Blog
Insights, guides, and best practices on MLOps, DevOps, Cloud, and AI from the Eprecisio team.
Sovereign AI Cloud: Running GPU Workloads Under GDPR, PDPL, and the EU AI Act
Under oath before the French Senate in 2025, Microsoft France's Legal Director admitted he could not guarantee EU customer data would never be handed to US authorities. That single sentence is the sovereign-cloud thesis. Here is what actually meets EU AI Act, GDPR, and PDPL for GPU workloads in 2026, with real vendor pricing.
Choosing a DevOps Consultancy for Regulated Industries and EU AI Act Compliance
Enforcement of EU AI Act Articles 26 and 27 turned on August 2, 2026, with fines up to EUR 35m or 7% of global turnover. Here is the 8-dimension evaluation framework a CTO should use to pick a DevOps consultancy that actually handles compliance, plus the 5 red-flag answers that disqualify a vendor.
vLLM vs TGI vs KServe: Choosing an LLM Inference Server on Kubernetes
The naive three-way comparison is a category error. TGI was archived on March 21, 2026, KServe is a serving platform that runs vLLM as its runtime, and vLLM is the reference implementation for MLPerf Inference 5.1. Here is what actually matters when picking an LLM inference stack for Kubernetes in 2026.
No More Egress Fees: What the EU Data Act Means for Your Cloud
January 12, 2027 is when cloud switching charges are banned across the EU. The AWS, Azure, and GCP egress waivers you have already seen were compliance moves ahead of it. Here is what a CTO should actually change in their architecture.
What Mythos 5's Shutdown Means for AI-Native Builders
The first US frontier model to hit hard export controls just took a generation of capability off the table for every customer worldwide. The story is interesting. The engineering lesson is more important.
One Month SaaS Revamp: AI-Assisted Dev, Test-First Policy, Weekly Releases
Three years of production SaaS accumulates debt quietly. Songplace went from monthly releases and fragile staging to weekly shipping in one month using an AI-assisted development loop and a test-first policy.
Production Alerting for an AI Gaming Platform: PagerDuty, Prometheus, Grafana
A live AI gaming platform had solid infrastructure but zero structured alerting. We built a 3-tier PagerDuty, Prometheus, Grafana, and Loki stack in three weeks. Here is what we built and why.
MLOps Tools We Actually Use in Production and Why We Picked Them
Not a listicle. This is the MLOps toolchain we run for production workloads, why we chose each tool over its alternatives, and the honest limitations we tell clients before they commit.
GPU Workload Optimization: What Actually Moves the Needle
GPU utilisation sitting at 30-40% while the model seems slow is almost never a model problem. Here is what we actually find and fix when auditing GPU infrastructure in production.
Scaling ML with Kubernetes: What Production Actually Looks Like
Running ML workloads on Kubernetes looks straightforward until your first multi-GPU training job silently runs 35% slower than it should. Here is what production Kubernetes for ML actually requires.