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Run standard Kubernetes on Scaleway Instances while Scaleway manages the control plane and core cluster components.

Build event-driven serverless applications with triggers, bindings, and several hosting plans.

Storage products and custom closet planning

MPEG-4 encoding tools with several audio and container choices

Technical and tag information for audio and video files

A YAML-based CLI for asserting the installed packages, services, files, ports, and other state of a system.

A coverage-guided fuzzer that mutates input corpora to find crashes and hangs in instrumented programs.

Promote application configuration through GitOps stages so a GitOps agent can deploy each stage.

Build and operate WordPress, Drupal, and Next.js websites through managed environments and Git-connected workflows.

Create repeatable local development environments with a Vagrantfile and managed virtual machines.

Deploy supported application code to managed dynos without administering the host servers.

Query and update YAML, JSON, XML, and other structured data from the command line.

Run GitHub Actions-compatible workflows on Depot compute with local-run and job-debugging tools.

Automate dependency and lockfile updates through reviewable pull requests across many repository platforms.

Show estimated cloud-cost changes and FinOps checks alongside infrastructure code reviews.

Model Kubernetes builds, deployments, tests, and local development as a dependency-aware action graph.

Trace and investigate AI application calls with a local or self-hosted observability interface.

A Go library for verifying infrastructure code by deploying it, checking behavior, and cleaning up resources.

Develop Python in a project-aware desktop IDE with a debugger, test runner, and optional coding-agent tools.

Provision Kubernetes clusters and node pools with Vultr-managed control-plane and worker-node operations.

An agent-based monitoring pipeline that turns checks and metrics into routed, actionable events.

Open a Git repository in a browser IDE backed by a Kubernetes development workspace.

Combine Python expressions and shell commands in one Python-based command prompt.

Develop, debug, and deploy Kubernetes applications through a shared CLI workflow.