This article provides a complete, practical walkthrough of the Http Cron 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:  
   Automating Real-Time ISS Tracking with n8n and ActiveMQ
   
   Meta Description:  
   Discover how to build an automated n8n workflow that fetches the position of the International Space Station (ISS) every minute and publishes updates to an ActiveMQ topic. Ideal for developers and space enthusiasts alike!
   
   Keywords:  
   n8n, workflow automation, ISS tracking, ActiveMQ, API integration, real-time data, satellite tracking, where the ISS at API, open-source automation, AMQP messaging
   
   Third-Party APIs Used:  
   - Where the ISS at API (https://wheretheiss.at)
   
   Article:
   
   Automating Real-Time ISS Tracking with n8n and ActiveMQ
   
   Have you ever wondered where the International Space Station (ISS) is at any given moment? With modern tools like n8n, an open-source workflow automation platform, it’s easier than ever to track the ISS in real time and distribute that data programmatically.
   
   In this article, we’ll walk through a simple yet powerful n8n workflow that retrieves the ISS’s live coordinates every minute and sends them to a topic queue using ActiveMQ via the Advanced Message Queuing Protocol (AMQP). This setup is perfect for developers building real-time dashboards, alert systems, or educational tools.
   
   The Workflow Overview
   
   Our n8n workflow consists of four core nodes:
   
   1. A Cron node that triggers the flow every minute.
   2. An HTTP Request node that fetches the ISS’s position from an external API.
   3. A Set node to extract and format the relevant data.
   4. An AMQP Sender node to publish the data to an ActiveMQ topic.
   
   Let’s break down each component.
   
   Step 1: Cron Node – Running Every Minute
   
   The automation is initiated by a Cron node configured to trigger once every minute. This ensures that the ISS’s position is retrieved in near real-time intervals. This timing is ideal for most applications requiring up-to-date geospatial data.
   
   Step 2: HTTP Request – Calling the ISS Position API
   
   Once triggered, the HTTP Request node sends a GET request to the Where the ISS at API endpoint:
   
   https://api.wheretheiss.at/v1/satellites/25544/positions
   
   To make sure we get the latest data, the node uses a dynamic query parameter:
   
   timestamps={{Date.now();}}
   
   This passes the current timestamp in milliseconds, ensuring each API call retrieves the most current position of the ISS. The response includes fields such as latitude, longitude, timestamp, and satellite name.
   
   Step 3: Set Node – Picking the Right Data
   
   As the response from the API contains a lot of information, the Set node helps streamline the data. It pulls out only the crucial fields:
   
   - Latitude
   - Longitude
   - Timestamp
   - Name
   
   These fields represent the current geographical position and identification of the ISS. Additionally, setting “keepOnlySet” to true discards any unused data, optimizing the payload for transmission.
   
   Step 4: AMQP Sender – Publishing Data to ActiveMQ
   
   The refined data is then passed to an AMQP Sender node, which publishes the information to a topic named iss-postition on an ActiveMQ broker. This enables seamless integration with other systems, services, or subscribers that are listening to the topic.
   
   Use Cases
   
   This workflow opens up many possibilities:
   
   - Real-time data displays for educational institutions or museums.
   - Integration with IoT devices that can respond to the ISS’s proximity.
   - Alert systems for amateur radio operators or astronomy hobbyists.
   - Backend data processing for predictive orbital models.
   
   What Makes This Workflow Stand Out
   
   - Fully Automated: Once activated, the workflow runs continuously without human intervention.
   - Real-Time Data: By using minute-level granularity, the workflow ensures fresh and highly relevant tracking data.
   - Scalable Architecture: Publishing to an ActiveMQ topic decouples the data producer from consumers, allowing multiple systems to use the ISS data independently.
   - Minimal Code: Thanks to n8n’s no-code/low-code approach, almost zero traditional programming is required to set this up.
   
   Final Thoughts
   
   Tracking the ISS is not only fascinating but can also serve practical and educational purposes. With n8n and third-party services like Where the ISS at API and ActiveMQ, you can go from idea to deployment in minutes. Whether you're building a space-themed app, enhancing your company's data architecture, or just geeking out over satellites, this workflow offers a robust, scalable, and easy-to-maintain solution.
   
   Take your first step into the world of automated ISS tracking—and keep looking up!
   
   🔗 Resources:
   - n8n: https://n8n.io  
   - Where the ISS at API: https://wheretheiss.at/w/developer  
   - ActiveMQ: https://activemq.apache.org  
   
   Ready to launch your own ISS tracker? Connect your tools and let the data flow!

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.