Tag: WSO2

  • WSO2 Applies AI to API Management

    WSO2 Applies AI to API Management

    WSO2 today unfurled a Choreo cloud platform through which DevOps teams can create and manage application programming interfaces (APIs) more efficiently by leveraging machine learning algorithms and other forms of artificial intelligence (AI).

    Eric Newcomer, WSO2 CTO, said the integration platform-as-a-service (iPaaS) eliminates all the tasks associated with setting up a platform for and managing services based on APIs.

    Choreo, available in beta, employs AI to learn historical activities and performance behaviors in order to anticipate the needs of a developer. As developers build an API, the platform will provide performance feedback, identify anomalies, map data and even complete code, said Newcomer.

    The Choreo platform also comes with built-in observability tools for monitoring API usage and troubleshooting APIs, added Newcomer.

    In addition, Choreo provides access to the open source Ballerina programming language the company developed to enable developers to create APIs using both low-code and procedural code as they see fit, noted Newcomer. The low-code diagram that developers create generates source code that developers can then run wherever they want, said Newcomer. Developers can close the entire repository Choreo provides, Newcomer added.

    Developers can also trigger low-code integration logic to control hundreds of software-as-a-service (SaaS) APIs via pre-built connectors and templates provided by WSO2 or ones they create themselves.

    WSO2 is also making it possible to deploy APIs via a single click in Kubernetes environments, which eliminates the need to manage cumbersome YAML files. That capability is based on technology that WSO2 gained via the acquisition of Performer that the company revealed today.

    Finally, WSO2 is making available an API marketplace through which organizations can share APIs, event streams, data sources and templates.

    With the rise of microservices-based applications, API management has become a lot more challenging. Each additional microservice adds an API that needs to be managed and maintained. As more APIs are employed, it becomes increasingly difficult for DevOps team to keep track of the dependencies that exist between all those APIs without the aid of machine learning algorithms.

    It’s not likely machine learning algorithms will replace the need for DevOps professionals anytime soon. However, it’s becoming apparent that many of the manual tasks that DevOps teams routinely perform today are becoming automated by machine learning algorithms. In other cases. DevOps teams are gaining new capabilities that would have either been impossible for them to do on their own or would simply have taken too much time to complete.

    Of course, it takes time for any AI platform to learn the DevOps environment. IT teams need to invest a significant amount of time training an AI model to recognize relevant issues in much the same way they might train any new member of a DevOps team. The only difference is, once a machine learning algorithm learns something, they never forget it. Nor do they take a day off or announce one day they are leaving the company because they got a better offer somewhere else.

    It may take a while before DevOps teams are able to strike the right balance between man and machine, but one thing that is certain is that AI in DevOps environments is here to stay.

  • WSO2 Advances Microservices Gateway

    WSO2 Advances Microservices Gateway

    At the Open Source and Software Development Conference (OSCON), WSO2 this week announced it has updated an open source microservices gateway to make it possible to expose multiple microservices through a single application programming interface (API).

    Additionally, version 3.0 of the WSO2 API Microgateway now includes the ability to automatically discover microservices and transform legacy API requests into a more modern format. WSO2 also added support for the OpenAPI Specification (OAS), formerly known as Swagger, to make it easier for developers to collaborate on creating APIs, and has separated the WSO2 API Microgateway toolkit from the runtime to enable greater scalability and smoother upgrades.

    Ken Oestreich, vice president of product marketing for WSO2, said the WSO2 API Microgateway is designed to accelerate the convergence of application development and integration into a single team. As part of that effort, WSO2 has been advocating the adoption of Ballerina, a general-purpose programming language designed from the ground up to make it easier for developers to integrate distributed applications on their own. For example, Ballerina makes it possible for developers to create and embed their own micro-enterprise service bus (ESB) within a distributed application, he said.

    Those integration engines then could be deployed and updated within any DevOps processes layered on top of a continuous integration/continuous deployment (CI/CD), Oestreich added.

    A WSO2 API Microgateway is designed to boot up in less than a second and provides authentication, authorization, rate limiting, service composition, discovery, transformation and analytics capabilities. It is designed to be integrated with the WSO2 API Manager, an open source API management platform that can run on-premises or in the cloud.

    As the number of microservices being created within organizations increases thanks to the rise of containers, Oestreich noted there is now a critical need for organizations to find a lightweight approach to building and managing all the APIs required to connect thousands of microservices. WSO2 provides a flow diagram through which organizations can visually manage that process, said Oestreich. As part of its support for containers, the WS02 API Gateway provides built-in support for container orchestration tools such as Kubernetes, which makes it possible to generate artifacts that can be applied directly to Kubernetes clusters.

    Organizations of all sizes are clearly struggling these days with API management. In theory, APIs should remain stable as the software components they connect to are updated. The trouble is, each new microservice generates its own set of APIs, and before too long, organizations find themselves trying to manage thousands of APIs that are all dependent on each other. The removal of any one API might not crash an application, but it could adversely impact performance as API calls are re-routed around the application.

    It’s not all clear these days who inside most organizations is responsible for managing APIs. Developers certainly create the APIs. However, once they are deployed in a production environment, their care and feeding often pass over to an IT operations team. Regardless of whom, however, once any of those APIs break it’s not long before the entire DevOps team knows about it. The challenge now is figuring out how to make the management of all those APIs as natural an extension of a DevOps process as possible.

    — Mike Vizard