From 154ab7b2f9ad80fe432d2c036d5e8c4ee171897b Mon Sep 17 00:00:00 2001
From: Balazs Gibizer <balazs.gibizer@est.tech>
Date: Thu, 11 Nov 2021 19:06:56 +0100
Subject: [PATCH] Add debug log for scheduler weight calculation

We have all the weighers enabled by default and each can have its own
multiplier making the final compute node order calculation pretty
complex. This patch adds some debug logging that helps understanding how
the final ordering was reached.

Change-Id: I7606d6eb3e08548c1df9dc245ab39cced7de1fb5
---
 nova/weights.py | 40 ++++++++++++++++++++++++++++++++++++----
 1 file changed, 36 insertions(+), 4 deletions(-)

diff --git a/nova/weights.py b/nova/weights.py
index 97dc7d32912e..75d51dc5f799 100644
--- a/nova/weights.py
+++ b/nova/weights.py
@@ -19,9 +19,14 @@ Pluggable Weighing support
 
 import abc
 
+from oslo_log import log as logging
+
 from nova import loadables
 
 
+LOG = logging.getLogger(__name__)
+
+
 def normalize(weight_list, minval=None, maxval=None):
     """Normalize the values in a list between 0 and 1.0.
 
@@ -128,13 +133,40 @@ class BaseWeightHandler(loadables.BaseLoader):
         for weigher in weighers:
             weights = weigher.weigh_objects(weighed_objs, weighing_properties)
 
+            LOG.debug(
+                "%s: raw weights %s",
+                weigher.__class__.__name__,
+                {(obj.obj.host, obj.obj.nodename): weight
+                 for obj, weight in zip(weighed_objs, weights)}
+            )
+
             # Normalize the weights
-            weights = normalize(weights,
-                                minval=weigher.minval,
-                                maxval=weigher.maxval)
+            weights = list(
+                normalize(
+                    weights, minval=weigher.minval, maxval=weigher.maxval))
+
+            LOG.debug(
+                "%s: normalized weights %s",
+                weigher.__class__.__name__,
+                {(obj.obj.host, obj.obj.nodename): weight
+                 for obj, weight in zip(weighed_objs, weights)}
+            )
+
+            log_data = {}
 
             for i, weight in enumerate(weights):
                 obj = weighed_objs[i]
-                obj.weight += weigher.weight_multiplier(obj.obj) * weight
+                multiplier = weigher.weight_multiplier(obj.obj)
+                weigher_score = multiplier * weight
+                obj.weight += weigher_score
+
+                log_data[(obj.obj.host, obj.obj.nodename)] = (
+                    f"{multiplier} * {weight}")
+
+            LOG.debug(
+                "%s: score (multiplier * weight) %s",
+                weigher.__class__.__name__,
+                {name: log for name, log in log_data.items()}
+            )
 
         return sorted(weighed_objs, key=lambda x: x.weight, reverse=True)