Fix for empty top-level models and non-empty sub-models

service_capacity_modeling/capacity_planner.py

@@ -368,8 +368,7 @@ def _plan_percentiles(
 
         mean_plans = []
         for mean_sub_model, mean_sub_desire in model_mean_desires.items():
-            mean_plans.append(
-                self._plan_certain(
+            mean_sub_plan = self._plan_certain(
                     model_name=mean_sub_model,
                     region=region,
                     desires=mean_sub_desire,
@@ -380,7 +379,8 @@ def _plan_percentiles(
                     instance_families=instance_families,
                     drives=drives,
                 )
-            )
+            if mean_sub_plan:
+                mean_plans.append(mean_sub_plan)
 
         mean_plan = cast(
             Sequence[CapacityPlan],
@@ -392,8 +392,7 @@ def _plan_percentiles(
             for percentile_sub_model, percentile_sub_desire in model_percentile_desires[
                 index
             ].items():
-                percentile_plan.append(
-                    self._plan_certain(
+                percentile_sub_plan = self._plan_certain(
                         model_name=percentile_sub_model,
                         region=region,
                         desires=percentile_sub_desire,
@@ -404,7 +403,9 @@ def _plan_percentiles(
                         instance_families=instance_families,
                         drives=drives,
                     )
-                )
+                if percentile_sub_plan:
+                    percentile_plan.append(percentile_sub_plan)
+
             percentile_plans[percentile] = cast(
                 Sequence[CapacityPlan],
                 [
@@ -443,8 +444,7 @@ def plan_certain(
             desires=desires,
             extra_model_arguments=extra_model_arguments,
         ):
-            results.append(
-                self._plan_certain(
+            sub_plan = self._plan_certain(
                     model_name=sub_model,
                     region=region,
                     desires=sub_desires,
@@ -455,7 +455,8 @@ def plan_certain(
                     instance_families=instance_families,
                     drives=drives,
                 )
-            )
+            if sub_plan:
+                results.append(sub_plan)
 
         return [functools.reduce(merge_plan, composed) for composed in zip(*results)]
 

tests/netflix/test_elasticsearch.py

@@ -39,7 +39,7 @@ def test_es_increasing_qps_simple():
         for zonal in cap_plan.least_regret[0].candidate_clusters.zonal:
             zonal_result[zonal.cluster_type].append(zonal_summary(zonal))
 
-    expected_families = set(["r", "m", "i"])
+    expected_families = {"r", "m", "i"}
     for cluster_type in list(zonal_result.keys()):
         zonal_by_increasing_qps = zonal_result[cluster_type]
 
@@ -62,6 +62,72 @@ def test_es_increasing_qps_simple():
         ), f"disk for {cluster_type} going down as QPS went up?"
 
 
+def test_es_simple_mean_percentiles():
+    simple = CapacityDesires(
+        service_tier=1,
+        query_pattern=QueryPattern(
+            estimated_read_per_second=Interval(
+                low=100, mid=1000, high=10_000, confidence=0.98
+            ),
+            estimated_write_per_second=Interval(
+                low=100, mid=1000, high=10_000, confidence=0.98
+            ),
+        ),
+        data_shape=DataShape(
+            estimated_state_size_gib=Interval(
+                low=20, mid=200, high=2000, confidence=0.98
+            ),
+        ),
+    )
+
+    cap_plan = planner.plan(
+        model_name="org.netflix.elasticsearch",
+        region="us-east-1",
+        desires=simple,
+        simulations=256,
+    )
+
+    assert len(cap_plan.mean) > 0, "mean is empty"
+    assert (
+        all(mean_plan for mean_plan in cap_plan.mean)
+    ), "One or more mean plans are empty"
+
+    assert len(cap_plan.percentiles) > 0, "percentiles are empty"
+    assert (
+        all(percentile_plan for percentile_plan in cap_plan.percentiles.values())
+    ), "One or more percentile plans are empty"
+
+
+def test_es_simple_certain():
+    simple = CapacityDesires(
+        service_tier=1,
+        query_pattern=QueryPattern(
+            estimated_read_per_second=Interval(
+                low=100, mid=1000, high=10_000, confidence=0.98
+            ),
+            estimated_write_per_second=Interval(
+                low=100, mid=1000, high=10_000, confidence=0.98
+            ),
+        ),
+        data_shape=DataShape(
+            estimated_state_size_gib=Interval(
+                low=20, mid=200, high=2000, confidence=0.98
+            ),
+        ),
+    )
+
+    cap_plan = planner.plan_certain(
+        model_name="org.netflix.elasticsearch",
+        region="us-east-1",
+        desires=simple,
+    )
+
+    assert len(cap_plan) > 0, "Resulting cap_plan is empty"
+    assert (
+        all(plan for plan in cap_plan)
+    ), "One or more plans is empty"
+
+
 def zonal_summary(zlr):
     zlr_cpu = zlr.count * zlr.instance.cpu
     zlr_cost = zlr.annual_cost