Spring Cloud Data Flow (SCDF) for Kubernetes 1.1 is now generally available, building on the open source SCDF version 2.6 released in August. The Kubernetes-based commercial offering leverages Tanzu Observability by Wavefront for dashboarding and observability, and enables developers to take their data pipelines to the next level with the introduction of Multi I/O for event-streaming applications.
Watch those pipelines
When developers are polled on the most desirable platform features, dashboards and the ability to observe what’s happening reliably are at the top of everyone’s wish list. That’s no surprise—there’s only so much that even the most talented developer can digest while watching a Matrix-style terminal window as text scrolls by.
So we are delighted to make Spring developers’ dreams come true with a new dashboard and observability for Spring Cloud Data Flow for Kubernetes. While useful out of the box, the dashboard is just the tip of the iceberg in terms of what’s possible when you start observing behavior patterns of event-streaming and batch applications at scale.
The new SCDF dashboard, powered by Tanzu Observability
For developers who want to understand how SCDF applications perform in production, Tanzu Observability provides an SCDF Integration tile with performance overview dashboards and detailed real-time message rates, throughput, latency, and error metrics. Such comprehensive observability enables developers to drill down and find the root cause of bottlenecks for event-streaming data pipelines and of increased latencies for batch data pipelines.
With the newly released Spring Boot dashboard, Spring developers can add observability across a breadth of application scenarios. To use the SCDF dashboard (as well as a new one for Spring Boot), sign up for the Tanzu Observability free trial.
Advanced event-streaming topologies
Event-streaming data-processing in SCDF typically takes the form of linear data pipelines with data coming from a single upstream topic, and the processed data published to a single downstream topic. While this has worked well for most common event-streaming use cases, there are many in which a more functional programming model is better suited.
For example, applications that interact with multiple upstream and downstream Kafka topics are a great fit for the functional programming model. However, this Multi I/O pattern can make it cumbersome to reason through and orchestrate the advanced nature of microservices with more than a single input/output.
So, in Spring Cloud Data Flow v1.1 for Kubernetes, we are launching an interactive dashboard and a brand new UI/UX to discover the function-style event handlers and Kafka Streams topologies with one or more input and output destinations (i.e., topics). The new dashboard will help with the discovery and interactive design of data pipelines made of advanced event-streaming applications. The functional-style design also extends to SCDF’s catalog of applications, in which the new Multi I/O dashboard is also available.
As we continue to explore functional-style applications in SCDF, we’re also writing an ongoing blog series (see Part 1 Part 2 Part 3 Part 4 Part 5 and Part 6) to highlight and articulate the design patterns as case studies.
We are re-designing all the current Spring Cloud Stream App Starters using java.util.function as a foundation. In this blog post, @dturanski introduces this initiative in much more detail. https://t.co/qSBaYNcl6N— sobychacko (@sobychacko) July 14, 2020
Get started today!
- Read the docs: Tanzu Observability for Spring Cloud Data Flow
- Download Spring Cloud Data Flow for Kubernetes 1.1
About the AuthorMore Content by Sabby Anandan