Performance profiling
If you like applying Performance profiling, every challenge here gives you a chance to practice it on a real industry brief.
- AnalysisBeginnerNew
Profile and Optimize a Virtual-Memory-Heavy Image Pipeline
Receive the Go pipeline source, a representative batch (1,200 photos averaging 12MB each, with 30 outliers over 80MB), and host specs (4-core, 16GB RAM, Linux kernel 5.15). Run …
- Virtual Memory
- Performance Profiling
- Memory Hierarchy
Computer Systems and Organization - CodeBeginnerNew
Build an I/O Benchmarking Harness for an Edge Storage Appliance
Receive the appliance specs (4x 7.68TB Gen4 NVMe, ZFS, Linux kernel 5.15), the 3 target workload profiles (4KB random read at QD32, 1MB sequential write at QD8, mixed 70/30 read…
- Io Benchmarking
- Fio
- System Calls
Computer Systems and Organization - CodeSeniorNew
Profile and Tame a P99-Latency Tail for an Ad-Auction Service
Receive the bidder source (Go, around 22,000 lines), production traces (eBPF + flame graphs from 30 minutes of peak traffic), and the host config (NUMA-2 socket, 96 cores, 384GB…
- Performance Optimization
- Ebpf
- Systems Language Proficiency (Go, Rust, C++)
Performance Engineering of Software Systems - CodeIntermediateNew
Scale Feature Pipelines for a Hyperscaler Search-Ranking Team
You receive a synthetic-but-realistic 80 GB sample of the ranking events plus the existing Spark pipeline (PySpark) and a Spark UI snapshot from a recent production run. Profile…
- Apache Spark
- Distributed Systems Design
- Performance Profiling
Machine Learning at Scale Practice your coursework on real scenarios.
Every challenge is shaped from real-world context — not generic exercises. The work mirrors what your degree prepares you for.
Why Ewance
- AnalysisIntermediateNew
Amortized-Analysis Investigation of a Production Cache
Read the C++ cache source (around 1,800 lines, custom open-addressing with periodic resize-and-rehash). Perform amortized analysis using all three methods (aggregate, accounting…
- Amortized Analysis
- Functions & Data Structures
- Algorithm Analysis
Advanced Algorithms - AnalysisIntermediateNew
Cost-Optimize a Large-Scale Spark Job for an Ad-Tech Platform
You receive the Spark job source (PySpark), the EMR cluster config, and 5 nights of job-history JSON. Profile the job with the Spark UI + EMR metrics, identify the top 3 cost dr…
- Spark Optimization
- Cloud Services
- Cost Engineering
Cloud Computing for Data and ML - AnalysisIntermediateNew
Diagnose a Memory-Hierarchy Bottleneck in a Trading-System Hot Path
Receive the normalizer source (around 4,000 lines of C++17), a replay harness that feeds 30 minutes of recorded market data, and host-machine specifications (Intel Xeon Gold 634…
- Memory Hierarchy
- Performance Profiling
- Perf
Computer Systems and Organization
How it works
From brief to credential, in six steps.
Step 01
Browse challenges aligned to your studies.
Step 02
Accept the one that fits your goals.
Step 03
Work through it with AI Copilot guidance.
Step 04
Submit for structured evaluation.
Step 05
Earn a verified credential.
Step 06
Add it to LinkedIn with one click.
Industry teams behind a decade of practitioner briefs
Hiring from this pool?
Sponsor a challenge and meet candidates through actual work.
Industry teams can shape briefs around the skills they hire for, then evaluate students on rubric-scored deliverables — not resumes.