FlowWright has always supported multi-tenancy from an engine perspective, Many customers who embed FlowWright's workflow capabilities into their applications and products see their users use their own application UI rather than using FlowWright's UI. And still some customers wanted to leverage FlowWright's UI elements and its engines in Saas multi-tenant environments. The main goal of SaaS - Software-as-a-Service is to have one copy of software serving many tenants or customers.
FlowWright REST API traditionally was secured using basic authentication with a username and password. Now, with the release of v9.7 of FlowWright, we support OAuth-based authentication. OAuth is secure - and popular with web application developers. Many applications (such as Facebook, LinkedIn, Twitter, HubSpot, SugarCRM, SalesForce) support OAuth authentication.
Business process management is cyclical process involving planning, implementation, and evaluation. Workflow plays a key role. The diagram below illustrates this process.
There are significant differences between a business rules engine and a workflow engine. A workflow engine can automate end-to-end, multi-layered processes of various complexities and timing, where a rules engine simply evaluates expressions and decision criteria. Both engines are designed to be used by technical and non-technical people alike. A workflow engine manages integration and automation comprehensively and makes use of rules through a business process analyst. A business rules engine analyzes and processes rules - rule that can be simple to complex, cascading, or even dynamically generated. But, at the end of the day, rules engines are limited to processing rules.
What is singleton? Singleton is a common software pattern that is used to ensure only a single instance of an object exists no matter how many times it is instantiated. FlowWright applies this concept to workflow processes to solve certain problems in regards to runtime data collection. A FlowWright step collects a great deal of data each time it executes, and it stores this runtime data within an execution iteration. If a step re-iterates many times, data created and stored can grow enormously resulting in unacceptable memory and processing use .
FlowWright supports many infrastructure configurations, including distributed processing. For security reasons, FlowWright customers often choose to install on-premise - either on their in-house servers or in dedicated servers within a data center.
Today, the massive amount of data we collect often drives company decision-making processes. For example, in autonomous vehicles - such as those produced by Tesla and Google - so much information is collected each nanosecond for use in real-time decision making that these vehicles wouldn't be able to function without it. Autonomous vehicles continuously analyze several key data points even to do something as simple as changing lanes: