Govern Kafka at pipeline scale

Data engineers at Adidas, Mercadona, and HPE use Kpow to trace message flows, diagnose connector failures, and monitor consumer lag across Confluent, MSK, and self-hosted clusters.

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One UI and API for any flavour of Kafka

Kpow connects to any Apache Kafka compatible platform, including MSK, Confluent, Redpanda, Aiven, Instaclustr, and self-hosted clusters.

Multi-cluster observability across providers in a single view
Task-level Kafka Connect diagnosis with stack traces, not status codes
Consumer group lag trending with historical context for root cause analysis

Built for logistics platforms that can't afford blind spots

One view across every cluster and provider

Unified interface across MSK, Confluent, and other providers for inspecting topics, consumer groups, brokers, and schemas.

Catch consumer lag before it becomes a customer problem

Stalled partitions cause stale inventory data and missed delivery windows. Kpow tracks lag over time to identify when and where problems occur.

Governance that scales with your organisation

RBAC, SAML/OAuth 2.0 integration, data masking, and audit logs with user attribution across every cluster your team manages.

Diagnose Connect failures in seconds, not hours

Surface task-level status and stack traces directly in the UI rather than searching logs across multiple systems.

How a national food distributor eliminated Kafka blind spots across 12+ clusters

Challenge

A major food distributor operating across multiple managed Kafka providers struggled with home-grown tooling that could not scale. Teams manually reviewed Connect logs and stitched together dashboards from different providers.

Solution

Single Kpow instance managing 12+ multi-provider clusters
Consumer group monitoring that surfaced a five-minute activity gap revealing a silent API failure
Connect diagnostics reducing troubleshooting from hours to minutes

Results

Single pane of glass across heterogeneous Kafka clusters
Connect errors resolved in minutes instead of hours
Proactive monitoring preventing customer-facing outages
Offset-level inspection catching data flow issues before production impact