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author | Vratko Polak <vrpolak@cisco.com> | 2018-06-12 14:55:42 +0200 |
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committer | Vratko Polak <vrpolak@cisco.com> | 2018-06-12 14:55:42 +0200 |
commit | 06ffc53e2b8cc99d3fe30925ac34b5ba543db048 (patch) | |
tree | e8fc7bd079c556fe2dc61d2af3f4873aea010213 /docs/new/cpta/methodology | |
parent | 801499cd0cceeb1c98ee36d606b883041d8e046c (diff) |
CSIT-1110 PAL: Fix warnings by moving new docs
Change-Id: Ie6483e9245872bc6991ed1f3c7aab60131e1eeb1
Signed-off-by: Vratko Polak <vrpolak@cisco.com>
Diffstat (limited to 'docs/new/cpta/methodology')
-rw-r--r-- | docs/new/cpta/methodology/index.rst | 208 |
1 files changed, 208 insertions, 0 deletions
diff --git a/docs/new/cpta/methodology/index.rst b/docs/new/cpta/methodology/index.rst new file mode 100644 index 0000000000..ff69eb1f9a --- /dev/null +++ b/docs/new/cpta/methodology/index.rst @@ -0,0 +1,208 @@ +.. _trending_methodology: + +Trending Methodology +==================== + +Overview +-------- + +This document describes a high-level design of a system for continuous +performance measuring, trending and change detection for FD.io VPP SW +data plane. It builds upon the existing FD.io CSIT framework with +extensions to its throughput testing methodology, CSIT data analytics +engine (PAL – Presentation-and-Analytics-Layer) and associated Jenkins +jobs definitions. + +Proposed design replaces existing CSIT performance trending jobs and +tests with new Performance Trending (PT) CSIT module and separate +Performance Analysis (PA) module ingesting results from PT and +analysing, detecting and reporting any performance anomalies using +historical trending data and statistical metrics. PA does also produce +trending dashboard and graphs with summary and drill-down views across +all specified tests that can be reviewed and inspected regularly by +FD.io developers and users community. + +Performance Tests +----------------- + +Performance trending is currently relying on the Maximum Receive Rate +(MRR) tests. MRR tests measure the packet forwarding rate under the +maximum load offered by traffic generator over a set trial duration, +regardless of packet loss. Maximum load for specified Ethernet frame +size is set to the bi-directional link rate. + +Current parameters for performance trending MRR tests: + +- **Ethernet frame sizes**: 64B (78B for IPv6 tests) for all tests, IMIX for + selected tests (vhost, memif); all quoted sizes include frame CRC, but + exclude per frame transmission overhead of 20B (preamble, inter frame + gap). +- **Maximum load offered**: 10GE and 40GE link (sub-)rates depending on NIC + tested, with the actual packet rate depending on frame size, + transmission overhead and traffic generator NIC forwarding capacity. + + - For 10GE NICs the maximum packet rate load is 2* 14.88 Mpps for 64B, + a 10GE bi-directional link rate. + - For 40GE NICs the maximum packet rate load is 2* 18.75 Mpps for 64B, + a 40GE bi-directional link sub-rate limited by TG 40GE NIC used, + XL710. + +- **Trial duration**: 10sec. +- **Execution frequency**: twice a day, every 12 hrs (02:00, 14:00 UTC). + +Note: MRR tests should be reporting bi-directional link rate (or NIC +rate, if lower) if tested VPP configuration can handle the packet rate +higher than bi-directional link rate, e.g. large packet tests and/or +multi-core tests. In other words MRR = min(VPP rate, bi-dir link rate, +NIC rate). + +Trend Analysis +-------------- + +All measured performance trend data is treated as time-series data that +can be modelled as concatenation of groups, each group modelled +using normal distribution. While sometimes the samples within a group +are far from being distributed normally, we do not have a better tractable model. + +The group boundaries are selected based on `Minimum Description Length`_. + +TODO: Decide the level of detail for describing group selection. + +Anomaly Detection +````````````````` + +Once the trend data is divided into groups, each group has its population average. +The start of the following group is marked as a regression (or progression) +if the new group's average is lower (higher) then the previous group's. + +Metrics +``````` + +TODO: Only needed for current trend compliance. + +Following statistical metrics are used as performance trend indicators +over the rolling window of last <N> sets of historical measurement data: + +- **TMM** : **Trimmed Moving Median**, median across the data set of <N> + values excluding the outliers. Used as a trending value and as a + reference for anomaly detection. + +Trend Compliance +```````````````` + +TODO: Apply new detection algorithm also to trend compliance. + +Trend compliance metrics are targeted to provide an indication of trend +changes over a short-term (i.e. weekly) and a long-term (i.e. +quarterly), comparing the last trend value, TMM[last], to one from week +ago, TMM[last - 1week] and to the maximum of trend values over last +quarter except last week, max(TMM[(last - 3mths)..(last - 1week)]), +respectively. This results in following trend compliance calculations: + ++-------------------------+---------------------------------+-----------+------------------------------------------+ +| Trend Compliance Metric | Trend Change Formula | Value | Reference | ++=========================+=================================+===========+==========================================+ +| Short-Term Change | (Value - Reference) / Reference | TMM[last] | TMM[last - 1week] | ++-------------------------+---------------------------------+-----------+------------------------------------------+ +| Long-Term Change | (Value - Reference) / Reference | TMM[last] | max(TMM[(last - 3mths)..(last - 1week)]) | ++-------------------------+---------------------------------+-----------+------------------------------------------+ + +Trend Presentation +------------------ + +Performance Dashboard +````````````````````` + +Dashboard tables list a summary of per test-case VPP MRR performance +trend and trend compliance metrics and detected number of anomalies. + +Separate tables are generated for tested VPP worker-thread-core +combinations (1t1c, 2t2c, 4t4c). Test case names are linked to +respective trending graphs for ease of navigation thru the test data. + +Trendline Graphs +```````````````` + +Trendline graphs show per test case measured MRR throughput values with +associated gruop averages. The graphs are constructed as follows: + +- X-axis represents performance trend job build Id (csit-vpp-perf-mrr- + daily-master-build). +- Y-axis represents MRR throughput in Mpps. +- Markers to indicate anomaly classification: + + - Outlier - gray circle around MRR value point. + - Regression - red circle. + - Progression - green circle. + +In addition the graphs show dynamic labels while hovering over graph +data points, representing (trend job build Id, MRR value) and the actual +vpp build number (b<XXX>) tested. + + +Jenkins Jobs +------------ + +Performance Trending (PT) +````````````````````````` + +CSIT PT runs regular performance test jobs measuring and collecting MRR +data per test case. PT is designed as follows: + +1. PT job triggers: + + a) Periodic e.g. daily. + b) On-demand gerrit triggered. + +2. Measurements and data calculations per test case: + + a) Max Received Rate (MRR) - send packets at link rate over a trial + period, count total received packets, divide by trial period. + +3. Archive MRR per test case. +4. Archive all counters collected at MRR. + +Performance Analysis (PA) +````````````````````````` + +CSIT PA runs performance analysis including trendline calculation, trend +compliance and anomaly detection using specified trend analysis metrics +over the rolling window of last <N> sets of historical measurement data. +PA is defined as follows: + +1. PA job triggers: + + a) By PT job at its completion. + b) On-demand gerrit triggered. + +2. Download and parse archived historical data and the new data: + + a) Download RF output.xml files from latest PT job and compressed + archived data. + b) Parse out the data filtering test cases listed in PA specification + (part of CSIT PAL specification file). + +3. Re-calculate new groups and their averages. + +4. Evaluate new test data (TODO: Update.): + + a) If within the range of (TMA +/- 3*TMSD) => Result = Pass, + Reason = Normal. (to be updated base on the final Jenkins code). + b) If below the range => Result = Fail, Reason = Regression. + c) If above the range => Result = Pass, Reason = Progression. + +5. Generate and publish results + + a) Relay evaluation result to job result. (to be updated base on the + final Jenkins code). + b) Generate a new set of trend summary dashboard and graphs. + c) Publish trend dashboard and graphs in html format on + https://docs.fd.io/. + +Testbed HW configuration +------------------------ + +The testbed HW configuration is described on +`this FD.IO wiki page <https://wiki.fd.io/view/CSIT/CSIT_LF_testbed#FD.IO_CSIT_testbed_-_Server_HW_Configuration>`_. + +.. _Minimum Description Length: https://en.wikipedia.org/wiki/Minimum_description_length |