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feat(e2e): jmx.py supports obtaining the maximum average value of all windows #1595

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Jul 23, 2024
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feat(e2e): jmx.py supports obtaining the maximum average value of all windows #1595

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20 changes: 20 additions & 0 deletions tests/kafkatest/services/monitor/jmx.py
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Original file line number Diff line number Diff line change
Expand Up @@ -40,6 +40,11 @@ def __init__(self, num_nodes, jmx_object_names=None, jmx_attributes=None, jmx_po
self.maximum_jmx_value = {} # map from object_attribute_name to maximum value observed over time
self.average_jmx_value = {} # map from object_attribute_name to average value observed over time

# AutoMQ inject start
self.jmx_windows_size = 11
self.jmx_window_max_avg_values = {} # map from object_attribute_name to the maximum average value observed over windows of time
# AutoMQ inject end

self.jmx_tool_log = os.path.join(root, "jmx_tool.log")
self.jmx_tool_err_log = os.path.join(root, "jmx_tool.err.log")

Expand Down Expand Up @@ -130,6 +135,21 @@ def read_jmx_output(self, idx, node):
aggregates_per_time.append(sum(values_per_node))
self.average_jmx_value[name] = sum(aggregates_per_time) / len(aggregates_per_time)
self.maximum_jmx_value[name] = max(aggregates_per_time)
# AutoMQ inject start
max_avg_value = float('-inf')
windows_size = self.jmx_windows_size
window_sum = sum(aggregates_per_time[:windows_size])
window_count = min(windows_size, len(aggregates_per_time))
if window_count > 0:
max_avg_value = window_sum / window_count
for i in range(windows_size, len(aggregates_per_time)):
window_sum -= aggregates_per_time[i - windows_size]
window_sum += aggregates_per_time[i]
window_avg = window_sum / windows_size
if window_avg > max_avg_value:
max_avg_value = window_avg
self.jmx_window_max_avg_values[name] = max_avg_value if max_avg_value != float('-inf') else 0
# AutoMQ inject end

def read_jmx_output_all_nodes(self):
for node in self.nodes:
Expand Down
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