, instances of
-cron jobs retry according to the `max_task_failures` attribute of the
-[Task](configuration-reference.md#task-objects) object. To get "run-until-success" semantics,
-set `max_task_failures` to `-1`.
-
-## Interacting with cron jobs via the Aurora CLI
-
-Most interaction with cron jobs takes place using the `cron` subcommand. See `aurora cron -h`
-for up-to-date usage instructions.
-
-### cron schedule
-Schedules a new cron job on the Aurora cluster for later runs or replaces the existing cron template
-with a new one. Only future runs will be affected, any existing active tasks are left intact.
-
-    $ aurora cron schedule devcluster/www-data/test/cron_hello_world /vagrant/examples/jobs/cron_hello_world.aurora
-
-### cron deschedule
-Deschedules a cron job, preventing future runs but allowing current runs to complete.
-
-    $ aurora cron deschedule devcluster/www-data/test/cron_hello_world
-
-### cron start
-Start a cron job immediately, outside of its normal cron schedule.
-
-    $ aurora cron start devcluster/www-data/test/cron_hello_world
-
-### job killall, job restart, job kill
-Cron jobs create instances running on the cluster that you can interact with like normal Aurora
-tasks with `job kill` and `job restart`.
-
-## Technical Note About Syntax
-
-`cron_schedule` uses a restricted subset of BSD crontab syntax. While the
-execution engine currently uses Quartz, the schedule parsing is custom, a subset of FreeBSD
-[crontab(5)](http://www.freebsd.org/cgi/man.cgi?crontab(5)) syntax. See
-[the source](https://github.com/apache/aurora/blob/master/src/main/java/org/apache/aurora/scheduler/cron/CrontabEntry.java#L106-L124)
-for details.
-
-## Caveats
-
-### Failovers
-No failover recovery. Aurora does not record the latest minute it fired
-triggers for across failovers. Therefore it's possible to miss triggers
-on failover. Note that this behavior may change in the future.
-
-It's necessary to sync time between schedulers with something like `ntpd`.
-Clock skew could cause double or missed triggers in the case of a failover.
-
-### Collision policy is best-effort
-Aurora aims to always have *at least one copy* of a given instance running at a time - it's
-an AP system, meaning it chooses Availability and Partition Tolerance at the expense of
-Consistency.
-
-If your collision policy was `CANCEL_NEW` and a task has terminated but
-Aurora has not noticed this Aurora will go ahead and create your new
-task.
-
-If your collision policy was `KILL_EXISTING` and a task was marked `LOST`
-but not yet GCed Aurora will go ahead and create your new task without
-attempting to kill the old one (outside the GC interval).
-
-### Timezone Configuration
-Cron timezone is configured indepdendently of JVM timezone with the `-cron_timezone` flag and
-defaults to UTC.

http://git-wip-us.apache.org/repos/asf/aurora/blob/f28f41a7/docs/deploying-aurora-scheduler.md
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diff --git a/docs/deploying-aurora-scheduler.md b/docs/deploying-aurora-scheduler.md
deleted file mode 100644
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-# Deploying the Aurora Scheduler
-
-When setting up your cluster, you will install the scheduler on a small number (usually 3 or 5) of
-machines.  This guide helps you get the scheduler set up and troubleshoot some common hurdles.
-
-- [Installing Aurora](#installing-aurora)
-  - [Creating the Distribution .zip File (Optional)](#creating-the-distribution-zip-file-optional)
-  - [Installing Aurora](#installing-aurora-1)
-- [Configuring Aurora](#configuring-aurora)
-  - [A Note on Configuration](#a-note-on-configuration)
-  - [Replicated Log Configuration](#replicated-log-configuration)
-  - [Initializing the Replicated Log](#initializing-the-replicated-log)
-  - [Storage Performance Considerations](#storage-performance-considerations)
-  - [Network considerations](#network-considerations)
-  - [Considerations for running jobs in docker](#considerations-for-running-jobs-in-docker)
-  - [Security Considerations](#security-considerations)
-  - [Configuring Resource Oversubscription](#configuring-resource-oversubscription)
-  - [Process Logs](#process-logs)
-- [Running Aurora](#running-aurora)
-  - [Maintaining an Aurora Installation](#maintaining-an-aurora-installation)
-  - [Monitoring](#monitoring)
-  - [Running stateful services](#running-stateful-services)
-    - [Dedicated attribute](#dedicated-attribute)
-      - [Syntax](#syntax)
-      - [Example](#example)
-- [Best practices](#best-practices)
-  - [Diversity](#diversity)
-- [Common problems](#common-problems)
-  - [Replicated log not initialized](#replicated-log-not-initialized)
-    - [Symptoms](#symptoms)
-    - [Solution](#solution)
-  - [Scheduler not registered](#scheduler-not-registered)
-    - [Symptoms](#symptoms-1)
-    - [Solution](#solution-1)
-- [Changing Scheduler Quorum Size](#changing-scheduler-quorum-size)
-    - [Preparation](#preparation)
-    - [Adding New Schedulers](#adding-new-schedulers)
-
-## Installing Aurora
-The Aurora scheduler is a standalone Java server. As part of the build process it creates a bundle
-of all its dependencies, with the notable exceptions of the JVM and libmesos. Each target server
-should have a JVM (Java 8 or higher) and libmesos (0.25.0) installed.
-
-### Creating the Distribution .zip File (Optional)
-To create a distribution for installation you will need build tools installed. On Ubuntu this can be
-done with `sudo apt-get install build-essential default-jdk`.
-
-    git clone http://git-wip-us.apache.org/repos/asf/aurora.git
-    cd aurora
-    ./gradlew distZip
-
-Copy the generated `dist/distributions/aurora-scheduler-*.zip` to each node that will run a scheduler.
-
-### Installing Aurora
-Extract the aurora-scheduler zip file. The example configurations assume it is extracted to
-`/usr/local/aurora-scheduler`.
-
-    sudo unzip dist/distributions/aurora-scheduler-*.zip -d /usr/local
-    sudo ln -nfs "$(ls -dt /usr/local/aurora-scheduler-* | head -1)" /usr/local/aurora-scheduler
-
-## Configuring Aurora
-
-### A Note on Configuration
-Like Mesos, Aurora uses command-line flags for runtime configuration. As such the Aurora
-"configuration file" is typically a `scheduler.sh` shell script of the form.
-
-    #!/bin/bash
-    AURORA_HOME=/usr/local/aurora-scheduler
-
-    # Flags controlling the JVM.
-    JAVA_OPTS=(
-      -Xmx2g
-      -Xms2g
-      # GC tuning, etc.
-    )
-
-    # Flags controlling the scheduler.
-    AURORA_FLAGS=(
-      -http_port=8081
-      # Log configuration, etc.
-    )
-
-    # Environment variables controlling libmesos
-    export JAVA_HOME=...
-    export GLOG_v=1
-    export LIBPROCESS_PORT=8083
-
-    JAVA_OPTS="${JAVA_OPTS[*]}" exec "$AURORA_HOME/bin/aurora-scheduler" "${AURORA_FLAGS[@]}"
-
-That way Aurora's current flags are visible in `ps` and in the `/vars` admin endpoint.
-
-Examples are available under `examples/scheduler/`. For a list of available Aurora flags and their
-documentation, see [this document](scheduler-configuration.md).
-
-### Replicated Log Configuration
-All Aurora state is persisted to a replicated log. This includes all jobs Aurora is running
-including where in the cluster they are being run and the configuration for running them, as
-well as other information such as metadata needed to reconnect to the Mesos master, resource
-quotas, and any other locks in place.
-
-Aurora schedulers use ZooKeeper to discover log replicas and elect a leader. Only one scheduler is
-leader at a given time - the other schedulers follow log writes and prepare to take over as leader
-but do not communicate with the Mesos master. Either 3 or 5 schedulers are recommended in a
-production deployment depending on failure tolerance and they must have persistent storage.
-
-In a cluster with `N` schedulers, the flag `-native_log_quorum_size` should be set to
-`floor(N/2) + 1`. So in a cluster with 1 scheduler it should be set to `1`, in a cluster with 3 it
-should be set to `2`, and in a cluster of 5 it should be set to `3`.
-
-  Number of schedulers (N) | ```-native_log_quorum_size``` setting (```floor(N/2) + 1```)
-  ------------------------ | -------------------------------------------------------------
-  1                        | 1
-  3                        | 2
-  5                        | 3
-  7                        | 4
-
-*Incorrectly setting this flag will cause data corruption to occur!*
-
-See [this document](storage-config.md#scheduler-storage-configuration-flags) for more replicated
-log and storage configuration options.
-
-## Initializing the Replicated Log
-Before you start Aurora you will also need to initialize the log on a majority of the schedulers.
-
-    mesos-log initialize --path="/path/to/native/log"
-
-The `--path` flag should match the `--native_log_file_path` flag to the scheduler.
-Failing to do this will result the following message when you try to start the scheduler.
-
-    Replica in EMPTY status received a broadcasted recover request
-
-### Storage Performance Considerations
-
-See [this document](scheduler-storage.md) for scheduler storage performance considerations.
-
-### Network considerations
-The Aurora scheduler listens on 2 ports - an HTTP port used for client RPCs and a web UI,
-and a libprocess (HTTP+Protobuf) port used to communicate with the Mesos master and for the log
-replication protocol. These can be left unconfigured (the scheduler publishes all selected ports
-to ZooKeeper) or explicitly set in the startup script as follows:
-
-    # ...
-    AURORA_FLAGS=(
-      # ...
-      -http_port=8081
-      # ...
-    )
-    # ...
-    export LIBPROCESS_PORT=8083
-    # ...
-
-### Considerations for running jobs in docker containers
-In order for Aurora to launch jobs using docker containers, a few extra configuration options
-must be set.  The [docker containerizer](http://mesos.apache.org/documentation/latest/docker-containerizer/)
-must be enabled on the mesos slaves by launching them with the `--containerizers=docker,mesos` option.
-
-By default, Aurora will configure Mesos to copy the file specified in `-thermos_executor_path`
-into the container's sandbox.  If using a wrapper script to launch the thermos executor,
-specify the path to the wrapper in that argument. In addition, the path to the executor pex itself
-must be included in the `-thermos_executor_resources` option. Doing so will ensure that both the
-wrapper script and executor are correctly copied into the sandbox. Finally, ensure the wrapper
-script does not access resources outside of the sandbox, as when the script is run from within a
-docker container those resources will not exist.
-
-In order to correctly execute processes inside a job, the docker container must have python 2.7
-installed.
-
-A scheduler flag, `-global_container_mounts` allows mounting paths from the host (i.e., the slave)
-into all containers on that host. The format is a comma separated list of host_path:container_path[:mode]
-tuples. For example `-global_container_mounts=/opt/secret_keys_dir:/mnt/secret_keys_dir:ro` mounts
-`/opt/secret_keys_dir` from the slaves into all launched containers. Valid modes are `ro` and `rw`.
-
-If you would like to supply your own parameters to `docker run` when launching jobs in docker
-containers, you may use the following flags:
-
-    -allow_docker_parameters
-    -default_docker_parameters
-
-`-allow_docker_parameters` controls whether or not users may pass their own configuration parameters
-through the job configuration files. If set to `false` (the default), the scheduler will reject
-jobs with custom parameters. *NOTE*: this setting should be used with caution as it allows any job
-owner to specify any parameters they wish, including those that may introduce security concerns
-(`privileged=true`, for example).
-
-`-default_docker_parameters` allows a cluster operator to specify a universal set of parameters that
-should be used for every container that does not have parameters explicitly configured at the job
-level. The argument accepts a multimap format:
-
-    -default_docker_parameters="read-only=true,tmpfs=/tmp,tmpfs=/run"
-
-### Process Logs
-
-#### Log destination
-By default, Thermos will write process stdout/stderr to log files in the sandbox. Process object configuration
-allows specifying alternate log file destinations like streamed stdout/stderr or suppression of all log output.
-Default behavior can be configured for the entire cluster with the following flag (through the `-thermos_executor_flags`
-argument to the Aurora scheduler):
-
-    --runner-logger-destination=both
-
-`both` configuration will send logs to files and stream to parent stdout/stderr outputs.
-
-See [this document](configuration-reference.md#logger) for all destination options.
-
-#### Log rotation
-By default, Thermos will not rotate the stdout/stderr logs from child processes and they will grow
-without bound. An individual user may change this behavior via configuration on the Process object,
-but it may also be desirable to change the default configuration for the entire cluster.
-In order to enable rotation by default, the following flags can be applied to Thermos (through the
--thermos_executor_flags argument to the Aurora scheduler):
-
-    --runner-logger-mode=rotate
-    --runner-rotate-log-size-mb=100
-    --runner-rotate-log-backups=10
-
-In the above example, each instance of the Thermos runner will rotate stderr/stdout logs once they
-reach 100 MiB in size and keep a maximum of 10 backups. If a user has provided a custom setting for
-their process, it will override these default settings.
-
-## Running Aurora
-Configure a supervisor like [Monit](http://mmonit.com/monit/) or
-[supervisord](http://supervisord.org/) to run the created `scheduler.sh` file and restart it
-whenever it fails. Aurora expects to be restarted by an external process when it fails. Aurora
-supports an active health checking protocol on its admin HTTP interface - if a `GET /health` times
-out or returns anything other than `200 OK` the scheduler process is unhealthy and should be
-restarted.
-
-For example, monit can be configured with
-
-    if failed port 8081 send "GET /health HTTP/1.0\r\n" expect "OK\n" with timeout 2 seconds for 10 cycles then restart
-
-assuming you set `-http_port=8081`.
-
-## Security Considerations
-
-See [security.md](security.md).
-
-## Configuring Resource Oversubscription
-
-**WARNING**: This feature is currently in alpha status. Do not use it in production clusters!
-See [this document](configuration-reference.md#revocable-jobs) for more feature details.
-
-Set these scheduler flag to allow receiving revocable Mesos offers:
-
-    -receive_revocable_resources=true
-
-Specify a tier configuration file path:
-
-    -tier_config=path/to/tiers/config.json
-
-Default [tier configuration file](../src/main/resources/org/apache/aurora/scheduler/tiers.json).
-
-### Maintaining an Aurora Installation
-
-### Monitoring
-Please see our dedicated [monitoring guide](monitoring.md) for in-depth discussion on monitoring.
-
-### Running stateful services
-Aurora is best suited to run stateless applications, but it also accommodates for stateful services
-like databases, or services that otherwise need to always run on the same machines.
-
-#### Dedicated attribute
-The Mesos slave has the `--attributes` command line argument which can be used to mark a slave with
-static attributes (not to be confused with `--resources`, which are dynamic and accounted).
-
-Aurora makes these attributes available for matching with scheduling
-[constraints](configuration-reference.md#specifying-scheduling-constraints).  Most of these
-constraints are arbitrary and available for custom use.  There is one exception, though: the
-`dedicated` attribute.  Aurora treats this specially, and only allows matching jobs to run on these
-machines, and will only schedule matching jobs on these machines.
-
-See the [section](resources.md#resource-quota) about resource quotas to learn how quotas apply to
-dedicated jobs.
-
-##### Syntax
-The dedicated attribute has semantic meaning. The format is `$role(/.*)?`. When a job is created,
-the scheduler requires that the `$role` component matches the `role` field in the job
-configuration, and will reject the job creation otherwise.  The remainder of the attribute is
-free-form. We've developed the idiom of formatting this attribute as `$role/$job`, but do not
-enforce this. For example: a job `devcluster/www-data/prod/hello` with a dedicated constraint set as
-`www-data/web.multi` will have its tasks scheduled only on Mesos slaves configured with:
-`--attributes=dedicated:www-data/web.multi`.
-
-A wildcard (`*`) may be used for the role portion of the dedicated attribute, which will allow any
-owner to elect for a job to run on the host(s). For example: tasks from both
-`devcluster/www-data/prod/hello` and `devcluster/vagrant/test/hello` with a dedicated constraint
-formatted as `*/web.multi` will be scheduled only on Mesos slaves configured with
-`--attributes=dedicated:*/web.multi`. This may be useful when assembling a virtual cluster of
-machines sharing the same set of traits or requirements.
-
-##### Example
-Consider the following slave command line:
-
-    mesos-slave --attributes="dedicated:db_team/redis" ...
-
-And this job configuration:
-
-    Service(
-      name = 'redis',
-      role = 'db_team',
-      constraints = {
-        'dedicated': 'db_team/redis'
-      }
-      ...
-    )
-
-The job configuration is indicating that it should only be scheduled on slaves with the attribute
-`dedicated:db_team/redis`.  Additionally, Aurora will prevent any tasks that do _not_ have that
-constraint from running on those slaves.
-
-## Best practices
-### Diversity
-Data centers are often organized with hierarchical failure domains.  Common failure domains
-include hosts, racks, rows, and PDUs.  If you have this information available, it is wise to tag
-the mesos-slave with them as
-[attributes](https://mesos.apache.org/documentation/attributes-resources/).
-
-When it comes time to schedule jobs, Aurora will automatically spread them across the failure
-domains as specified in the
-[job configuration](configuration-reference.md#specifying-scheduling-constraints).
-
-Note: in virtualized environments like EC2, the only attribute that usually makes sense for this
-purpose is `host`.
-
-## Common problems
-So you've started your first cluster and are running into some issues? We've collected some common
-stumbling blocks and solutions here to help get you moving.
-
-### Replicated log not initialized
-
-#### Symptoms
-- Scheduler RPCs and web interface claim `Storage is not READY`
-- Scheduler log repeatedly prints messages like
-
-  ```
-  I1016 16:12:27.234133 26081 replica.cpp:638] Replica in EMPTY status
-  received a broadcasted recover request
-  I1016 16:12:27.234256 26084 recover.cpp:188] Received a recover response
-  from a replica in EMPTY status
-  ```
-
-#### Solution
-When you create a new cluster, you need to inform a quorum of schedulers that they are safe to
-consider their database to be empty by [initializing](#initializing-the-replicated-log) the
-replicated log. This is done to prevent the scheduler from modifying the cluster state in the event
-of multiple simultaneous disk failures or, more likely, misconfiguration of the replicated log path.
-
-### Scheduler not registered
-
-#### Symptoms
-Scheduler log contains
-
-    Framework has not been registered within the tolerated delay.
-
-#### Solution
-Double-check that the scheduler is configured correctly to reach the master. If you are registering
-the master in ZooKeeper, make sure command line argument to the master:
-
-    --zk=zk://$ZK_HOST:2181/mesos/master
-
-is the same as the one on the scheduler:
-
-    -mesos_master_address=zk://$ZK_HOST:2181/mesos/master
-
-## Changing Scheduler Quorum Size
-Special care needs to be taken when changing the size of the Aurora scheduler quorum.
-Since Aurora uses a Mesos replicated log, similar steps need to be followed as when
-[changing the mesos quorum size](http://mesos.apache.org/documentation/latest/operational-guide).
-
-### Preparation
-Increase [-native_log_quorum_size](storage-config.md#-native_log_quorum_size) on each
-existing scheduler and restart them. When updating from 3 to 5 schedulers, the quorum size
-would grow from 2 to 3.
-
-### Adding New Schedulers
-Start the new schedulers with `-native_log_quorum_size` set to the new value. Failing to
-first increase the quorum size on running schedulers can in some cases result in corruption
-or truncating of the replicated log used by Aurora. In that case, see the documentation on
-[recovering from backup](storage-config.md#recovering-from-a-scheduler-backup).

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-# Design Documents
-
-Since its inception as an Apache project, larger feature additions to the
-Aurora code base are discussed in form of design documents. Design documents
-are living documents until a consensus has been reached to implement a feature
-in the proposed form.
-
-Current and past documents:
-
-* [Command Hooks for the Aurora Client](design/command-hooks.md)
-* [Health Checks for Updates](https://docs.google.com/document/d/1ZdgW8S4xMhvKW7iQUX99xZm10NXSxEWR0a-21FP5d94/edit)
-* [JobUpdateDiff thrift API](https://docs.google.com/document/d/1Fc_YhhV7fc4D9Xv6gJzpfooxbK4YWZcvzw6Bd3qVTL8/edit)
-* [REST API RFC](https://docs.google.com/document/d/11_lAsYIRlD5ETRzF2eSd3oa8LXAHYFD8rSetspYXaf4/edit)
-* [Revocable Mesos offers in Aurora](https://docs.google.com/document/d/1r1WCHgmPJp5wbrqSZLsgtxPNj3sULfHrSFmxp2GyPTo/edit)
-* [Supporting the Mesos Universal Containerizer](https://docs.google.com/document/d/111T09NBF2zjjl7HE95xglsDpRdKoZqhCRM5hHmOfTLA/edit?usp=sharing)
-* [Tier Management In Apache Aurora](https://docs.google.com/document/d/1erszT-HsWf1zCIfhbqHlsotHxWUvDyI2xUwNQQQxLgs/edit?usp=sharing)
-* [Ubiquitous Jobs](https://docs.google.com/document/d/12hr6GnUZU3mc7xsWRzMi3nQILGB-3vyUxvbG-6YmvdE/edit)
-
-Design documents can be found in the Aurora issue tracker via the query [`project = AURORA AND text ~ "docs.google.com" ORDER BY created`](https://issues.apache.org/jira/browse/AURORA-1528?jql=project%20%3D%20AURORA%20AND%20text%20~%20%22docs.google.com%22%20ORDER%20BY%20created).

http://git-wip-us.apache.org/repos/asf/aurora/blob/f28f41a7/docs/design/command-hooks.md
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-# Command Hooks for the Aurora Client
-
-## Introduction/Motivation
-
-We've got hooks in the client that surround API calls. These are
-pretty awkward, because they don't correlate with user actions. For
-example, suppose we wanted a policy that said users weren't allowed to
-kill all instances of a production job at once.
-
-Right now, all that we could hook would be the "killJob" api call. But
-kill (at least in newer versions of the client) normally runs in
-batches. If a user called killall, what we would see on the API level
-is a series of "killJob" calls, each of which specified a batch of
-instances. We woudn't be able to distinguish between really killing
-all instances of a job (which is forbidden under this policy), and
-carefully killing in batches (which is permitted.) In each case, the
-hook would just see a series of API calls, and couldn't find out what
-the actual command being executed was!
-
-For most policy enforcement, what we really want to be able to do is
-look at and vet the commands that a user is performing, not the API
-calls that the client uses to implement those commands.
-
-So I propose that we add a new kind of hooks, which surround noun/verb
-commands. A hook will register itself to handle a collection of (noun,
-verb) pairs. Whenever any of those noun/verb commands are invoked, the
-hooks methods will be called around the execution of the verb. A
-pre-hook will have the ability to reject a command, preventing the
-verb from being executed.
-
-## Registering Hooks
-
-These hooks will be registered via configuration plugins. A configuration plugin
-can register hooks using an API. Hooks registered this way are, effectively,
-hardwired into the client executable.
-
-The order of execution of hooks is unspecified: they may be called in
-any order. There is no way to guarantee that one hook will execute
-before some other hook.
-
-
-### Global Hooks
-
-Commands registered by the python call are called _global_ hooks,
-because they will run for all configurations, whether or not they
-specify any hooks in the configuration file.
-
-In the implementation, hooks are registered in the module
-`apache.aurora.client.cli.command_hooks`, using the class
-`GlobalCommandHookRegistry`. A global hook can be registered by calling
-`GlobalCommandHookRegistry.register_command_hook` in a configuration plugin.
-
-### The API
-
-    class CommandHook(object)
-      @property
-      def name(self):
-        """Returns a name for the hook."
-
-      def get_nouns(self):
-        """Return the nouns that have verbs that should invoke this hook."""
-
-      def get_verbs(self, noun):
-        """Return the verbs for a particular noun that should invoke his hook."""
-
-      @abstractmethod
-      def pre_command(self, noun, verb, context, commandline):
-        """Execute a hook before invoking a verb.
-        * noun: the noun being invoked.
-        * verb: the verb being invoked.
-        * context: the context object that will be used to invoke the verb.
-          The options object will be initialized before calling the hook
-        * commandline: the original argv collection used to invoke the client.
-        Returns: True if the command should be allowed to proceed; False if the command
-        should be rejected.
-        """
-
-      def post_command(self, noun, verb, context, commandline, result):
-        """Execute a hook after invoking a verb.
-        * noun: the noun being invoked.
-        * verb: the verb being invoked.
-        * context: the context object that will be used to invoke the verb.
-          The options object will be initialized before calling the hook
-        * commandline: the original argv collection used to invoke the client.
-        * result: the result code returned by the verb.
-        Returns: nothing
-        """
-
-    class GlobalCommandHookRegistry(object):
-      @classmethod
-      def register_command_hook(self, hook):
-        pass
-
-### Skipping Hooks
-
-To skip a hook, a user uses a command-line option, `--skip-hooks`. The option can either
-specify specific hooks to skip, or "all":
-
-* `aurora --skip-hooks=all job create east/bozo/devel/myjob` will create a job
-  without running any hooks.
-* `aurora --skip-hooks=test,iq create east/bozo/devel/myjob` will create a job,
-  and will skip only the hooks named "test" and "iq".

http://git-wip-us.apache.org/repos/asf/aurora/blob/f28f41a7/docs/developing-aurora-client.md
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-Getting Started
-===============
-
-The client is written in Python, and uses the
-[Pants](http://pantsbuild.github.io/python-readme.html) build tool.
-
-Client Configuration
-====================
-
-The client uses a configuration file that specifies available clusters. More information about the
-contents of this file can be found in the
-[Client Cluster Configuration](client-cluster-configuration.md) documentation. Information about
-how the client locates this file can be found in the
-[Client Commands](client-commands.md#cluster-configuration) documentation.
-
-Building and Testing the Client
-===============================
-
-Building and testing the client code are both done using Pants. The relevant targets to know about
-are:
-
-   * Build a client executable: `./pants binary src/main/python/apache/aurora/client:aurora`
-   * Test client code: `./pants test src/test/python/apache/aurora/client/cli:all`
-
-If you want to build a source distribution of the client, you need to run `./build-support/release/make-python-sdists`.
-
-Running/Debugging the Client
-============================
-
-For manually testing client changes against a cluster, we use [Vagrant](https://www.vagrantup.com/).
-To start a virtual cluster, you need to install Vagrant, and then run `vagrant up` for the root of
-the aurora workspace. This will create a vagrant host named "devcluster", with a mesos master, a set
-of mesos slaves, and an aurora scheduler.
-
-If you have a change you would like to test in your local cluster, you'll rebuild the client:
-
-    vagrant ssh -c 'aurorabuild client'
-
-Once this completes, the `aurora` command will reflect your changes.
-
-Running/Debugging the Client in PyCharm
-=======================================
-
-It's possible to use PyCharm to run and debug both the client and client tests in an IDE. In order
-to do this, first run:
-
-    build-support/python/make-pycharm-virtualenv
-
-This script will configure a virtualenv with all of our Python requirements. Once the script
-completes it will emit instructions for configuring PyCharm:
-
-    Your PyCharm environment is now set up.  You can open the project root
-    directory with PyCharm.
-
-    Once the project is loaded:
-      - open project settings
-      - click 'Project Interpreter'
-      - click the cog in the upper-right corner
-      - click 'Add Local'
-      - select 'build-support/python/pycharm.venv/bin/python'
-      - click 'OK'
-
-### Running/Debugging Tests
-
-After following these instructions, you should now be able to run/debug tests directly from the IDE
-by right-clicking on a test (or test class) and choosing to run or debug:
-
-[![Debug Client Test](images/debug-client-test.png)](images/debug-client-test.png)
-
-If you've set a breakpoint, you can see the run will now stop and let you debug:
-
-[![Debugging Client Test](images/debugging-client-test.png)](images/debugging-client-test.png)
-
-### Running/Debugging the Client
-
-Actually running and debugging the client is unfortunately a bit more complex. You'll need to create
-a Run configuration:
-
-* Go to Run → Edit Configurations
-* Click the + icon to add a new configuration.
-* Choose python and name the configuration 'client'.
-* Set the script path to `/your/path/to/aurora/src/main/python/apache/aurora/client/cli/client.py`
-* Set the script parameters to the command you want to run (e.g. `job status <job key>`)
-* Expand the Environment section and click the ellipsis to add a new environment variable
-* Click the + at the bottom to add a new variable named AURORA_CONFIG_ROOT whose value is the
-  path where the your cluster configuration can be found. For example, to talk to the scheduler
-  running in the vagrant image, it would be set to `/your/path/to/aurora/examples/vagrant` (this
-  is the directory where our example clusters.json is found).
-* You should now be able to run and debug this configuration!
-
-Making thrift schema changes
-============================
-See [this document](thrift-deprecation.md) for any thrift related changes.

http://git-wip-us.apache.org/repos/asf/aurora/blob/f28f41a7/docs/developing-aurora-scheduler.md
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-Java code in the aurora repo is built with [Gradle](http://gradle.org).
-
-
-Prerequisite
-============
-
-When using Apache Aurora checked out from the source repository or the binary
-distribution, the Gradle wrapper and JavaScript dependencies are provided.
-However, you need to manually install them when using the source release
-downloads:
-
-1. Install Gradle following the instructions on the [Gradle web site](http://gradle.org)
-2. From the root directory of the Apache Aurora project generate the gradle
-wrapper by running:
-
-    gradle wrapper
-
-
-Getting Started
-===============
-
-You will need Java 8 installed and on your `PATH` or unzipped somewhere with `JAVA_HOME` set. Then
-
-    ./gradlew tasks
-
-will bootstrap the build system and show available tasks. This can take a while the first time you
-run it but subsequent runs will be much faster due to cached artifacts.
-
-Running the Tests
------------------
-Aurora has a comprehensive unit test suite. To run the tests use
-
-    ./gradlew build
-
-Gradle will only re-run tests when dependencies of them have changed. To force a re-run of all
-tests use
-
-    ./gradlew clean build
-
-Running the build with code quality checks
-------------------------------------------
-To speed up development iteration, the plain gradle commands will not run static analysis tools.
-However, you should run these before posting a review diff, and **always** run this before pushing a
-commit to origin/master.
-
-    ./gradlew build -Pq
-
-Running integration tests
--------------------------
-To run the same tests that are run in the Apache Aurora continuous integration
-environment:
-
-    ./build-support/jenkins/build.sh
-
-
-In addition, there is an end-to-end test that runs a suite of aurora commands
-using a virtual cluster:
-
-    ./src/test/sh/org/apache/aurora/e2e/test_end_to_end.sh
-
-
-
-Creating a bundle for deployment
---------------------------------
-Gradle can create a zip file containing Aurora, all of its dependencies, and a launch script with
-
-    ./gradlew distZip
-
-or a tar file containing the same files with
-
-    ./gradlew distTar
-
-The output file will be written to `dist/distributions/aurora-scheduler.zip` or
-`dist/distributions/aurora-scheduler.tar`.
-
-Developing Aurora Java code
-===========================
-
-Setting up an IDE
------------------
-Gradle can generate project files for your IDE. To generate an IntelliJ IDEA project run
-
-    ./gradlew idea
-
-and import the generated `aurora.ipr` file.
-
-Adding or Upgrading a Dependency
---------------------------------
-New dependencies can be added from Maven central by adding a `compile` dependency to `build.gradle`.
-For example, to add a dependency on `com.example`'s `example-lib` 1.0 add this block:
-
-    compile 'com.example:example-lib:1.0'
-
-NOTE: Anyone thinking about adding a new dependency should first familiarize themself with the
-Apache Foundation's third-party licensing
-[policy](http://www.apache.org/legal/resolved.html#category-x).
-
-Developing Aurora UI
-======================
-
-Installing bower (optional)
-----------------------------
-Third party JS libraries used in Aurora (located at 3rdparty/javascript/bower_components) are
-managed by bower, a JS dependency manager. Bower is only required if you plan to add, remove or
-update JS libraries. Bower can be installed using the following command:
-
-    npm install -g bower
-
-Bower depends on node.js and npm. The easiest way to install node on a mac is via brew:
-
-    brew install node
-
-For more node.js installation options refer to https://github.com/joyent/node/wiki/Installation.
-
-More info on installing and using bower can be found at: http://bower.io/. Once installed, you can
-use the following commands to view and modify the bower repo at
-3rdparty/javascript/bower_components
-
-    bower list
-    bower install <library name>
-    bower remove <library name>
-    bower update <library name>
-    bower help
-
-Faster Iteration in Vagrant
----------------------------
-The scheduler serves UI assets from the classpath. For production deployments this means the assets
-are served from within a jar. However, for faster development iteration, the vagrant image is
-configured to add the `scheduler` subtree of `/vagrant/dist/resources/main` to the head of
-`CLASSPATH`. This path is configured as a shared filesystem to the path on the host system where
-your Aurora repository lives. This means that any updates under `dist/resources/main/scheduler` in
-your checkout will be reflected immediately in the UI served from within the vagrant image.
-
-The one caveat to this is that this path is under `dist` not `src`. This is because the assets must
-be processed by gradle before they can be served. So, unfortunately, you cannot just save your local
-changes and see them reflected in the UI, you must first run `./gradlew processResources`. This is
-less than ideal, but better than having to restart the scheduler after every change. Additionally,
-gradle makes this process somewhat easier with the use of the `--continuous` flag. If you run:
-`./gradlew processResources --continuous` gradle will monitor the filesystem for changes and run the
-task automatically as necessary. This doesn't quite provide hot-reload capabilities, but it does
-allow for <5s from save to changes being visibile in the UI with no further action required on the
-part of the developer.
-
-Developing the Aurora Build System
-==================================
-
-Bootstrapping Gradle
---------------------
-The following files were autogenerated by `gradle wrapper` using gradle 1.8's
-[Wrapper](http://www.gradle.org/docs/1.8/dsl/org.gradle.api.tasks.wrapper.Wrapper.html) plugin and
-should not be modified directly:
-
-    ./gradlew
-    ./gradlew.bat
-    ./gradle/wrapper/gradle-wrapper.jar
-    ./gradle/wrapper/gradle-wrapper.properties
-
-To upgrade Gradle unpack the new version somewhere, run `/path/to/new/gradle wrapper` in the
-repository root and commit the changed files.
-
-Making thrift schema changes
-============================
-See [this document](thrift-deprecation.md) for any thrift related changes.

http://git-wip-us.apache.org/repos/asf/aurora/blob/f28f41a7/docs/development/client.md
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+Developing the Aurora Client
+============================
+
+The client is written in Python, and uses the
+[Pants](http://pantsbuild.github.io/python-readme.html) build tool.
+
+
+Building and Testing
+--------------------
+
+Building and testing the client code are both done using Pants. The relevant targets to know about
+are:
+
+   * Build a client executable: `./pants binary src/main/python/apache/aurora/client:aurora`
+   * Test client code: `./pants test src/test/python/apache/aurora/client/cli:all`
+
+If you want to build a source distribution of the client, you need to run `./build-support/release/make-python-sdists`.
+
+
+Running/Debugging
+------------------
+
+For manually testing client changes against a cluster, we use [Vagrant](https://www.vagrantup.com/).
+To start a virtual cluster, you need to install Vagrant, and then run `vagrant up` for the root of
+the aurora workspace. This will create a vagrant host named "devcluster", with a mesos master, a set
+of mesos slaves, and an aurora scheduler.
+
+If you have a change you would like to test in your local cluster, you'll rebuild the client:
+
+    vagrant ssh -c 'aurorabuild client'
+
+Once this completes, the `aurora` command will reflect your changes.
+
+
+Running/Debugging in PyCharm
+-----------------------------
+
+It's possible to use PyCharm to run and debug both the client and client tests in an IDE. In order
+to do this, first run:
+
+    build-support/python/make-pycharm-virtualenv
+
+This script will configure a virtualenv with all of our Python requirements. Once the script
+completes it will emit instructions for configuring PyCharm:
+
+    Your PyCharm environment is now set up.  You can open the project root
+    directory with PyCharm.
+
+    Once the project is loaded:
+      - open project settings
+      - click 'Project Interpreter'
+      - click the cog in the upper-right corner
+      - click 'Add Local'
+      - select 'build-support/python/pycharm.venv/bin/python'
+      - click 'OK'
+
+### Running/Debugging Tests
+After following these instructions, you should now be able to run/debug tests directly from the IDE
+by right-clicking on a test (or test class) and choosing to run or debug:
+
+[![Debug Client Test](../images/debug-client-test.png)](../images/debug-client-test.png)
+
+If you've set a breakpoint, you can see the run will now stop and let you debug:
+
+[![Debugging Client Test](../images/debugging-client-test.png)](../images/debugging-client-test.png)
+
+### Running/Debugging the Client
+Actually running and debugging the client is unfortunately a bit more complex. You'll need to create
+a Run configuration:
+
+* Go to Run → Edit Configurations
+* Click the + icon to add a new configuration.
+* Choose python and name the configuration 'client'.
+* Set the script path to `/your/path/to/aurora/src/main/python/apache/aurora/client/cli/client.py`
+* Set the script parameters to the command you want to run (e.g. `job status <job key>`)
+* Expand the Environment section and click the ellipsis to add a new environment variable
+* Click the + at the bottom to add a new variable named AURORA_CONFIG_ROOT whose value is the
+  path where the your cluster configuration can be found. For example, to talk to the scheduler
+  running in the vagrant image, it would be set to `/your/path/to/aurora/examples/vagrant` (this
+  is the directory where our example clusters.json is found).
+* You should now be able to run and debug this configuration!

http://git-wip-us.apache.org/repos/asf/aurora/blob/f28f41a7/docs/development/committers-guide.md
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+Committer's Guide
+=================
+
+Information for official Apache Aurora committers.
+
+Setting up your email account
+-----------------------------
+Once your Apache ID has been set up you can configure your account and add ssh keys and setup an
+email forwarding address at
+
+  http://id.apache.org
+
+Additional instructions for setting up your new committer email can be found at
+
+  http://www.apache.org/dev/user-email.html
+
+The recommended setup is to configure all services (mailing lists, JIRA, ReviewBoard) to send
+emails to your @apache.org email address.
+
+
+Creating a gpg key for releases
+-------------------------------
+In order to create a release candidate you will need a gpg key published to an external key server
+and that key will need to be added to our KEYS file as well.
+
+1. Create a key:
+
+               gpg --gen-key
+
+2. Add your gpg key to the Apache Aurora KEYS file:
+
+               git clone https://git-wip-us.apache.org/repos/asf/aurora.git
+               (gpg --list-sigs <KEY ID> && gpg --armor --export <KEY ID>) >> KEYS
+               git add KEYS && git commit -m "Adding gpg key for <APACHE ID>"
+               ./rbt post -o -g
+
+3. Publish the key to an external key server:
+
+               gpg --keyserver pgp.mit.edu --send-keys <KEY ID>
+
+4. Update the changes to the KEYS file to the Apache Aurora svn dist locations listed below:
+
+               https://dist.apache.org/repos/dist/dev/aurora/KEYS
+               https://dist.apache.org/repos/dist/release/aurora/KEYS
+
+5. Add your key to git config for use with the release scripts:
+
+               git config --global user.signingkey <KEY ID>
+
+
+Creating a release
+------------------
+The following will guide you through the steps to create a release candidate, vote, and finally an
+official Apache Aurora release. Before starting your gpg key should be in the KEYS file and you
+must have access to commit to the dist.a.o repositories.
+
+1. Ensure that all issues resolved for this release candidate are tagged with the correct Fix
+Version in Jira, the changelog script will use this to generate the CHANGELOG in step #2.
+
+2. Create a release candidate. This will automatically update the CHANGELOG and commit it, create a
+branch and update the current version within the trunk. To create a minor version update and publish
+it run
+
+               ./build-support/release/release-candidate -l m -p
+
+3. Update, if necessary, the draft email created from the `release-candidate` script in step #2 and
+send the [VOTE] email to the dev@ mailing list. You can verify the release signature and checksums
+by running
+
+               ./build-support/release/verify-release-candidate
+
+4. Wait for the vote to complete. If the vote fails close the vote by replying to the initial [VOTE]
+email sent in step #3 by editing the subject to [RESULT][VOTE] ... and noting the failure reason
+(example [here](http://markmail.org/message/d4d6xtvj7vgwi76f)). Now address any issues and go back to
+step #1 and run again, this time you will use the -r flag to increment the release candidate
+version. This will automatically clean up the release candidate rc0 branch and source distribution.
+
+               ./build-support/release/release-candidate -l m -r 1 -p
+
+5. Once the vote has successfully passed create the release
+
+               ./build-support/release/release
+
+6. Update the draft email created fom the `release` script in step #5 to include the Apache ID's for
+all binding votes and send the [RESULT][VOTE] email to the dev@ mailing list.
+

http://git-wip-us.apache.org/repos/asf/aurora/blob/f28f41a7/docs/development/design-documents.md
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diff --git a/docs/development/design-documents.md b/docs/development/design-documents.md
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+Design Documents
+================
+
+Since its inception as an Apache project, larger feature additions to the
+Aurora code base are discussed in form of design documents. Design documents
+are living documents until a consensus has been reached to implement a feature
+in the proposed form.
+
+Current and past documents:
+
+* [Command Hooks for the Aurora Client](design/command-hooks.md)
+* [Health Checks for Updates](https://docs.google.com/document/d/1ZdgW8S4xMhvKW7iQUX99xZm10NXSxEWR0a-21FP5d94/edit)
+* [JobUpdateDiff thrift API](https://docs.google.com/document/d/1Fc_YhhV7fc4D9Xv6gJzpfooxbK4YWZcvzw6Bd3qVTL8/edit)
+* [REST API RFC](https://docs.google.com/document/d/11_lAsYIRlD5ETRzF2eSd3oa8LXAHYFD8rSetspYXaf4/edit)
+* [Revocable Mesos offers in Aurora](https://docs.google.com/document/d/1r1WCHgmPJp5wbrqSZLsgtxPNj3sULfHrSFmxp2GyPTo/edit)
+* [Supporting the Mesos Universal Containerizer](https://docs.google.com/document/d/111T09NBF2zjjl7HE95xglsDpRdKoZqhCRM5hHmOfTLA/edit?usp=sharing)
+* [Tier Management In Apache Aurora](https://docs.google.com/document/d/1erszT-HsWf1zCIfhbqHlsotHxWUvDyI2xUwNQQQxLgs/edit?usp=sharing)
+* [Ubiquitous Jobs](https://docs.google.com/document/d/12hr6GnUZU3mc7xsWRzMi3nQILGB-3vyUxvbG-6YmvdE/edit)
+
+Design documents can be found in the Aurora issue tracker via the query [`project = AURORA AND text ~ "docs.google.com" ORDER BY created`](https://issues.apache.org/jira/browse/AURORA-1528?jql=project%20%3D%20AURORA%20AND%20text%20~%20%22docs.google.com%22%20ORDER%20BY%20created).


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