Service Fabric (continued)    

Part 2 compared Paxos and Raft. Part 3 discussed SF-Ring and Part 4 discussed its architecture. This article describes its usage scenarios.

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.

Service Fabric is also useful for scenarios that require low-latency reads and writes, such as in online gaming or instant messaging. Applications can be built to be interactive and stateful without having to create a separate store or cache. Gaming and instant messaging are some examples of this scenario.

Applications that must reliably process events or streams of data run well on Service Fabric with its optimized reads and writes. Service Fabric supports application processing pipelines, where results must be reliable and passed on to the next processing stage without any loss. These pipelines include transactional and financial systems, where data consistency and computation guarantees are essential.

Stateful applications that perform intensive data computation and require the colocation of processing (computation) and data in applications benefit from Service Fabric as well. Stateful Service Fabric services eliminate that latency, enabling more optimized reads and writes. As an example, real-time recommendation selections for customers that require a round trip-time latency of less than hundred milliseconds are handled with ease.

Service Fabric also supports highly available services and provides fast failover by creating multiple secondary service replicas. If a node, process, or individual service goes down due to hardware or other failure, one of the secondary replicas is promoted to a primary replica with minimal loss of service.

Individual services can also be partitioned where services are hosted by different hosts. Individual services can also be created and removed on the fly. Services can be scaled from a few instances on a few nodes to thousands of instances on several nodes and dialed down as well. Service Fabric helps with the complete life cycles.

Examples of stateless services include Azure Cloud Services and that for stateful microservices that must maintain authoritative state beyond the request and its response include ASP.Net and node.js services Service Fabric provides high availability and consistency of state through simple APIs that provide transactional guarantees backed by replication.

Stateful services in Service Fabric bring high availability to all types of applications and not just those that depend on a database or a data store. This covers both relational and big data stores. Applications can have both their state and data managed for additional performance gains without sacrificing reliability, consistency or availability

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.

Stateful microservices simplify application design because they remove the need for the additional queues and caches and have traditionally been required to address the availability and latency requirements of purely stateless applications. Service Fabric provides reliable services and reliable actors programming models and reduce the application complexity while achieving high throughput and low latency.