Background
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Unified benchmarking framework validated edge system performance reliably

Client: Global technology provider | Solution: Automated framework standardized edge performance testing across systems.

Edge systems lacked consistent performance baselines

Engineering teams tested edge hardware with fragmented tools and inconsistent parameters. Performance data varied across labs, making it difficult to validate system behavior or compare configurations. Results came as raw logs with no visual analysis, and tests focused primarily on storage while ignoring CPU, memory, and network metrics. 

Solution 

Calsoft built an automated benchmarking framework using open-source tools integrated through Python. Teams could run standardized tests and view results through visual dashboards. 

  • Simulate I/O patterns with FIO for storage benchmarking 
  • Measure network throughput using iperf3 under load 
  • Validate CPU and memory with sysbench stress tests 
  • Automate execution and visualization with Python scripts 

The framework incorporated edge-specific constraints like power limits and thermal behavior to reflect real deployment conditions. 

Business Value

Background
Performance visibility
Performance visibility
Quantified CPU, memory, storage, and network metrics across edge systems
Benchmark repeatability
Benchmark repeatability
Enabled consistent testing with reusable profiles across hardware and environments
Load test reliability
Load test reliability
Validated system endurance under stress with fio and stress-ng simulations
Test automation
Test automation
Reduced manual setup by integrating tools under a Python automation layer
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Edge Performance Benchmarking Framework