HOW TO RUN FROM A ZOMBIE: CLOUDSTACK DISTRIBUTED PROCESS MANAGEMENT John Burwell ([email protected] | [email protected] @john_burwell) Tuesday, June 25, 13 

I Am Not A Zombie • Apache CloudStack PMC Member • Consulting Engineer @ Basho Technologies • Ran operations and designed automated provisioning for hybrid analytic/virtualization clouds • Led architectural design and server-side development of a SaaS physical security platform Tuesday, June 25, 13 

Current Process Management • No consistent system-wide model • Fail slowly, fail quietly • Resource overcommitment issues • Lack of instrumentation Tuesday, June 25, 13 

What is a cloud? Tuesday, June 25, 13 

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Hopefully not ... Tuesday, June 25, 13 

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Hosts Virtual Routers Virtual Machines Primary Storage Networks Secondary Storage Load

Resource Process State A

At it’s core, CloudStack ... Integrates infrastructure components Manages resources Tuesday, June 25, 13 

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Consistency Availability Partition

CloudStack provides zones, clusters, and pods to partition resources. Tuesday, June 25, 13 

Orchestration operations are eventually consistent Tuesday, June 25, 13 

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... but resource operations must be consistent & serialized. Tuesday, June 25, 13 

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A system can not be simultaneously consistent and available. Tuesday, June 25, 13 

Orchestration

CP Resource? • Ordered/Serialized operations • Prevent overcommitment • Execution location independent • Lock free Tuesday, June 25, 13 

Orchestration Coordination 1. Build a list of commands to be executed against a resource 2. Enqueue the list of commands to the resource management layer for execution 3. A process applies the commands to the resource 4. Aggregate the results from the reply Tuesday, June 25, 13 

Resource Process State Queue 1 1 Unit

Unit Of Work (UoW) • Definition: A ordered list of commands executed against a one and only one resource. • Created in the Orchestration layer • Executed by processes in the resource management layer • Failure of a command halts UoW execution Tuesday, June 25, 13 

Instrumentation • Collect and report statistics on a per resource basis • Inspect and remove pending UoWs for a resource • Kill a running process • View a history of UoWs completed by a resource Tuesday, June 25, 13 

• Process execution fails • Resources become unavailable • Slow consumers When Gravity Fails Tuesday, June 25, 13 

Fail Fast; Fail Loudly • If the resource can be returned to a consistent state, reply with the process failure • If the resource can not be returned to a consistent state, change the transition the resource to a failure state, drain the queue of pending UoWs, and reply with the process failure for each UoW • The orchestration layer will determine the appropriate recovery strategy (e.g. retry request on another resource) Tuesday, June 25, 13 

Preventing A Logjam • Bounded Queues • Request and Message Timeouts • A failure to enqueue a request or a request timeout trigger a the resource’s circuit breaker Tuesday, June 25, 13 

How could we implement this model? Tuesday, June 25, 13 

Lightweight Threads A thread that is not scheduled by the operating system -- avoiding context switch overhead. Tuesday, June 25, 13 

Actor Model • An actor represents state and behavior • Communicate by message passing • Each actor is allocated a lightweight thread and mailbox • Location independent Tuesday, June 25, 13 

Mailbox Resource Actor FSM Orchestration Unit

Java Actor Frameworks • Akka (http://akka.io) • Quasar (https://github.com/puniverse/quasar) Tuesday, June 25, 13 

Summary • Orchestration and Resource Management must be properly divided to satisfy CAP • To provide resource serialization guarantees, assign a queue and a process to each resource • Fast fast, fail loudly • An Actor Model based on lightweight threads may provide the scalability required to dedicate a queue and process per resource Tuesday, June 25, 13 

Thoughts? Questions? Tuesday, June 25, 13 

Thank you! Slides available @ http://speakerdeck.com/jburwell Tuesday, June 25, 13