Design and manage Kubernetes infrastructure visually without YAML
Imagine viewing Kubernetes clusters across multiple clouds in a browser and designing infrastructure with your team. Meshery is an open-source platform for managing Kubernetes-based infrastructure and applications. It uses GitOps workflows to perform pre-deployment validation and handles complex configurations through visual editing.
380+ integrations and single-screen management
Meshery supports more than 380 cloud-native infrastructure integrations. You can configure, deploy, and operate Kubernetes clusters from various cloud providers on a single screen. The platform automatically infers relationships between resources to maintain configuration consistency. It also provides a catalog of pre-validated design templates, making it easy to apply configuration best practices.
Pre-deployment validation and PR-based collaboration
The dry-run feature validates whether deployment specifications are accepted by the Kubernetes API server before they are applied. When connected to a GitHub repository, infrastructure snapshots are displayed within pull requests (PRs), enabling visual comparison of changes before merging. Workspaces serve as the central hub for teams to organize cloud-native projects and manage environment-specific access permissions.
Scalability as an internal developer platform foundation
Meshery offers various extension points, including gRPC adapters, hot-loadable React packages, Golang plugins, NATS topic subscriptions, and REST and GraphQL API interfaces. This allows it to be utilized as the foundation for an organization's internal developer platform (IDP). It provides tools and integrations that enable multiple teams to build isolated multi-tenant environments on shared Kubernetes infrastructure while maintaining security through role-based access control (RBAC).
Load generation and performance characterization
Use the Fortio load generator to create TCP, gRPC, and HTTP loads and evaluate the performance of applications and infrastructure. Load profiles can be finely tuned with parameters such as duration and concurrent thread count, and test results are visualized as histograms to help understand response time distributions. It integrates with Prometheus and Grafana to collect cluster and application metrics and import existing dashboards to visualize performance data. It adheres to cloud-native performance specifications to measure performance in the context of infrastructure overhead.
Things to know before adoption
Meshery is released under the Apache 2.0 license and runs on various platforms, including Docker, Kubernetes, Linux, Mac, and Windows. You can deploy it in container form using mesheryctl. Since the repository size reaches tens of GB, sparse cloning is recommended when cloning for contributions to exclude unnecessary generated models or documentation snapshots. It is suitable for teams that need visual management of complex multi-cluster environments and GitOps workflows, but it may be overkill if the goal is simply managing a single cluster.