How to Use Checkly for Design Workflows
A practical guide to using Checkly for design workflows: workflow, tips, and when to use something else.
Why Use Checkly for Design Workflows?
Design workflows rely heavily on user interfaces, interactive prototypes, and design systems that need continuous validation. When your design team builds interactive prototypes, maintains component libraries, or runs user testing platforms, these systems must work flawlessly across different browsers, devices, and geographic locations.
Checkly excels at monitoring design workflows because it combines browser automation with API monitoring in a developer-friendly package. You can write Playwright scripts to test interactive prototypes, validate design system components render correctly, and ensure your design tools remain accessible. Unlike basic uptime monitors that only check if a page loads, Checkly executes real user interactions—clicking buttons, filling forms, and navigating complex user flows that design teams care about.
The monitoring-as-code approach means your design team can version control their monitoring scripts alongside design assets, making it easy to update checks when prototypes evolve or new components get added to your design system.
Getting Started with Checkly
You'll need a Checkly account and the Checkly CLI installed on your development machine. Checkly operates on a freemium model with 5,000 check runs per month on the free tier, sufficient for small design teams monitoring a handful of prototypes.
First, install the Checkly CLI:
```bash npm install -g @checkly/cli ```
Create a new monitoring project:
```bash mkdir design-monitoring cd design-monitoring npx checkly init ```
This generates a basic project structure with TypeScript configuration. You'll authenticate with your Checkly account during initialization.
The key advantage for design workflows is Checkly's global monitoring locations. You can run checks from 20+ locations including US East (Virginia), US West (Oregon), Europe (Frankfurt), Asia Pacific (Singapore), and others. This matters when your design team serves global users or when you're testing CDN performance for design assets.
Step-by-Step Setup
Let's set up monitoring for a design system component library hosted at `https://your-design-system.com`.
Browser Check for Component Rendering
Create a browser check that validates your button components render correctly:
```typescript // checks/button-component.check.ts import { BrowserCheck, Frequency } from '@checkly/cli/constructs' import { chromium } from 'playwright'
new BrowserCheck('button-component-check', { name: 'Design System - Button Components', frequency: Frequency.EVERY_5M, locations: ['us-east-1', 'eu-west-1', 'ap-southeast-1'], code: { entrypoint: './button-test.spec.ts' } }) ```
The actual test script validates component functionality:
```typescript // button-test.spec.ts import { test, expect } from '@playwright/test'
test('Button components render and respond correctly', async ({ page }) => { await page.goto('https://your-design-system.com/components/buttons') // Check primary button renders const primaryButton = page.locator('[data-testid="primary-button"]') await expect(primaryButton).toBeVisible() await expect(primaryButton).toHaveCSS('background-color', 'rgb(37, 99, 235)') // Test button interaction await primaryButton.click() await expect(page.locator('[data-testid="click-feedback"]')).toBeVisible() // Validate button states const disabledButton = page.locator('[data-testid="disabled-button"]') await expect(disabledButton).toBeDisabled() }) ```
API Check for Design Asset Delivery
Design workflows often depend on CDNs serving fonts, icons, and other assets. Monitor these with API checks:
```typescript // checks/design-assets.check.ts import { ApiCheck, AssertionBuilder, Frequency } from '@checkly/cli/constructs'
new ApiCheck('design-assets-cdn', { name: 'Design Assets CDN Performance', frequency: Frequency.EVERY_2M, locations: ['us-east-1', 'eu-west-1', 'ap-southeast-1'], request: { url: 'https://cdn.your-design-system.com/fonts/inter-regular.woff2', method: 'GET' }, assertions: [ AssertionBuilder.statusCode().equals(200), AssertionBuilder.responseTime().lessThan(800), AssertionBuilder.header('content-type').contains('font/woff2') ] }) ```
Prototype User Flow Validation
For interactive prototypes, create end-to-end flows that mirror real user journeys:
```typescript // checks/prototype-flow.check.ts import { BrowserCheck, Frequency } from '@checkly/cli/constructs'
new BrowserCheck('prototype-user-flow', { name: 'Product Prototype - Complete User Journey', frequency: Frequency.EVERY_10M, locations: ['us-east-1', 'eu-west-1'], code: { entrypoint: './prototype-flow.spec.ts' } }) ```
```typescript // prototype-flow.spec.ts import { test, expect } from '@playwright/test'
test('User can complete product configuration flow', async ({ page }) => { await page.goto('https://prototype.your-company.com/configurator') // Step 1: Select product category await page.click('[data-testid="category-electronics"]') await expect(page.locator('[data-testid="product-grid"]')).toBeVisible() // Step 2: Configure product options await page.selectOption('[data-testid="color-select"]', 'blue') await page.click('[data-testid="size-large"]') // Step 3: Add to cart await page.click('[data-testid="add-to-cart"]') await expect(page.locator('[data-testid="cart-confirmation"]')).toContainText('Added to cart') // Validate final state const cartCount = page.locator('[data-testid="cart-count"]') await expect(cartCount).toContainText('1') }) ```
Deploy your checks:
```bash checkly deploy ```
This pushes your monitoring configuration to Checkly's global infrastructure, which will begin executing checks according to your specified frequencies and locations.
Tips and Best Practices
Use data attributes for reliable selectors. Design prototypes change frequently. Instead of relying on CSS classes that might evolve, add `data-testid` attributes to key elements you want to monitor. This keeps your checks stable even when visual designs change.
Set appropriate check frequencies. Design systems don't need minute-by-minute monitoring. Every 5-10 minutes is usually sufficient unless you're actively developing or have critical user testing sessions running.
Monitor from relevant locations. If your design team primarily serves users in North America and Europe, focus monitoring on `us-east-1`, `us-west-2`, and `eu-west-1`. Adding too many locations increases costs without proportional value for design workflows.
Use environment variables for different environments. Your design team likely has staging and production versions of prototypes:
```typescript const baseUrl = process.env.ENVIRONMENT === 'production' ? 'https://design-system.company.com' : 'https://staging-design-system.company.com' ```
Set up alerting channels your design team actually uses. Checkly supports Slack, Microsoft Teams, email, and webhook notifications. Configure alerts to reach the right people—usually the design engineering team rather than general infrastructure teams.
Watch out for rate limits. Some design tools and prototyping platforms have rate limits that could trigger if you check too frequently. Figma's API, for example, has request quotas that aggressive monitoring could exhaust.
Consider check costs. Browser checks consume more resources than API checks. A browser check costs roughly 10x an API check in terms of Checkly's pricing. For design workflows monitoring multiple component pages, you might hit usage limits faster than expected.
When Checkly Isn't the Right Fit
Checkly works well for monitoring live design systems and interactive prototypes, but it has limitations for certain design workflows.
If your design process relies heavily on Figma files, Sketch libraries, or other design tool APIs, you might need specialized design tool monitoring instead of browser-based checks. Checkly can't directly validate that your Figma components match your implemented design system.
For design workflows that require complex visual regression testing, dedicated tools like Percy or Chromatic offer better pixel-perfect comparison capabilities. Checkly's browser checks can validate functional behavior but aren't optimized for detecting subtle visual changes.
Teams doing intensive mobile app prototype testing might find Checkly's browser-based approach insufficient. While you can test responsive web prototypes, native mobile app prototypes require different tooling.
If your design team needs real user monitoring rather than synthetic checks, Checkly won't capture actual user behavior data. You'd need RUM tools like LogRocket or FullStory alongside or instead of synthetic monitoring.
Conclusion
Checkly provides design teams with a code-first approach to monitoring their digital assets. By combining browser automation with API monitoring, you can ensure design systems remain functional, prototypes work across different regions, and design assets load quickly for users worldwide.
The monitoring-as-code approach fits naturally into design engineering workflows, allowing teams to version control their monitoring scripts alongside design tokens and component libraries. While it requires some technical setup, the result is comprehensive monitoring that grows with your design system.
For design teams building web-based prototypes, component libraries, or design systems, Checkly offers the right balance of functionality and simplicity to keep your design infrastructure reliable.
Compare Checkly with alternatives on ServerSpotter.
Tools mentioned in this article
Checkly
Monitoring as code with Playwright and API checks
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