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Storyblocks Partners with Confluent to Redesign Its Data Pipeline and Slash Technical Debt

Confluent is definitely the central pillar of our data infrastructure. All data collection that isn’t an application database is going on our central pipeline through Confluent.

Charles DeVeas | Director of Engineering
Storyblocks

Challenge

Create an event bus to improve data collection, event-driven communication between microservices, and data discovery for new use cases.

Solution

Confluent Cloud creates a seamless flow of data across systems and empower developers to take full advantage of streaming event-based data.

Results

  • Reduced technical debt and TCO from REST APIs and modernized a monolithic application
  • Consolidated search for audio and visual files
  • Support of rebranding effort
  • Vastly improved data visibility, collection, and communication for data scientists and developers
storyblocks-featured

Ranked the fourth-fastest growing media company in the U.S. by Inc. Magazine, Storyblocks was born out of a desire to solve the problem of a lack of accessible, affordable stock for creatives. It’s the first unlimited download subscription-based provider of stock video and audio, claiming over 100,000 customers in the television and video production industry, including NBC and MTV, plus tens of thousands of hobbyists looking to enhance their video projects and productions. Storyblocks’ subscribers can download an unlimited number of clips from a vast and rapidly growing library of stock video, production music, motion backgrounds, sound effects, special effects, and more.

As the company transitioned from scrappy disruptor to major industry player, it began to experience issues with a monolithic application they had built when the company was started. They also experienced other issues later with synchronous REST API calls between services, after they had split the monolith into microservices. Namely, developers and data engineers couldn’t resolve issues fast enough or iterate on their search functionality with sufficient agility, and were taking on a significant amount of technical debt as an increasing amount of data threatened to slow down the productivity and time to market for new features.

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