Sonos reduces operational overhead by 90% using Amazon OpenSearch Service

As Sonos expanded its product catalog, data volumes from connected devices and user interactions grew. Even moderate spikes in data traffic could cause failures or even data loss, making it harder to analyze performance and to iterate quickly. Engineering teams would spend time manually tuning clusters and managing shards instead of building new features.

To keep pace, the company set out to modernize its telemetry infrastructure—used to monitor, debug, and enhance product performance—to better support innovation at scale.

Additionally, limited access to business intelligence tools meant teams had to rely on a small group of analysts to get the insights they needed. This slowed down decision-making and created bottlenecks across departments. Sonos needed a more reliable, scalable, and user-friendly data solution—one that would empower teams across the company to access and act on insights independently.

With most of its data pipelines already on AWS, Sonos migrated to Amazon OpenSearch Service, an AWS-managed service that lets developers run and scale OpenSearch clusters without having to worry about managing, monitoring, and maintaining infrastructure. This migration streamlined how Sonos stores, searches, and scales its telemetry data. As part of this transition, the company implemented automated index life cycle management with intelligent rollover policies, thereby removing manual intervention for index management and shard tuning. As a result, Sonos improved system reliability and freed up engineering teams to focus on innovation rather than infrastructure.

Sonos engineers built a flexible data collection framework that prioritized alpha beta product data—essential for fast, iterative development—while still maintaining access to valuable production logs. To manage costs efficiently, they used the tiered storage system in Amazon OpenSearch Service, keeping long-term data accessible without relying on high-cost storage solutions.

Setting up Amazon CloudWatch, which is used to observe and monitor resources and applications, let teams create dashboards and alerts. As a result, these teams gained greater visibility into system performance. This helped to deliver faster, data-driven decisions and to be more proactive in monitoring.

Additionally, Sonos adopted AWS Lambda, a service used to run code without thinking about servers or clusters, and Amazon OpenSearch Ingestion, a feature of Amazon OpenSearch Service that lets users ingest, filter, transform, enrich, and route data to an Amazon OpenSearch domain or Serverless collection. Using these services, Sonos automated data processing workflows and streamlined the ingestion of telemetry data into OpenSearch clusters.

By fully embracing the AWS environment, Sonos streamlined operations, improved performance, and created a scalable foundation to support future innovation and product growth. The company drastically reduced infrastructure costs and reduced operational overhead by 90 percent. Since migrating to the new solution, the telemetry system has also maintained zero outages to date, boosting developer confidence and accelerating innovation cycles.

By leaning into the migration and modernization expertise of AWS, Sonos confidently transitioned to a scalable, fully managed environment, unlocking faster insights, lowering costs, and increasing agility. With the new purpose-built solution, Sonos accelerated innovation while reducing operational risk.

Today, teams across the organization—from product analysts to engineers—can access the data they need without reaching out for specialized support. The fully managed Amazon OpenSearch Service has removed the burden of manual cluster management, freeing up teams to focus on delivering better sound experiences, faster. As Sonos continues to grow, its AWS-powered infrastructure provides the scalability and efficiency needed to meet rising demand while keeping operational costs in check.