Cloud Computing Workflows

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Cloud Computing Workflows

• Anushri Khandekar

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Cloud Computing

• Delivering applications or services in on-demand
  environment
• Hundreds of thousands of users / applications
• Systems should be fast, secure and available
• Intelligent infrastructure
• Transparency
• Scalability
• Monitoring
• Security
• All services and associated data

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Workflows

• Operational aspect of a work procedure
• how tasks are structured,
• who performs them,
• what their relative order is,
• how they are synchronized,
• how information flows to support the tasks and
• how tasks are being tracked.

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Workflow Management

• An activity is a discrete step in a business
  process (workflow).
• Activities range from calling a remote service to
  perform a task, e.g. calculating taxes,
  performing currency conversions, looking up
  inventory, to custom-defined services.
• Activities are orchestrated together in a
  workflow in BizTalk using XOML (eXtensible Object
  Markup Language).
• Other languages BPEL, ebXML, XPDL etc.

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Workflows in Cloud

• Microsoft allows hosting of Biztalk activities in
  a cloud at biztalk labs.
• Developers integrate those cloud hosted
  activities into a BizTalk workflow
  (orchestration) by calling them as they would any
  other web-based service or hosted activity.
• Service orchestration business process is
  modeled using workflows
• Invokes Internet Service Bus and perform HTTP
  request
• Language used XOML
• Main task First create a workflow instance and
  start it

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Transparency

• Actual Implementation of services obscured
• Another version of virtualization
• Transparent load-balancing and application
  delivery
• Solution to be automated and integrated in
  workflow process
• Example
• A service running with a single server, more
  users join in hence additional servers required,
  transparency allows integration without
  interrupting the service running or
  reconfiguration.

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Scalability

• Scale up and build mega data centers
• Not transparent Need configuration or
  re-architecting
• Potential of interrupting services is huge
• Ability to transparently scale the service
  infrastructure and the solution
• On-demand, real time scaling
• Control node provides dynamic application
  scalability
• Integration with virtualization solution or
  orchestration with workflow process to manage
  provisioning

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Intelligent Monitoring

• Control node intelligent monitoring
  capabilities
• Server overwhelming or application performance
  affected by network conditions behavior outside
  accepted norms
• More than knowing when a service in trouble what
  action should be taken
• Example application responding slowly, adjust
  application requests add more server if required
• Detect and participate in the provisioning of new
  instance

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Capacity Management

• From buckets to rivers
• Constrained set of resources predict peak usage
  and have in-house data centre to manage them
• Unlimited computing power with cloud How IT
  departments properly manage this river?
• Constraint on new model
• Not upper limit of computing power but speed at
  which new services can be provisioned and put
  into production
• Scaling up means
• Initiate new system, transfer data, connect
  existing system, test combined system, manage
  complete life cycle

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Capacity Management

• Traditional life cycle stages
• Modeling, provisioning, monitoring, maintaining,
  and modifying.
• Important here Maintaining Modifying
• Elastic means provisioning and de-provisioning
• Is it right time to add an IT asset or get rid of
  an asset?
• Economic benefits rely on when to stop using an
  asset
• Utilize the cloud for additional capacity when it
  is apparent your own data centre can't handle the
  load and it is cost-prohibitive to invest in
  additional servers and infrastructure to increase
  capacity

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Problem Statement

• Efficient management of workflows in a cloud
  environment to allow fast scaling up and scaling
  down
• Storing scalability/ compressibility options for
  every node in the workflow
• Input events and output events of every node in
  workflow
• Mechanism to integrate new scaled model of web
  service in original cloud workflow

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Proposed Idea
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Workflow Management

• Workflow management important heavy workflow of
  traditional waterfall approaches with smallest
  detail will slow down the use of cloud computing
• Separate main workflow from details of mechanism
  required to scale any activity node
• Have efficient way of storing this information

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Workflow Management

• Workflow Main
• Has the cloud structure with each web service as
  an activity node
• Workflow Shadow
• Has sub-workflows for other options for each
  activity nodes
• Workflows Online or Offline.
• Online running and executing at a particular
  time
• Offline workflows in passive state waiting for
  an event to trigger them

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Activity Node
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Scalability Options

• Considering transparency, two ways to scale a
  workflow
• Scale an activity node
• Addition of new activity node
• More tricky, dynamic, according to environment
• Scale an activity node
• When? store criteria
• Example, for a web server if load increases above
  a threshold, expand
• How? again as a workflow
• Example, store all the steps to be done in order
  to expand, configure and connect the node back to
  original workflow

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Cloudbursting vs Bursting the Cloud

• Cloudbursting is to allow the cloud to act as
  overflow resources in the event your own
  infrastructure becomes overloaded
• Critical tasks (revenue generating) in own
  datacentre
• Bursting in the cloud is applied to resources
  such as servers, application servers, application
  delivery systems, and other infrastructure
  required to provide on-demand computing
  environments

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Bursting the cloud

• Automate the cloud's data centre
• Requires more than simple workflow systems
• on-demand control and management over all devices
  in the delivery chain
• from the storage to the application and web
  servers to the load-balancers and acceleration
  offerings that deliver the applications to
  end-users
• Data centre orchestration many moving parts
  and pieces be coordinated in order to perform a
  highly complex set of tasks

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Hadoop As a Service

• Automated installation and provisioning
• Research Questions
• How to support multi-tenancy with QoS
  differentiation
• How to optimize workflows across users with
  fluctuating capacity requirements
• Key features
• On-demand creation
• Dynamic resource flexing

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Differentiated Hadoop services

• Problem
• More important jobs should preempt less important
  jobs
• Time critical jobs need to meet deadlines
• Test jobs need no stringent QoS guarantees
• How to get users to truthfully reveal their
  resource requirements?

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Differentiated Hadoop services

• Approach
• Market-based resource allocator, Tycoon
• Continuous bidding (of spending rates) for
  resource capacity
• Proportional allocation
• Allocation materialized as VM
• Users can evaluate and select providers based on
  cost/benefit metrics (best value for money)
• Gives incentive to users to be judicial about
  capacity requests and time to submit

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Economic workflow optimization

• Assumption
• Not all subtasks need maximum capacity at all
  times
• Approach
• Automatically rescale the capacity as needed to
  optimize the cost/benefit ratio of the workflow
  as a whole
• Opportunity
• Application scalability profile not perfectly
  linear

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Optimization strategies

• Node Priority
• P Some nodes more performance critical than
  others
• S Boost spending on critical nodes (e.g. master
  funding boost)
• Workflow Priority
• P Some workflows more performance critical than
  others (although they look the same to the
  system)
• S Declare relative priority of workflows and
  split budget accordingly
• Job Priority
• P Some stages of a workflow are more i/o
  intensive, others more cpu intensive
• S Boost resource spending during
  resource-intense stages of workflow
• Bottleneck Mitigation
• P During map/reduce synch up some nodes may be
  bottlenecks
• S Redistribute funds to active bottlenecks

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Optimization strategies

• Best Response
• P When other users place competing bids, optimal
  configuration/allocation might change
• S Find game theoretical best response bids
  continuously to maximize utility
• Risk
• P Some users are more risk averse than others
  (can tolerate less fluctuations)
• S Bid on nodes based on predicted guarantee to
  deliver a QoS level

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Managing Resources

• Includes clear policies on
• who to admit
• how to arbitrate among competing requests
• what resource capacity may be requested over what
  time frames
• Isolated Datacentre
• Reset, reboot, power up, power down, get status
• Bias towards large and short experiments
• Site coordination required, e.g. accounting

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XOML

• Original Cloud Activities
• CloudHttpSend
• CloudHttpReceive
• CloudIfElse
• CloudSequence
• Activity node details should be stored with
  this
• CloudServiceBusSend
• CloudDelay
• CloudWhile

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Microsoft Azure
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Citrix Cloud Centre

• XenServer Cloud Edition a complete, cloud-ready
  virtual infrastructure
• NetScaler to load balance, speed access to
  backend VMs and dynamically provision workloads.
• "There's more to providing cloud computing than
  simply providing a flat virtual infrastructure.
  You want to have workflows, you want SLAs, you
  want to be able to automate and move things
  around, and that's essentially what Citrix is
  bringing to the table -- a full suite of tools to
  do all of that."
• James Staten
• Citrix WANScaler and Citrix Workflow Studio
• Single Automated Cohesive system

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Conclusions

• Workflow management matters because much of the
  benefits of cloud computing comes from the speed
  and ease with which IT resources can be created
  and put into production.

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• Thank you !!!

Questions ???