Building Real‑Time Burndown Dashboards with Netlify Edge, Bubble, and REST APIs

TL;DR

• Netlify Edge brings serverless logic closer to users, reducing latency and improving performance for dynamic web apps.
• You can integrate Bubble (a no‑code app builder) with REST APIs hosted on Netlify Edge to create real‑time dashboards.
• Burndown charts are perfect for tracking sprint progress; building them dynamically on the edge keeps data fresh and fast.
• We’ll walk through building a real‑time burndown dashboard using Netlify Edge, a REST API, and Bubble’s visual front end.
• Includes performance, security, and scalability insights for production‑grade deployments.

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What You’ll Learn

1. What Netlify Edge Functions are and how they differ from standard serverless functions.
2. How to use Bubble to build a front end that consumes a REST API.
3. How to design and deploy a REST API on Netlify Edge for real‑time data updates.
4. How to visualize agile metrics (like burndown charts) dynamically.
5. How to secure, test, and monitor your edge‑deployed applications.

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Prerequisites

• Basic familiarity with HTTP APIs and JavaScript.
• A Netlify account and CLI installed (npm install -g netlify-cli).
• A Bubble account (free tier is fine).
• Some understanding of Agile metrics (e.g., story points, sprint velocity).

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Introduction: Why Edge Functions + Bubble + REST APIs Make Sense

The web has shifted from monolithic apps to distributed, edge‑first architectures. Netlify Edge Functions allow developers to run logic geographically close to users¹, cutting latency and improving user experience. When combined with Bubble’s no‑code front end, teams can prototype and iterate on data‑driven dashboards without maintaining a traditional backend.

When you add a REST API into the mix, you get a flexible, interoperable layer for exchanging data between systems — perfect for integrating with project management tools like Jira, Trello, or Linear.

And that’s where burndown charts come in.

A burndown chart visualizes remaining work in a sprint. If you can automate its generation and update it in real time, you get a powerful, living view of your team’s progress — no spreadsheets required.

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Understanding Netlify Edge Functions

Netlify Edge Functions run on Deno runtime environments², executing JavaScript or TypeScript code at CDN edge nodes. They differ from standard Netlify Functions (which run in AWS Lambda regions) by being globally distributed and executing instantly near users.

Feature	Netlify Edge Function	Netlify Function
Runtime	Deno	Node.js
Execution Location	Global CDN edge	AWS Lambda region
Cold Start	~0 ms (pre‑warmed)	100–300 ms typical
Use Case	Low‑latency personalization, routing, dynamic content	Heavy computation, background tasks

When to Use vs When NOT to Use

Use Edge Functions When...	Avoid Edge Functions When...
You need fast responses for dynamic content	You need long‑running tasks (>50 ms compute time)
You’re personalizing content per request	You require specialized native modules
You want global consistency and low latency	You need intensive CPU or memory operations

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Designing the Architecture

Let’s visualize how our system will work:

flowchart TD
  A[User Browser] -->|HTTP Request| B[Bubble Frontend]
  B -->|Fetch| C[Netlify Edge REST API]
  C -->|Query| D[Project Management Tool API]
  D -->|Data JSON| C
  C -->|Processed Data| B
  B -->|Render Chart| A

Components

1. Bubble Frontend: Displays the burndown chart and interacts with the REST API.
2. Netlify Edge Function: Acts as a proxy and data processor.
3. Project Tool API: Source of sprint or task data (e.g., Jira Cloud REST API³).

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Step‑by‑Step Tutorial: Building a Real‑Time Burndown Dashboard

Step 1: Set Up a New Netlify Project

mkdir edge-burndown
cd edge-burndown
netlify init

This creates a new Netlify site linked to your Git repository.

Step 2: Create an Edge Function

Create the folder structure:

mkdir -p netlify/edge-functions

Then create netlify/edge-functions/burndown.js:

export default async (request, context) => {
  const jiraUrl = 'https://your-jira-instance.atlassian.net/rest/api/3/search';
  const jql = 'project = ABC AND sprint in openSprints()';

  const response = await fetch(`${jiraUrl}?jql=${encodeURIComponent(jql)}`, {
    headers: {
      'Authorization': `Basic ${btoa('email@example.com:api_token')}`,
      'Accept': 'application/json'
    }
  });

  const data = await response.json();
  
  // Process issues to calculate remaining story points
  const totalPoints = data.issues.reduce((sum, issue) => sum + (issue.fields.customfield_10016 || 0), 0);
  const completedPoints = data.issues.filter(i => i.fields.status.name === 'Done')
                                     .reduce((sum, i) => sum + (i.fields.customfield_10016 || 0), 0);

  const remaining = totalPoints - completedPoints;

  return new Response(JSON.stringify({ totalPoints, completedPoints, remaining }), {
    headers: { 'Content-Type': 'application/json' }
  });
};

Deploy it:

netlify deploy --prod

Now you have a REST endpoint like https://your-site.netlify.app/.netlify/edge-functions/burndown.

Step 3: Connect Bubble to the API

1. In Bubble, open the API Connector plugin.
2. Create a new API called NetlifyBurndown.
3. Set the endpoint to your deployed URL.
4. Initialize the call to fetch the response structure.
5. Use Bubble’s Chart Element to visualize the data.

Step 4: Build the Burndown Chart

In Bubble, use the Chart.js plugin or Bubble’s built‑in charting features to plot:

• X‑axis: Sprint days.
• Y‑axis: Remaining story points.

You can schedule Bubble workflows to call the API every few minutes, ensuring the chart updates automatically.

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Before vs After: Traditional vs Edge‑Deployed Dashboards

Aspect	Traditional Server	Netlify Edge
API Latency	~200–400 ms (regional)	~20–50 ms (edge‑distributed)
Scalability	Requires load balancer	Auto‑scales globally
Maintenance	Manual scaling & caching	Managed by Netlify
Integration	Requires backend devs	Works with no‑code front ends

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Common Pitfalls & Solutions

Pitfall	Cause	Solution
CORS errors from Bubble	Missing CORS headers	Add Access-Control-Allow-Origin: * in Edge Function response
API rate limits	Too many requests to Jira	Cache responses using context.cookies or Netlify Edge cache API
JSON parsing errors	Malformed API response	Wrap JSON.parse in try/catch and log errors
Authentication issues	Invalid API token	Use environment variables in Netlify for credentials

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Testing and Monitoring

Unit Testing

You can test Edge Functions locally using Netlify’s CLI:

netlify dev

Then hit your local endpoint:

curl http://localhost:8888/.netlify/edge-functions/burndown

Expected output:

{
  "totalPoints": 120,
  "completedPoints": 80,
  "remaining": 40
}

Observability

Netlify provides request logs and function execution metrics in the dashboard⁴. For deeper observability, integrate with Datadog or New Relic via webhooks.

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Security Considerations

• Authentication: Store API tokens in Netlify environment variables; never hard‑code credentials.
• Rate Limiting: Use Netlify’s built‑in caching or add custom logic to limit outbound API calls.
• Data Privacy: Avoid logging sensitive data in Edge Functions.
• OWASP Compliance: Sanitize all external inputs and validate JSON responses⁵.

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Performance and Scalability Insights

Edge Functions are inherently scalable because they run on Netlify’s global CDN network¹. For I/O‑bound tasks like fetching data from REST APIs, edge execution typically reduces response latency significantly.

Performance Tip: Combine multiple API calls using Promise.all() to parallelize requests.

const [jiraData, githubData] = await Promise.all([
  fetch(jiraUrl),
  fetch(githubUrl)
]);

This approach is widely used in production systems to handle multiple integrations concurrently⁶.

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Real‑World Example: Agile Analytics at Scale

Large organizations often use edge‑deployed analytics to visualize sprint progress across distributed teams. For example, global teams using tools like Jira Cloud can experience latency when dashboards query regional servers. Running aggregation logic on Netlify Edge reduces that delay, ensuring real‑time updates for every user, regardless of geography.

While this guide uses Bubble for simplicity, the same architecture can power dashboards in React, Vue, or Svelte — all consuming the same REST API.

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Common Mistakes Everyone Makes

1. Mixing Edge and Serverless Functions incorrectly: Keep quick, stateless operations at the edge; move heavy lifting to serverless.
2. Ignoring caching: Without caching, you’ll hit API limits fast.
3. Overcomplicating Bubble workflows: Keep Bubble as a presentation layer; let Netlify handle logic.
4. Skipping error handling: Always wrap fetch calls in try/catch.

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Troubleshooting Guide

Issue	Symptom	Fix
404 on Edge Function	Function not deployed	Check folder name: must be netlify/edge-functions
401 Unauthorized	Invalid credentials	Verify Netlify env vars and API tokens
Chart not updating	Bubble cache	Add a timestamp query param to API calls
Slow response	Upstream API latency	Add caching logic or schedule background fetches

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When to Use This Architecture

Use this setup if:

• You need real‑time dashboards that update instantly.
• Your users are globally distributed.
• You want to prototype quickly without backend infrastructure.

Avoid it if:

• You need heavy data aggregation or long‑running jobs.
• You require complex authentication flows better served by traditional servers.

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Future Outlook

Edge computing is becoming the default for modern web apps. Netlify’s Edge Functions are part of a broader industry shift toward distributed execution — similar to Cloudflare Workers and Vercel Edge Functions⁷. As more no‑code tools like Bubble add API integrations, the line between developer and designer continues to blur.

Expect to see more hybrid stacks where:

• Edge APIs handle logic.
• No‑code front ends render data.
• Real‑time visualizations replace static dashboards.

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Key Takeaways

✅ Summary:

• Netlify Edge Functions enable near‑instant, globally distributed REST APIs.
• Bubble can consume those APIs to build dynamic dashboards.
• Burndown charts are an excellent use case for real‑time updates.
• Secure, test, and monitor your edge deployments for production readiness.
• This stack scales effortlessly and reduces maintenance overhead.

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FAQ

Q1: Can I use Node.js libraries in Netlify Edge?
Yes — Edge Functions use the Deno runtime², which supports modern web APIs. You can use Node.js built-in modules, but you need to prefix the import with node:, for example import { randomBytes } from "node:crypto". Also, npm packages are supported: You can install npm packages and import them by package name (e.g., import _ from "lodash").

Q2: How do I cache API responses?
Use context.rewrite() or Netlify’s Edge cache API to store responses temporarily.

Q3: Is Bubble suitable for production dashboards?
Yes, for internal tools and moderate traffic. For high‑traffic apps, consider React or Svelte front ends.

Q4: Can I combine multiple APIs in one Edge Function?
Absolutely. Use Promise.all() for parallel calls and merge results before returning JSON.

Q5: How can I monitor errors in production?
Use Netlify’s function logs or integrate with third‑party observability tools.

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Next Steps

• Explore Netlify Edge Functions documentation.
• Learn Bubble API Connector best practices.
• Experiment with real‑time charting libraries like Chart.js or Recharts.
• Subscribe to our newsletter for more edge computing deep dives.

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Footnotes

1. Netlify Docs – Edge Functions Overview: https://docs.netlify.com/edge-functions/overview/ ↩ ↩²

2. Deno Runtime Documentation: https://deno.land/manual ↩ ↩²

3. Atlassian Jira Cloud REST API Reference: https://developer.atlassian.com/cloud/jira/platform/rest/v3/intro/ ↩

4. Netlify Observability and Logs: https://docs.netlify.com/monitor-sites/logs/ ↩

5. OWASP API Security Top 10: https://owasp.org/API-Security/ ↩

6. MDN Web Docs – Promise.all(): https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Promise/all ↩

7. Cloudflare Workers Documentation: https://developers.cloudflare.com/workers/ ↩