docs/static/v0.4/overview/index.html
As the service mesh management plane, Meshery enables the adoption, operation, and management of any service mesh and their workloads. Meshery’s powerful performance management functionality is accomplished through implementation of Service Mesh Performance (SMP). Meshery’s multi-mesh management functionality leverages Service Mesh Interface (SMI). 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:
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 helps users weigh the value of their service mesh deployment against the overhead incurred in running a service mesh. Meshery provides statistical analysis of the request latency and throughput seen across various permutations of your workload, infrastructure and service mesh 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, the Envoy project, for example, refuses to publish performance data because such tests can be:
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 service meshes 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 service meshes. 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.
Establish a performance benchmark and track performance against this baseline as your environment changes over time.
Infrastructure diversity is a reality for any enterprise. Whether you’re running a single service mesh or multiple types of service meshes, you’ll find that Meshery supports your infrastructure diversity (or lack thereof).
| Platform | Status |
|---|---|
| Meshery Adapter for Consul | stable |
| Meshery Adapter for Istio | stable |
| Meshery Adapter for Linkerd | stable |
| Meshery Adapter for Network Service Mesh | stable |
| Meshery Adapter for Octarine | stable |
| Meshery Adapter for Open Service Mesh | stable |
| Platform | Status |
|---|---|
| Meshery Adapter for Citrix Service Mesh | beta |
| Meshery Adapter for Kuma | beta |
| Meshery Adapter for NGINX Service Mesh | beta |
| Meshery Adapter for Traefik Mesh | beta |
| Platform | Status |
|---|---|
| Meshery Adapter for App Mesh | alpha |
| Meshery Adapter for Tanzu Service Mesh | alpha |