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@@ -49,7 +49,6 @@ A self-service engineering platform, <a href="https://meshery.io">Meshery</a>, i
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<!-- [Meshery](https://meshery.io) is the cloud native management plane offering lifecycle, configuration, and performance management of Kubernetes, service meshes, and your workloads. -->
<p>Leverage built-in relationships to enforce configuration best practices consistently from code to Kubernetes. Enhance development process by building custom rules in Open Policy Agent's Rego query language.
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<imgalt="Meshery and Open Policy Agent Integration"src=".github/assets/images/readme/meshery-policies-2.png"style="margin-right:10px;"width="70%" />
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<p>Leverage built-in relationships to enforce configuration best practices consistently from code to Kubernetes. Configure your infrastructure with confidence without needing to know or write Open Policy Agent's Rego query language.
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<imgalt="Meshery and Open Policy Agent Integration"src=".github/assets/images/readme/meshery-policies-2.png"style="margin-right:10px;"width="50%" />
<h3>Visually and collaboratively manage your infrastructure</h3>
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<p>Meshery uses <ahref="https://docs.meshery.io/concepts/logical/relationships">relationships</a> to define how and when components interrelate with one another. Meshery supports a variety of relationships between components. These relationships are categorized into two types: semantic and non-semantic.</p>
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<h3>Manage your connections with Environments</h3>
<p><ahref="https://docs.meshery.io/concepts/logical/environments">Environments</a> make it easier for you to manage, share, and work with a collection of resources as a group, instead of dealing with all your Connections and Credentials on an individual basis.</p>
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<h3>Workspaces: Your team's Google Drive for cloud native projects</h3>
<p>Workspaces let you organize your work and serve as the central point of collaboration for you and your teams and point of access control to Environments and their resources.</p>
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<h3>Manage infra performance with Performance Profiles</h3>
<p>Create and reuse performance profiles for consistent characterization of the configuration of your infrastructure in context of how it performs.</p>
<h3> See changes to your infra before you merge</h3>
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<p>Get snapshots of your infrastructure directly in your PRs. Preview your deployment, view changes pull request-to-pull request and get infrastructure snapshots within your PRs by connecting Kanvas to your GitHub repositories.
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<p>Whether managing multiple Meshery deployments, importing designs, discoverying Kubernetes clusters, do so with ease using Meshery CLI in your terminal.</p>
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<h3>Platform Engineering with Meshery's Extension Points</h3>
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<p>Meshery includes both REST APIs and GraphQL APIs, pluggable adapters via gRPCs, hot-loadable ReactJS and hot-loadable Golang binaries. The great number of extension points in Meshery make it ideal as the foundation of your internal developer platform.
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<h3>Access the Cloud Native Patterns for Kubernetes</h3>
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<h2>Performance Management</h2>
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<details>
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<summary><h3>Manage infra performance with Performance Profiles</h3></summary>
<p>Create and reuse performance profiles for consistent characterization of the configuration of your infrastructure in context of how it performs.</p>
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<h3>Manage the performance of your infrastructure and its workloads</h3>
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- Compare performance across infrastructure deployments.
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</details>
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<h3>Platform Engineering with Meshery's Extension Points</h3>
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<p>Meshery includes both REST APIs and GraphQL APIs, pluggable adapters via gRPCs, hot-loadable ReactJS and hot-loadable Golang binaries. The great number of extension points in Meshery make it ideal as the foundation of your internal developer platform.
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<h2>Performance Management</h2>
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<h3>Adhering to Cloud Native Standards</h3>
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<details>
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<summary><h3>Load Generation and Microservice Performance Characteristization</h3></summary>
<imgalt="Shows an illustrated light mode meshery logo in light color mode and a dark mode meshery logo dark color mode."src="https://raw.githubusercontent.com/layer5io/layer5/master/src/assets/images/service-mesh-performance/stacked/smp-light-text.svg"width="18%"align="left"style="margin-left:10px;" />
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In an effort to produce service mesh agnostic tooling, Meshery uses the <ahref="https://smp-spec.io">Service Mesh Performance</a> specification as a common format to capture and measure your infrastructure's performance against a universal cloud native performance index. As an implementation of Service Mesh Interface (SMI), Meshery participates in advancing cloud native infrastructure adoption through the standardization of APIs.
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Meshery offers load generation and performance characterization to help you assess and optimize the performance of your applications and infrastructure. Here's how it works:
-**Multiple Load Generators:** Meshery supports various load generators, including Fortio, Wrk2, and Nighthawk, allowing users to choose the tool that best suits your needs.
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-**Configurable Performance Profiles:** Meshery provides a highly configurable set of load profiles with tunable facets, enabling users to generate TCP, gRPC, and HTTP load. You can customize parameters such as duration, concurrent threads, concurrent generators, and load generator type. Save your load test configurations as Performance Profiles, making it easy to rerun tests with the same settings and track performance variations over time.
-**Metrics Collection:** Meshery can connect to one or more Prometheus instances to gather telemetric data, including Kubernetes and application metrics. It also integrates with Grafana, allowing users to import existing dashboards and visualize performance data.
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-**Statistical Analysis:** Meshery performs statistical analysis on the results of performance tests, presenting data in the form of histograms with latency buckets. This helps users understand the distribution of response times and identify potential bottlenecks.
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-**Performance Test Profiles:** Meshery allows users to customize and save their load test configuration in the form of a Performance Test Profile. This enables users to easily return to Meshery to run the same set of customized tests again and again, tracking variations in performance over time.
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Comparison of Test Results: Meshery enables users to compare the difference in request performance (latency and throughput) between independent performance tests.
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-**Kubernetes Cluster and Workload Metrics:** Meshery provides performance test results alongside environment metrics, including control and data plane metrics
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as well as cluster node resource metrics, so that operators may easily understand the overhead of their control plane and data plane in context of the overhead incurred on nodes within the cluster.
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Meshery is the cloud native utility for uniformly managing the performance of microservices and the infrastructure that run them. As an implementation of the Service Mesh Performance ([SMP](https://smp-spec.io/)), Meshery enables you to measure the value provided by Docker, Kubernetes, or a service mesh in the context of the overhead incurred.
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<p>In an effort to produce infrastructure agnostic tooling, Meshery uses the <ahref="https://smp-spec.io">Cloud Native Performance</a> specification as a common format to capture and measure your infrastructure's performance against a universal cloud native performance index. Meshery participates in advancing cloud native infrastructure adoption through the standardization of APIs. Meshery enables you to measure the value provided by Docker, Kubernetes, or a service mesh in the context of the overhead incurred.</p>
- Follow this [tutorial workshop](https://github.com/layer5io/istio-service-mesh-workshop/blob/master/lab-2/README.md) to set up and deploy the BookInfo sample app on Istio using Meshery.
- Follow this [tutorial workshop](https://github.com/layer5io/istio-service-mesh-workshop/blob/master/lab-2/README.md) to set up and deploy the BookInfo sample app on Istio using Meshery.
Identify overhead involved in running {{page.component}}, various {{page.component}} configurations while running different workloads and on different infrastructure. The adapter facilitates data plane and control plane performance testing.
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