Virgin Australia Saves 300 Hours/Month

Executive Summary

By accelerating onboarding and simplifying workflows, Virgin Australia reclaimed up to 300 hours per month for their developers and testers. They also improved visibility and standardization across their Kafka environment, accelerating development cycles and data utilization.

Challenge

To maintain its competitive edge, Virgin Australia embarked on an ambitious initiative to modernize and replatform its legacy systems, with Kafka at the core. However, the team soon encountered challenges:

• Limited visibility — Teams lacked intuitive tools to effectively visualize and troubleshoot Kafka data flows
• Complex user access — Provisioning users onto Confluent Cloud and controlling access for diverse user groups was time-consuming and inefficient
• Fragmented operations — Without centralized tools, collaboration and operational efficiency were hindered

To address these issues, Virgin Australia implemented Conduktor Desktop in 2022, empowering users to monitor, manage, and maintain their Kafka data flows.

Growing pains

As Kafka adoption grew, provisioning licenses and maintaining local installations became increasingly difficult for the platform team, creating bottlenecks for innovation.

"With Desktop, we had to provision accounts, issue API keys, and manage individual licenses," Scot McPhee, a Platform Engineer at Virgin Australia, explains. "It was okay for developers but cumbersome for other users like testers and analysts."

Solution

To address these challenges and standardize their Kafka user experience, Virgin Australia upgraded to Conduktor Scale at the end of 2024.

With Scale, Virgin Australia teams could now:

• Centralize deployment — Automatic user updates, eliminating the need for individualized software installations
• Simplify user management — Facilitating operations like onboarding and access provisioning
• Gain comprehensive visibility — Powerful built-in tools and integrations with third-party observability solutions
• Prevent issues proactively — Rapidly detecting, investigating, and debugging issues before they impact downstream applications
• Accelerate development cycles — Enabling testers and developers to efficiently access and validate Kafka data

Results

The use of Conduktor Scale has delivered quantifiable improvements:

• Increased efficiency — Roughly 48 hours per week saved for testers and 20 hours per week for developers
• Widespread adoption — A diverse range of users, including testers and analysts, now actively use Kafka
• Shortened investigations — Teams use advanced tools and visualizations to better understand and troubleshoot their Kafka environment

Beyond these measurable gains, Scot highlighted the "unquantifiable" value: "Being able to share data seamlessly and collaborate across teams without friction has saved countless hours. It's improved the quality of questions and insights we receive, which boosts overall productivity in ways that are hard to quantify."

What's Next

Virgin Australia utilizes Kafka to power several real-time use cases, such as streaming flight data to internal and external consumers, as well as ingesting booking information from third-party travel sites to update flyer profiles.

With Kafka and Conduktor, the Virgin Australia team can support even more business verticals and streaming data applications, positioning it for future growth in a complex, competitive industry.

Frequently Asked Questions

How much time did Virgin Australia save with Conduktor Scale?

Virgin Australia reclaimed up to 300 hours per month—roughly 48 hours per week for testers and 20 hours per week for developers through simplified workflows and centralized deployment.

What is the difference between Conduktor Desktop and Scale?

Conduktor Scale is a centralized deployment that eliminates individual license provisioning, provides automatic updates, SSO integration, and user group management—making it easier to scale across an organization.

How does Conduktor improve Kafka onboarding?

Conduktor simplifies user management and provisioning, enabling testers, analysts, and developers to efficiently access and validate Kafka data without extensive technical knowledge.