Infrastructure
Intelligence Hub
SANI—01
— Field notes from the platform layer. I document what I learn building AI infrastructure, serving models, and running clouds — clusters, GPUs, and pipelines, logged in public.
Serving LLMs at 4x:
vLLM, KV-Cache
& Autoscaling
Inference engineering field log — how continuous batching + PagedAttention took a 7B model from 18 → 74 tok/s on one A10G, and how I autoscale it on Kubernetes without burning budget.
Archived
Deployed Live
Learning Logs
& Field Notes
Filter by engineering track. Add your own tags, delete ones you don't use — the filter bar is yours. Tags persist locally.
LOG.ALL
TRK.INFRA
RCV.24H
LIVE.REC
Deployed
Infrastructure Stacks
Not demos — reproducible stacks. Inference gateways, GPU schedulers, IDPs, GitOps pipelines. Each with Terraform/Helm you can actually run.
ENGINEERING DEPT.
STACKS →
Serving, scheduling,
observability & delivery.
Production-grade infra.
Infrastructure
Signal Index
Build Rate
S1 Platform
Engineering Expedition
Arafat Sani
AI Infrastructure / Inference Engineer
Tier 1 Triage→TO
Reliable Ops
IT Support Specialist with B.S. Computer Science, M.S. Data Science and 4+ years across help desk, desktop, service desk and NOC-style operations.
Support Coverage Focus
Windows 10/11, macOS/iOS, Microsoft 365 and Google Workspace, Active Directory/MFA access, LAN/Wi-Fi/VPN and TCP/IP/DNS/DHCP, ServiceNow ticketing and knowledge-base documentation.
- ◉ Service Desk & Ticketing Unit
- ◈ Systems / Network Unit
Arafat Sani
AI infrastructure & inference engineer with an M.S. in Data Science and 4+ years of ops roots across help desk and NOC-style environments.
Builds &
Case Studies
◈ Hiring for IT support, help desk, desktop or service desk — or want onboarding, ticketing and device support done right? I reply within 48 hours.
◇ DISCUSSION