An open-source, cloud native manager for designing and managing Kubernetes-based infrastructure and applications across multiple clouds.
Meshery is an open-source cloud native manager that enables the design and management of Kubernetes-based infrastructure and applications across multiple clouds. It provides a visual, collaborative platform for GitOps, freeing teams from manual YAML management while handling complex multi-cluster deployments. The project solves the problem of fragmented tooling and configuration complexity in cloud native environments.
Platform engineers, DevOps teams, and SREs managing Kubernetes clusters and cloud native applications across multiple environments. It's also valuable for developers seeking self-service infrastructure management and collaborative design tools.
Developers choose Meshery for its comprehensive, extensible approach to cloud native management that combines visual design, performance testing, and multi-cluster operations in a single platform. Its unique selling point is the combination of collaborative GitOps workflows with extensive extensibility options for building internal developer platforms.
Meshery, the cloud native manager
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Provides a unified interface to manage Kubernetes clusters across any cloud, as evidenced by the single pane of glass feature and support for 300+ integrations.
Enables GitOps workflows with visual infrastructure design, allowing teams to collaboratively manage configurations without deep YAML knowledge, as shown in the Workspaces and MeshMap features.
Offers built-in load generation and performance characterization tools, supporting multiple load generators and performance profiles for optimizing applications.
Features numerous extension points including gRPC adapters, hot-loadable React packages, and REST/GraphQL APIs, making it ideal for building custom internal developer platforms.
Consists of multiple interconnected components like Meshery Operator, MeshSync, and Meshery Broker, leading to a non-trivial setup and operational overhead.
The platform's breadth of features and conceptual models (e.g., Workspaces, Environments) requires significant time investment to master, which might deter smaller teams.
Running Meshery involves deploying several containers and operators, which can consume substantial cluster resources, potentially impacting performance for resource-constrained environments.