Kubernetes, GPU, and AI infrastructure guides paired with practical tools for operators and platform teams.
Turn Kubernetes and AI infrastructure notes into checks you can run today.
Start with the highest-signal Kubernetes, GPU, and AI infrastructure guides.
A concrete walkthrough into Linux stack overflow protections — how canaries, NX, ASLR, PIE, and RELRO actually work, what they stop, what they don't, and what breaks when you enable them.
A detailed look at the system calls behind malloc — brk/sbrk for heap growth, mmap for large allocations and thread arenas, and the internal kernel data structures for process memory.
A walkthrough into how Linux dynamically links shared libraries at runtime — PIC, GOT, PLT, lazy binding, gdb tracing, and the real cost of -fPIC.
A concrete guide to GPU overprovisioning strategies, including scheduler-level oversubscription, time slicing, memory controls, MIG, vGPU, queue backfill, and operational guardrails.
A concrete guide to choosing between serverless GPUs and dedicated GPUs for startups, based on cost structure, delivery speed, performance predictability, operations burden, and team maturity.
A concrete walkthrough into Linux glibc (ptmalloc2) heap memory management — arenas, chunks, bins, tcache, and how each structure becomes an attack surface.
Start with the basics, then continue to operations and troubleshooting topics.
A curated reading track for Kubernetes.
A curated reading track for System.
A curated reading track for GPU.
New notes, guides, and long-form pieces from the main archive.
A concrete walkthrough into Linux stack overflow protections — how canaries, NX, ASLR, PIE, and RELRO actually work, what they stop, what they don't, and what breaks when you enable them.
A detailed look at the system calls behind malloc — brk/sbrk for heap growth, mmap for large allocations and thread arenas, and the internal kernel data structures for process memory.
A walkthrough into how Linux dynamically links shared libraries at runtime — PIC, GOT, PLT, lazy binding, gdb tracing, and the real cost of -fPIC.
A concrete guide to GPU overprovisioning strategies, including scheduler-level oversubscription, time slicing, memory controls, MIG, vGPU, queue backfill, and operational guardrails.
A concrete guide to choosing between serverless GPUs and dedicated GPUs for startups, based on cost structure, delivery speed, performance predictability, operations burden, and team maturity.
A concrete walkthrough into Linux glibc (ptmalloc2) heap memory management — arenas, chunks, bins, tcache, and how each structure becomes an attack surface.
A concrete comparison of five AI agent frameworks - OpenClaw, ZeroClaw, PicoClaw, Nanobot, and IronClaw - covering size, architecture, security tradeoffs, and adoption fit.
An engineering-oriented comparison of KAI-Scheduler’s Reservation Pod approach and HAMi’s hard isolation path, including trade-offs, failure modes (noisy neighbor), and how the two layers can complement each other.
A concrete boundary guide: Docker packages and runs containers, Kubernetes orchestrates and keeps services stable at scale, and OpenStack turns datacenter hardware into an IaaS resource pool (VM/network/storage).
An engineering-oriented guide to hetGPU: how a compiler + runtime stack can make one GPU binary run across NVIDIA/AMD/Intel/Tenstorrent, including SIMT vs MIMD, memory model gaps, and live kernel migration.
A concrete guide to Linux cgroups — from V1's multiple hierarchies to V2's unified model, with real gotchas for CPU throttling, OOM behavior, and production debugging.
A walkthrough into Kubernetes GPU virtualization through gpu-manager startup flow, including device interception, topology awareness, scheduling, and allocation mechanics.
Understand ELF files from sections and segments to relocations and dynamic linking, with concrete examples for debugging Linux binaries and loader issues.
Understand calling conventions, stack frames, call/ret behavior, debugging observation, and security implications from the assembly view.
Safely inspect a live Pod without baking debugging tools into production images.
Learn concrete Kubernetes RBAC least-privilege patterns, how to reduce overbroad permissions, and which checks catch risky role bindings before incidents.
A concrete rollout path for Kubernetes NetworkPolicy: start with default deny, whitelist DNS and key dependencies, and avoid breaking production traffic.
How to make autoscaling predictable: right requests, sane HPA behavior, VPA recommendations, and capacity-aware cluster scaling.
How CPU/memory requests and limits actually affect scheduling, throttling, OOMKills, and autoscaling.
A concrete Kubernetes troubleshooting playbook for Pending Pods, CrashLoopBackOff, readiness failures, networking issues, and node-level problems.
Combine Deployment rollingUpdate settings with PodDisruptionBudgets to keep availability during upgrades and node maintenance.
Use better Kubernetes probes by choosing the right signal, tuning thresholds, and avoiding false restarts, traffic drops, and noisy rollouts.
Learn how liveness, readiness, and startup probes work in Kubernetes, what each one should check, and how to avoid restart loops and false failures.
Use Helm to deploy a MySQL cluster on Kubernetes while understanding chart defaults, persistence, networking, and production tradeoffs.
Learn how kubectl port-forward works, when to use it for debugging, and how it differs from Services, Ingress, and production traffic paths.
Understand how to run MySQL replication on Kubernetes, including primary-replica design, storage concerns, failover risks, and operational checks.
Understand when to use a headless Service in Kubernetes, how DNS works without a virtual IP, and why it matters for StatefulSets and peer discovery.
Learn when to use a StatefulSet in Kubernetes, how stable Pod identity works, and why ordering and persistent storage matter.
Understand how StorageClass enables dynamic provisioning in Kubernetes, how default classes work, and how to choose the right storage policy.
Learn how PersistentVolumes and PersistentVolumeClaims work in Kubernetes, how binding happens, and how to troubleshoot storage lifecycle issues.