#operations
15 posts.
The Kafka Partition Looks Fine, but the Disk Is Full
Kafka 4.3 adds Partition Size Percentage metrics for retention pressure, but Kafka operators still need physical free-space monitoring for log.dirs.
AI Learned Code, but Software Learns in Operation
AI can absorb enormous written knowledge, but usable software improves through running instances, operational feedback, and production reality.
Kafka Streams After 4.2: Two Changes That Make Failures Less Painful
Kafka Streams operations often hurt around bad records and rebalances. This post explains how DLQ support and the Streams Rebalance Protocol change the operating model after Kafka 4.2.
Before Removing a Kafka Broker, Cordon First
Apache Kafka 4.3 introduced cordoned.log.dirs. This post explains what it means, how to use it, and why disk or broker decommissioning should start by blocking new replica placement.
Kafka 4.0 Consumer Rebalance: Coordination Moves to the Broker
Apache Kafka 4.0 made the new rebalance protocol generally available. This post explains what changes from the old protocol, why broker-side assignment matters, and what it means operationally.
Why Did Kafka OOM When Memory Was Still Available?
Kafka broker memory is not just heap and page cache. Direct buffers can fail allocation even when system memory and heap graphs still look healthy.
Why Turn Immutable YAML Logs into Full Objects?
A practical look at why stream/event-based YAML processing can be a better fit than building a full DOM or object tree when high-volume YAML logs only need filtering.
Can Kafka Client Metrics Really Close the Observability Gap?
A practical look at Kafka client telemetry from KIP-714: how it works, which metrics it can collect, how to configure it, and where the operational limits are.
The Large Payload Kafka Handles Well, and the One It Should Not Carry
Kafka is strong at high-volume event streams, but large file payloads can create storage amplification across the whole system.
The Kafka Broker Slowed Down, but Kafka Was Not the Cause
A practical incident-style walkthrough of a Kafka broker throughput drop, follower replicas falling out of ISR, and the storage path contention below the VM.
Your Kafka Looks Balanced. Your Brokers Disagree
Leader partition counts can look even while Kafka brokers carry very different network and storage load. This post explains how to read balancing through partition weight.
Consumer Groups Are Not Queues: What Kafka Share Groups Change
Why Kafka Share Groups were added, how they differ from traditional Consumer Groups, and when to use them.
Five Roles Redis Plays in AI Applications
A practical look at how Redis supports AI applications as a cache, session store, retrieval helper, async work layer, and operational control plane.
Consumer Lag Is Not a Health Score: Thinking in Kafka Consuming Pressure
A practical way to read Kafka Consumer Lag together with producer rate and consumer group capacity instead of treating lag as an absolute health signal.
Still Using Redis Only as a Cache? A Practical Look at Redis Streams
A practical look at Redis Streams as an append-only event log with consumer groups, pending messages, acknowledgements, and lightweight event processing.