Fastly vs Netlify

Comcast and Fastly’s New Content Delivery Model Powers Highest Quality Experience for Peacock’s Biggest Live Events

Fastly announces a new content delivery model with Comcast to power Peacock's biggest live events.

Fastly Unveils AEDA: Autonomous Edge Security in Gemini Enterprise

Discover Fastly’s Autonomous Edge Defense Agent (AEDA) in Gemini Enterprise, designed to streamline incident response and slash MTTR.

Akamai surges after $11.6B Anthropic CPU deal

Akamai Technologies' shares surged up to 16.4% after announcing an $11.6 billion deal with AI company Anthropic for dedicated cloud computing capacity over seven years, marking the largest deal in Akamai's history. The deal focuses on CPU-based infrastructure for agentic AI workloads, with an option to expand to $20 billion. Anthropic will receive a warrant for up to 5% of Akamai's stock, vesting based on spending milestones. Akamai expects $5.5 billion in capital spending plus $1.7 billion for components, and analysts estimate this equates to about 77 megawatts of computing power. Revenue is expected to begin in 2027, with an annual run rate of $1.7 billion by end of 2028. CNBC's Jim Cramer highlighted Akamai as a buy, citing its low valuation (under 16 times expected earnings) and the Anthropic deal, while suggesting a pullback for Cloudflare (279 times earnings) and Fastly (50 times earnings). Akamai is repositioning with edge computing to handle AI workloads closer to users.

• Akamai signed an $11.6 billion deal with Anthropic for dedicated cloud computing capacity over 7 years, the largest in Akamai's history.
• The deal can be expanded to up to $20 billion and includes a warrant granting Anthropic up to 5% of Akamai's stock, vesting based on spending milestones.
• Computing capacity focuses on CPUs for agentic AI, not GPUs; Akamai expects $5.5 billion in capital spending (plus $1.7 billion for components), ~77 MW of power.

TypeSafe Jev now available in AI Gateway

TypeSafe’s Jev model is now available through Netlify’s AI Gateway with zero configuration required. Install @typesafe-ai/sdk and use it directly in your Netlify Functions — no API keys to create, no provider config, no base URLs to wire up. AI Gateway handles credentials automatically, and usage is billed to your Netlify credits like every other model in the gateway.

WebHaste Launches Local-First CMS for Smaller Websites

WebHaste, a free, local-first Content Management System (CMS) developed by Destination Toolbox, has been released in public beta. Designed for teams building and managing smaller websites (under 100 pages), it aims to eliminate server-side infrastructure headaches like plugin updates, SSL certificate management, and security concerns. The CMS operates as a Chrome extension, offering file management, visual editing, real-time previews, and template rendering. It deploys finished sites to CDNs like Cloudflare Pages and Netlify, and supports local ownership of site files. Key features include built-in SEO (sitemaps, meta descriptions, OpenGraph tags), agency-friendly tools (shared drives, Git, per-page tracking pixels), and AI collaboration readiness with file-aware AI agents for content management without publishing rights. The product is positioned as an alternative to database-driven systems like WordPress for simpler sites, including informational sites, blogs, campaign landing pages, and portfolios.

• WebHaste is a free, local-first CMS released in public beta.
• The CMS is available as a Chrome extension and deploys to Cloudflare Pages and Netlify.
• WebHaste targets smaller websites, including informational sites and blogs under 100 pages.

Scaling a Dev Project to 10K RPS with SQLite

This technical analysis details how a developer scaled a side-project backend to handle 10,000 requests per second (RPS) on an 8GB RAM DigitalOcean droplet. Following a sudden traffic surge driven by a viral tweet, the initial Flask and Heroku setup failed due to thread-per-request bottlenecks and memory exhaustion. The architecture was redesigned using Python's AsyncIO, a bounded SQLite connection pool capped at 200 connections operating in Write-Ahead Logging (WAL) mode, and OS-level backlog limits. On the client side, vanilla JavaScript and the native navigator.sendBeacon() method were implemented to ensure fire-and-forget analytics tracking with zero framework overhead. These optimizations successfully stabilized RAM usage at 180MB with zero errors during high-concurrency testing.

• A viral tweet caused a Flask and Heroku backend analytics endpoint to crash due to thread-per-request bottlenecks under heavy concurrent load.
• The developer rebuilt the architecture using Python's AsyncIO, SQLite in WAL mode, and a connection pool bounded to 200 connections.
• Load testing on a DigitalOcean 8GB droplet achieved 12,000 requests per second with stable 180MB RAM usage and zero errors.