In the context of Maximo and its integration with KAFKA, what common issue might require troubleshooting?

Question

Options

• AMessage serialization errors
• BQueue partition imbalances
• CInadequate topic retention policies
• DExcessive consumer group lag

• A
  10% (3)
• B
  3% (1)
• C
  3% (1)
• D
  84% (26)

Explanation

Excessive consumer group lag is correct because in Maximo-Kafka integrations, Maximo typically acts as a consumer subscribing to Kafka topics (e.g., for work orders, asset events, or IoT data). When Maximo's processing throughput can't match the rate at which messages are produced, the offset gap between the latest message and the last processed message (consumer lag) grows - a chronic, operational issue requiring active monitoring and tuning. The other options describe real Kafka concepts but don't fit as the primary Maximo-specific concern: message serialization errors (A) are configuration-time failures caught early in development, not recurring operational problems; queue partition imbalances (B) conflates Kafka's partition model with traditional queue terminology and is more of a cluster-admin concern than a Maximo integration issue; inadequate topic retention (C) is a setup misconfiguration rather than an ongoing integration troubleshooting scenario.

Memory tip: Think of Maximo as a slow reader in a fast-moving library - "consumer lag" is how many unread books pile up. If Maximo can't keep pace with the Kafka stream, the lag grows and events get stale. Lag = Maximo falling behind.

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