5 posts tagged with "Multi-Cloud"

Different infrastructure underneath. One foundation for the blueprint you choose.

Here is a small thing that still delights me. Take the kind cluster running on your laptop, run one command, and it shows up in the same console as a production cluster on EKS: same deploy pipeline, same add-ons, same cost view. Not a simulation of production. The same blueprint running on the same foundation.

I want to explain why we built it that way, because behind that small trick sits our entire argument about how infrastructure should work for startups and mid-size companies. It starts with giving Kubernetes credit for what it actually standardized, and being honest about what it never did.

Requests are not waste: teams use them to preserve schedulable capacity for bursts, startup spikes, and reliability. They also determine how workloads fit on nodes, so more headroom than a workload needs can block consolidation or occupy capacity another workload could use.

AstroPulse shows requests beside time-averaged usage for every cluster, namespace, and application. The gap starts an investigation; it does not prescribe a new request.

Compare requested headroom with average use, then decide whether the gap is intentional.

Many startups begin with one application and a hosted deployment service. That is usually the right decision. The team can ship without first building networking, deployment automation, or an operations layer.

The requirements change as the company adds services, environments, enterprise customers, private networking, and infrastructure ownership. The team still needs a short path to production, but the applications now need to run in infrastructure the company controls.

AstroPulse gives growing engineering teams a repeatable path from code to production in infrastructure they control, without requiring them to build the platform themselves.

From code in the editor to a healthy application, with one platform reused across multiple services.

Six months in as platform lead and you have a spreadsheet you haven't shown your manager. Eleven Kubernetes clusters. EKS for production. GKE for the ML team. Two on-prem clusters behind the firewall that predate your tenure. A handful of Kind clusters developers spun up locally. Each one has its own deployment pipeline, its own credentials rotation process, its own way of answering "is this service healthy?"

Your team isn't building features anymore. You're maintaining eleven slightly different versions of the same tooling.

astroctl infra k8s register --name my-cluster

Introduction​

You want the simplicity of "push code, get a live URL"—the developer experience Vercel pioneered—but with full control over your deployment, infrastructure, and compliance. This guide shows you how to build that experience on your own AWS infrastructure using AstroPulse and open-source tools: kpack, cert-manager, external-dns, and nginx-ingress.

You'll build a production-grade platform that delivers Git-push deployments with automatic TLS certificates, preview URLs, and complete observability—all running on infrastructure you own and control. Unlike hosted PaaS platforms, you'll be building on Kubernetes with full deployment control. That means you can run any workload: microservices (with or without public endpoints), stateful databases, WebSockets, long-running background jobs, AI/ML model training and serving, or traditional web applications in any language. You get the simple developer experience with complete architectural control.

How operations work: The infrastructure industry is moving toward an agentic era—AI agents autonomously handling complex workflows (MCP, A2A, multi-agent orchestration). We're heading toward infrastructure that self-configures, self-heals, and self-optimizes. We're not there yet, but Nova brings you AI-assisted operations today with human-in-the-loop. Day 1 (this guide): You build the platform. Day 2 (ongoing): Nova analyzes issues, diagnoses problems, recommends fixes—you approve. As AI matures, more becomes autonomous.