MediaKind Achieves 80% Log Optimization
Last year, MediaKind was set to onboard new customers which would cause a 6x growth in log data volume. Before onboarding these customers, MediaKind adopted Edge Delta to optimize log volumes. Doing so helped MediaKind reduce Elastic Cloud log ingest by 80% – all without impacting data visibility. Read on to learn how.
Overview of MediaKind
MediaKind is an Emmy Award-winning media technology company. It provides quality live broadcasts and streaming capabilities to some of the world's biggest media and entertainment companies, such as AT&T, Comcast, and more.
Throughout its success, MediaKind has maintained its commitment to technology innovation. MediaKind’s SRE Architect, Richard Chin explains, "As a relatively young player in this market, we have ample freedom to propose and enhance various aspects of our technology stacks.” He continues, “The management team is highly committed to continuous improvement, prioritizing efficient system operations, and placing a strong emphasis on DevOps."
The Challenge: New Customers Drove Huge Log Data Growth
MediaKind uses Elastic Cloud, which has helped the company effectively monitor their core applications. However, when log volumes spike, the platform becomes noisy and costs rise dramatically. This was already an issue, considering MediaKind supports broadcasts watched by millions of people worldwide. But, the issue came to a head when the company anticipated a dramatic rise in log volumes as they engaged new customers.
With its new customers, MediaKind would grow from 100 channels to over 1,000. They forecasted their logging volumes to jump from about 500GB per day to over 3TB per day. These large log volumes would be difficult for MediaKind to monitor without dropping data or spending an unreasonable amount on observability tools. So, Chin and his team began evaluating solutions to help them control log data growth. Specifically, they considered tools that helped them process data upstream – not only after it was ingested into Elastic Cloud.
As Chin explains, “There’s a lot more possibility with observability today. And there are powerful tools available now, like Edge Delta – to analyze logs and get insights upstream.”
How Edge Delta Optimizes Log Data Volumes
Chin and his team turned to Edge Delta to help them analyze data as it’s created at the source, and control what is ingested into Elastic Cloud. Specifically, MediaKind uses Edge Delta to extract metrics from log data upstream and cluster repetitive loglines.
These aspects were game changers for MediaKind because they were able to optimize their log data by over 80%. In addition, they were able to reduce the noisiness of the datasets for their developers. “The main motivation behind our decision was the significant log optimization rate. The combined capabilities of Edge Delta made it a powerful solution,” Chin notes.
Moreover, Edge Delta offers a complete solution for Chin and his team. "Having everything conveniently bundled into one package was particularly appealing," says Chin.
In addition to the above benefits, MediaKind has enjoyed collaborating with Edge Delta. “Working with Edge Delta has been really great – the team is very responsive,” Chin notes.
Edge Delta has proven to be a valuable solution to help MediaKind control their observability costs. By adopting Edge Delta, MediaKind has been able to deliver a quality user experience as it scaled and optimized log volumes by over 80%.