# Kafka Health & Risks *Stop Firefighting. Start Predicting.*

Your Kafka monitoring shows what's happening now. Conduktor Insights shows what's about to break.

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## You can't fix what you can't see

Most teams discover Kafka risks during an incident. By then the data loss or the outage has already happened.

- **Silent Data Loss Risks** — RF=1 with active consumers means zero redundancy on data people depend on. One broker failure, and it's gone.
- **Under-Replication** — Topics running below their replication factor right now. Lose one more broker and writes block or data is lost.
- **Partition Problems** — Too few partitions and you can't scale. Skewed partitions overload some brokers while others sit idle.
- **Unknown VIPs** — Which topics are business-critical? Without visibility, the topic feeding 47 services gets the same treatment as a test topic.

## Topic intelligence for health and risk

Conduktor Insights analyzes every topic across your clusters to surface exactly where reliability, performance, and governance need attention.

Risk Analysis

## Identify risks before they become incidents

Find topics that could cause data loss, performance degradation, or service disruptions. Insights correlates replication, volume, and consumer activity to surface risks that simple threshold alerts miss.

- **Low replication factor detection**: Find single-replica topics instantly
- **Partition skew analysis**: Identify uneven data distribution
- **Single partition bottlenecks**: Spot topics that can't scale
- **Actionable remediation recommendations**

Data loss
Cluster efficiency
Load imbalance

VIP Topics & Governance

## Govern your most critical topics

Automatically identify your business-critical topics by consumer activity, throughput, and fanout, then check whether those exact topics are governed. The topics feeding the most services are the ones a schema gap or ad-hoc provisioning hurts most.

- **Automatic VIP detection**: surface topics with high consumer counts, heavy throughput, and wide fanout
- **Schema coverage on critical topics**: which VIP topics have a registered contract, and which leave consumers exposed
- **Serialization consistency**: Avro, JSON, and Protobuf usage across your highest-impact streams
- **Self-service coverage**: which critical topics were provisioned through governed channels versus created ad-hoc

Governance for VIP topics

Topic Health

## Actionable health recommendations

Get a comprehensive health score for your entire cluster and detailed recommendations for each topic that needs attention.

- **Cluster health score**: Instant 0-100 assessment
- **Per-topic configuration recommendations**
- **Retention policy optimization suggestions**
- **Prioritized action items based on impact**

Insights overview

## Insights for every team, not just admins

- **RBAC-aware by default** — Insights respects Console permissions, so developers, SREs, and team leads see the health of the topics they own without a platform admin in the loop.
- **Filter to what you own** — Scope every view by application or topic prefix pattern, so each team works from a view shaped by the topics they touch.
- **Export for review** — Pull any view to CSV for offline analysis, audit evidence, or a regular governance cadence with stakeholders.

## Impact

Measurable impact from teams using Conduktor Insights.

- **Risks surfaced before incidents** — Find RF=1 topics, under-replication, and partition skew before a broker failure turns them into an outage.
- **5 min to first insight** — Instant visibility without agents, code changes, or complex setup.
- **100% topic visibility** — Every topic analyzed across risk, VIP, governance, and health.
- **Visibility for every team** — RBAC-aware views put topic health in the hands of the people who own each topic.

Looking to attribute and cut Kafka spend? See [Kafka Cost Allocation & Chargeback →](https://www.conduktor.io/solutions/use-case/kafka-chargeback)

## Get started with Kafka Health & Risks

Move from reactive to predictive Kafka management. Get a personalized walkthrough of Conduktor Insights.

[Request a Demo](https://www.conduktor.io/contact/demo) [Read Documentation](https://docs.conduktor.io/guide/insights)

## Frequently asked questions

How is this different from Prometheus/Grafana? | Monitoring tells you what's happening now. Insights tells you what's about to become a problem. We analyze patterns across topics to surface risks you'd never think to alert on, like partition skew ratios or topics with RF=1 that haven't failed yet.
Do I need a large Kafka deployment to benefit? | No. Even small deployments accumulate hidden risk: single-replica topics, partition skew, schema gaps, and configuration drift. Insights surfaces these regardless of cluster size.
What about cost and chargeback? | Cost control sits alongside health and risk inside Insights. For the full cost story, including attribution and chargeback, see [Kafka Cost Allocation & Chargeback](https://www.conduktor.io/solutions/use-case/kafka-chargeback).
How does Insights integrate with my existing setup? | Insights connects read-only to your Kafka clusters. No agents to install, no code changes required. Works with Confluent, AWS MSK, Redpanda, and self-managed Kafka. [See the integration guide](https://docs.conduktor.io/guide/insights).