Apache NiFi frontend modernization

Apache NiFi frontend modernization complete

Apache NiFi’s 2.0.0 release included several upgrades that make the platform faster, more secure, and easy to use. One thing that really stands out to us, however, is how transformational Apache NiFi’s frontend modernization really is. The platform has been redesigned to be faster, more intuitive, and visually appealing while at the same time familiar to long time NiFi users.

This release brings a host of improvements, including performance upgrades, a fully implemented Material Design Specification 3 interface, and introduces capabilities for unit and e2e testing to ensure quality and reliability.

What else went into Apache NiFi’s frontend modernization? Check out our list below.

Complete tech stack overhaul

The frontend has been rebuilt from the ground up using a modern tech stack built with the latest Angular 18+, optimizing performance, scalability, and future readiness. This update ensures a smoother, faster experience for users and enables ongoing improvements.

Dependency upgrades

All dependencies, including frameworks, libraries, and tools, have been updated to their latest versions. These upgrades deliver improved security, compatibility, and access to the latest features.

Developer experience improvements

This frontend overhaul also brings substantial improvements for developers. The modernized tech stack and updated testing suite streamline the development workflow, enabling faster, more efficient coding and debugging. Componentized architecture, ngrx store, improved dependency management, and detailed testing coverage allow developers to build, maintain, and expand the platform with greater confidence and flexibility.

Material Design Specification 3 implementation

The entire UI now follows Material Design Specification 3, introducing a cohesive, modern visual style. This includes updated typography, refined icons, and improved visual hierarchy for a clearer, more organized interface.

Light and dark mode themes

Users can now switch between light and dark mode themes, providing greater flexibility and a personalized experience. Each theme has been carefully designed to ensure readability and comfort in any environment.

Updated typography

The typography has been updated throughout the application, enhancing readability and establishing a consistent look and feel across all components. The new typography aligns with accessibility standards, improving the overall user experience.

Enhanced User Experience (UX)

The new UI offers a simplified, intuitive experience that enhances navigation and workflow efficiency. With a focus on usability, layouts have been restructured, interactions refined, and the user journey is now seamless. Users can also customize their experiences by choosing the light or dark mode theme and can optionally enable or disable UI animations or the user may simply rely on their OS settings for these features.

UI testing coverage

Frontend components now include limited unit testing. This will allow for future continued coverage to ensure quality and that each component functions as expected, contributing to a stable and predictable user experience. End-to-end testing is now also possible.

Apache NiFi frontend modernization

Accessibility enhancements

Significant strides have been made in meeting accessibility standards, including support for screen readers, ensured color contrast ratios, and improved keyboard navigation, ensuring that all users, including those with disabilities, can interact with the platform effectively.

What to expect

Users will experience a refreshed look, along with light and dark themes for tailored comfort. The updated interface maintains familiar functionality while introducing a more streamlined, visually appealing layout.

Apache NiFi frontend modernization

Top Related Posts

Continuous Integration for NiFi Flows in GitHub

Datavolo is proud to announce the release of a GitHub Action designed to help with Continuous Integration of Apache NiFi Flows and make reviewing of changes between two flow versions as easy as possible. At Datavolo, collaboration on the Flow Definitions is done by...

Next Generation Apache NiFi | NiFi 2.0.0 is GA

Apache NiFi is about to turn 10 years old as an Apache Software Foundation (ASF) project and it is in use by over 8,000 enterprises around the globe. No better time for this incredibly flexible and powerful framework to finalize its 2.0.0 version. Welcome to the Next...

Streaming Data to Iceberg From Any Source

New support for writing to Apache Polaris-managed Apache Iceberg tables enables Datavolo customers to stream transformed data from nearly any source system into Iceberg. Originally created by Snowflake, Polaris allows customers to use any query engine to access the...

How we use the Kubernetes Operator pattern

Organizations using NiFi for business-critical workloads have deep automation, orchestration, and security needs that Kubernetes by itself cannot support. In this second installment of our Kubernetes series, we explore how the Kubernetes Operator pattern alleviates...

Constructing Apache NiFi Clusters on Kubernetes

Introduction Clustering is a core capability of Apache NiFi. Clustered deployments support centralized configuration and distributed processing. NiFi 1.0.0 introduced clustering based on Apache ZooKeeper for coordinated leader election and shared state tracking. Among...

Onward with ONNX® – How We Did It

Digging into new AI models is one of the most exciting parts of my job here at Datavolo. However, having a new toy to play with can easily be overshadowed by the large assortment of issues that come up when you’re moving your code from your laptop to a production...

Survey Findings – Evolving Apache NiFi

Survey of long time users to understand NiFi usage Datavolo empowers and enables the 10X Data Engineer. Today's 10X Data Engineer has to know about and tame unstructured and multi-modal data. Our core technology, Apache NiFi, has nearly 18 years of development,...

Apache NiFi – designed for extension at scale

Apache NiFi acquires, prepares, and delivers every kind of data, and that is exactly what AI systems are hungry for.  AI systems require data from all over the spectrum of unstructured, structured, and multi-modal and the protocols of data transport are as varied...