Pepitedata
  • Home
  • Audits
  • Expert Call
  • About
  • Blog
  • Contact

data

AI

Distilling frontier reasoning into a local model: what actually works

A small coding model mocked on r/LocalLLM is actually a clean case of execution-verified distillation. Here is how the method works, when distilling a frontier model into a cheap local one pays off, and the three things the hype leaves out.

By Julien Laurenceau, 2 months2026-06-22 ago
Abstract visualization of Sail engine bridging Rust and Spark technologies
apache spark

Sail: When Apache Spark Meets Rust (A Practitioner’s Deep Dive)

Sail is an open-source Apache Spark replacement written in Rust. It drops the JVM, speaks Spark Connect, and runs 4 to 6 times faster than Spark with native accelerators on ClickBench. A deep dive into its architecture, benchmarks, and production readiness.

By Julien Laurenceau, 2 months ago
Abstract illustration of GPU data flow and infrastructure optimization with geometric chip patterns
AI

Why Your GPU Infrastructure Costs 40% More Than It Should

Most AI infrastructure teams spend 35-60% more on GPU compute than they need to. The cause isn’t cloud pricing. It is architecture, and it is fixable.

By Julien Laurenceau, 2 months ago
Abstract grid of glowing compute cells densely packed into reserved cluster capacity
apache spark

Spark on Kubernetes Reserves CPU It Never Uses. Here’s the Overcommit Fix.

Spark sets executor CPU requests equal to limits, so a Kubernetes cluster reserves twice the CPU it uses and refuses to schedule pending pods. Kubernetes has no native overcommit. Here is the mutating-webhook operator I use to fix it.

By Julien Laurenceau, 3 months2026-05-31 ago
Diagram: MinIO erasure-coding storage inflation on small objects — per-drive xl.meta metadata replicated across the erasure set
data

Stop using MinIO as a NoSQL database — why S3 object stores collapse on small-file workloads

Two MinIO platforms, same root cause: used as a NoSQL store. Field notes on LIST IOPS, XFS directory limits, scanner & heal SLAs, the erasure-coding storage-efficiency inversion on small objects, and why Apache Cassandra (or Ceph) is the right answer on-prem in 2026.

By Julien Laurenceau, 3 months2026-05-17 ago
data

When the Lakehouse Works, but the Operating Model Breaks… Especially On-Premises

Note: This article was inspired by a LinkedIn post by Can Sinan A. on the hidden operational cost of an Iceberg migration, especially when governance moves from one access-control plane to several layers: catalog, storage and engine configuration Introduction Many organizations are modernizing their data platforms with lakehouse architectures. The Read more

By Julien Laurenceau, 4 months2026-05-04 ago
AI

Tesla’s .SMOL Format Shows Why Most Enterprise Data Lakes Are Architecturally Wrong

When Tesla published patent WO2024073080 describing a new file format internally called “.smol”, the headline was simple: 4x reduction in IOPS for AI training. Most people read this as a hardware story. It isn’t. It’s a data architecture story. And it exposes a structural weakness in how most enterprise data Read more

By Julien Laurenceau, 6 months2026-02-11 ago
ceph

Migrating Unmanaged OSDs to Managed OSDs in Ceph Squid

If you are running Ceph Squid with a mix of managed and unmanaged OSDs, there is one thing worth stating clearly upfront: There is no in-place adoption mechanism in Squid. You cannot “import” an existing OSD into the orchestrator. If an OSD was deployed manually or predates your orchestrator setup, Read more

By Julien Laurenceau, 6 months2026-02-05 ago
AI

GPUs Changed Everything. Storage Is the Bottleneck Again.

GPUs are no longer the bottleneck. Data movement is. I recently attended an online talk that stayed with me longer than most.Not because of a new GPU announcement, but because it clearly articulated something I have seen repeatedly over the years, across very different systems. That message, strongly emphasized by Read more

By Julien Laurenceau, 7 months2026-01-23 ago
apache spark

Apache Spark smoke tests on kubernetes

Introduction Benchmarking remains a critical (and often underestimated) tool when designing or validating large-scale data platforms. While many teams rely on synthetic workloads or production replays, standardized benchmarks still play a key role when comparing architectures, tuning clusters, or validating infrastructure choices. TPCx-HS is one of those benchmarks: designed to Read more

By Julien Laurenceau, 7 months2026-01-12 ago

Posts pagination

Previous 1 2 3 Next
  • Privacy Policy
  • Mentions légales
  • CGV
  • Cookies
Hestia | Developed by ThemeIsle