Spring Cloud Data Flow for Kubernetes Adds Real-Time Alerts and New Dashboard

December 9, 2020 Sabby Anandan

We are pleased to announce that Spring Cloud Data Flow for Kubernetes 1.2.0 is now generally available. This commercial offering bundles the latest open source release of Spring Cloud Data Flow with several new features designed to boost developer productivity. The new product is supported by VMware as part of VMware Spring Runtime.

We’ve seen a remarkable amount of interest in Spring Cloud Data Flow for three key scenarios:

  • Mainframe and ETL modernizations – Incumbent workloads on heritage systems tend to be brittle and difficult to change. With Spring Cloud Data Flow, enterprises achieve greater resiliency and release velocity, and move towards a CI/CD model for offline and large-scale data processing.

  • Event-streaming data pipelines – These pipelines transport and process data across various business systems to deliver real-time insights that can lead to better business decisions.

  • Building blocks for event-driven architectures – Enterprises adopt CQRS, event sourcing, and other design patterns to build resilient, data-intensive architectures.

This new release helps developers and data engineers be more productive. In particular, developers will enjoy real-time alerts when new versions of apps land in backing Docker registries.

Let’s take a closer look at this headline feature.

Use dashboard alerts for rolling event streams and batch data pipeline upgrades

Enterprises use Spring Cloud Data Flow to orchestrate thousands of event streaming and batch job applications. It can be tricky to manually comb all these apps at enterprise scale; developers must search for new updates before triggering a one-off deployment. This is the challenge addressed by the new alerts feature.

With visual alerts in the dashboard, developers can confidently initiate the rolling upgrade deployment of recently updated apps from within the Spring Cloud Data Flow dashboard. Check out this video to see it in action!

The Spring Cloud Data Flow dashboard gets a makeover

The new Dashboard features wizard-style workflows and API automation. We’ve made plenty of changes in the code itself, too. The dashboard has been completely redesigned and rewritten with Clarity design components. (In fact, the majority of UI controls are inherited from Clarity).

The new design has proven to be a big time-saver in our testing, and we’re excited for you to try it out! Share your experience with us on GitHub.

Deeper integration with VMware Tanzu Observability and Kafka Streams

What else can you expect in the release? The open source Spring Cloud Data Flow v2.7.0 foundation brings several noteworthy capabilities. 

Use Tanzu Observability to monitor Spring Cloud Data Flow components

The Spring Cloud Data Flow integration tile for Wavefront was recently updated so that the metrics/monitoring dashboard renders telemetry for your event streaming and batch jobs as well as Spring Cloud Data Flow’s internal components.

In this new release, all the various statistics for server-side API invocations and latency metrics are readily available from a single Tanzu Observability dashboard.

Orchestrate Kafka Stream apps and get deeper integration with Tanzu Observability

Due to demand from customers and the community, we have added Kafka and Kafka Streams-focused metrics. Now, developers can examine Kafka Streams performance in real time.

Define and launch task and batch jobs programmatically

Spring Cloud Data Flow excels at helping you programmatically create and deploy event streaming data pipelines. This pattern is particularly useful for CI/CD-centered deployment automation. To help you handle additional use cases, we have extended the same developer experience with fluent-style APIs to define and launch task and batch jobs programmatically. The CI/CD or GitOps enthusiasts in your org can now extend their practices to event streaming and batch job deployments!

It’s time to try Spring Cloud Data Flow for Kubernetes

Ready to get started? Download and install Spring Cloud Data Flow for Kubernetes 1.2 on your favorite Kubernetes distro. Then check out the operator and developer guides to learn more about the new release!

 

About the Author

Sabby Anandan

Sabby Anandan is a Product Manager on the Spring Team at VMware. He focuses on building products that address the challenges faced with iterative development and operationalization of data-intensive applications at scale. Before joining VMware, Sabby worked in engineering and management consulting positions. He holds a Bachelor’s degree in Electrical and Electronics from the University of Madras and a Master’s in Information Technology and Management from Carnegie Mellon University.

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