Today the community celebrates KEDA 1.0, an open source project aimed at providing event-driven scale capabilities for container workloads. Introduced earlier this year, Red Hat is contributing to KEDA both via the upstream project and by bringing its utility to customers using enterprise Kubernetes and containers with Red Hat OpenShift. We celebrate this milestone with Microsoft and the wider community.
“Event driven applications are a key pattern for cloud native applications and serverless computing like Azure Functions. Working with the community and Red Hat has helped bring the KEDA project to this milestone, enabling event-driven applications on Kubernetes and Red Hat OpenShift,” said Jeff Hollan, principal PM, Microsoft Azure, Microsoft.
KEDA: Kubernetes-based event-driven autoscaling
With KEDA, Kubernetes can scale applications using a pull-based mechanism, and enable Kubernetes to scale apps to and from zero. With this 1.0 release, the project now supports a number of different "scalers," including Apache Kafka, Azure Event Hub, Azure Service Bus, RabbitMQ, Prometheus, AWS SQS and others. The metrics based approach to auto-scaling from KEDA allows Kubernetes to react to incoming events even before the CPU is impacted.
As the community post highlights, KEDA has seen growth and engagement in a few notable ways. This 1.0 milestone is a result of hundreds of merged pull requests and dozens of contributors.
Serverless and Red Hat OpenShift
Our goal is to continue making KEDA a first class citizen in OpenShift, easy to consume and install, so you won’t need to be an expert and can focus on your application, freeing developers from infrastructure concerns.
With the work being done to build a Kubernetes Operator for KEDA using the Operator SDK, and the built-in support for Operators in OpenShift 4 we are making the installation and management of KEDA in OpenShift easier. Through KEDA, Red Hat can enable Azure Functions as a workload for the platform, available as a developer preview on OpenShift, delivering a hybrid FaaS solution that can consume events from Azure Services as well as other additional event sources.
Working with the serverless community
Red Hat is working with the cloud-native community to enable portability of serverless applications in hybrid environments. We also work on Knative as well as a part of this goal in helping developers build and run serverless applications anywhere Kubernetes runs. We see Knative and KEDA as complementary projects, where one can address the needs for push-based requests while the other is focused on pull-based auto-scaling.
Red Hat’s heritage is in contributing to and connecting enterprises with key open source community projects. This case is no different -- we connect these community projects on OpenShift to help provide options for various types of workloads on Kubernetes. We believe working together across these projects can help maximize choice and flexibility for our Red Hat OpenShift customers.
We congratulate the community on reaching this 1.0 milestone, and look forward to continued work alongside Microsoft and others to help provide greater choice for developers that want to be able to build and deploy applications anywhere.
You can join the community and learn more at keda.sh or github.com/kedacore/keda.
Sull'autore
William Markito Oliveira is an energetic and passionate product leader with expertise in software engineering and distributed systems. He leads a group of product managers working on innovative and emerging technologies.
He has worked in global and distributed organizations, with success building high-performance teams and successful products. He also has experience establishing internal and external partnerships delivering high-value outcomes. Oliveira is engaged in open source by fostering communities and governance, and he's looking forward to embracing new technologies and paradigms with a focus on distributed systems. He's spoken at multiple software conferences and co-authored a few books on the field.
Currently, Oliveira is focused on the intersection between serverless, cloud computing, and Kubernetes and applying AI/ML concepts whenever possible.
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