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Open-Source DevOps · berops

claudie

Claudie is an open-source platform that lets you build and manage Kubernetes clusters across multiple cloud providers, on-premises data centers, and hybrid environments from a single configuration file. It abstracts away cloud-specific differences so you can mix AWS, Azure, GCP, and bare-metal servers in one cluster.

Source: GitHub — github.com/berops/claudie
783
GitHub stars
58
Forks
Go
Primary language
Apache-2.0
License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

FieldValue
Repositoryberops/claudie
Ownerberops
Primary languageGo
LicenseApache-2.0 — OSI-approved
Stars783
Forks58
Open issues57
Latest releasev0.15.0 (2026-06-29)
Last updated2026-07-08
Sourcehttps://github.com/berops/claudie

What claudie is

Go-based Kubernetes cluster provisioning engine that operates on a management cluster and creates declaratively-defined multi-cloud/hybrid-cloud workload clusters via InputManifest CRDs. Includes integrated load-balancing, persistent storage, and supports node pools spanning 11+ providers (AWS, Azure, GCP, OCI, Hetzner, Exoscale, OpenStack, CloudRift, Verda, OVHcloud, on-premises).

Quickstart

Get the claudie source

Clone the repository and explore it locally.

terminalbash
git clone https://github.com/berops/claudie.gitcd claudie# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

Multi-cloud cost optimization

Dynamically distribute workloads across providers with different pricing models to minimize spend while maintaining unified cluster management and avoiding cloud lock-in.

Hybrid cloud and data locality compliance

Run nodes on-premises and in cloud providers simultaneously within the same cluster; useful for GDPR/compliance scenarios requiring data residency while leveraging cloud elasticity.

Managed Kubernetes for underserved providers

Operate Kubernetes on cloud providers (Hetzner, Exoscale, OCI) or bare-metal infrastructure that lack native managed Kubernetes offerings, using declarative IaC for repeatability.

Implementation considerations

  • Requires a stable management cluster to host Claudie operators; ephemeral test clusters (Minikube, Kind) work for evaluation but production deployments need persistent state management.
  • Each supported provider (AWS, Azure, GCP, OCI, etc.) requires separate credential secrets created as Kubernetes Secrets; audit and rotate these carefully.
  • Network policies (Cilium or standard) are optional but recommended hardening; plan CNI compatibility early if using security-sensitive workloads.
  • InputManifest schema defines cluster topology and scaling parameters; changes are applied declaratively but operators must understand cloud-specific feature availability (e.g., not all providers support DNS healthchecks or Spot instances).
  • Storage and load-balancing are pre-configured but may require tuning for specific workload requirements; review Claudie's integrated solutions against existing tools (e.g., Istio, Helm).

When to avoid it — and what to weigh

  • Need production-grade SLA support — Project has 783 stars and moderate community adoption; no indication of commercial support agreements or managed service offering. Use cases requiring vendor-backed SLAs should evaluate commercial alternatives.
  • Limited operational Kubernetes expertise — Claudie runs on and requires a separate management cluster plus cert-manager dependency. Operators must understand Kubernetes cluster lifecycle, YAML manifests, and multi-cloud credential management.
  • Single cloud provider migration path — If your strategy is to run on one cloud provider with eventual single-cloud managed Kubernetes adoption, Claudie's multi-cloud abstraction overhead adds unnecessary complexity.
  • Highly specialized or proprietary networking — Claudie enforces specific load-balancing and storage architectures; environments with rigid existing network policies or storage subsystems may face integration friction.

License & commercial use

Licensed under Apache License 2.0 (Apache-2.0), a permissive OSI-approved license. Allows commercial use, modification, and distribution with minimal restrictions (requires license copy and notice of changes).

Apache-2.0 explicitly permits commercial use. However, note: (1) no warranty or liability are provided by the license; (2) no indication of commercial support, SLAs, or indemnification from Claudie maintainers (berops); (3) users bear full operational risk for production clusters. Legal and procurement teams should review usage terms and consider whether supplemental support agreements are needed.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

SignalAssessment
MaintenanceActive
DocumentationAdequate
License clarityClear
Deployment complexityHigh
DEV.co fitGood
Assessment confidenceHigh
Security considerations

Claudie manages cloud credentials via Kubernetes Secrets; standard K8s secret encryption, RBAC, and network policies apply. Optional hardening via network policies provided. No third-party security audit data shared. Multi-cloud credential aggregation increases attack surface if management cluster is compromised; implement strict access controls, secret rotation, and audit logging. No details on vulnerability disclosure process or security response SLA provided.

Alternatives to consider

Terraform + manual Kubernetes provisioning

Lower-level IaC approach; more control over cloud resources but requires custom scripts for cluster lifecycle management and lacks integrated load-balancing/storage abstractions.

Cluster API (CAPI) + provider-specific controllers

Kubernetes-native declarative cluster provisioning; more mature ecosystem and wider CAPI provider support, but steeper learning curve and less unified load-balancing/storage narrative.

Cloud-vendor managed multi-cloud solutions (e.g., AWS Outposts, Azure Stack)

Native vendor support and SLAs; eliminates operational burden but locks into single vendor's multi-cloud story and typically higher cost.

Software development agency

Build on claudie with DEV.co software developers

If you're considering Claudie for production, engage your infrastructure team to assess management cluster resilience, credential rotation policies, and whether the declarative model fits your cluster lifecycle workflows.

Talk to DEV.co

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claudie FAQ

Can Claudie manage existing Kubernetes clusters or only create new ones?
Not clearly stated in the provided data. Claudie appears focused on provisioning new clusters via InputManifest; whether it can adopt or manage pre-existing clusters requires review of full documentation.
What is the typical time to provision a multi-cloud cluster?
README states scale-up/scale-down happens 'in the matter of minutes' but does not specify initial cluster creation time. Actual duration depends on provider API responsiveness, node count, and region choices.
Do I need to run the management cluster 24/7?
Yes, effectively. Claudie maintains infrastructure state on the management cluster. While it is not explicitly stated that it must be always-on, any downtime would prevent cluster scaling, updates, or remediation until the management cluster recovers.
What happens if a cloud provider API is unreachable?
Not detailed in provided data. Resilience during provider outages would require review of Claudie's retry logic, queuing, and failover handling.

Custom software development services

Adopting claudie is usually one piece of a larger software development effort. As a software development agency, DEV.co provides software development services and web development expertise — pairing senior software developers and web developers with your team to design, build, and operate open-source devops software in production.

Evaluate Claudie for Your Multi-Cloud Strategy

If you're considering Claudie for production, engage your infrastructure team to assess management cluster resilience, credential rotation policies, and whether the declarative model fits your cluster lifecycle workflows.