The DigitalOcean Newsletter: May 2026

The DigitalOcean Newsletter

Your monthly deep dive into all things DigitalOcean, including product updates, new tutorials, upcoming events, and more.

Inside the AI-Native Cloud

At Deploy 2026, we launched the DigitalOcean AI-Native Cloud, a full-stack platform purpose-built for the inference and agentic era. Five layers. One open stack from silicon to agents.

This month, we're going deeper.

AI workloads break many assumptions the old clouds were built on. AI runs in loops. Agents think, then act, then think again. A single user task can span hundreds of thousands of tokens, traverse half a dozen tools, hit a knowledge base, write code, execute it, and persist state, all before returning an answer. Hyperscalers leave the integration to you. Inference-only providers sit on someone else's compute and stack their margin on top. GPU rental shops give you silicon, but not a system.

With the AI-Native Cloud, you don't need to wait in a hyperscaler queue behind a frontier lab. You don't need to glue together a Neo Cloud, an inference wrapper, and a vector database vendor. You don't need to compromise on openness, on economics, or on developer experience.

Read the full walkthrough from CPTO Vinay Kumar: Powering the Inference Era: Inside the DigitalOcean AI-Native Cloud.

Request-based autoscaling is now available on App Platform

Now, you can automatically scale based on live HTTP traffic signals (requests per second and P95 response latency) so your infrastructure reacts to what’s actually happening, not what happened minutes ago. Learn more

How DigitalOcean Built Its Inference Router, Now in Public Preview

DigitalOcean shared a deep dive into the infrastructure behind its new Inference Router, designed to automatically route AI requests to the best model based on cost, latency, and task type. Powered by purpose-built routing models and the open-source Plano proxy, the system helps developers reduce inference costs while improving performance across agentic and multi-model workflows. Read the deep dive

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• AI inference workloads need the proper tech stack to run smoothly but require specific selection criteria. Read about current market offerings with our guide to 10 AI inference platforms for production, and get tips on how to select the most effective option for your team.  
• Interested in using a strong compression format for your Ubuntu system? Go through our step-by-step tutorial on how to install 7-Zip on Ubuntu and you’ll get common commands, format choices, and troubleshooting tips. 
• AI security is continually evolving as AI-backed attacks, injection prompts, malicious code, and more emerge. Educate yourself on the main types of AI security risks and how to develop digital hygiene practices to reduce potential attack vectors.  
• Inference routing streamlines model deployment in a production environment and enables AI applications to select the best model based on task complexity, cost, and latency. Test your skills with a hands-on inference routing tutorial that runs through the DigitalOcean Inference Router supporting a Python bot application.
• Nous Research’s Hermes Agent is an open-source, self-improving AI agent that can integrate new data over time and update its parameters. Create a grocery application with Hermes Agent and Docker to demonstrate how it works in a real-world use case and can automatically handle tasks.
• When it comes to AI, more companies are focusing on inference rather than on AI model and dataset training. But what does this mean for the underlying AI cloud technology? Get insights on changing AI infrastructure strategy and why going from training to inference changes cloud requirements.