Add release notes for Newton blueprints
Change-Id: Id643dae85b1df86796d27fa885aa7c7303d4f4d8
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---
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features:
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- Added a standard way to both declare and fetch
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configuration options so that whenever the
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administrator generates the Watcher
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configuration sample file, it contains the
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configuration options of the plugins that are
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currently available.
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---
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features:
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- Added a generic scoring engine module, which
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will standarize interactions with scoring engines
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through the common API. It is possible to use the
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scoring engine by different Strategies, which
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improve the code and data model re-use.
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---
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features:
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- Added an in-memory cache of the cluster model
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built up and kept fresh via notifications from
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services of interest in addition to periodic
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syncing logic.
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---
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features:
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- Added a way to add a new action without having to
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amend the source code of the default planner.
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---
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features:
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- Added a way to create periodic audit to be able to
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optimize continuously the cloud infrastructure.
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---
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features:
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- Added a way to compare the efficacy of different
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strategies for a give optimization goal.
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---
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features:
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- Added a way to return the of available goals depending
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on which strategies have been deployed on the node
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where the decison engine is running.
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---
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features:
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- Allow decision engine to pass strategy parameters,
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like optimization threshold, to selected strategy,
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also strategy to provide parameters info to end user.
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---
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features:
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- Copy all audit templates parameters into
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audit instead of having a reference to the
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audit template.
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---
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features:
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- Added a strategy that monitors if there is a higher
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load on some hosts compared to other hosts in the
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cluster and re-balances the work across hosts to
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minimize the standard deviation of the loads in
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the cluster.
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---
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features:
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- Added a new strategy based on the airflow
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of servers. This strategy makes decisions
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to migrate VMs to make the airflow uniform.
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---
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features:
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- Added policies to handle user rights
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to access Watcher API.
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---
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features:
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- Added a strategy based on the VM workloads of
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hypervisors. This strategy makes decisions to
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migrate workloads to make the total VM workloads
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of each hypervisor balanced, when the total VM
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workloads of hypervisor reaches threshold.
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