Background
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Hardware benchmarking validated big data performance at enterprise scale

Client: Enterprise infrastructure provider | Solution: Automated benchmarking framework validated scalability

Testing couldn't keep pace with deployment

Engineers spent days configuring test environments manually. Benchmark results weren't reproducible across geographies. Each hardware variant required separate setup, and teams had no way to track performance changes across releases or compare configurations reliably. 

Solution 

Calsoft built an automated benchmarking framework using containerized environments and industry-standard tools. The system simulated realistic big data workloads and delivered consistent, traceable results. 

  • Deploy test environments on demand with automated orchestration 
  • Run SparkBench, BigBench, and HiBench workloads at scale 
  • Track performance across hardware variants with version control 
  • Tune parameters dynamically through runtime configuration 

The framework enabled engineering teams to validate end-to-end performance from storage through compute, mirroring operational conditions. 

Business Value

Background
System scalability assurance
System scalability assurance
Validated performance under multi-node big data and ML conditions
Regression detection
Regression detection
Enabled consistent comparison across builds and architecture changes
Engineering efficiency
Engineering efficiency
Reduced test setup and analysis time by over 40% through automation
Benchmark standardization
Benchmark standardization
Established repeatable methodology across global teams and lab environments
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Automated Benchmarking Framework for Big Data Hardware Validation