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Live incident correlation
Correlate brokers, topics, and consumer groups in a single view during live incidents.
Master Kafka at peak trading scale
Platform engineers at Article, Mercadona, and Scholastic use Kpow to trace consumer lag, enforce access controls, and inspect live message data across Confluent, MSK, and self-hosted clusters.
Introducing Kpow
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.
Enterprise-scale inspection
Inspect message payloads and schemas at enterprise scale without writing throwaway consumer scripts.
A trail for every operation
Audit trail for every cluster operation, from topic config changes to consumer group resets.
Benefits
Built for retail platforms that can't afford blind spots
Most Kafka tools give you either infrastructure metrics or data-level visibility. Kpow gives you both. Trace consumer lag to its root cause in seconds, inspect messages without custom tooling, and maintain a full governance trail across every cluster in your estate.
Faster incident response during peak trading
Black Friday, flash sales, seasonal spikes. When consumer lag starts climbing across your inventory or pricing pipelines, Kpow lets you correlate broker health, partition distribution, and consumer group state in one view. No more context-switching between Grafana, CLI tools, and CloudWatch. Find the root cause in minutes, not hours.
Inspect live data without building throwaway consumers
Deserialization failures, schema mismatches, poison pills. Kpow's data inspection lets engineers browse live topic data with full schema awareness and field-level masking. Debug production issues by looking at the actual messages, without exposing PII or writing one-off consumer scripts.
Governance that scales with your team
Fifteen squads across merchandising, supply chain, payments, and marketing, all touching the same clusters. Kpow logs every administrative action with user attributes and timestamps, integrates with SAML and OAuth 2.0 for granular RBAC, and streams audit events to Slack, Teams, or your SIEM. Give teams self-service access to Kafka without losing control.
Multi-cluster visibility from a single deployment
Separate clusters for e-commerce, POS, supply chain, and analytics is standard at enterprise retail scale. Kpow manages them all from one deployment. One view for capacity planning, cost attribution, and cross-cluster incident detection, instead of four separate monitoring stacks.
Customer spotlight
How a European supermarket giant gained real-time visibility across 1,000+ stores
A major European retailer operating over 1,000 stores was managing a growing Kafka estate powering inventory, pricing, and order pipelines. Their open source Kafka UI couldn't keep up. Message inspection was limited to small volumes, multi-cluster visibility was non-existent, and the team had no reliable way to debug data quality issues at production scale.
Challenge
Message inspection was limited to small volumes, multi-cluster visibility was non-existent, and the team had no reliable way to debug data quality issues at production scale.
Solution
Kpow replaced their existing tooling with enterprise-scale data inspection across millions of daily messages with full schema awareness, unified multi-cluster management from a single deployment, and real-time audit logging of all administrative operations across clusters.
Results
The retailer reduced mean-time-to-resolution for Kafka incidents during peak trading periods, eliminated reliance on custom consumer scripts for production debugging, and established a complete governance trail for cluster operations, supporting GDPR and PCI DSS requirements.
Resources
Learn from teams running Kafka at scale
See how retailers and e-commerce platforms architect Kafka for peak-season resilience, data quality, and governance without sacrificing developer velocity.
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Read case studyLaunch Kpow in your environment in under 10 minutes
Connect to any Kafka cluster in minutes. Deploy via Docker, Helm, or JAR. Full access for 30 days.