Liqo

Enable dynamic and transparent Kubernetes multi-cluster topologies

Say goodbye to complex integrations 👋

Multi-cluster for real!
Everything you need to build multi-cluster topologies

Extend namespaces across clusters

Extend the namespaces of the consumer clusters, to have namespaces distributed across the clusters where resources are replicated. Allowing to distribute Configurations, Secrets, Services and other resources across your clusters.

Inter-cluster networking

Create a seamless, CNI and K8s distribution agnostic network mesh between clusters, enabling direct communication between pods of different clusters.

Seemless pods offloading

Your consumer clusters can transparently schedule pods on other clusters. Enabling resource sharing, data locality or geographical distribution of the applications.

Why Liqo?

A complete toolkit for Kubernetes multi-cluster, from networking to storage, designed to be declarative, extensible, and production-ready.

Workload Offloading

Transparent workload offloading to remote clusters. Collapse an entire remote cluster to a virtual node, fully compliant with standard Kubernetes.

Inter-cluster Networking

Transparent multi-cluster pod-to-pod and pod-to-service connectivity regardless of CNI plugins. All cross-cluster traffic flows through secured tunnels.

Cross-cluster Storage

Remote execution of stateful workloads with the data gravity approach. Extend database HA techniques to multi-cluster scenarios seamlessly.

Extensibility

Modular and extensible architecture designed to integrate with existing tools and platforms. Build on top of Liqo to fit your specific multi-cluster requirements.

Declarative Configuration

Fully cloud-native and declarative. Manage multi-cluster topologies as code, seamlessly integrating with GitOps workflows, CI/CD pipelines, and automation tools.

Multi-environment Support

Works across heterogeneous infrastructures: on-premise, public cloud, edge, and multi-cloud. Supports any Kubernetes distribution, managed or self-hosted, with no vendor lock-in.

Use Cases

From AI workloads requiring remote GPU access to hybrid cloud deployments and edge computing: Liqo adapts to your multi-cluster needs.

AI Inference at Scale

Serve AI models across clusters by transparently accessing remote GPUs. Schedule inference workloads on GPU-equipped provider clusters without changing your deployments.

GPUAI/ML

Distributed ML Training

Burst training jobs to clusters with available GPU capacity. Leverage Liqo's network fabric for high-throughput cross-cluster communication during distributed training.

GPUAI/ML

Cloud Bursting

Seamlessly offload peak workloads from on-premise clusters to cloud providers. Scale beyond your local capacity without re-architecting applications.

Hybrid Cloud

Edge Computing

Run your workloads at the edge while centrally managing deployments and configurations.

EdgeAI/ML

High Availability

Extend stateful workloads across regions. Achieve multi-cluster HA without managing independent replicas manually.

Hybrid & Multi-Cloud

Span workloads across on-premise, public cloud, and multi-cloud environments. A single control plane with Liqo's virtual nodes abstracts away infrastructure differences.