This article provides a complete, practical walkthrough of the Wait Code Monitor 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:  
   Preventing Duplicate Workflow Executions in n8n Using Redis-Based Locking
   
   Meta Description:  
   Learn how to use Redis to prevent concurrent and duplicate workflow executions in n8n with this efficient Redis lock pattern implementation using webhook data and control nodes.
   
   Keywords:  
   n8n, Redis locking, n8n workflow automation, concurrency control, prevent duplicate workflows, Redis in automation, webhook execution lock, n8n webhook, automation scalability, Redis TTL
   
   Third-Party APIs and Services Used:
   - Redis (via the n8n Redis node)
   - Slack (assumed, based on JSON.parse of Slack-style payload – not explicitly authenticated in this workflow but implied)
   - n8n Webhook (built-in, not third-party)
   - JavaScript execution (n8n Code node, built-in logic)
   
   Article:
   
   ---
   
   ## How to Prevent Duplicate Workflow Executions in n8n Using Redis-Based Locking
   
   In any automated system, managing concurrency is critical—especially when dealing with external triggers like webhooks that can arrive simultaneously or be duplicated. Duplicate webhook calls, whether intentional or accidental, can result in harmful data duplication, redundant API calls, or unnecessary loads on resources.
   
   In this article, we explore a robust n8n workflow engineering pattern designed to prevent such issues. Using Redis as a distributed lock mechanism, this workflow ensures that only one execution proceeds for a given request while any duplicates are quietly dismissed or queued for later execution. Let’s break down how it works.
   
   ---
   
   ### What Problem Does It Solve?
   
   This pattern protects against executing the same workflow more than once when concurrent or identical webhook calls are received. Consider external services (like Slack, Stripe, or any webhook-emitting system) sending out retry requests—without proper control, your automation may run multiple times concurrently, consuming unjustified resources or creating inconsistent application states.
   
   With Redis-based locking, we can:
   
   - Acquire a unique lock per request before any business logic executes.
   - Queue or drop duplicate webhook attempts.
   - Release the lock after successful completion, enabling the next request to proceed.
   
   ---
   
   ### How the Workflow Works — Step by Step
   
   #### 1. Webhook Trigger and Payload Parsing
   
   The workflow starts with a Webhook node called “Incoming Webhook Data”. When initiated, it receives payloads (likely from Slack based on the payload structure) and passes them to the “Fetch Webhook Data & Declare lockValue” node. Here, JavaScript is used to parse the incoming JSON payload and extract three variables: `var1`, `var2`, and `var3`. These are combined into a unique identifier called `lockValue` (e.g., `"abc-def-ghi"`).
   
   This `lockValue` helps in identifying whether a specific webhook request has been processed already.
   
   #### 2. Redis Lock Check
   
   Next, the "Check Redis Lock" node queries Redis for any existing lock under the Redis key `xyz-lock`. This lock key stores whatever `lockValue` was set previously.
   
   An IF node named “redisLock existence boolean” evaluates whether the result from Redis is empty (meaning no existing lock). If there is no lock found, the workflow attempts to acquire one.
   
   #### 3. Acquire Redis Lock
   
   If the lock does not exist, the “Acquire Redis Lock” node sets the lock in Redis using the current `lockValue`. It includes a TTL (time-to-live) parameter—180 seconds in this case—to ensure the lock expires even if the workflow crashes.
   
   If acquiring the lock fails (e.g., if another webhook just got in milliseconds earlier), the workflow proceeds to “Poll for lock”, effectively waiting until the lock is released or a different logic path is taken.
   
   #### 4. Avoid Duplicate Execution
   
   Through an evaluation node named “duplicateWebhook boolean”, the workflow checks whether the current webhook’s `lockValue` matches the existing Redis lock’s value. If it's the same, it’s considered a duplicate and the flow ends via the "END" node. Otherwise, it proceeds to check further lock conditions or queue the request, depending on setup.
   
   #### 5. Workflow Selection and Execution
   
   Once the lock is successfully acquired, the workflow routes logic through a “Workflow Switch”. This node conditionally forwards the flow to one of three “Set” nodes (Workflow 1, Workflow 2, Workflow 3) which act as stand-ins for real workflows or logic modules.
   
   Each of these ultimately leads to the lock being discarded through the “Discard Redis Lock” node, ensuring future requests can re-enter.
   
   #### 6. Releasing the Lock
   
   Once the selected workflow completes successfully, the lock is released via Redis using the Delete operation. This guarantees that the system is ready to handle new incoming webhook events with fresh locks.
   
   ---
   
   ### Key Highlights
   
   - ✅ Prevents race conditions and duplicate data entries.
   - 🕒 Uses Redis TTL to automatically expire locks (180s configured here).
   - 🔃 Efficiently parses and verifies incoming webhooks before processing.
   - 🧠 Smart branching using IF conditions and Switch nodes to choose workflow paths.
   - 💡 Helps scale n8n workflows in production environments where external triggers are frequent.
   
   ---
   
   ### Use Cases
   
   - Handling Slack interactions or API button clicks sent via webhooks.
   - Stripe webhooks that retry frequently for assurance of delivery.
   - Integration hubs where multiple clients might send similar webhook payloads concurrently.
   
   ---
   
   ### Final Thoughts
   
   This workflow design showcases the power of using Redis not just as a fast storage solution, but also as a gatekeeper in a distributed system where multiple events compete for attention. By implementing locking in this way, n8n users can ensure that workflows behave predictably, perform optimally, and scale reliably—even under high-frequency webhook activity.
   
   This pattern is perfect for developers, DevOps engineers, and no-code builders looking to implement idempotency and concurrency control in their automation chains.
   
   Happy automating with n8n!
   
   ---
   
   Let me know if you’d like a copy of this as a Markdown file or styled for a blog CMS.

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.