Merge pull request #24 from RongGu/br-pr6

update architecture-and-concepts doc page

Author: cheyang

docs/core-concepts/architecture-and-concepts.md

@@ -3,4 +3,42 @@ sidebar_label: Architecture and Concepts
 sidebar_position: 3
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+
 # Architecture and Concepts
+
+## Architecture
+
+Fluid is built in the Kubernetes native fashion. It lies between existing underlying cloud native storage systems and the upper layer data-intensive applications. The architecture of Fluid in Kubernetes is as following:
+
+![](../static/img/docs/architecture.png)
+Specifically, Fluid is logically split into a data plane and a control plane.
+
+- The control plane is composed of **Dataset/Runtime Controller** and **Application Manager**
+  - **Dataset/Runtime Controller:** It manages the datasets and also automates the data operations of the dataset, like data load, data migrate, data process and so on.
+  - **Application Manager**: It is responsible for scheduling the workload pods according to cache location and managing their life cycles. 
+- The data plane is composed of Runtime Plugin and CSI Plugin:
+  - **Runtime Plugin**: As a highly extensible plugin, it can help turn various data cache engines into self-managing, self-scaling, self-healing and observable cache services inside of Kubernetes by providing the common framework of Fluid.
+  - **Data Access Plugin**: It is responsible for managing different kinds of storage clients in container mode in the same manner. It supports both CSI Plugin and sidecar mode to run FUSE containers.
+
+The following diagram shows the different components.
+
+![](../static/img/docs/componnents.png)
+
+## Key Concepts
+
+For achieving its goals, Fluid provides some core concepts.
+
+**Dataset**: A Dataset is a set of data logically related that can be used by computing engines, such as Spark for big data analytics and TensorFlow for AI applications. 
+* Same as native Kubernetes API definitions, including CRDs
+* Users describe the data’s source, type, access mode and cache location
+* Users can use observability to make scaling decisions of distributed cache
+
+**Runtime**: The Runtime enforces dataset isolation/share, provides version management, and enables data acceleration by defining a set of interfaces to handle DataSets throughout their lifecycle, allowing for the implementation of management and acceleration functionalities behind these interfaces. Fluid has two kind of Runtime: CacheRuntime and ThinRuntime.
+* CacheRuntime, which implements distributed caching solutions including Alluxio, JuiceFS, Vineyard and others 
+* ThinRuntime, that provides a unified access interface to systems like CubeFS, GlusterFS, NFS and others.
+
+**Data Operations**: Unlike traditional PVC-based storage abstraction, Fluid takes an Application-oriented perspective to abstract the “process of manipulating data on Kubernetes”. It introduces the concept of elastic Dataset and implements it as a first-class citizen in Kubernetes to enable Dataset CRUD operation, permission control, and data access acceleration. Besides the basic operations like creation, Fluid also provides a set of operations for the defined  Dataset for users to manipulate the data flow. 
+* Data Load prefetches data from dataset source to cache system.
+* Data Migration syncs data between external storages and dataset .
+* Data Process can be used to transform, split, applying dimensionality reduction to data
+Distributed cache scale up and down.