K6 Performance Data Analysis - CPS-2587
# | Test Name | Unit | No Load | 500 AVC events / Sec | % loss / grain | 1000 AVC events / Sec | % loss / grain |
3a | CM-handle ID search with No filter | milliseconds | 1002.51 | 1066.74 | -6.41 | 1007.36 | -0.48 |
3b | CM-handle ID search with Module filter | milliseconds | 243.27 | 258.88 | -6.42 | 247.30 | -1.66 |
3c | CM-handle ID search with Property filter | milliseconds | 2233.34 | 2403.60 | -7.62 | 2210.88 | 1.01 |
3d | CM-handle ID search with Cps Path filter | milliseconds | 2276.14 | 2448.58 | -7.58 | 2278.06 | -0.08 |
3e | CM-handle ID search with Trust Level filter | milliseconds | 11352.99 | 12282.97 | -8.19 | 11119.16 | 2.06 |
4a | CM-handle search with No filter | milliseconds | 8392.92 | 9174.56 | -9.31 | 8344.07 | 0.58 |
4b | CM-handle search with Module filter | milliseconds | 10577.62 | 11420.00 | -7.96 | 10525.88 | 0.49 |
4c | CM-handle search with Property filter | milliseconds | 12499.24 | 13382.81 | -7.07 | 12315.46 | 1.47 |
4d | CM-handle search with Cps Path filter | milliseconds | 13016.59 | 14144.85 | -8.67 | 12793.77 | 1.71 |
4e | CM-handle search with Trust Level filter | milliseconds | 22222.07 | 23839.57 | -7.28 | 22134.21 | 0.40 |
5a | NCMP overhead for Synchronous single CM-handle pass-through read | milliseconds | 34.28 | 35.15 | -2.53 | 34.65 | -1.08 |
5b | NCMP overhead for Synchronous single CM-handle pass-through read with alternate id | milliseconds | 92.48 | 95.15 | -2.88 | 91.33 | 1.24 |
6a | NCMP overhead for Synchronous single CM-handle pass-through write | milliseconds | 39.94 | 42.18 | -5.62 | 41.87 | -4.83 |
6b | NCMP overhead for Synchronous single CM-handle pass-through write with alternate id | milliseconds | 90.35 | 96.70 | -7.03 | 90.95 | -0.66 |
7 | Legacy batch read operation | events/second | 116.18 | 109.83 | 5.47 | 113.45 | 2.36 |
Overview
The following document provides an in-depth analysis of K6 performance data collected from various test builds. The dataset measures key performance indicators such as search efficiency across different scenarios.
Key Metrics and Observations
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CM Data Performance Test Results
Overview
This page documents the results of the CM data performance test conducted to evaluate the system's response time under different loads. The tests measured the impact of processing 500 and 1,000 AVC events per second on various CM-handle search and NCMP overhead operations.
Test Details
Test Environment: [Nordix-onap-cps-performance-test-k6 ]
Load Conditions:
No Load: Baseline measurement without additional event processing.
500 AVC events/sec: Moderate load scenario.
1000 AVC events/sec: High load scenario.
Metric: Response time in milliseconds (ms) for search and pass-through operations.
Objective: Measure performance degradation (percentage loss/gain) under different load conditions.
Results Summary
CM-Handle ID Search Performance
This test measures the time required to search for a CM-handle ID with different filters.
Test Name | No Load (ms) | 500 AVC events/sec (ms) | % Loss/Gain | 1000 AVC events/sec (ms) | % Loss/Gain |
|---|---|---|---|---|---|
No Filter | 1,003 | 1,067 | -6.4% | 1,122 | -12.0% |
Module Filter | 243 | 259 | -6.4% | 264 | -8.7% |
Property Filter | 2,233 | 2,404 | -7.6% | 2,541 | -13.8% |
Cps Path Filter | 2,276 | 2,449 | -7.6% | 2,589 | -13.7% |
Trust Level Filter | 11,353 | 12,283 | -8.2% | 13,367 | -17.7% |
Analysis:
All ID search operations show performance degradation as load increases.
The Trust Level Filter search has the highest latency, with a 17.7% increase in response time at 1,000 AVC events/sec.
CM-Handle Search Performance
These tests measure search time for CM-handles with various filters.
Test Name | No Load (ms) | 500 AVC events/sec (ms) | % Loss/Gain | 1000 AVC events/sec (ms) | % Loss/Gain |
|---|---|---|---|---|---|
No Filter | 8,393 | 9,175 | -9.3% | 9,809 | -16.9% |
Module Filter | 10,578 | 11,420 | -8.0% | 12,000 | -13.4% |
Property Filter | 12,499 | 13,383 | -7.1% | 14,519 | -16.2% |
Cps Path Filter | 13,017 | 14,145 | -8.7% | 14,925 | -14.7% |
Trust Level Filter | 22,222 | 23,840 | -7.3% | 25,452 | -14.5% |
Analysis:
Performance degradation is noticeable, especially at 1,000 AVC events/sec.
CM-handle search with No Filter shows a 16.9% degradation, indicating it is heavily impacted by load.
Trust Level Filter search remains the slowest operation across tests.
NCMP Overhead Analysis
This test measures the additional processing time for synchronous pass-through read/write operations.
Test Name | No Load (ms) | 500 AVC events/sec (ms) | % Loss/Gain | 1000 AVC events/sec (ms) | % Loss/Gain |
|---|---|---|---|---|---|
Read | 34 | 35 | -2.5% | 37 | -7.5% |
Read (Alternate ID) | 92 | 95 | -2.9% | 98 | -6.1% |
Write | 40 | 42 | -5.6% | 46 | -14.6% |
Write (Alternate ID) | 90 | 97 | -7.0% | 100 | -10.7% |
Analysis:
Read operations are less affected by load compared to write operations.
Write operations, especially at 1,000 AVC events/sec, show a 14.6% increase in processing time.
Legacy Batch Read Performance
This test measures batch read operations per second.
Test Name | No Load (events/sec) | 500 AVC events/sec | % Loss/Gain | 1000 AVC events/sec | % Loss/Gain |
|---|---|---|---|---|---|
Legacy Batch Read | 116 | 110 | 5.5% | 107 | 8.1% |
Analysis:
Unlike search and write operations, legacy batch read performance improves under load, showing a 5.5% gain at 500 AVC events/sec and 8.1% gain at 1,000 AVC events/sec.
Conclusion & Recommendations
Performance Degradation Observed: Across all test cases, response times increase under load, with Trust Level Filter searches being the most affected.
Read vs. Write Operations: NCMP synchronous write operations degrade more than read operations under high load.
Batch Read Stability: While performance shows a slight gain under load, batch reads remain consistent and improve efficiency as the event rate increases.
Recommendations:
Optimize Search Queries: Trust Level and CPS Path filters should be optimized to reduce processing time under high load.
Parallel Processing for Write Operations: Implementing parallelism or batching for synchronous writes may reduce the observed degradation.