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-rw-r--r--docs/cpta/data/index.rst8
-rw-r--r--docs/cpta/index.rst14
-rw-r--r--docs/cpta/introduction/index.rst17
-rw-r--r--docs/cpta/methodology/index.rst48
-rw-r--r--docs/cpta/trending/index.rst4
5 files changed, 48 insertions, 43 deletions
diff --git a/docs/cpta/data/index.rst b/docs/cpta/data/index.rst
index a81f25e8fb..f9992ed335 100644
--- a/docs/cpta/data/index.rst
+++ b/docs/cpta/data/index.rst
@@ -1,8 +1,8 @@
-Daily Trending Data
-===================
+Performance Data
+================
-The data used to generate the trending plots is available in a CSV and
-pretty ASCII formats:
+Performance test data used to generate the trendline graphs is available
+in a CSV and pretty ASCII formats:
- `csv format <../_static/vpp/cpta-trending.csv>`_,
- `pretty ASCII format <../_static/vpp/cpta-trending.txt>`_.
diff --git a/docs/cpta/index.rst b/docs/cpta/index.rst
index fb4fc7a808..3fd92c6f79 100644
--- a/docs/cpta/index.rst
+++ b/docs/cpta/index.rst
@@ -1,11 +1,11 @@
-Continuous Performance Trending and Analysis
-============================================
+Continuous Performance Trending
+===============================
-This auto-generated document contains VPP performance trending graphs and data.
-It is generated using CSIT continuous trending test and analysis jobs and is
-updated daily. More detail is available on
-`CSIT Performance Trending and Analysis <https://wiki.fd.io/view/CSIT/PerformanceTrendingAnalysis>`_
-wiki page.
+This document contains VPP performance dashboard, trendline graphs and
+performance test data. It is generated using FD.io CSIT continuous
+performance trending and analysis jobs and is updated daily. See
+:ref:`trending_methodology` section for more details including trend
+analysis and anomaly detection methodology.
Contents
--------
diff --git a/docs/cpta/introduction/index.rst b/docs/cpta/introduction/index.rst
index c724c30bad..016037b067 100644
--- a/docs/cpta/introduction/index.rst
+++ b/docs/cpta/introduction/index.rst
@@ -8,13 +8,12 @@ Performance dashboard tables provide the latest VPP throughput trend,
trend compliance and detected anomalies, all on a per VPP test case
basis. Linked trendline graphs enable further drill-down into the
trendline compliance, sequence and nature of anomalies, as well as
-pointers to performance test builds/logs and VPP builds.
-
-Performance trending is currently based 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. See :ref:`trending_methodology` section for
-more detail including trend and anomaly calculations.
+pointers to performance test builds/logs and VPP builds. Performance
+trending is currently based 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. See :ref:`trending_methodology` section for more detail including
+trend and anomaly calculations.
Data samples are generated by the CSIT VPP performance trending jobs
executed twice a day (target start: every 12 hrs, 02:00, 14:00 UTC). All
@@ -36,8 +35,8 @@ Legend to table:
Tested VPP worker-thread-core combinations (1t1c, 2t2c, 4t4c) are listed
in separate tables in section 1.x. Followed by trending methodology in
-section 2. and daily trending graphs in sections 3.x. Daily trending
-data used for graphs is provided in sections 4.x.
+section 2. and trendline graphs in sections 3.x. Performance test data
+used for trendline graphs is provided in sections 4.x.
VPP worker on 1t1c
------------------
diff --git a/docs/cpta/methodology/index.rst b/docs/cpta/methodology/index.rst
index 5efdfaae32..227dfbcb02 100644
--- a/docs/cpta/methodology/index.rst
+++ b/docs/cpta/methodology/index.rst
@@ -97,6 +97,8 @@ Outlier Detection
Outlier evaluation of test result of value <X> follows the definition
from previous section:
+ ::
+
Outlier Evaluation Formula Evaluation Result
====================================================
X < (Q1 - 1.5 * IQR) Outlier
@@ -109,6 +111,8 @@ To verify compliance of test result of valid value <X> against defined
trend metrics and detect anomalies, three simple evaluation formulas are
used:
+ ::
+
Anomaly Compliance Evaluation
Evaluation Formula Confidence Level Result
=============================================================================
@@ -129,7 +133,9 @@ 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
+ ::
+
+ Trend
Compliance Metric Change Formula V(alue) R(eference)
=============================================================================================
Short-Term Change ((V - R) / R) TMM[last] TMM[last - 1week]
@@ -179,15 +185,15 @@ data per test case. PT is designed as follows:
#. PT job triggers:
- #. Periodic e.g. daily.
- #. On-demand gerrit triggered.
+ - Periodic e.g. daily.
+ - On-demand gerrit triggered.
#. Measurements and data calculations per test case:
- #. MRR Max Received Rate
+ - MRR Max Received Rate
- #. Measured: Unlimited tolerance of packet loss.
- #. Send packets at link rate, count total received packets, divide
+ - Measured: Unlimited tolerance of packet loss.
+ - Send packets at link rate, count total received packets, divide
by test trial period.
#. Archive MRR per test case.
@@ -203,18 +209,18 @@ PA is defined as follows:
#. PA job triggers:
- #. By PT job at its completion.
- #. On-demand gerrit triggered.
+ - By PT job at its completion.
+ - On-demand gerrit triggered.
#. Download and parse archived historical data and the new data:
- #. Download RF output.xml files from latest PT job and compressed
+ - Download RF output.xml files from latest PT job and compressed
archived data.
- #. Parse out the data filtering test cases listed in PA specification
+ - Parse out the data filtering test cases listed in PA specification
(part of CSIT PAL specification file).
- #. Evalute new data from latest PT job against the rolling window of
+ - Evalute new data from latest PT job against the rolling window of
<N> sets of historical data for trendline calculation, anomaly
detection and short-term trend compliance. And against long-term
trendline metrics for long-term trend compliance.
@@ -222,23 +228,23 @@ PA is defined as follows:
#. Calculate trend metrics for the rolling window of <N> sets of
historical data:
- #. Calculate quartiles Q1, Q2, Q3.
- #. Trim outliers using IQR.
- #. Calculate TMA and TMSD.
- #. Calculate normal trending range per test case based on TMM and
+ - Calculate quartiles Q1, Q2, Q3.
+ - Trim outliers using IQR.
+ - Calculate TMA and TMSD.
+ - Calculate normal trending range per test case based on TMM and
TMSD.
#. Evaluate new test data against trend metrics:
- #. If within the range of (TMA +/- 3*TMSD) => Result = Pass,
+ - If within the range of (TMA +/- 3*TMSD) => Result = Pass,
Reason = Normal. (to be updated base on the final Jenkins code).
- #. If below the range => Result = Fail, Reason = Regression.
- #. If above the range => Result = Pass, Reason = Progression.
+ - If below the range => Result = Fail, Reason = Regression.
+ - If above the range => Result = Pass, Reason = Progression.
#. Generate and publish results
- #. Relay evaluation result to job result. (to be updated base on the
+ - Relay evaluation result to job result. (to be updated base on the
final Jenkins code).
- #. Generate a new set of trend summary dashboard and graphs.
- #. Publish trend dashboard and graphs in html format on
+ - Generate a new set of trend summary dashboard and graphs.
+ - Publish trend dashboard and graphs in html format on
https://docs.fd.io/.
diff --git a/docs/cpta/trending/index.rst b/docs/cpta/trending/index.rst
index ed8c63fec3..1560c5ece4 100644
--- a/docs/cpta/trending/index.rst
+++ b/docs/cpta/trending/index.rst
@@ -1,5 +1,5 @@
-Daily Trending Graphs
-=====================
+Trendline Graphs
+================
.. toctree::