The meshIQ blog.
Our blog offers insights into pivotal and disruptive technologies, including Hybrid Cloud, Messaging Middleware, AI, and more, contributed by meshIQ experts and innovators.
Featured.
AIOps, Messaging, Middleware Optimization, Observability, Streaming
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.
Apache ActiveMQ®, Data Streaming, Messaging, Middleware, Middleware Optimization, Monitoring, MQ, SaaS
ActiveMQ Log Analysis & Diagnostics: The Expert Guide
Senior engineers who are fast at diagnosing ActiveMQ incidents share one trait: they know exactly what they are looking for in the broker log before they open it. They know the PFC signature, the OOM warning pattern, the journal recovery sequence, and the connection drop format. For them, the log is not text to search through, it is a structured operational record that maps each entry to a specific broker state.
Apache ActiveMQ®, Devops, General, Messaging, Middleware, Monitoring, MQ, Observability, SaaS
ActiveMQ Capacity Planning: The Complete Framework
Most ActiveMQ deployments are sized in one of two ways: either under-provisioned from underestimating growth (“we’ll upgrade when we need to”) or over-provisioned from anxiety (“better give it 32GB just in case”). Both approaches are avoidable with a structured capacity planning framework that translates your messaging workload characteristics into specific hardware and configuration requirements.
Apache ActiveMQ®, Devops, Messaging, Middleware, Middleware Optimization, Monitoring, MQ, Observability, SaaS
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.
Apache ActiveMQ®, Messaging, Middleware, Middleware Optimization, Monitoring, MQ
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.
Apache Kafka®, Devops, meshIQ, Middleware, Middleware Optimization, Observability
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.
Apache ActiveMQ®, Middleware Optimization, Monitoring, Observability
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:
Apache ActiveMQ®, Devops, Middleware Optimization, Monitoring
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.
Apache ActiveMQ®, Apache Kafka®, IBM MQ, Integration, meshIQ, Middleware, Middleware Optimization
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.
AIOps, Integration, meshIQ, Middleware, Observability, Streaming
The AI Bottleneck: Why Your Modern Models Are Choking on Legacy and Streaming Data Architecture
Enterprise AI struggles not from inadequate models, but from fragmented data architecture. Critical business data remains trapped in legacy systems or lost in streaming complexity. Success requires bridging the gap between modern intelligence layers and underlying systems of record.
Apache ActiveMQ®
Apache ActiveMQ 5.19.7 and 6.2.6
On May 27, the Apache ActiveMQ project shipped two releases on the same day: 5.19.7 and 6.2.6. Look at the changelogs side by side and the story is clear — this isn’t a feature drop. It’s a coordinated security-hardening pass applied to both maintained branches of ActiveMQ Classic at once, with the same fixes deliberately backported so that no supported line is left behind.
Apache ActiveMQ®
Upgrading to ActiveMQ 5.19.7 or 6.2.6
The latest Apache ActiveMQ releases – 5.19.7 and 6.2.6, both from May 27 – are good releases to apply. They close known dependency CVEs and tighten the broker’s default posture. (We covered the full list of changes in our release overview.) But here’s the catch with any “secure-by-default” update: hardening defaults means turning things off.
IBM MQ, meshIQ, Middleware, Middleware Optimization, Monitoring, Observability
The Silent Killer of IBM MQ®: How One Leaky App Can Crash Your Entire Estate
A single leaky application can crash your entire IBM MQ® estate by consuming OS resources through unclosed connections. Traditional monitoring misses these silent killers. Learn how proactive observability detects OPPROCS anomalies before they trigger infrastructure failures.