April 2026 Summaries

The integration of Checkly's new extended checks and CLI commands with Rocky AI's root cause analysis (RCA) allows coding agents to seamlessly identify and fix issues in the same session without human intervention. Previously, two separate AI agents—one monitoring production from the outside and another handling application code from the inside—could not communicate directly, necessitating human involvement to relay information. Now, Rocky AI's analysis is directly accessible to coding agents, enabling them to pull in diagnostics and suggested fixes, thus optimizing incident resolution and reducing the time spent on manual triage. This enhancement facilitates a streamlined, automated workflow where agents quickly address alerts by leveraging Rocky AI's comprehensive analysis, which includes failed checks, error messages, and user-impact assessments. The new functionality also extends to Checkly's public API, offering endpoints to retrieve and generate RCAs for error groups, thereby enabling a more efficient, automated process from alert detection to problem-solving and code updates.

Vince Graics, a Staff QA Engineer at World of Books, discusses the challenges and solutions related to synthetic monitoring of Shopify storefronts due to Shopify's bot detection mechanisms. He explains that Shopify's system can misidentify headless browsers as threats, leading to issues such as rate limits and Cloudflare challenges, which hinder monitoring efforts. To address these, Graics suggests using Shopify's bot protection headers, which involve registering a crawler in the Shopify admin to receive specific HTTP signature headers that allow monitoring requests to bypass bot protection. He also discusses handling consent pop-ups using Playwright's page.addLocatorHandler() and testing the checkout process with Shopify Flow to automate refunds for test transactions, thus ensuring the monitoring setup is robust and reflects the real user experience. Graics emphasizes the importance of maintaining up-to-date credentials and environment configurations within Checkly, using Playwright fixtures for header injection and consent handling, and deploying through a CI/CD pipeline to achieve effective Monitoring as Code.

The Checkly Playwright Reporter is an npm package designed to enhance the functionality of Playwright by sending test results to Checkly as cloud test sessions, providing a centralized and shareable platform for analysis with AI-powered insights and enhanced debugging tools like trace-derived views and system performance graphs. Unlike other solutions that primarily offer hosting, this reporter offers deeper understanding by organizing every request, response, and console output into filterable views, and supports features like automatic secret scrubbing and git metadata integration. It is available at no extra cost on all Checkly plans and can be easily integrated into existing Playwright setups by installing the package and configuring it in `playwright.config.ts`. The reporter does not replace Playwright or automatically convert tests into production monitors but facilitates the process of taking important tests into production monitoring through Checkly's Playwright monitoring workflow. Teams benefit from a persistent repository of test results, which aids in understanding recurring failures and optimizing test management both locally and in CI environments.