Case Study
TuneIn lowers cloud costs and increases visibility into cloud spending with Flexera
At a glance
Industry: Media
Location: San Francisco, CA
Employees: Less than 500
Products: Flexera Ocean, Flexera One Cloud Commitment Management
Featured results
- More 25% than savings of the entire AWS bill. TuneIn uses Flexera Ocean to leverage spot instances and Flexera One Cloud Commitment Management to manage RI’s for workloads running on Kubernetes.
- Using Flexera Ocean and Flexera One Cloud Commitment Management to leverage spot and reserved instances for maximum cost savings
- High availability for mixed instance types
- Kubernetes cost allocation and showback helps make business decisions
Introduction
TuneIn, the leading live streaming and on-demand audio service, brings together live sports, news, music, podcasts and radio from around the globe. With 75 million monthly active users, TuneIn is one of the most widely used streaming audio platforms in the world. TuneIn broadcasts over 100,000 owned & operated and partner radio stations and boasts more than 5.7 million podcasts. With premiere distribution across 200 platforms and connected devices, TuneIn empowers listeners to ‘hear’ what they love wherever ‘here’ might be. TuneIn Premium subscribers also unlock exclusive access to commercial-free news from top networks like CNBC, CNN, FOX News Radio and MSNBC, as well as commercial-free music channels for every mood and activity.
The challenge
TuneIn is an audio streaming service that delivers live news, radio, sports, music and podcasts to more than 75 million active monthly users. After experiencing some outages in their data centers several years ago, TuneIn’s engineering leadership decided to migrate their applications and services to the AWS cloud to stop managing their own physical infrastructure.
After the migration, the cost of cloud operations was higher than prior hosting costs and drawing the finance team’s attention, who wanted to reduce the bills for Kubernetes and cloud infrastructure-related services. Although they were hoping to save on costs with AWS Reserved Instances, it was not a reliable option—siloed teams were running their own EC2, Autoscaling Groups (ASGs), ECS and Kubernetes/EKS stacks with little consistency in instance families and types across workloads made it difficult to commit to reserved capacity.
Engineering teams also needed more visibility into spending data as they were moving more applications to Kubernetes. But the task of calculating these metrics took significant time and effort, and with no dedicated FinOps team to track it, costs were quickly growing.
The solution
Flexera offered TuneIn a solution for FinOps that would give them the savings they were looking for by using spot instances, the reliability they needed with an enterprise-grade SLA and in-depth visibility into the cost of workloads running in their Kubernetes clusters.
“We were never willing to use spot instances,” said Ryan White, Senior Director of Engineering Operations at TuneIn. The inherent volatility of spot instances makes them risky, but TuneIn trusted Flexera to run their Kubernetes workloads on spot instances after a successful trial of Ocean* and coordination with developers to adjust their workloads to make them more resilient to the nature of spot disruptions. With Flexera, TuneIn saw immediate benefits in cost savings, cost analysis capabilities and high availability for their applications.
“We don’t even have to think about provisioning cloud infrastructure, Spot* just handles it all for us. The beauty of Spot is that we just set it and forget it”
The result
Using Flexera Ocean and Flexera One Cloud Commitment Management to leverage spot and reserved instances for maximum cost savings
Running spot instances is inherently cheaper—up to 90% in some cases—but they come with the risk that the cloud provider can take back the spot instances applications are running on if they’re needed elsewhere.
With millions of users streaming TuneIn content, using their website and apps, and sending requests for content from hundreds of types of devices like Alexa and Google Home, losing service was not an option. Instead of hiring someone to analyze their AWS usage, manage instances and ensure availability, TuneIn uses Ocean to leverage spot instances and Cloud Commitment Management to manage reserved instances (RIs) for workloads running on Kubernetes. TuneIn is able to save more than 25% of their entire AWS bill (including storage, networking, etc.) while also mitigating the risk of service disruption by utilizing spot capacity across a range of instance families and sizes.
The savings don’t stop there. Cloud Commitment Management provided TuneIn with savings of over 40% on RIs. Additionally, the product’s flexibility allows TuneIn to maximize savings while avoiding long–term commitment lock-in. In one instance, TuneIn needed to temporarily increase capacity to support a testing project. Cloud Commitment Management cost-effectively increased TuneIn’s RIs by more than 340% over 11 days. Then, two weeks later when testing was complete, it reduced their total RIs by an equivalent amount in only three days.
“We don’t even have to think about provisioning cloud infrastructure, Spot* just handles it all for us. The beauty of Spot is that we just set it and forget it,” said White.
High availability for mixed instance types
For TuneIn, highly available systems are critical to maintaining quality customer experiences. In addition to Ocean’s predictive capabilities that anticipate disruptions to the spot market, TuneIn can also leverage Ocean’s unique ability to use different instance types spot instances. By leveraging Kubernetes affinity and anti-affinity rules, which can be applied by node, availability zone, and even instance type/size, TuneIn is able to strategically declare rules for instance types to keep infrastructure from going dark when there is an outage or disruption in the spare capacity market.
Kubernetes cost allocation and showback helps make business decisions
As their footprint in the cloud grew, so did TuneIn’s cloud bill, especially after they built their in-house real-time transcoding service, which converts upstream feeds (i.e., from radio stations, podcasts, live sporting events etc.) into the right audio format. This application, running at scale on top of Kubernetes, is critical to the business, ensuring that TuneIn’s streams could be hosted in-house and highly available.
The teams managing TuneIn’s API’s and streaming services needed to know how much they were spending per application/service and stream, along with other deployments, to understand profit and loss margins. Using Ocean, they’ve seen how much they are spending per Kubernetes namespace, deployment and even pod, and can easily calculate the cost per stream. This granular visibility into spending data isn’t possible by looking at only an AWS bill, and any estimate based on just that would have been an educated guess at best.
“Being able to pull out the cost data from the Ocean UI to determine how much we’re spending by service and by stream has been hugely beneficial to multiple teams,” said White.
Next steps