30% of data will be real-time by 2025 making real-time API management critical for the successful deployment of event-based applications.
The race for digital transformation is on, and every business worldwide is participating including companies serving financial services, transportation, energy, retail, healthcare, and more. In the transformation, technology and business teams are focused on information management for distributed data sources.
Organizations face the challenge of harnessing constantly expanding and evolving data sources and the complex ecosystem in which they reside. Importantly, 30% of data in the global datasphere, will be real-time by 2025, according to IDC. Therefore, for event-based applications and real-time systems that are fundamental to new business opportunities, there is a clear need that must be addressed: Real-time API management.
The Traditional Approach
Traditional API management tools provide ways to help unify and normalize distributed data sources, but these tools are fundamentally built around polling-based resources (e.g., REST and SOAP) – an approach that is incompatible with the requirements for processing live data. In the diverse ecosystems of today’s digital world, architectures can include any combination of polling-based, event-based, and bespoke infrastructures – often with perplexing integration requirements. Businesses require a platform that delivers the operational benefits of API management and is designed to handle the unique interactions of real-time.
Why Real-Time API Management?
Real-Time API management can manage, optimize, secure, and distribute live data, no matter the origin – providing intelligence on the network edge and a single source of truth for an organization’s information. Use cases exist across all industries, wherever there is business value in immediate data distribution: sports and trading feeds, geo-location data, IoT sensor streams, and many others.
Modern platforms need to combine the benefits of API management with the power of real-time, they also need to be able to join together both polling and event-based back-ends to provide a single unified platform for managing and distributing live data. In doing so, this removes the traditional constraints of data management, allowing businesses to create new revenue channels from pre-existing infrastructure, while greatly simplifying the development of new and innovative applications. The key outcomes of Real-Time API Management should be efficiency, scalability, and cost-effectiveness.
Extending Data to the Edge
Any solution must integrate with existing data sources and extend them to new consumers over edge networks such as web, mobile, and satellite. It must complement and enhance in-place APIs, building more sophisticated real-time features on top of existing infrastructure, without having to rip and replace everything. In addition, for use cases where data is accessed via proprietary or bespoke systems, a solution should include SDKs and application adapters (e.g., Excel) for the publication and consumption of data with custom logic and sophisticated control mechanisms.
The extension of real-time data is not solely based on the concept of making internal streams accessible over the Internet. For many mobile or IoT applications, there is a need for real-time data to be sent from remote devices back to a central event processing system. Therefore, enterprises require a platform that provides fully bi-directional communication – the same integration points allow data ingestion at scale, enabling businesses to both distribute internal feeds while receiving remote data streams, for collection and processing within back-end systems.
Managing Multiple Applications
For most businesses, the data coming from internal sources and legacy systems is unlikely to be suitably formatted for external application consumption. This problem is exacerbated when considering the potential and likelihood for multiple applications to be built on top of the same common data feeds. Normalizing and structuring data on a per-application basis can be time-consuming, error-prone, and complex, especially when it is incumbent upon the development teams of each front-end application to communicate their specific requirements to the owners of the back-end systems. Therefore, the key to success is applying structure. Features such as categorization, aliases, and dynamic views, reduce the complexity of how applications access and consume data, resulting in less development work and faster time-to-market.
Freeing Up Development Resource
An important benefit of real-time API management is the way in which it simplifies the development of applications. Modern applications often require multiple types of data interactions – event streams, direct messaging, and time-series data are all leveraged to deliver rich application experiences and functionality.
What enterprises should be looking for is a unified platform which supports multiple mechanisms for distributing data among systems, applications, and devices; with security and management layers applied above all data flows. With this in place, development teams are able to focus on core business features instead of low-level transport concerns, which in turn allows organizations to quickly and easily capitalize on existing or new data sources with significantly lower development costs and go-to-market time.
Quality of Service
A key differentiator between conventional and real-time API management is quality of service, which affects the performance and viability of all aspects of the data flow. When dealing with polling-based REST APIs, the ability to explicitly handle connection quality is limited by the fundamental delivery mechanisms. By comparison, real-time API management operates on streams of data, providing significantly more sophisticated mechanisms for maintaining consistent and reliable data delivery. Automatic optimization of data assures extremely efficient performance, even for large numbers of remote devices – ideal for IoT scenarios where the cost of bandwidth can be a significant issue.
Real-time API management solutions must manage real-time data and scale. The wide array of corporate applications require different types of scale including the abilities to: serve large and often variable client volume, to handle tens or hundreds of thousands of unique data streams, and to provide high throughput of data across geographically dispersed and/or remote regions. REST-based approaches often require large numbers of server instances to support heavy traffic loads, plus the associated operational complexity of coordinating data and monitoring systems.