Digitalocean Compute

What it does

This skill enables AI agents to manage DigitalOcean compute resources, including Droplets (virtual machines), App Platform (PaaS), Functions (FaaS), and Kubernetes clusters. It allows for provisioning VMs with custom configurations, deploying applications using Git or container images, creating event-driven functions, and managing Kubernetes deployments – all directly through the agent. The skill supports GPU offerings for AI workloads as well.

When to use it

• When deciding on a compute model (VMs, PaaS, serverless, Kubernetes) for an application.
• To provision virtual machines (Droplets), deploy applications using App Platform, or create lightweight API functions.
• For planning and deploying GPU-backed workloads.

Key capabilities

• Droplet Management: Configuration of region, size, OS image, SSH keys, Volumes, firewalls, and VPC settings for VMs.
• App Platform Deployment: Connecting Git repositories/container registries, defining build commands, setting environment variables, configuring domains & HTTPS.
• Functions Creation: Creating namespaces, deploying functions via doctl or the Control Panel, managing triggers and monitoring execution.
• Kubernetes Management: (Implied - not detailed) Managing Kubernetes clusters within DigitalOcean.
• GPU Support: Provisioning GPU Droplets and Bare Metal GPUs for AI workloads.

Example prompts

• "Create a new Droplet in the Frankfurt region with Ubuntu 22.04."
• "Deploy my application from this GitHub repository to App Platform."
• "Show me the logs for my DigitalOcean Function named 'image-processor'."

Tips & gotchas

• Requires familiarity with DigitalOcean concepts like regions, Droplet plans, and OS images.
• Token estimate indicates a relatively high token cost (4000-5200) for full functionality, suggesting complex operations may require significant context.
• The skill leverages doctl for function deployment; ensure this tool is accessible if using that feature.