Tunecore is a New York-based independent music distribution and publishing service with over 250,000 artists on its roster, generating over $2 Billion in revenue for it's artists, and more than 200 billion streams and downloads.
Following Believe Music's (AKA Believe Digital) acquisition of Tunecore, we were involved in making progressive changes and planning Tunecore’s cutover into Believe’s expansive digital music distribution system.
Tunecore and Believe together have a formidable digital supply chain that covers Apple Music, Spotify, Tidal, Amazon Music, Youtube Music, Pandora, Tiktok and over 150 other digital partners.
Our brief was challenging, and involved:
Distribution systems have rapidly evolved with the music industry, and the digital revolution has replaced traditional systems (from the CD era) with digital stakeholders and platforms to bridge the gap between creators and their audiences.
Digital music distribution is incredibly competitive, and optimizing the timeline between mastering and distribution is crucial.
Sample this - over 14.6 million tracks are uploaded to Spotify every year (that’s 40,000 songs in a day) - and most of these uploads are processed through independent music distribution platforms like Tunecore.
Tunecore helps hundreds of thousands of independent artists send their digital assets to diverse digital partners, and publishes their catalog across marketplaces, stores and streaming services online.
But this is where it gets complex.
Digital ingestion systems aren’t standardized across retailers, making it essential for XML or DDEX delivery specifications and the transcoding processes to be precise. And when two of the biggest players, Believe and Tunecore, bring their catalogs and systems together - accuracy is everything.
Our primary challenge was with a backfill process that we had to initiate.
Tunecore had to transfer a backlog of 8 million songs to Believe’s backend, and their catalog albums and tracks had unique identifiers that had to be streamlined and standardized to the requirements of the new system.
In our roadmap for accelerating the transcoding process, we anticipated issues with metadata variances between digital retailers.
The ingestion systems across retailers, marketplaces and services have unique delivery specifications, and this was a challenge we had to take into account while planning our transcoding pipeline.
Our research was extensively focused on studying the current systems used by Tunecore and Believe, in order to explore alternatives that could help improve cost efficiencies and allow the system to scale seamlessly.
We also had to study existing and new metadata standards like XML and DDEX to streamline the product and release data, and make the files easy to access, catalog and transfer.
Since accelerated transcoding was a key component, we explored prepackaged transcoding services like AWS Lambda and Elastic Transcoder.
Our recommendations included AWS Lambda for on-demand transcoding and AWS SQS for queue processing to handle high volume transfers.
To future-proof the system, we also recommended AWS Cloudwatch for monitoring pipelines and scaling, so that it could handle loads of upto 500,000 MAU.
With an eye on performance improvement and complete modernization, our team set to work.
To modernize and drive faster iterations on the overall infrastructure and database design, we extracted and refactored the distribution system from the current application to its own microservice.
Digital music distribution is a rapidly growing space, with increasing YoY growth and escalating demand. We adopted AWS services into the current system to enable on-demand scaling through its supported services/features.
As part of our progressive changes, we also extracted transcoding into its own service. After evaluating AWS elastic transcoding, we settled on using AWS Lambda, which masters WAV files to FLAC using FFmpeg and extracts metadata from audio files through MediaInfo.
Over the project lifecycle, we’ve also driven better observability and improved test coverage from as low as 30% to 80%.
True to our vision, our extractions and implementation drastically reduced the transcoding time and paved the way for optimized, better performance.
We were significantly able to minimize the timeline for transcoding and distribution, helping Believe, Tunecore and their thousands of artists deliver music to their audiences at scale.