
Release 95.4: Concurrent data inspect, Strimzi support, and consumer group improvements

Release Info
Kpow can be found on Dockerhub
docker pull factorhouse/kpow:95.4View our Docker quick start guide for help getting started.
Kpow can be found on ArtifactHub
Helm version: 1.0.77
helm repo add factorhouse https://charts.factorhouse.io
helm repo update
helm install --namespace factorhouse --create-namespace my-kpow factorhouse/kpow --version 1.0.77 \
--set env.LICENSE_ID="00000000-0000-0000-0000-000000000001" \
--set env.LICENSE_CODE="KPOW_CREDIT" \
--set env.LICENSEE="Your Corp\, Inc." \
--set env.LICENSE_EXPIRY="2024-01-01" \
--set env.LICENSE_SIGNATURE="638......A51" \
--set env.BOOTSTRAP="127.0.0.1:9092\,127.0.0.1:9093\,127.0.0.1:9094" \
--set env.SECURITY_PROTOCOL="SASL_PLAINTEXT" \
--set env.SASL_MECHANISM="PLAIN" \
--set env.SASL_JAAS_CONFIG="org.apache.kafka.common.security.plain.PlainLoginModule required username=\"user\" password=\"secret\";"
--set env.LICENSE_CREDITS="7"View our Helm instructions for help getting started.
Kpow can be found on the AWS Marketplace
View our AWS Marketplace documentation for help getting started.
Kpow can be downloaded and installed as a Java JAR file. This JAR is compatible with Java versions 17+.
View our JAR quick start guide for help getting started.
Kpow can be downloaded and installed as a Java JAR file. This JAR is compatible with Java versions 11+.
View our JAR quick start guide for help getting started.
Kpow can be downloaded and installed as a Java JAR file. This JAR is compatible with Java versions 11+.
View our JAR quick start guide for help getting started.
For more information, read the Kpow accessibility documentation.
Kpow 95.4 introduces concurrent data inspect queries, Strimzi support, and improved consumer group management and monitoring.
Data inspect improvements
Concurrent workers
Kpow's data inspect engine now supports concurrent access. If multiple team members use data inspect at the same time, you may have noticed occasional "query is queued" messages. This release addresses that.
By default, Kpow runs a single data inspect worker, meaning only one query can execute at a time. Other requests are queued until the worker is free. This is usually fine (queries complete quickly once the result limit is reached) but can become a bottleneck when multiple users are active or long-running queries monopolise the worker. The result limit is the first of SAMPLER_TIMEOUT_MS or 100 consumed records.
You can now increase the number of concurrent workers with the SAMPLER_N_WORKERS environment variable. The right value depends on your team's usage patterns. Each worker maintains its own consumer thread pool (default: 3 threads), so increasing workers will proportionally increase Kpow's resource usage and the number of concurrent consumers reading from your brokers. Worth considering if your cluster is already under significant load.
If the queue buffer is at capacity (default: 1000), requests are rejected and users will see a "Rejected" state for their query.
Data policies and String deserialization
Kpow now allows deserialization of string data even when matching data policies exist, provided the Auto deserializer is in use. The Auto deserializer exhaustively checks all structured message formats (JSON, Avro, Protobuf, etc.) before falling back to String, so the message is genuinely unstructured and not subject to any masking rules.
Base64 deserializer
Kpow now includes a Base64 deserializer in Data Inspect, making it easy for teams working with binary message formats to decode and view raw topic data directly. Like the String deserializer, Base64 is non-redactable if you have data policies configured.
Strimzi support
Kpow now supports connecting to Strimzi Kafka clusters. Strimzi users will need to pull a tagged version of the Docker image:
docker pull factorhouse/kpow:95.4-strimzi
Read more about our Strimzi integration in the docs.
Consumer group improvements
Offset management controls
You can now reset consumer group offsets to start, commit, or end positions with a single click, at either the topic or individual partition level. Previously this required manually entering offset values.
Improved lag calculation for empty consumer groups
We've improved lag calculation for Empty consumer groups. Previously, lag was only calculated for active groups, derived from active member assignments. Since Empty groups have no active members, lag is now calculated from all known assignments.
We've also fixed a bug where offset management actions were not visible for empty assignments in the UI.
Simple consumer groups
Kpow classifies a consumer as "simple" if the group uses manual partition assignment with no group coordination (e.g. legacy consumers). This release brings two changes to simple consumer support:
- Dimensionality: monitor simple consumer groups from Group, Topic, and Broker dimensions
- Offset management: now available for simple consumer groups from the UI and API
Read more about simple consumer management in the docs.
Release v95.4 Changelog
Kpow
Added
- Data inspect workers to handle concurrent queries
- Strimzi support
- Code folding in the Schema Registry editor for Avro and JSON schemas.
- Base64 deserializer in data inspect
Fixed
- Empty consumers reset offset actions available in UI
- Empty consumer lag calculation
- Auto SerDes: allow fallback to String when data policies applied
Changed
- Added simple consumers by dimension in UI
- Added simple consumer offset management actions
- Added
deploymentAnnotationson Helm Charts - Sort tenancy overview UI alphabetically and add sorting options
- Consumer offset management: add controls to reset a topic to start, commit or end positions
- The Kafka internal topic
__transaction_stateis included in Kpow'shide_internal_resourcestenant
Flex
Fixed
- Job chart dropdown presets now use record reads & writes for sorting
Changed
- Added
deploymentAnnotationson Helm Charts

Release 95.4: Concurrent data inspect, Strimzi support, and consumer group improvements
Kpow 95.4 introduces concurrent data inspect queries, Strimzi support, and improved consumer group management and monitoring.

Release 95.3: Memory leak fix for in-memory compute users
95.3 fixes a memory leak in our in-memory compute implementation, reported by our customers.

Release 95.2: quality-of-life improvements across Kpow, Flex & Helm deployments
95.2 focuses on refinement and operability, with improvements across the UI, consumer group workflows, and deployment configuration. Alongside bug fixes and usability improvements, this release adds new Helm options for configuring the API and controlling service account credential automounting.
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