Merge pull request #1 from jamieplu/jamieplu/docs/service-mesh-to-clo…

…ud-native

[Docs] Update overview.md for broader description

docs/pages/getting-started/overview.md

@@ -5,14 +5,16 @@ permalink: /getting-started/overview
 language: en
 ---
 
-As the cloud native 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](https://smp-spec.io) (SMP). Meshery's cloud native management functionality leverages [Service Mesh Interface](https://smi-spec.io) (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.
+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 your running workloads on Kubernetes or outside of Kubernetes. 
+
+Meshery implmenents both [Service Mesh Performance](https://smp-spec.io) (SMP) and [Service Mesh Interface](https://smi-spec.io) (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's Functionality
 
 Meshery features can be categorized by:
 
 1. Cloud Native Performance Management
-   - Workload and service mesh performance characterization
+   - Workload and cloud native performance characterization
    - Prometheus and Grafana integration
 1. Cloud Native Configuration Management
    - Configuration best practices
@@ -30,37 +32,33 @@ 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 is for service mesh patterns
+### Meshery is for cloud native patterns
 
-Meshery integrates with Open Application Model (OAM) to enable users to deploy service mesh patterns.
+Through MeshModel, Meshery describes infrastructure under management, enabling you to define cloud native designs and patterns and then to export those designs and share within the <a href="https://meshery.io">Meshery Catalog</a>. 
 
 ### Meshery is for performance management
 
-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:
+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.
 
-- Involved
-- Misinterpreted
+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 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.
+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 antive  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.
+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.
 
-1. By leveraging Meshery you could achieve apples-to-apples performance comparison of service meshes
+1. By leveraging Meshery you can achieve apples-to-apples performance comparison
 1. Track your service mesh performance from release to release.
-1. Understand behavioral differences between service meshes.
+1. Understand behavioral differences between cloud native infrastructure.
 1. Track your application performance from version to version.
 
-<a href="https://raw.githubusercontent.com/meshery/meshery/master/docs/assets/img/readme/meshery_lifecycle_management.png"><img alt="Layer5 Service Mesh Community" src="{{ site.baseurl }}{% link assets/img/readme/meshery_lifecycle_management.png %}"  width="100%" align="center"/></a>
+<a href="https://raw.githubusercontent.com/meshery/meshery/master/docs/assets/img/readme/meshery_lifecycle_management.png"><img alt="Meshery Lifecycle Management" src="{{ site.baseurl }}{% link assets/img/readme/meshery_lifecycle_management.png %}"  width="100%" align="center"/></a>
 Establish a performance benchmark and track performance against this baseline as your environment changes over time.
 
-## Meshery is for any service mesh
+## Meshery is for all cloud native infrastructure
 
-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).
+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).
 
-### Supported Service Meshes
+<!-- ### Supported Service Meshes
 
 #### **Stable**
 
@@ -90,4 +88,4 @@ Infrastructure diversity is a reality for any enterprise. Whether you're running
 {% if adapter.project_status == "alpha" -%}
 | <img src="{{ adapter.image }}" style="width:20px" /> [{{ adapter.name }}]({{ site.baseurl }}{{ adapter.url }}) | {{ adapter.project_status }} |
 {% endif -%}
-{% endfor %}
+{% endfor %} -->