Testing Horizontal Pod Autoscaler Configuration in Apache Airflow
This test suite validates the Horizontal Pod Autoscaler (HPA) functionality for the Apache Airflow webserver in Helm deployments. It ensures proper scaling behavior, metric configurations, and label management for Kubernetes HPA resources.
Test Coverage Overview
Implementation Analysis
Technical Details
Best Practices Demonstrated
apache/airflow
helm_tests/webserver/test_hpa_webserver.py
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from __future__ import annotations
import jmespath
import pytest
from tests.charts.helm_template_generator import render_chart
class TestWebserverHPA:
"""Tests HPA."""
def test_hpa_disabled_by_default(self):
"""Disabled by default."""
docs = render_chart(
values={},
show_only=["templates/webserver/webserver-hpa.yaml"],
)
assert docs == []
def test_should_add_component_specific_labels(self):
docs = render_chart(
values={
"webserver": {
"hpa": {"enabled": True},
"labels": {"test_label": "test_label_value"},
},
},
show_only=["templates/webserver/webserver-hpa.yaml"],
)
assert "test_label" in jmespath.search("metadata.labels", docs[0])
assert jmespath.search("metadata.labels", docs[0])["test_label"] == "test_label_value"
@pytest.mark.parametrize(
"min_replicas, max_replicas",
[
(None, None),
(2, 8),
],
)
def test_min_max_replicas(self, min_replicas, max_replicas):
"""Verify minimum and maximum replicas."""
docs = render_chart(
values={
"webserver": {
"hpa": {
"enabled": True,
**({"minReplicaCount": min_replicas} if min_replicas else {}),
**({"maxReplicaCount": max_replicas} if max_replicas else {}),
}
},
},
show_only=["templates/webserver/webserver-hpa.yaml"],
)
assert jmespath.search("spec.minReplicas", docs[0]) == 1 if min_replicas is None else min_replicas
assert jmespath.search("spec.maxReplicas", docs[0]) == 5 if max_replicas is None else max_replicas
def test_hpa_behavior(self):
"""Verify HPA behavior."""
expected_behavior = {
"scaleDown": {
"stabilizationWindowSeconds": 300,
"policies": [{"type": "Percent", "value": 100, "periodSeconds": 15}],
}
}
docs = render_chart(
values={
"webserver": {
"hpa": {
"enabled": True,
"behavior": expected_behavior,
},
},
},
show_only=["templates/webserver/webserver-hpa.yaml"],
)
assert jmespath.search("spec.behavior", docs[0]) == expected_behavior
@pytest.mark.parametrize(
"metrics, expected_metrics",
[
# default metrics
(
None,
{
"type": "Resource",
"resource": {"name": "cpu", "target": {"type": "Utilization", "averageUtilization": 80}},
},
),
# custom metric
(
[
{
"type": "Pods",
"pods": {
"metric": {"name": "custom"},
"target": {"type": "Utilization", "averageUtilization": 80},
},
}
],
{
"type": "Pods",
"pods": {
"metric": {"name": "custom"},
"target": {"type": "Utilization", "averageUtilization": 80},
},
},
),
],
)
def test_should_use_hpa_metrics(self, metrics, expected_metrics):
docs = render_chart(
values={
"webserver": {
"hpa": {"enabled": True, **({"metrics": metrics} if metrics else {})},
},
},
show_only=["templates/webserver/webserver-hpa.yaml"],
)
assert expected_metrics == jmespath.search("spec.metrics[0]", docs[0])