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Experiment: trailing-slash canonical on 20 top docs pages
Add an explicit per-page `canonical:` (full www + /docs + trailing-slash URL, matching the served/indexed URL) to the 20 highest-keyword-coverage docs pages. The rest of the site keeps the auto-generated no-slash canonical as the control group. Goal: over ~3 weeks, see whether byte-exact trailing-slash canonicals change how Google canonicalizes/indexes these pages vs. the no-slash canonical (which 308s to the served slash URL). Evaluate ~2026-07-27. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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comparisons/frameworks/playwright-vs-cypress.mdx

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sidebarTitle: Playwright vs Cypress
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learn_playwright:
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parent: "Getting started"
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canonical: 'https://www.checklyhq.com/docs/comparisons/frameworks/playwright-vs-cypress/'
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---
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Playwright and Cypress are two frameworks both closely associated with end-to-end testing of production websites. Both frameworks can do quite a bit more than 'making sure nothing on your site is broken' and their design philosophies, architectures, and use cases are different.
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detect/synthetic-monitoring/api-checks/overview.mdx

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title: 'API Checks Overview'
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description: 'Monitor API endpoints with comprehensive HTTP request validation, performance testing, and detailed response analysis.'
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sidebarTitle: 'Overview'
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canonical: 'https://www.checklyhq.com/docs/detect/synthetic-monitoring/api-checks/overview/'
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<Tip>
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**Monitoring as Code**: Learn more about the [API Check Construct](/constructs/api-check).

detect/uptime-monitoring/tcp-monitors/overview.mdx

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title: 'TCP Monitors Overview'
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description: 'Monitor the availability and performance of your TCP services.'
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sidebarTitle: Overview
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canonical: 'https://www.checklyhq.com/docs/detect/uptime-monitoring/tcp-monitors/overview/'
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<Tip>

guides/auto-waiting-methods.mdx

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Playwright's auto-waiting is a great feature to avoid test flakiness, but in some situations it doesn't work as expected, what are the alternatives?
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tags:
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- FAQ
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canonical: 'https://www.checklyhq.com/docs/guides/auto-waiting-methods/'
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import PlaywrightCheckSuiteTryOut from "/snippets/playwright-check-suite-tryout.mdx"

guides/end-to-end-monitoring.mdx

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description: Learn end-to-end monitoring with playwright to test key website flows. Follow our guide that gets you up and running in 10 minutes.
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tags: Playwright
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sidebarTitle: What is End-to-End Monitoring?
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canonical: 'https://www.checklyhq.com/docs/guides/end-to-end-monitoring/'
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---
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## An overview of end-to-end monitoring
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integrations/alerts/telegram.mdx

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title: 'Send Alerts via Telegram'
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description: 'Find out how Checkly integrates with Telegram to send failure, degradation, and recovery messages to any chat'
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sidebarTitle: 'Telegram'
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canonical: 'https://www.checklyhq.com/docs/integrations/alerts/telegram/'
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Checkly integrates with [Telegram](https://telegram.org/) and can

learn/incidents/slo-sla-sli.mdx

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learn_incidents:
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canonical: 'https://www.checklyhq.com/docs/learn/incidents/slo-sla-sli/'
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When we talk about keeping services running smoothly, we often hear about SLAs, SLOs, and SLIs. But what do these terms mean, and how are they different? SLAs, or Service Level Agreements, are like promises between a service provider and a customer. They outline what the customer can expect in terms of service quality.

learn/kubernetes/monitoring-challenges.mdx

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We explore the unique challenges of monitoring Kubernetes environments and the open-source tools that can improve visibility and control.
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weight: 1
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canonical: 'https://www.checklyhq.com/docs/learn/kubernetes/monitoring-challenges/'
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Managing Kubernetes in production is no small feat, especially when it comes to monitoring and observability. As modern applications grow in complexity, traditional methods of monitoring, limited to CPU and memory usage, often fall short. In this article, we explore the unique challenges of monitoring Kubernetes environments and the open-source tools that can improve visibility and control.
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learn/kubernetes/structured-logging.mdx

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Best practices for structured logging.
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learn_kubernetes
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canonical: 'https://www.checklyhq.com/docs/learn/kubernetes/structured-logging/'
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For developers and administrators, adopting structured logging means enhancing observability, streamlining log analysis, and improved system performance. In this post we’ll cover the fundamentals of structured logging in Kubernetes, its practical applications, and best practices for implementing it in your systems.

learn/monitoring/api-monitoring.mdx

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learn_monitoring:
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canonical: 'https://www.checklyhq.com/docs/learn/monitoring/api-monitoring/'
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API monitoring is the practice of evaluating how an API (Application Programming Interface) is performing over time via several different metrics, including verifying availability, verifying correctness (i.e., is the data that is being sent and received correctly?), and measuring performance and asserting that against a performance threshold. The goal is to determine whether the APIs are functioning as they should and whether they are available and functioning at an optimal level for the other applications and services that rely on them.

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