TIR v2: the whole stack around the GPU, in one console
TIR v2 puts VMs, load balancers, auto scaling, managed Kubernetes and PostgreSQL in the same project as your GPU training and inference. One console, one bill.
E2E Networks Blog
How we validated 1,024 NVIDIA B200 GPUs: HPL, NCCL and Nemotron-4 340B results
HPL, NCCL all_reduce and Nemotron-4 340B training results from our 1,024-GPU NVIDIA HGX B200 cluster in Chennai, and how to reproduce them.
Multi-Node LLM Training on Slurm: sbatch to Production
Learn how multi-node LLM training works on Slurm, from your first sbatch script to a production-ready run with shared storage, NCCL tests and checkpoints.
Critical PHP Vulnerabilities Allow Unauthenticated Remote Code Execution (CVE-2026-109618, CVE-2026-109619): Patch Now
Two critical PHP vulnerabilities, CVE-2026-109618 and CVE-2026-109619 (CVSS v4.0 9.2), can allow unauthenticated remote code execution on PHP installations that serve web requests. Affected deployments, fixed versions, temporary mitigations and remediation steps.
Scale to Zero for Dev Inference: Stop Paying for Idle GPUs
Dev and test inference endpoints sit idle most of the day. See how scale to zero, a Shared File System and an async queue on TIR stop idle GPU billing.
How to Optimise GPU Cost Across Training and Inference With a Private Cluster
Training needs GPUs in bursts, inference needs them all day. See how TIR Private Cluster shares one GPU pool across both to raise utilisation and cut cost.
Multi-Node Megatron-LM Training on Slurm: 49% MFU on 16× H200
A complete multi-node Megatron-LM setup on a Slurm GPU cluster: the full sbatch script, NCCL pinned to 400G InfiniBand, hourly checkpointing, and 487–489 TFLOP/s per GPU (49% MFU) on 16× NVIDIA H200.
How to Deploy a Fine-Tuned Model as an API
Your fine-tuned model works in the notebook. Here's how to serve it as a production API with auth, autoscaling and logs, and how to do it on TIR.
cPanel & WHM Security Update, September 2026: What It Fixes and What to Do Now
cPanel has announced a security update for cPanel & WHM addressing multiple vulnerabilities, including issues rated up to Critical severity, affecting version 120 and later. Affected versions, update configuration checks and remediation steps.
Where can a regulated Indian financial entity run AI workloads?
Public cloud, sovereign cloud, private GPU cluster or on-premise: how the four options compare on data custody, cost, audit burden and speed for RBI-regulated entities.
Security Advisory: Mysterious Elephant Threat Actor
E2E Networks security advisory on the Mysterious Elephant threat actor (also tracked as APT-C-08, APT-K-47, and TAG-179), a cyber espionage campaign using phishing emails and Remcos RAT to target government and public sector organizations in South Asia. Learn the potential impact, who is at risk, and recommended actions.
Critical Security Advisory: FortiBleed Campaign Exposes Thousands of Fortinet Firewall Credentials
A critical security advisory covering the FortiBleed incident which exposed administrator credentials for over 73,000 Fortinet FortiGate devices. Learn about affected systems, attack mechanisms, and immediate remediation steps.
E2E goes live with next-generation NVIDIA B200 cluster deployed using NVIDIA Certified Reference Architecture
E2E Networks goes live with its next-generation NVIDIA B200 cluster deployed using NVIDIA Certified Reference Architecture, bringing sovereign, high-performance AI infrastructure to India.
Running AI at Scale: The Infrastructure Reality Nobody Talks About
Most conversations about AI focus on models, what they can do, how accurate they are, how to fine-tune them. Very few go into what happens after deployment: how do you keep a large cluster of expensive hardware running continuously...
Scaling AI in production: What Nobody Tells You
Everyone has access to the same frontier models now. So where does the actual competitive edge come from? According to the team behind E2E Cloud TIR platform (an end-to-end AI development platform), the answer is increasingly about how efficiently...
Benchmarking Open ASR Models on NVIDIA L4: Parakeet vs Whisper vs Nemotron Speech
Open-weight ASR has reached a point where the model choice is only half the decision. The other half is configuration — and most teams get it wrong by ...
How We Learned to Stop Fighting Our GPU Servers
Practical Guide to AI Infrastructure Stability Lessons from building NarrateAI — a multi-VM AI pipeline running Parakeet ASR, Qwen2.5-72B and Nemotron on E2E Networks GPU cloud.
NVIDIA A30 vs V100 for LLM Inference: vLLM, TGI, TensorRT-LLM Benchmark (7B–70B Models)
A detailed benchmark comparing NVIDIA A30 vs V100 GPUs for LLM inference across vLLM, TGI, and TensorRT-LLM. Covers throughput, latency, cost efficiency, and scaling for 7B–70B models.
Demystifying NVIDIA Nemotron 3 Super
A complete guide to running NVIDIA Nemotron-3-Super-120B on H100 GPUs. Covers architecture, hardware requirements, quantization, vLLM and llama.cpp setup, and real-world performance benchmarks..
The Future of AI Was Just Revealed at GTC 2026
Discover the key announcements from NVIDIA GTC 2026, including AI factories, the Vera Rubin supercomputer, and the rise of token-driven infrastructure. Learn how AI is becoming a new industrial revolution.
TokenPeak: We Built a Tool That Auto-Tunes vLLM — And the Results Surprised Us
Discover how TokenPeak benchmarks and optimizes vLLM configurations to maximize tokens per second. Includes real results on DeepSeek R1 32B and insights on performance, cost, and energy efficiency.
Critical Security Advisory: CVE-2025-66478 — Remote Code Execution Vulnerability in Next.js
Critical security vulnerability (CVSS 10.0) affecting Next.js applications using React Server Components. Immediate patching required to prevent remote code execution.
Fine-Tuning Qwen3-8B for Medical Reasoning on E2E Networks A100 GPU
Learn to fine-tune Qwen3-8B for medical reasoning using QLoRA on E2E Networks A100 GPU. Step-by-step guide with 4-bit quantization, dataset prep, and evaluation.
DeepSeek V3.2: Open-Source Reasoning at Gold Medal Level
Technical breakdown of DeepSeek V3.2's sparse attention (DSA), scaled RL post-training, and synthetic agentic task generation. Covers gold-medal results at IMO 2025, IOI 2025, and ICPC. Includes deployment guide for 8x H200 GPUs on E2E Networks with vLLM.
NVIDIA A100 vs H100 vs H200: GPU Comparison for AI
Compare A100, H100 & H200 GPUs for AI: real vLLM benchmarks, ₹189-502.55/hr India pricing, and clear guidance on when each GPU saves you money. Start building today.
4-bit LLM Training with QAT & Unsloth | Complete Guide
Learn Quantization-Aware Training (QAT) for 4-bit LLMs using Unsloth. Step-by-step H100 GPU setup on E2E Networks. QAT recovers 69% accuracy loss vs PTQ.
NVIDIA A100 GPU Price in India: Cloud (₹179/hr) vs Purchase Guide (2025)
Complete A100 GPU pricing: ₹179-189/hr cloud vs ₹7-11.5L purchase. Compare 40GB/80GB variants, A100 vs H100, break-even analysis & India-specific costs. E2E Networks guide.
NVIDIA H200 Price in India: Complete Cloud vs Purchase Guide (2025)
Complete guide to NVIDIA H200 pricing in India. Compare E2E Networks cloud rates (₹502.55/hr on-demand, ₹88/hr spot) vs purchase costs (₹40-50 lakhs). Learn when H200's 141GB memory advantage delivers ROI over H100.
NVIDIA H100 Price in India: Complete Cloud vs Purchase Guide (2025)
Complete H100 GPU pricing guide for India: ₹379.05/hr cloud vs ₹30L+ purchase. Hidden costs, ROI analysis, spot instances at ₹70/hr. 2000+ GPUs available.
EAGLE-3 Speculative Decoding: 2-6x Faster LLM Inference Guide
Complete guide to EAGLE-3 speculative decoding for LLM inference acceleration. Learn training-time test, multi-layer fusion, and achieve 2-6x speedup with vLLM/SGLang deployment on GPU.