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.
Blog
Your AI Agents Can Take Action Now. Can You Prove They Should Have?
Enterprise AI agents clear every demo and pilot, then hit a compliance wall. The gap isn’t technology—it’s architecture. Discover why governance must sit inside the execution flow across six control points, not bolt on afterward as an afterthought at input and output only.
Article
The foundation agentic AI can’t function without
Why agentic AI requires unified operational context across middleware and how telemetry correlation enables predictive insights at scale.
Press Release
2026 Open-Source Messaging Broker Analysis Benchmarks Enterprise-Grade Guaranteed Delivery Across Apache ActiveMQ®, Apache Artemis™, and RabbitMQ®
New meshIQ study examines JMS, native, and AMQP 1.0 workloads to reveal how protocol choice, batching, and architecture shape durable messaging performance.
Article
The Future of Intelligent Retail Starts With a Connected Foundation
Agentic AI in retail requires unified middleware visibility and end-to-end transaction tracking across all systems and partners.
Blog
ActiveMQ Upgrade & Patching Strategy: The Expert Guide
On October 27, 2023, the Apache Software Foundation published CVE-2023-46604, a CVSS 10.0 remote code execution vulnerability in Apache ActiveMQ® that allowed unauthenticated attackers to execute arbitrary code by exploiting the OpenWire protocol’s ClassInfo deserialization.
Blog
ActiveMQ Performance Benchmarks: A Complete Methodology Guide
Most ActiveMQ performance benchmarks are wrong, not slightly off, but fundamentally invalid for capacity planning. Performance benchmarking done incorrectly is worse than not benchmarking at all. A number that looks like a throughput measurement but was collected without JVM warmup, without latency percentiles, with the load generator co-located on the broker host, and while producer
Factsheet
AgentGuard
AI agents are no longer just generating responses—they’re executing decisions. AgentGuard governs those decisions while they happen.
Blog
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.
Blog
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.
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.