This article provides a complete, practical walkthrough of the Http Googlefirebaserealtimedatabase Update Webhook n8n agent. It connects HTTP Request, Webhook across approximately 1 node(s). Expect a Intermediate setup in 15-45 minutes. One‑time purchase: €29.

What This Agent Does

This agent orchestrates a reliable automation between HTTP Request, Webhook, handling triggers, data enrichment, and delivery with guardrails for errors and rate limits.

It streamlines multi‑step processes that would otherwise require manual exports, spreadsheet cleanup, and repeated API requests. By centralizing logic in n8n, it reduces context switching, lowers error rates, and ensures consistent results across teams.

Typical outcomes include faster lead handoffs, automated notifications, accurate data synchronization, and better visibility via execution logs and optional Slack/Email alerts.

How It Works

The workflow uses standard n8n building blocks like Webhook or Schedule triggers, HTTP Request for API calls, and control nodes (IF, Merge, Set) to validate inputs, branch on conditions, and format outputs. Retries and timeouts improve resilience, while credentials keep secrets safe.

Third‑Party Integrations

• HTTP Request
• Webhook

Import and Use in n8n

1. Open n8n and create a new workflow or collection.
2. Choose Import from File or Paste JSON.
3. Paste the JSON below, then click Import.
4. Show n8n JSON

   Title:  
   Tracking the International Space Station in Real-Time with n8n and Firebase
   
   Meta Description:  
   Learn how to build an automated workflow using n8n that fetches the current location of the International Space Station (ISS) every minute and stores the data in Google Firebase Realtime Database.
   
   Keywords:  
   n8n workflow, ISS tracking, Firebase Realtime Database, satellite location API, real-time data, automation, HTTP request, Google Firebase, International Space Station, space API, workflow automation, no-code tools
   
   Third-Party APIs Used:
   
   - Where the ISS at (https://wheretheiss.at/) – for retrieving the ISS’s current location
   - Google Firebase Realtime Database – for storing the fetched data
   
   Article:
   
   Automating Real-Time ISS Location Tracking Using n8n and Firebase
   
   The International Space Station (ISS) travels around the Earth at a blazing speed of about 7.66 km/s, orbiting our planet every 90 minutes. Keeping track of its location in real-time can be both fascinating and valuable for educational, research, or even personal interest projects. Thanks to modern APIs and automation tools, you no longer need a NASA-grade setup to achieve this. In this article, we’ll show you how to build an automated workflow using the no-code automation tool n8n that fetches the ISS’s position every minute and stores the information in Google Firebase Realtime Database.
   
   Let’s break down this powerful (yet simple) automation.
   
   Overview of the Workflow
   
   This n8n workflow is designed to do one thing: track the location of the International Space Station every minute and store that data automatically in a cloud database. Here's how it works in four automated steps:
   
   1. Trigger: A Cron node initiates the workflow every minute.  
   2. Fetch Data: An HTTP Request node queries the "Where the ISS at" API for the current position of the ISS.  
   3. Format Data: A Set node structures the latitude, longitude, and timestamp into a clean format.  
   4. Save Data: A Firebase Realtime Database node pushes this structured information into the cloud.
   
   Step-by-Step Breakdown
   
   1. Cron Node – The Timekeeper  
   The Cron node is the heartbeat of the workflow. It triggers every minute, thanks to its configured schedule (`mode: everyMinute`). This ensures that the location of the ISS is fetched at a 60-second interval, giving you near real-time data.
   
   2. HTTP Request Node – Accessing the ISS Location Data  
   Once triggered, the workflow initiates an HTTP GET request to the public API at https://api.wheretheiss.at/v1/satellites/25544/positions. The ISS’s NORAD satellite ID is 25544, which is passed to the API endpoint. Along with the current UNIX timestamp (calculated using JavaScript within n8n), the API returns a JSON response that contains location details, including:
   
   - latitude
   - longitude
   - altitude
   - velocity
   - visibility
   - timestamp
   
   In this workflow, only the first object of the response array is used, focusing on the coordinates and timestamp.
   
   3. Set Node – Extracting and Organizing the Data  
   To prepare the data for storage, the Set node isolates the most essential values: latitude, longitude, and timestamp. Using expressions within n8n, values are pulled directly from the HTTP node’s JSON output and mapped accordingly. The use of “keepOnlySet” ensures that only these relevant fields are passed forward, keeping the data payload clean and focused.
   
   4. Google Firebase Realtime Database Node – Persistent Storage  
   The final node in the workflow pushes the data to a Google Firebase Realtime Database under the path "iss". Each push operation adds a new record, preserving historical location data over time. This structure is well-suited for building visual dashboards, data analysis scripts, or even triggering alerts when the ISS is nearby.
   
   Use Cases and Benefits
   
   This automation may initially seem like a simple example, but it unlocks significant potential:
   
   - Educational Content: Schools or museums can build live ISS tracking displays.
   - Data Analysis: Collect location data over time for deeper statistical analysis.
   - Notifications: Pair with additional nodes to get alerts when the ISS passes over a certain location.
   - Visualizations: Use the stored data to build maps or time-lapse visualizations in tools like Google Maps, Power BI, or even your own web app.
   
   Bonus: Why Use n8n?
   
   n8n (short for "Node-Node") is a popular open-source workflow automation tool that allows non-developers—or developers who want to save time—to automate and integrate operations across different platforms. It supports over 200 official nodes out of the box, including APIs, databases, messaging services, and more. Its drag-and-drop interface, combined with the ability to write custom code where needed, offers an excellent blend of flexibility and usability.
   
   Conclusion
   
   With just a few nodes and no complex coding, this workflow automates the process of tracking the ISS’s position and storing it in a scalable, cloud-based database. It’s a perfect demonstration of how powerful no-code and low-code tools like n8n can be when combined with open APIs and cloud infrastructure.
   
   Whether you're a space enthusiast, a developer looking to prototype a spatial tracking app, or an educator bringing STEM to life in the classroom, this workflow offers a simple yet high-impact starting point.
   
   Stay curious—and keep looking up!
   
   Ready to build this yourself? Try it on n8n today and bring the final frontier down to Earth.
   
   —
   
   If you found this helpful or want to expand this setup to include more satellites or conditional alerting, keep exploring n8n’s capabilities. The stars (and data) are the limit.

5. Set credentials for each API node (keys, OAuth) in Credentials.
6. Run a test via Execute Workflow. Inspect Run Data, then adjust parameters.
7. Enable the workflow to run on schedule, webhook, or triggers as configured.

Tips: keep secrets in credentials, add retries and timeouts on HTTP nodes, implement error notifications, and paginate large API fetches.

Validation: use IF/Code nodes to sanitize inputs and guard against empty payloads.

Why Automate This with AI Agents

AI‑assisted automations offload repetitive, error‑prone tasks to a predictable workflow. Instead of manual copy‑paste and ad‑hoc scripts, your team gets a governed pipeline with versioned state, auditability, and observable runs.

n8n’s node graph makes data flow transparent while AI‑powered enrichment (classification, extraction, summarization) boosts throughput and consistency. Teams reclaim time, reduce operational costs, and standardize best practices without sacrificing flexibility.

Compared to one‑off integrations, an AI agent is easier to extend: swap APIs, add filters, or bolt on notifications without rewriting everything. You get reliability, control, and a faster path from idea to production.

Best Practices

• Credentials: restrict scopes and rotate tokens regularly.
• Resilience: configure retries, timeouts, and backoff for API nodes.
• Data Quality: validate inputs; normalize fields early to reduce downstream branching.
• Performance: batch records and paginate for large datasets.
• Observability: add failure alerts (Email/Slack) and persistent logs for auditing.
• Security: avoid sensitive data in logs; use environment variables and n8n credentials.

FAQs

Can I swap integrations later? Yes. Replace or add nodes and re‑map fields without rebuilding the whole flow.

How do I monitor failures? Use Execution logs and add notifications on the Error Trigger path.

Does it scale? Use queues, batching, and sub‑workflows to split responsibilities and control load.

Is my data safe? Keep secrets in Credentials, restrict token scopes, and review access logs.