Hosting

LLM inference looks like “just another API” — until latency spikes, queues back up, and your GPUs sit at 95% memory with no obvious explanation.

OpenClaw is a self-hosted AI assistant designed to run with local LLM runtimes like Ollama or with cloud-based models such as Claude Sonnet.

AWS S3 remains the “default” baseline for object storage: it is fully managed, strongly consistent, and designed for extremely high durability and availability.
Garage and MinIO are self-hosted, S3-compatible alternatives: Garage is designed for lightweight, geo-distributed small-to-medium clusters, while MinIO emphasises broad S3 API feature coverage and high performance in larger deployments.

LLM systems fail in ways that traditional API monitoring cannot surface — queues fill silently, GPU memory saturates long before CPU looks busy, and latency blows up at the batching layer rather than the application layer. This guide covers an end-to-end observability strategy for LLM inference and LLM applications: what to measure, how to instrument it with Prometheus, OpenTelemetry, and Grafana, and how to deploy the telemetry pipeline at scale.

Strategic guide to hosting large language models locally, on consumer hardware, in containers, or in the cloud. Compare tools, performance trade-offs, and cost considerations.

The AWS Free plan is not working for me and Pay-as-you-go is hidden for new CloudFront Distributions on AWS Console .

Self-hosting LLMs keeps data, models, and inference under your control-a practical path to AI sovereignty for teams, enterprises, nations.

Deploying a Hugo static site to AWS S3 using the AWS CLI provides a robust, scalable solution for hosting your website. This guide covers the complete deployment process, from initial setup to advanced automation and cache management strategies.

Hugo caching strategies are essential for maximizing the performance of your static site generator. While Hugo generates static files that are inherently fast, implementing proper caching at multiple layers can dramatically improve build times, reduce server load, and enhance user experience.

The future of AI isn’t just about smarter models - it’s about smarter silicon. Specialized hardware for LLM inference is driving a revolution similar to Bitcoin mining’s shift to ASICs.

Here we have a Python Lambda example of SQS Message Processor + REST API with API Key Protection + Terraform script to deploy it for serverless execution.

Here’s a quick info on Write.as / WriteFreely - how it fits into the fediverse, where to get managed hosting, what the usage trend looks like, and how to self-host (plus rough costings).

Proxmox Virtual Environment (Proxmox VE) is an open-source, type-1 hypervisor and datacenter orchestration platform built on Debian.

The AWS Cloud Development Kit (AWS CDK) is a framework that enables you to define and provision cloud infrastructure using familiar programming languages like TypeScript, Python, Java and Go.

I’m comparing self-hosted Kubernetes variants that suit the Ubuntu-based homelab with 3 nodes (16GB RAM, 4 cores each), focusing on ease of setup and maintenance, support for persistent volumes and LoadBalancers.

GitHub Actions is an automation and CI/CD platform within GitHub, used to build, test, and deploy your code based on events like pushes, pull requests, or on a schedule.