In today’s 24/7 world, downtime is costly. Very costly. Every minute of downtime can equate to anything from thousands to millions of dollars in revenue losses for businesses and often irrevocable damage to brand reputation. Back in 2021, Amazon’s 13 minutes of downtime cost the organization an estimated $2,646,501. In the same year, an outage that lasted hours on Facebook, Instagram, and WhatsApp cost Meta an estimated $100M. According to New Relic’s 2023 Observability Forecast, the median annual cost of an outage has now reached an estimated $7.75 million.

Quickly detecting and resolving issues is business-critical when it comes to preventing expensive downtime and meeting customers’ ever-increasing expectations. If your customers spot outages, you have a problem. Yet only a fraction of engineers have access to the full observability and monitoring tools needed to maintain system reliability and performance. Many of the legacy tools used run in silos, managed separately from the app or API’s code and fail to provide development teams with the insight, speed, scale, and accuracy needed. Consequently, 82% of businesses take more than an hour on average to address faults.

Recognizing this problem, Hannes Lenke, Timo Euteneuer, and Tim Nolet set out on their mission to enable engineers to detect and resolve issues 10x faster and in 2020 Checkly was born. Long believing that code itself must drive and configure monitoring and observability, the team built a new paradigm in Monitoring as Code (MaC). MaC enables development organizations to configure, understand, and own the monitoring of their production services – all from within their own repositories.

By integrating advanced, proactive and purpose-built synthetic monitoring tools inside code repositories, Checkly ensures monitoring is always in sync with the latest code changes. Engineers can simulate user interactions continuously in more than 20 locations worldwide using automated Playwright scripts, and get automatic, real-time, accurate alerts alongside detailed insights that help them turn alerts into action. This not only makes it easier for developers to track and manage everything in one place, but it helps catch issues early, without the usual delays and false positives seen with legacy tools. All while empowering the DevOps team to understand and own the monitoring of their services.

We first met the Checkly team via the open-source community just after the company’s founding. It was clear from the onset that Hannes, Timo, and Tim had a deep understanding of the software development lifecycle. In addition, they all had proven experience as repeat founders in the web monitoring and observability space. Moreover, Checkly’s early customers were already seeing the potential of the code-first synthetic monitoring platform. When I spoke to the team at Humio, then one of our portfolio companies (now part of CrowdStrike) and an early adopter of Checkly, they raved about the product and how it was part of the emerging MaC paradigm. The opportunity ahead was clear and Accel led the company’s $2.25M seed round in April 2020. Given the number of observability and developer-first companies already in our portfolio, such as Humio, Instana, Sentry, Snyk – Checkly was a natural fit for the Accel family.

Fast forward to today and Checkly is announcing its $20M Series B led by our friends at Balderton and unveiling Checkly Traces. The company now has more than 1,000 paying customers, including 1Password, Airbus, Autodesk, AutoTrader, commercetools, CrowdStrike, Deno, Render, Sentry, and Vercel.

Every day, thousands of developers run 30M+ checks on Checkly’s platform and the platform has seen 3x growth among enterprise customers. In addition, MaC is now part of two Gartner Hype Cycles, and Checkly has been named a Cool Vendor – all validating the team’s approach.

But the company is just getting started. Having shifted Synthetics left, the team is now expanding and shifting Observability left with Checkly Traces, which will enable engineers to resolve issues even faster by connecting synthetics with tracing. This will provide engineers with immediate insight into failures and ensure there’s no longer a need for manual data correlation.

Thank you, Hannes and the Checkly team, for choosing us to partner with you on this journey. You’ve achieved so much in such a short time and we’re looking forward to seeing what’s ahead!