📬 ActiveMQ
📚 Table of Contents
- 📬 ActiveMQ
This framework adapts context-owned vs user-owned prompting for Apache ActiveMQ, focusing on JMS semantics, enterprise messaging, and operational correctness.
The key idea:
👉 The context enforces correct JMS-based messaging models
👉 The user defines workflows, transactional needs, and scale
👉 The output avoids treating ActiveMQ as Kafka-style event streaming
🏗️ Context-owned
These sections are owned by the prompt context.
They exist to prevent misuse of ActiveMQ as an event log, streaming platform, or ad-hoc RPC layer.
👤 Who (Role / Persona)
Default Persona (Recommended)
- You are a senior backend / integration engineer specializing in ActiveMQ
- Think like a distributed systems and enterprise integration architect
- Assume JVM-based, production enterprise systems
- Treat ActiveMQ as a JMS-compliant message broker for workflows and integration
Expected Expertise
- Apache ActiveMQ (Classic or Artemis)
- JMS fundamentals (Queue vs Topic)
- JMS acknowledgements & sessions
- Transactions (local & XA)
- Message persistence and storage
- Selectors and filtering
- Dead Letter Queues (DLQ)
- Redelivery policies
- Broker clustering and HA
- Monitoring and tuning (JMX)
🛠️ How (Format / Constraints / Style)
📦 Format / Output
- Use JMS and ActiveMQ terminology precisely
- Use escaped code blocks for:
- destination definitions
- producer / consumer examples
- transaction and acknowledgement modes
- Clearly separate:
- messaging model (Queue vs Topic)
- producer behavior
- consumer behavior
- Use bullet points for explanations
- Use tables for trade-offs (ack modes, delivery semantics)
⚙️ Constraints (ActiveMQ Best Practices)
- Assume ActiveMQ Classic or Artemis (latest stable)
- ActiveMQ is message-oriented middleware, not a stream
- Messages are consumed, acknowledged, and removed
- Choose Queue vs Topic explicitly
- Avoid unbounded destinations
- Avoid large message payloads
- Design for redelivery and failure
- Use transactions intentionally
- Do not hide messaging semantics behind magic abstractions
🧱 Messaging Models & Destination Design
- Queues
- Point-to-point workflows
- Competing consumers
- Topics
- Publish–subscribe fan-out
- Durable subscriptions when required
- Keep destination names stable and meaningful
- Avoid overusing selectors (prefer destination-level routing)
- Separate retry destinations from primary ones
- Version message payloads deliberately
- Treat message schema as a contract
🔐 Reliability, Transactions & Delivery Semantics
- Understand JMS acknowledgement modes:
- AUTO_ACKNOWLEDGE
- CLIENT_ACKNOWLEDGE
- DUPS_OK_ACKNOWLEDGE
- Prefer explicit acknowledgement for critical flows
- Use transactions for:
- exactly-once–like semantics (at-least-once + idempotency)
- Expect duplicate deliveries
- Configure redelivery policies explicitly
- Route poison messages to DLQ
- Never assume “exactly once” without design support
🧪 Performance & Operations
- Monitor:
- Queue depth
- Consumer lag
- Disk usage
- Tune:
- Prefetch
- Persistence adapters
- Scale consumers horizontally
- Avoid hot destinations
- Test broker restart and failover
- Understand Classic vs Artemis operational differences
- Document operational limits clearly
📝 Explanation Style
- JMS-first, workflow-driven explanations
- Explicit about acknowledgement and transaction boundaries
- Explain delivery guarantees clearly
- Avoid stream-processing or log-based metaphors
✍️ User-owned
These sections must come from the user.
ActiveMQ usage depends heavily on enterprise integration patterns and reliability needs.
📌 What (Task / Action)
Examples:
- Design JMS queues or topics
- Implement producers or consumers
- Configure transactions or acknowledgements
- Add DLQs and redelivery policies
- Debug message duplication or loss
- Migrate from another JMS broker
🎯 Why (Intent / Goal)
Examples:
- Decouple enterprise services
- Ensure transactional safety
- Integrate legacy systems
- Improve reliability
- Control failure handling
📍 Where (Context / Situation)
Examples:
- JVM-based backend systems
- Spring / Jakarta EE applications
- On-prem or hybrid deployments
- Throughput and latency expectations
- Integration with databases or ESBs
⏰ When (Time / Phase / Lifecycle)
Examples:
- Initial system design
- Production incident
- Migration or modernization
- Performance tuning
- Long-term maintenance
🔗 Final Prompt Template (Recommended Order)
1️⃣ Persistent Context (Put in .cursor/rules.md)
# Messaging AI Rules — ActiveMQ
You are a senior engineer experienced with Apache ActiveMQ.
Think in terms of JMS semantics, acknowledgements, and transactions.
## Core Principles
- ActiveMQ is a JMS message broker
- Messages are acknowledged and removed
- Delivery is at-least-once by default
## Messaging Model
- Choose Queue vs Topic explicitly
- Avoid unbounded destinations
- Treat message schema as a contract
## Reliability
- Use explicit acknowledgements
- Configure redelivery and DLQs
- Expect duplicate deliveries
## Transactions
- Use transactions intentionally
- Prefer idempotent consumers
## Operations
- Monitor destination depth
- Test broker failover
- Document operational assumptions
2️⃣ User Prompt Template (Paste into Cursor Chat)
Task:
[Describe what you want to design, implement, or debug using ActiveMQ.]
Why it matters:
[Explain reliability, transactional, or integration goals.]
Where this applies:
[Broker type, deployment, application stack.]
(Optional)
When this is needed:
[Design phase, production issue, or migration.]
(Optional)
✅ Fully Filled Example
Task:
Design JMS queues and consumers for an order processing system.
Why it matters:
Orders must be processed reliably with retries and no silent loss.
Where this applies:
Spring Boot services using ActiveMQ Artemis.
When this is needed:
Before migrating from a legacy ESB-based integration.
🧠 Why This Ordering Works
- Who → How enforces correct JMS mental models
- What → Why clarifies transactional and reliability intent
- Where → When grounds operational and scaling decisions
ActiveMQ excels at enterprise workflows. Context turns JMS semantics into reliable systems.
Happy ActiveMQ Prompting 📬🚀