Insights hub.
From success stories to strategic insights — explore the ideas shaping what’s next.
Featured resources.
Whitepaper
The Messaging Middleware Scaling Journey
Learn how enterprises manage scaling challenges across Apache Kafka®, MQ, RabbitMQ, Solace, and more.
Blog
Modernizing Middleware for the AI Era
As AI adoption accelerates, middleware complexity intensifies. In this discussion with meshIQ CEO Navdeep Sidhu, discover why governance—not speed—has become the defining factor for enterprise success, and why fragmented middleware environments can no longer be ignored in the AI era.
Report
Multi-Protocol Performance Benchmarks: Open-Source Messaging Brokers (2026)
Equip your architecture and DevOps teams with the data needed to choose, configure and scale open-source messaging fabric for your modern hybrid infrastructure.
Press Release
meshIQ Announces Strategic Partnership with Dataeko, Expands Presence in India
meshIQ partners with Dataeko to advance middleware modernization and expand regional expertise across India’s enterprise market.
Blog
ActiveMQ Backup and Disaster Recovery: Complete DR Guide
A message broker’s backup and disaster recovery plan is the last line of defense against scenarios that HA cannot address: a full datacenter outage, catastrophic hardware failure that destroys both primary and secondary nodes, accidental message deletion, or KahaDB corruption that prevents the broker from starting.
Blog
ActiveMQ JVM Memory & GC Tuning: Heap Sizing, G1GC, ZGC Guide
The JVM is the runtime foundation of every ActiveMQ deployment. Message throughput, delivery latency, producer flow control triggers, OOM crashes, and GC-induced delivery pauses all trace back to JVM memory configuration. Yet ActiveMQ ships with a 512MB heap and no GC logging, appropriate for a developer laptop, not for an enterprise message broker handling millions of messages a day.
Whitepaper
Beyond the Queue: A Modernization Framework for Transitioning from IBM MQ™ and TIBCO® to Apache Kafka®
A practical migration framework for DevOps leads and middleware admins moving from IBM MQ™ and TIBCO™ EMS to Apache Kafka®.
Article
meshIQ 12.1: Scaling Telemetry for Agentic AI Management
MeshIQ 12.1 architecture consolidates legacy roots into a unified data layer supporting petabyte-scale telemetry ingestion for agentic AI management.
Ebook
Apache Camel™ Production Stability Playbook
Proven Troubleshooting, Reliability, and Performance Practices for Keeping Apache Camel™ Routes Healthy at Scale.
Blog
Who’s Driving Your Data? How to Regain Control of Your Apache Kafka® Infrastructure
Apache Kafka® often succeeds faster than operational maturity can keep pace. Consumer lag, partition drift, and configuration sprawl create dangerous blind spots. Learn how unified visibility, governance, and automation transform reactive Kafka operations into predictive control.
Ebook
Apache ActiveMQ® Performance Checklist
5 Production-Hardened Configuration Settings to Prevent Downtime, Eliminate Bottlenecks, and Keep Apache ActiveMQ® Running Reliably at Scale.
Blog
Troubleshooting ActiveMQ Producer Flow Control Blocks
The alert comes in at 2 AM: your order processing service is unresponsive. The application is not crashed, threads are running, the JVM is healthy, but no messages are being sent. Your operations team traces it to a blocked send() call on an ActiveMQ connection. Hours later, after restarting the application, someone finds this line in the broker log from 11 PM the previous day:
Blog
ActiveMQ Protocol Comparison: AMQP vs MQTT vs OpenWire vs STOMP
One of ActiveMQ’s most powerful and underappreciated capabilities is its protocol polyglotism: a single broker can simultaneously accept Java JMS clients over OpenWire, Python services over AMQP, IoT sensors over MQTT, and Ruby scripts over STOMP, all routing messages between each other without protocol bridges or translation middleware.
Blog
The Real Cost of Custom Code: Why Buying a Unified Middleware Management Platform Protects Enterprise IT Budgets
Building custom middleware monitoring appears cost-effective but creates expensive maintenance debt, fragmented visibility, and operational risk. Enterprise teams spend 60-80% of IT budgets on software maintenance while unified platforms deliver immediate, production-ready capabilities.