Report host memory bandwidth as a metric in Nova

This spec proposes to introduce host memory bandwidth as a host metric.
Memory bandwidth can be a essential piece in determining VM performance
bottlenecks and further can be used for better NUMA based placements.

Using the linux platform interfaces like perf APIs, nova-compute
should be able to expose Host's memory bandwidth utilization on every
NUMA node.This memory b/w can be leveraged in Openstack by exposing
it as a monitor.

Change-Id: I26b0766f234f38d54efa3a5f101dca2959621419
Blueprint: memory-bw

specs/liberty/approved/mem-bw.rst

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+..
+ This work is licensed under a Creative Commons Attribution 3.0 Unported
+ License.
+
+ http://creativecommons.org/licenses/by/3.0/legalcode
+
+==========================================
+Report host memory b/w as a metric in Nova
+==========================================
+
+https://blueprints.launchpad.net/nova/+spec/memory-bw
+
+This spec proposes to introduce host memory b/w as a host metric.
+Memory b/w can be a essential piece in determining VM performance
+bottlenecks and further can be used for better NUMA based placements.
+
+Using Linux platform interface like linux perf APIs, nova-compute
+should be able to expose host's memory bandwidth utilization on
+every NUMA node.
+This memory b/w can be leveraged in Openstack by exposing it as a
+monitor.
+
+This will follow a similar approach as the already existing monitor
+for CPU.(cpu_monitor.py)
+
+Problem description
+===================
+
+Workload optimization for high CPU/Memory intensive workload can be
+challenging. This applies to workloads running Redis/Hadoop etc.
+Host Memory B/W utilization data is a key indicator to denote the
+memory bus overload and can be exposed via the Linux Perf APIs.
+This metric can then be leveraged for better placement/optimization
+of high CPU/memory intensive workloads.
+
+
+Use Cases
+----------
+
+* Get memory b/w stats as a metric data by adding a new subclass
+  of BaseResourceMonitor.
+
+
+Project Priority
+-----------------
+
+None
+
+
+Proposed change
+===============
+
+Performance co-pilot (PCP) is a system performance and analysis
+framework available with most of the popular distros. The linux perf
+APIs are called via the PCP tool. The PCPD daemon can be used to
+obtain/fetch values of the Nest/Uncore memory PMU counters on each
+NUMA node.
+
+PCP provides the python bindings that would be called via openstack
+monitor code in nova to obtain the desired values for memory bandwidth
+utilization.
+
+Estimated changes are going to be in the following places:
+
+* Extend the Resource monitor framework to implement a optional
+  monitor for Memory B/W utilization, much in line with the CPU
+  monitor.
+
+* Define two methods in the virt driver parent class and implement
+  them in the livirt driver:
+
+  - `get_max_memory_bw`: Returns the maximum memory bandwidth for each
+    NUMA node.
+
+  - `get_memory_bw_counter_agg`: Returns the value of the aggregated counter
+    values associated with memory bandwidth for each NUMA node.
+
+  Nova shall calculate the diff of the aggregated counter values over two calls
+  and calculate the rate. This rate will be compared against the maximum bw
+  value to obtain the utilization. get_max_memory_bw shall be called only once
+  during the initialization of the monitor.
+
+  The unit of representation of the rate will be made consistent with the
+  value obtained from the counters.
+
+* Introduce a nova object model representation of the data.
+
+
+Alternatives
+------------
+
+The alternative is to call the perf APIs directly but that introduces
+platform specific dependencies. PMU counter names and the math to derive
+memory bandwidth shall vary across platforms and types of hardware. This
+gap shall be bridged by PCP.
+
+
+Data model impact
+-----------------
+
+None
+
+
+REST API impact
+---------------
+
+None
+
+Security impact
+---------------
+
+None.
+
+Notifications impact
+--------------------
+
+None
+
+Other end user impact
+---------------------
+
+None
+
+
+Performance Impact
+------------------
+
+The performance impact is negligible since the data is aggregated by the
+hardware and accessed via PCP. Openstack will call this API once a minute
+with an option to increase the interval.
+
+Other deployer impact
+---------------------
+
+The following packages should be added to the system:
+
+    * pcp
+    * python-pcp
+
+Developer impact
+----------------
+
+None
+
+Implementation
+==============
+
+Assignee(s)
+-----------
+
+Primary assignee:
+  Sudipta Biswas sbiswas7
+
+Other assignee:
+  Pradipta Banerjee bpradipt
+
+
+Work Items
+----------
+
+1. Use pcp python bindings to obtain the memory bw utilization.
+
+2. Perform data sampling in the monitoring code.
+
+3. Create metrics plugin to sample the memory b/w data.
+
+
+Dependencies
+============
+
+None
+
+
+Testing
+=======
+
+The changes will be exercised through unit tests.
+
+Documentation Impact
+====================
+
+None
+
+
+References
+==========
+
+http://pcp.io/
+
+