I joined Checkly a few months ago, and because our platform enables you to use Microsoft’s Playwright to run your synthetic monitoring, I started getting my hands dirty with the end-to-end testing framework. I’m a massive fan of learning in public, so I started publishing weekly Playwright tips on YouTube. Did you miss a few videos? Don’t sweat it! Here’s the first collection of Playwright tricks I discovered over the last few months.

Not in a reading mood? You also can watch the talk I gave at DjangoCon 2022. One of Sentries core company values is “for every developer”. We want to support every developer out there with our tools. But not every developer uses the newest or widely adopted tech stack, so we also try to support older versions of libraries and frameworks.

Part two of a three-part guide to assuring performance and availability of critical cloud services across public and hybrid clouds and the internet Monitoring your user traffic is critical for knowing the quality of the digital experience you are delivering, but what about the performance of new cloud or container deployments, expected new users in a new region, or new web pages or applications that don’t have established traffic? This is where synthetic testing can be invaluable.

Properly testing a service’s APIs to ensure that it can handle production traffic presents many challenges for engineers—SREs need to guarantee the resiliency of their application, while developers must ensure that their features perform well at any given scale. Speedscale is a testing framework built for Kubernetes applications that enables you to load test with real-world production scenarios by replaying actual API traffic that your application has experienced.

Testing is commonly understood to be an essential and fundamental part of software development, but when and how to test is open to a wider variety of opinions. DevOps practitioners often advocate for performance and quality testing early in the development and deployment process. This is known as a “shift left” approach.

How can you tell if your systems are reliable when under load? A common answer is to open your observability dashboards, wait for a high-traffic event (like Black Friday), and cross your fingers. While this approach is certainly effective, it's far from ideal. Without proactive reliability and load testing, we have no idea if a system will hold up to real-world usage patterns, which could mean a production outage at the worst possible time.

Load testing is one of the most common ways to test the resiliency of your applications. In this blog we show how recording production data with Speedscale and exporting to a K6 load tests gives you the best of both worlds. Whether or not it’s important for your organization, there are clear benefits to be had from implementing these types of tests. By doing so, you can: When it comes to load testing, two of the most modern tools are Speedscale and K6.

At ObservabilityCON, we announced our first step towards launching a native integration between Grafana k6 load testing and Grafana Tempo tracing (k6 x Tempo) in Grafana Cloud. We created k6 x Tempo to help dev, testing, and operation teams analyze their performance test results more effectively and proactively improve the reliability of their business-critical applications.