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Defeating AWS OOM and Cloud Costs: A Zero-Cloud-Cost Architecture using 128GB Bare-Metal, Polars, and jemalloc

Enterprises continuously burn thousands of dollars on AWS high-memory instances (e.g., r5.4xlarge) to avoid Out-Of-Memory (OOM) crashes when processing massive datasets or running local LLM inferences. Scaling vertically in the cloud is a costly workaround for inefficient memory architecture.

We engineered a Zero-Cloud-Cost, fully Air-Gapped data infrastructure that fundamentally eradicates OOM errors by locking the memory footprint to a constant O(1) space.

The Hardware & Tech Stack

The baseline is a bare-metal HPC fortress: an HP Z4 G4 Workstation equipped with an Intel Xeon W-2155 (10C/20T), 128GB ECC RAM, and an RTX 5060 Ti 16GB.

Rather than relying on pandas (which loads entire datasets into RAM and causes alignment cliffs), we utilized Polars LazyFrames and out-of-core streaming. State management was completely migrated from in-memory accumulation to an SQLite WAL (Write-Ahead Logging) database, utilizing atomic 2-phase commits per 50,000-row chunk.

Eradicating the OOM Killer with jemalloc

Python and glibc's memory allocator notoriously delay memory returns, leading to severe fragmentation and inevitable SIGKILL terminations in containerized environments. We bypassed this entirely by hard-injecting libjemalloc2 into the Docker container.

By injecting LD_PRELOAD=/usr/lib/x86_64-linux-gnu/libjemalloc.so.2 and aggressively tuning _RJEM_MALLOC_CONF="background_thread:true,dirty_decay_ms:0,muzzy_decay_ms:0", we forced immediate background memory reclamation.

Deterministic Evidence

The results are deterministic and reproducible:

  • Throughput & Memory Footprint: Processed 10M+ rows while the host RAM remained strictly locked between 7GB and 9GB maximum (O(1) constant space) despite processing massive continuous datasets.
  • Cloud Costs & Egress: $0.00.
  • Security: 100% offline (launched with --network none), mathematically guaranteeing zero PHI/PII data leakage for absolute HIPAA/GDPR compliance.

Cloud scalability is not a panacea for poor data engineering. On-premise, air-gapped HPC provides deterministic performance, absolute data privacy, and zero recurring compute costs.

Need a HIPAA/GDPR-compliant, Zero-Cloud-Cost infrastructure deployed directly to your bare-metal environment?
I do not ask for your sensitive data; I deliver the air-gapped architecture so you can process it securely yourself.

👉 Hire me on Upwork for Fixed-Price enterprise consulting:
https://www.upwork.com/freelancers/shotamatsubara

👉 Connect with me on LinkedIn:
https://www.linkedin.com/in/shota-matsubara-hpc/

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