Service Fabric (continued)    

Part 2 compared Paxos and Raft. Part 3 discussed SF-Ring and Part 4 discussed its architecture. This article describes compute planning and scaling.

Service Fabric supports a wide variety of business applications and services. These applications and services can be stateless or stateful. They are run with high efficiency and load balancing. It supports real-time data analysis, in-memory computation, parallel transactions, and event processing in the applications. Applications can be scaled in or out depending on the changing resource requirements.

Service Fabric handles hosts stateful services that must support large scale and low latency. It can help process data on millions of devices where the data for the device and the computation are co-located. It is equally effective for both core and edge services and scales to IoT traffic. Apps and services are all deployed in the same Service Fabric cluster through the Service Fabric deployment commands and yet each of them is independently scaled and made reliable with guarantees for resources. This independence improves agility and flexibility.

Capacity and Scaling are two different considerations for Service Fabric and must be reviewed individually. Cluster capacity considerations include Key considerations include initial number and properties of cluster node types, durability level of each node type, which determines Service Fabric VM privileges within Azure infrastructure, and reliability level of the cluster, which determines the stability of Service Fabric system services and overall cluster function

A cluster requires a node type. A node type defines the size, number, and properties for a set of nodes (virtual machines) in the cluster. Every node type that is defined in a Service Fabric cluster maps to a virtual machine scale set aka VMSS. A primary node type is reserved to run critical system services. Non-primary node types are used for backend and frontend services.

Node type planning considerations depend on whether the application has multiple services or if they have different infrastructure needs such as greater RAM or higher CPU cycles or if any of the application services need to scale out beyond hundred nodes or if the cluster spans availability zones.