As the cloud native management plane, Meshery enables the adoption, operation, and management of Kubernetes clusters and their lifecycle. Meshery’s powerful performance management functionality is useful whether you are running workloads on Kubernetes or outside of Kubernetes.
Meshery implmenents both Service Mesh Performance (SMP) and Service Mesh Interface (SMI) and Meshery is the conformance tool for SMI. Meshery integrates with Open Application Model (OAM) to enable users to deploy service mesh patterns. Meshery enables operators to deploy WebAssembly filters to Envoy-based data planes. Meshery facilitates learning about functionality and performance of service meshes and incorporates the collection and display of metrics from applications running on or across service meshes.
Meshery features can be categorized by:
- Cloud Native Performance Management
- Workload and cloud native performance characterization
- Prometheus and Grafana integration
- Cloud Native Configuration Management
- Configuration best practices
- Cloud Native Lifecycle Management
- Cloud native provisioning and workload onboarding
- Meshery Operator and MeshSync
- Cloud native patterns and Open Application Model integration
- Data Plane Intelligence
- Registry and configuration of WebAssembly filters for Envoy
- Cloud Native Interoperability and Federation
- Manage multiple service meshes concurrently
- Connect to multiple clusters independently
Meshery is for Developers, Operators, and Product Owners
Whether making a Day 0 adoption choice or maintaining a Day 2 deployment, Meshery has useful capabilities in either circumstance. Targeted audience for Meshery project would be any technology operators that leverage service mesh in their ecosystem; this includes developers, devops engineers, decision makers, architects, and organizations that rely on microservices platform.
Meshery is for cloud native patterns
Meshery is for performance management
Meshery helps users weigh the value of their cloud native deployments against the overhead incurred in running different deployment scenarios and different configruations. Meshery provides statistical analysis of the request latency and throughput seen across various permutations of your workload, infrastructure and infrastructure configuration. In addition to request latency and throughput, Meshery also tracks memory and CPU overhead in of the nodes in your cluster. Measure your data plane and control plane against different sets of workloads and infrastructures.
Anytime performance questions are to be answered, they are subjective to the specific workload and infrastructure used for measurement. Given this challenge, many projects refuse to publish their own performance data, because such tests can be quite invovled and misinterpreted.
Beyond the need for performance and overhead data under a permutation of different workloads (applications) and types and sizes of infrastructure resources, the need for cross-project, apple-to-apple comparisons are also desired in order to facilitate a comparison of behavioral differences between cloud native and selection of their use. Individual projects shy from publishing test results of other, competing service meshes. An independent, unbiased, credible analysis is needed.
Meshery is intended to be a vendor and project-neutral utility for uniformly benchmarking the performance of cloud native infrastructure. Between service mesh and proxy projects (and surprisingly, within a single project), a number of different tools and results exist. Meshery allows you to pick an efficient set of tools for your ecosystem by providing performance evaluation and metrics.
- By leveraging Meshery you can achieve apples-to-apples performance comparison
- Track your service mesh performance from release to release.
- Understand behavioral differences between cloud native infrastructure.
- Track your application performance from version to version.
Meshery is for all cloud native infrastructure
Infrastructure diversity is a reality for any enterprise. Whether you’re running a single Kubernetes cluster or multiple Kubernetes clusters, you’ll find that Meshery supports your infrastructure diversity (or lack thereof).