8983f78ca1
After releasing the rc-final of Watcher for Mitaka, we need to clean-up specs folder before moving to Newton. Change-Id: I8de45ebae47c0b9c8c25e17285d553c9870deea0
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181 lines
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This work is licensed under a Creative Commons Attribution 3.0 Unported
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License.
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http://creativecommons.org/licenses/by/3.0/legalcode
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==========================================
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Workload Based Migration Strategy
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==========================================
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https://blueprints.launchpad.net/watcher/+spec/workload-balance-migration-strategy
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This spec proposes a new Watcher migration strategy based on the VM workloads
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of hypervisors. This strategy makes decisions to migrate workloads to make the
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total VM workloads of each hypervisor balanced, when the total VM workloads of
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hypervisor reaches threshold.
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Note: * VM workloads means how much CPUs the VM instance fully used, eg a VM
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instance has 4 CPUs, the VM workload range is [0.00 , 4.00].
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* This strategy is based on that all hosts have the same CPUs.
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Problem description
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===================
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In current Data Center, VM workloads on each hypervisor may not balance, some
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are extremely high, some are idle, which will reduce the cooling efficiency,
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this strategy will balance the workloads when the CPU utilization of
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hypervisor reaches threshold.
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Use Cases
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----------
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As an administrator, I want to be able to trigger an audit that controls the
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CPU utilization below a certain threshold.
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In order to:
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* balance the workloads on each hypervisor, make it close to average workload
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value of all hypervisors.
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Project Priority
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-----------------
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Not relevant because Watcher is not in the big tent so far.
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Proposed change
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===============
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Watcher already has its decision framework, so this strategy should be a new
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class which extend the base strategy class.
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* Set the threshold in 2 steps: hard coded first, then through the template.
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see: https://blueprints.launchpad.net/watcher/+spec/optimization-threshold
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Threshold is the trigger value to start workload balancing.
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It can be the percentage of CPU utilization of hypervisor.
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* Create a new Python class to extend the "BaseStrategy" class.
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* Use the Nova objects framework to get free CPU/Memory/Disk of hypervisors.
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* Use the Ceilometer client to get VM "cpu_util" to calculate the workloads.
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The time window is 5 minutes here, will be configurable as threshold.
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It uses ceilometer aggregation API to get the average value of "cpu_util".
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* An algorithm to detect if the threshold of workloads has been reached, it
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will figure out the suitable VM to be moved, and it will filter the viable
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targets according to the free resource information of hypervisors from
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previous step and choose the one with lowest workloads. It will use
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select-destinations-filter when it is ready.
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It will also do some check to avoid the corner case, such as "ping pong".
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Alternatives
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------------
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No alternative
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Data model impact
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-----------------
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None
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REST API impact
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---------------
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None
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Security impact
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---------------
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None
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Notifications impact
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--------------------
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None
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Other end user impact
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---------------------
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None
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Performance Impact
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------------------
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There used to be some performance issues regarding the query of metrics from
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the Ceilometer database. This is one of the reasons why it was rarely used in
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production environment. These issues may now be solved thanks to an
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abstraction layer which enables anybody to change the underlying metrics
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storage backend easily.
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There is a performance issue when you query the Nova DB to get CPU usage
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metrics.
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Other deployer impact
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---------------------
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None
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Developer impact
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----------------
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None
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Implementation
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==============
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Assignee(s)
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-----------
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Primary assignee:
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<edwin-zhai>
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Work Items
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----------
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1. function to calculate the total VM workloads of hypervisors.
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2. function to filter hypervisors by Nova basic metrics(free CPU/Memory/Disk).
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3. Rewrite execute function to add the algorithm to detect the threshold and
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to pick up the suitable VM to be moved and choose the target hypervisors,
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generate the solution.
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Dependencies
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============
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* https://blueprints.launchpad.net/watcher/+spec/optimization-threshold
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* https://blueprints.launchpad.net/watcher/+spec/select-destinations-filter
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* http://docs.openstack.org/developer/python-novaclient/api.html
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* https://blueprints.launchpad.net/watcher/+spec/get-goal-from-strategy
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Testing
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=======
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Unit tests and functional test, will use a fake metrics set for running
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functional test.
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Documentation Impact
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====================
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A documentation explaining how to use this new optimization strategy.
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References
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==========
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None
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History
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=======
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None |