Case Study
TuneIn cuts AWS costs by 25% while gaining Kubernetes visibility
Using Ocean and Cloud Commitment Management, TuneIn leveraged Spot instances and RIs to save money on K8s workloads.
At a glance
Industry: Media
Location: San Francisco, CA
Employees: Less than 500
Products: Flexera Ocean, Flexera Cloud Commitment Management
Featured results
- 25% savings on AWS bill using Spot instances with Ocean
- 40% savings with Reserved Instances using Cloud Commitment Management
- Unit cost visibility for key product offer
- High availability for mixed instance types ensures positive customer experience
- K8s cost allocation helps to drive accountability for costs
about TuneIn
TuneIn is an audio streaming service that delivers live sports, news, music, podcasts, and radio around the globe. With 75 million monthly active users, TuneIn is one of the most widely used streaming audio platforms in the world
The challenge
After experiencing some outages in their data centers, TuneIn’s engineering leadership decided to migrate their applications and services to Amazon Web Services (AWS) and stop managing their own physical infrastructure.
As their footprint in the cloud grew, so did TuneIn’s cloud bill – particularly after they built their real-time transcoding service, which converts feeds 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.
After the migration, the cost of cloud operations was higher than prior on-premises hosting costs and was drawing the finance team’s attention. Although they were hoping to save on costs with AWS Reserved Instances (RIs), siloed teams were running their own Amazon EC2 instances / Autoscaling Groups (ASGs), and Amazon ECS (Elastic Container Service) / Amazon EKS (Elastic Kubernetes Service) stacks with little consistency in instance families and types across workloads. This made it difficult to commit to reserved capacity.
Engineering teams also needed more visibility into costs as they were migrating applications to Kubernetes. Calculating costs took significant time and effort, and with no dedicated FinOps team to track govern, costs were quickly growing.
The solutions
Flexera offered TuneIn a solution that would give them the savings and reliability with an enterprise-grade SLA and in-depth visibility into the cost of workloads running in Kubernetes clusters: Flexera Ocean.
“We were never willing to use (Amazon EC2) Spot instances,” said Ryan White, Senior Director of Engineering Operations at TuneIn. Running Spot instances is cheaper—up to 90% in some cases—but their usage comes with the fact that AWS can take back the instance at any time if its compute power is 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.
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 with Flexera Ocean.
Flexera also offered another solution to help TuneIn take advantage of additional savings from cloud commitment discounts and manage their complex fleet of RIs: Flexera Cloud Commitment Management. The product’s flexibility allows TuneIn to maximize savings while avoiding long-term commitment lock-in.
The results
Instead of hiring someone to analyze their AWS usage, manage instances, and ensure availability, TuneIn uses Flexera Ocean to safely leverage Spot instances and they use Flexera Cloud Commitment Management to manage Reserved Instances (RIs) for workloads running on Kubernetes.
High availability and savings with Spot
Ocean’s predictive capabilities anticipate Spot interruptions and replace instances without disruption. TuneIn also leverages Ocean’s unique ability to use different types of Spot instances. By using Kubernetes affinity and anti-affinity rules, which can be applied by node, availability zone, and even instance type/size, users can strategically declare rules for instance types to keep infrastructure from going dark when there is an outage or disruption in the spare capacity market.
“We don’t even have to think about provisioning cloud infrastructure; Ocean just handles it all for us. The beauty of Ocean is that we just set it and forget it.”
With Flexera Ocean, TuneIn saved more than 25% on their AWS bill (including storage, networking, etc.) while also effectively eliminating the risk of Spot service disruption by utilizing Spot capacity across a range of instance families and sizes.
Unit cost visibility
The teams managing TuneIn’s APIs and streaming services needed to know how much they were spending per application/service and stream, to understand profit and loss margins. Using Ocean, TuneIn can now see how much they are spending per Kubernetes Namespace, deployment, and even pod, and can easily calculate the unit cost per stream. This granular, workload-level visibility into usage and cost isn’t available on the AWS bill.
“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.
Reserved Instances coverage for testing
The savings don’t stop there. Flexera Cloud Commitment Management delivered TuneIn savings of over 40% with RIs. 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 eleven days. Then, two weeks later when testing was complete, it reduced their total RIs by an equivalent amount in only three days.
Closing
For TuneIn, highly available systems are critical to maintaining quality customer experiences. With Flexera, TuneIn saw immediate benefits in cost savings and cost analysis capabilities – all with high availability for their applications.
Next steps
Understand what your Kubernetes workloads really cost—and where you can save with Flexera Ocean
Additional Cases