CNCF Graduates Dapr to Help Improve Developer Productivity
The Cloud Native Computing Foundation (CNCF) this week at the KubeCon + CloudNativeCon 2024 conference announced that the open-source Distributed Application Runtime (Dapr) has officially graduated.
Dapr has grown to over 3,700 individual contributors from more than 400 organizations, with 21 maintainers drawn from eight different organizations. Dapr SDKs have been downloaded 70 million times, with 50 million image pulls. It is commercially supported by Diagrid, which has also created a software-as-a-service (SaaS) platform, dubbed Conductor Enterprise, that makes it simpler to deploy microservices on Kubernetes clusters. A graph created by Diagrid also provides a dynamic overview of services and infrastructure components employing the Dapr framework.
Diagrid CEO Mark Fussell said officially graduating reflects a level of maturity in an era where enterprise IT organizations have become more circumspect about what open-source software they are willing to deploy. Organizations want to be sure there is a robust community supporting the project and that the appropriate cybersecurity reviews have been conducted, he added.
At its core, Dapr is a portable runtime originally developed at Microsoft that makes it easy for any developer to build distributed applications. It provides a set of reusable integrated application programming interfaces (APIs) for handling a range of functions, including communication, state, and encryption, eliminating the need for developers to write the same boilerplate code multiple times over. The overall goal is to enable developers to spend more time writing business logic.
The Dapr control plane, which, among other capabilities, deploys Dapr sidecars for each application, is hosted on Kubernetes and is deployed with Helm charts. It has also already integrated OpenTelemetry to generate and export telemetry data and Prometheus to collect and analyze runtime metrics.
Dapr maintainers, going forward, are now focused on the upcoming v1.15 release, due next month, that will add an AI conversational API, in alpha, that can be used to invoke different large language models (LLMs) along with a more stable workflow API implementation.
Initially, the adoption of Dapr has been driven by individual developers. However, with the rise of platform engineering as a methodology for managing DevOps workflows at scale, it’s apparent more organizations are trying to centralize application development. Dapr provides a consistent framework that supports multiple programming languages, including Java and Python, in a way that reduces friction across the application development workflows. Otherwise, IT teams will need to provide access to either a similar framework for each programming language employed or support multiple equivalents of custom integration code created by individual developers, that they will then need to maintain.
It’s only a matter of time before more development teams realize they are essentially writing the same integration code multiple times over. At a time when the pressure to deliver cloud-native applications on time is only increasing, developers are looking for ways to become much more efficient. Dapr provides a method to accelerate the development of cloud-native applications, at a time when many organizations are clearly under increased pressure to build cloud-native applications faster than ever.
