Eight Sleep Achieves End-to-End Observability With Datadog | Datadog
Case study

Eight Sleep achieves end-to-end observability with Datadog

Electronics

125 Employees

New York City

会社情報 Eight Sleep

Eight Sleep is a sleep fitness company that developed a proprietary technology that uses AI and machine learning models to track bio signals and optimize body recovery and rest through temperature control.

“There is huge value in having that single pane of glass to look at various metrics and determine how key user interactions are performing. It helps us move toward 99.9% reliability.”

case-studies/bob_kinney
Bob Kinney
Senior Software Development Engineer
Eight Sleep
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“There is huge value in having that single pane of glass to look at various metrics and determine how key user interactions are performing. It helps us move toward 99.9% reliability.”

Bob Kinney
Senior Software Development Engineer
Eight Sleep
なぜDatadogなのか?
  • Easily integrates into Eight Sleep’s existing platform
  • Single pane of glass improves observability
  • Dashboards enable easy visibility into latency or regressions from code changes
  • Improves application reliability
Challenge

Eight Sleep was looking for a strong observability solution. The company also wanted to better understand how users were experiencing its app and prevent any issues before they occurred.

主な成果
Reliable user experience

Single pane of glass dashboard helps move toward 99.9% reliability

Laser-focused troubleshooting

Small IT team can better prioritize

Quick mean time to resolution (MTTR)

From ~half hour to minutes

Lack of visibility drives need for improved observability

Eight Sleep is on a mission to optimize sleep. The company makes a pod that uses sensors to track and improve sleep by dynamically adjusting mattress temperatures based on a user’s sleep stages. The sensors also record key health metrics for each user. Customers use a paired app to view sleep and health metrics, adjust temperatures, get insights, and more. Data collected from sensors is streamed to the company’s AWS cloud-hosted platform.

When senior software development engineer Bob Kinney joined the company, Eight Sleep lacked robust observability tools. Kinney was tasked with finding an alternate observability solution. He also wanted to better understand how users experienced the company’s app and prevent any issues before they occurred. At the time, Eight Sleep used a solution that performed uptime testing for a few public endpoints, but it was too basic and lacked configurability. Engineers often got paged in the middle of the night for what ultimately proved to be false alarms.

With a small development team, Eight Sleep needed a tool that could help it accomplish tasks quickly and easily. “Our competitors in this space have three to four times as many engineers as we do,” says Kinney. “To ship the value that we do to customers with this team size, we needed a tool that could do the job it said it could do with minimum work required on our side.”

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Enabling better app-level visibility

Kinney and his team first adopted Datadog Application Performance Monitoring (APM) to improve observability across the Eight Sleep application. APM gave the company improved visibility into how the application was performing. The Eight Sleep development team could also build dashboards to visualize telemetry from applications, which gave them easy visibility into latency or regressions from code changes. “Datadog won me over with the ease of use and how quickly I was able to get observability,” says Kinney.

Kinney and his team then onboarded Datadog Synthetic Monitoring to observe how its systems and applications were performing for end users using simulated requests and actions. Using Datadog Synthetic Monitoring enabled Kinney’s team to compose multi-step API synthetic tests that replicated user journeys, which gave them confidence they would be notified when something broke.

Kinney says Datadog’s ability to integrate into Eight Sleep’s existing platform and consolidate all monitors in one place is a huge benefit to his team. “We've moved all service logging to Datadog and enabled APM tracing for all services. There is huge value in having that single pane of glass to look at various metrics and determine how key user interactions are performing. It helps us move toward 99.9 percent reliability on our alarm dismissal and temperature controls; two fundamental user interactions customers rely on. Plus, having something we could quickly get up and running and start seeing value from right away was huge.”

Eight Sleep also recently added Datadog Real User Monitoring (RUM) to enable end-to-end visibility into user journeys, which enables his small development team to deliver new platform features and functionality faster.

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“If Datadog didn’t offer these tools and features, my team would have to build them. Datadog gives us the freedom to focus on the things that actually add value for our customers.”

Improving reliability for a growing customer base

Eight Sleep’s use of Datadog solutions helps it identify the root cause of issues and troubleshoot faster. As a result, MTTR has gone from about a half hour to just minutes. Eight Sleep’s development team is also confident their remediation steps will work. “Being able to push a fix is like night and day compared to where we were when I first joined,” says Kinney. “Before, there was a lot of guessing. Now we can clearly point to a root cause before we take action.”

Meanwhile, Datadog frees Eight Sleep’s small development team to focus on value-added tasks. “If Datadog didn’t offer these tools and features, my team would have to build them. Datadog gives us the freedom to focus on the things that actually add value for our customers,” says Kinney. “We can iterate quickly while validating that we haven’t broken functionality.”

Ultimately, Datadog's solutions allow Eight Sleep to better support its rapidly growing customer base and improve reliability. “It's about ensuring our backend is online and available 24/7 to interact with our customers’ devices successfully,” says Kinney. “Datadog just works; it does what it says it will do, and it gets out of our way. For a team our size, that's exactly what we needed.”

リソース

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