# How LinkedIn Stopped Relying on Users to Report Bugs

> Discover how LinkedIn improved infrastructure monitoring with Checkly, preventing bugs from reaching users and enhancing service reliability.

Source: https://www.checklyhq.com/blog/linkedin-case-study/

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# How LinkedIn Stopped Relying on Users to Report Bugs

[Nočnica Mellifera](https://www.checklyhq.com/blog/author/nica-mellifera/)

December 31, 2024 · Updated January 14, 2025

When making changes to your production services, it’s important to have a plan for how to detect problems and roll back changes. How many roll out plans would include: “if it breaks, don’t worry, the users will tell us!” But if your monitoring coverage of production services isn’t complete, you’re implicitly relying on your users to tell you when something breaks.

## How LinkedIn improved their infrastructure monitoring with Checkly

We recently published a [case study with the LinkedIn team about how Checkly helped LinkedIn find problems before their users do](https://www.checklyhq.com/case-study/modernizing-linkedins-monitoring-infrastructure/). LinkedIn a global leader in professional networking, faced challenges managing its complex, custom-built infrastructure, which includes legacy systems and technologies like Espresso, Venice, and Kafka. The company’s internal synthetic monitoring system struggled with limited visibility and delayed issue detection, resulting in prolonged Mean Time to Detect (MTTD). These limitations often led to service disruptions that were only identified through user-reported issues or delayed product experience metrics. Additionally, transitioning site reliability engineering (SRE) teams into software engineering roles created gaps in test ownership, further complicating the management of LinkedIn’s end-to-end monitoring processes.

To address these challenges, LinkedIn partnered with Checkly, adopting its Monitoring as Code (MaC) solution to modernize and enhance reliability. Checkly enabled LinkedIn to automate TLS monitoring, implement dynamic API checks, and integrate Playwright-based tests into its CI/CD pipeline. By running proactive end-to-end tests every 15 minutes, LinkedIn significantly reduced MTTD and empowered its engineers to take ownership of monitoring. The integration provided real-time visibility into user experience, reduced costs through efficient testing processes, and ensured critical user flows were protected during deployments. This collaboration has not only improved system stability but also supports LinkedIn’s long-term goals of infrastructure modernization and engineering empowerment.

### Read the whole story

[Check out our complete LinkedIn case study on our site](https://www.checklyhq.com/case-study/modernizing-linkedins-monitoring-infrastructure/). If you’d like to learn how Checkly can help transform your production monitoring, [book a demo with us today](https://calendly.com/d/5gk-49g-f76/checkly-demo).

[Nočnica Mellifera Developer Advocate Nočnica Mellifera (She/Her) was a developer for seven years before moving into developer relations. She specializes in containerized workloads, serverless, and public cloud engineering. Nočnica has long been an advocate for open standards, and has given talks and workshops on OpenTelemetry and Kubernetes architecture. She enjoys making music that friends have described as "unlistenable." In her spare time she cares for her two children and hundreds of houseplants.](https://www.checklyhq.com/blog/author/nica-mellifera/)

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