Januar 2019 - Seite 28 von 89 - Cloud Computing Köln

Azure API Management has just introduced preview support of OpenAPI Specification v3 – the latest version of the broadly used open-source standard of describing APIs. Implementation of the feature is based on the OpenAPI.NET SDK.

In this blog post we will explore:

The benefits of using OpenAPI Specification for your APIs.
How you can create APIs from OpenAPI Specification documents in Azure API Management.
How you can export your APIs as OpenAPI Specification documents.
The remaining work for the general availability release.

Why you should use OpenAPI Specification for your APIs

OpenAPI Specification is a widely adopted industry standard. The OpenAPI Initiative has been backed by over 30 companies, including large corporations such as Microsoft.

OpenAPI Specification lets you abstract your APIs from their implementation. The API definitions are language-agnostic.

They are also easy to understand, yet precise. Your APIs are represented through YAML or JSON files, readable for humans as well as machines.

The wide adoption of OpenAPI Specification has resulted in an extensive tooling ecosystem. Functionality of the tools ranges from facilitating collaborative process of designing APIs, to automatically generating client SDKs and server implementations in popular programming languages.

How to import OpenAPI Specification v3 definitions in Azure API Management

If your APIs are defined in an OpenAPI Specification file, you can easily import them in Azure API Management. The Azure portal will automatically recognize the right version of your OpenAPI Specification files. You can learn how to import your APIs through the visual interface by following our tutorial, “Import and publish your first API.”

Alternatively, you can import APIs using the REST API call, with the contentFormat payload parameter set to openapi, openapi+json, or openapi-link.

During import, if the servers field of the specification contains multiple entries, API Management will select the first HTTPS URL. If there aren't any HTTPS URLs, the first HTTP URL will be selected. If there aren't any HTTP URLs, the backend service URL will be empty.

The import functionality has a few restrictions. For example, it does not support examples and multipart/form-data fields.

How to export OpenAPI Specification v3 definitions in Azure API Management

With Azure API Management, you can also easily export your APIs in the OpenAPI Specification v3 format.

API specifications can be downloaded from your developer portal as JSON or YAML files. The developer portal is an automatically generated, fully customizable website, where visitors can discover APIs, learn how to use them, try them out interactively, and finally sign up to acquire API keys.

You can also export the specifications through the visual interface of the Azure portal or a REST API call, with the format query parameter set to openapi-link.

How to get started and what’s coming next

You can try the current functionality in a matter of minutes by importing your APIs from OpenAPI Specification files. Before the feature becomes generally available, we will implement export in a JSON format through a REST API call. In the coming months, we will also add OpenAPI Specification v3 import and export support in the PowerShell SDK.

Let us know what you think!
Quelle: Azure

23. Januar 2019

da Agency

Build an AI-powered, customer service virtual agent with Chatbase

These days, most people don’t tolerate more than one or two bad customer service experiences. For contact centers drowning in customer calls and live chats, an AI-powered customer service virtual agent can reduce that risk by complementing humans to provide personalized service 24/7, without queuing or waiting. But the status-quo approach to designing those solutions (i.e., intuition and brainstorming) is slow, based on guesswork, and just scratches the surface on functionality — usually, causing more harm than good because the customer experience is poor.Built within Google’s internal incubator called Area 120, Chatbase is a conversational AI platform that replaces the risky status quo approach with a data-driven one based on Google’s world-class machine learning and search capabilities. The results include faster development (by up to 10x) of a more helpful and versatile virtual agent, and happier customers!Lessons learned along the journeyInitially, Chatbase provided a free-to-use analytics service for measuring and optimizing any AI-powered chatbot. (That product is now called Chatbase Virtual Agent Analytics.) After analyzing hundreds of thousands of bots and billions of messages in our first 18 months of existence, we had two revelations about how to help bot builders in a more impactful way: one, that customer service virtual agents would become the primary use case for the technology; and two, that using ML to glean insights from live-chat transcripts at scale would drastically shorten development time for those agents while creating a better consumer experience. With those lessons learned, Chatbase Virtual Agent Modeling (currently available via an EAP) was born.Virtual Agent Modeling explainedVirtual Agent Modeling (a component in the Cloud Contact Center AI solution) uses Google’s core strengths in ML and search to analyze thousands of transcripts, categorizing customer issues into “drivers” and then digging deeper to find specific intents (aka customer requests) per driver. For complex intents, Chatbase models simple yet rich flows developers can use to build a voice or chat virtual agent that handles up to 99% of interactions, responds helpfully to follow-up questions, and knows exactly when to do a hand-off to a live agent.In addition, the semantic search tool finds potentially thousands of training phrases per intent. When this analysis is complete, developers can export results to their virtual agent (via Dialogflow) — cutting weeks, months, or even years from development time.Don’t settle for the slow status quoAccording to one Fortune 100 company upgrading its customer service virtual agent with Virtual Agent Modeling, “This new approach to virtual agent development moves at 200 mph, compared to 10-20 mph with current solutions.” Furthermore, it expects to nearly double the number of interactions its virtual agent can handle, from 53% of interactions to 92%.If you have at least 100,000 English-language live-chat transcripts available and plan to deploy or enhance either a voice or chat customer service virtual agent in 2019, Virtual Agent Modeling can help you get into that fast lane. Request your personal demo today!
Quelle: Google Cloud Platform