DevOps & AI Architecture Roadmaps
Step-by-step sequential learning pipelines designed to take you from foundational concepts to multi-region production platforms without skipping the edge cases or engineering trade-offs.
LLMOps & Production AI Infrastructure
Deep-dive into speculative decoding, mixture-of-experts clustering, distributed training, and low-latency model serving.
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READ IN ORDERHow low-level inference engineering, 4-bit quantization, and speculative decoding push 1,000+ tokens/sec out of a consumer RTX 3090.
How asynchronous NVMe streaming, router logit lookahead, and tiered ring buffers push production-grade inference out of commodity hardware.
How tensor parallelism, 200 Gb/s RoCE, and low-level runtime forensics turn raw multi-GPU hardware into a rock-solid, 1-million-token AI serving platform.
How fine-grained 2.9 bpw mixed quantization, unified memory management, and DSpark speculative decoding fit DeepSeek V4.1 Flash across dual NVIDIA DGX Sparks.
Kubernetes & Platform Engineering Track
Master cluster architecture, production ingress, gitops deployments, and high-availability operations from fundamentals to scale.
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READ IN ORDEREver thought learning DevOps could be fun? Check out this blog post where I explore gamified resources that teach CI/CD, containers, Kubernetes, and more — all through interactive games!
A quick dive into the Linux file system essentials every DevOps engineer should master in 2025. From file permissions to logs, mounts, and container file systems, this guide highlights the key areas to focus on for better infrastructure management and debugging.
This guide provides 50 DevOps project ideas, organized from beginner to advanced levels, covering all essential aspects of DevOps. Whether you're just starting or looking to level up, these projects span key DevOps areas.
How to take a Node.js application from local git push to zero-downtime AWS deployment using CodePipeline, CodeBuild, and CodeDeploy.
How to Practice These Architectures Locally
You don't need a multi-thousand-dollar cloud bill to master these roadmaps. Every configuration in these tracks can be spun up in lightweight local sandboxes:
Run multi-node Kubernetes clusters inside Docker containers in seconds. Supports Cilium eBPF installation.
kind create cluster --config k8s.yamlEmulate AWS services (S3, SQS, IAM, DynamoDB, VPC) locally on your laptop without AWS credentials or charges.
docker run -p 4566:4566 localstackBenchmark OpenAI-compatible model serving APIs locally with quantized weights (Q4/AWQ) on consumer GPUs or Apple Silicon.
vllm serve meta-llama/Llama-3-8B