This article provides a complete, practical walkthrough of the Http Rabbitmq Update Scheduled 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:  
   Automating ISS Location Updates with n8n and RabbitMQ
   
   Meta Description:  
   Learn how to build an automated workflow in n8n that fetches the International Space Station’s location every minute and publishes updates to a RabbitMQ queue.
   
   Keywords:  
   n8n, ISS tracker, RabbitMQ, automation, satellite tracking, API, real-time updates, ISS location, wheretheiss.at, n8n workflow, cron job, message queue
   
   Third-Party APIs Used:
   - wheretheiss.at API (https://api.wheretheiss.at/): Provides real-time positional data of the International Space Station
   
   Article:
   
   Tracking the International Space Station (ISS) in Real-Time Using n8n and RabbitMQ
   
   In the era of automation, streamlining the process of retrieving and distributing real-time data has never been more impactful—or more exciting. A great example of this is watching the movements of the International Space Station (ISS) as it orbits Earth. In this article, we’ll walk through how you can use n8n, a powerful workflow automation tool, to build a pipeline that retrieves the ISS’s location every minute and publishes it to a RabbitMQ message queue.
   
   Let’s explore how this workflow works, the technologies involved, and how you can implement it in your stack.
   
   Why Track the ISS?
   
   The ISS completes an orbit around Earth approximately every 90 minutes, and its movements provide a fascinating playground for space enthusiasts, educators, and real-time data stream applications. Whether you’re monitoring its path for a classroom demonstration or as part of a larger system like satellite-ground tracking or alerting mechanisms, having up-to-the-minute positional data is essential.
   
   The Workflow Overview
   
   The workflow, created using n8n, is composed of four primary nodes:
   
   1. Cron Trigger
   2. HTTP Request
   3. Set Node (Data Transformation)
   4. RabbitMQ Node (Message Publishing)
   
   Let’s break down each piece.
   
   Step 1: Trigger the Flow Every Minute (Cron Node)
   
   The workflow uses n8n’s Cron node to initiate the process every 60 seconds. This time-based trigger ensures regular polling of data from the ISS tracking API.
   
   In the configuration, the cron is set to run every minute using the "everyMinute" mode:
   
   ```json
   "triggerTimes": {
     "item": [
       {
         "mode": "everyMinute"
       }
     ]
   }
   ```
   
   This reliable trigger forms the heartbeat of the automation.
   
   Step 2: Fetch the Latest ISS Position (HTTP Request Node)
   
   Once the Cron node activates the workflow, it hands off control to the HTTP Request node, which issues a GET request to the WhereTheISS.at API:
   
   ```plaintext
   https://api.wheretheiss.at/v1/satellites/25544/positions?timestamps=TIMESTAMP
   ```
   
   The satellite ID “25544” corresponds to the ISS. The timestamp passed dynamically via JavaScript (using Date.now()) fetches the current location data. This public and lightweight API is ideal for frequent polling due to its simple response structure and performance.
   
   Step 3: Extract and Format Data (Set Node)
   
   After receiving the response, the Set node processes the data to extract only the relevant fields: latitude, longitude, timestamp, and the name of the satellite.
   
   This transformation ensures that only useful information is passed down to the next step, reducing payload size and improving readability for downstream systems.
   
   Here’s an example of the extracted data:
   
   ```json
   {
     "Latitude": 50.114962699999998,
     "Longitude": 8.683877199999999,
     "Timestamp": 1706791187,
     "Name": "iss"
   }
   ```
   
   Step 4: Publish to RabbitMQ
   
   Finally, the formatted data is sent to RabbitMQ using n8n’s built-in RabbitMQ node. The message is published to the queue named "iss-position". This decouples the data collection layer from the consumers, allowing multiple downstream applications—like display boards, dashboards, or alerting systems—to subscribe to the ISS position feed in real time.
   
   Using RabbitMQ as the transport layer has several advantages:
   
   - Scalability: Multiple consumers can subscribe to the queue without modifying the producer.
   - Reliability: Messages are queued even if consumers go offline temporarily.
   - Decoupling: Producers and consumers are loosely connected, promoting flexibility and modularity.
   
   Real-World Use Cases
   
   - Educators can build a live classroom ISS tracker
   - Developers can create an augmented reality app to visualize the ISS trajectory
   - Weather and aerospace analysts can use it in satellite coordination and planning tools
   - Tech enthusiasts can run a live telemetry dashboard at home
   
   Why n8n?
   
   n8n stands out because of its open-source nature, visual workflow editor, and easy extensibility. The platform empowers both developers and non-developers to build complex automations without writing extensive code.
   
   Additionally, its node-based architecture provides native support for hundreds of services and data processing techniques, meaning that this ISS tracker can be extended with features like email alerts, Slack messages, or even integration with IoT devices.
   
   Conclusion
   
   With only a few nodes and an intuitive visual setup, you can create a powerful, time-triggered ISS location broadcasting system using n8n and RabbitMQ. This simple yet effective workflow opens the door to countless applications in education, space-tech, real-time monitoring, and automation.
   
   Whether you're an automation architect or a space enthusiast, tracking the ISS in real time has never been easier or more rewarding.
   
   Start experimenting today—and let the ISS inspire your next automation!
   
   Have questions or want to extend the workflow? You can explore more possibilities at n8n.io or try more APIs like WhereTheISS.at to integrate space data into your own apps.
   
   Happy automating!

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.