A queue is backing up. An application team is reporting failed transactions. Or while investigating an unrelated routing issue, you discover messages that simply look out of place. Standard IBM MQ message browsing lets administrators and support teams inspect queue contents without consuming or removing messages.[1] But in active enterprise environments, discovering a suspicious [...]
This is Part 5 of a 5-part series exploring The Protobuf Visibility Gap in Kafka Operations | Previous Article A custom Kafka consumer is often the first troubleshooting idea when a team needs to inspect Protobuf data. The logic appears simple: obtain the schema, connect to the topic, deserialize the record, and print the fields. [...]
REST APIs are changing how teams manage enterprise middleware. For IBM MQ teams, that can be a very good thing. REST and Swagger-style API documentation make it easier to script common actions, integrate with change systems, reduce manual work, and give operations teams faster ways to interact with MQ environments. But there is a [...]
Confluent Message Browser vs. Infrared360: Two Protobuf Inspection Workflows This is Part 4 of a 5-part series exploring The Protobuf Visibility Gap in Kafka Operations | Previous Article | Next Article A useful product comparison starts by acknowledging the overlap. Confluent Cloud's message browser and Confluent Platform Control Center can display, filter, validate, download, and [...]
Why Risk and Operations Teams Inspect Business Values Inside Kafka Records This is Part 3 of a 5-part series exploring The Protobuf Visibility Gap in Kafka Operations | Previous Article | Next Article A risk or operations team does not inspect Kafka message content merely because the technology makes it possible. The team inspects content [...]
Kafka Monitoring Can Show the Symptom. Protobuf Record Inspection Can Reveal the Cause This is Part 2 of a 5-part series exploring The Protobuf Visibility Gap in Kafka Operations | Previous Article | Next Article Kafka operations teams depend on monitoring because distributed streaming systems can fail in many ways. Brokers can become unavailable, partitions [...]
Middleware Performance: What Experienced Teams Monitor, Manage, and Automate Middleware performance testing is the practice of validating how messaging and integration infrastructure behaves under realistic transaction patterns—not just whether a queue manager, broker, channel, or application endpoint is technically “up.” IBM’s documentation on monitoring your IBM MQ network emphasizes the value of gathering statistics [...]
Protobuf Visibility Without Schema Registry: A More Flexible Way to Inspect Kafka Records This is Part 1 of a 5-part series exploring The Protobuf Visibility Gap in Kafka Operations | Next Article Protocol Buffers, usually called Protobuf, give development teams an efficient way to serialize structured data. A .proto file defines the fields, types, [...]
Secure MQ Administration: Why MQ Monitoring Alone Isn’t Enough For enterprise IT leaders, IBM MQ is often one of the most critical layers in the technology stack. It moves high-value transactions, connects core systems, and supports applications that the business cannot afford to interrupt. That is why secure MQ administration requires more than another [...]
IBM MQ Configuration Drift: How to Detect and Prevent It with Infrared360 Configuration drift happens when IBM MQ queue managers, queues, channels, listeners, security records, or other object definitions no longer match the approved baseline. In IBM MQ environments, configuration drift can create operational risk, security exposure, compliance gaps, and avoidable troubleshooting work. A queue [...]
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