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Kafka Metrics, Dashboards, & Alerts
– Built Into Your Streaming Platform

Kafka Metrics, Dashboards, & Alerts – Built Into Your Streaming Platform

Kafka Metrics, Dashboards, & Alerts – Built Into Your Streaming Platform

Condense gives you Kafka‑grade observability as part of the platform: pipeline‑aware metrics, dashboards, and alerts on managed Kafka in your own cloud

Condense gives you Kafka‑grade observability as part of the platform: pipeline‑aware metrics, dashboards, and alerts on managed Kafka in your own cloud

Condense gives you Kafka‑grade observability as part of the platform: pipeline‑aware metrics, dashboards, and alerts on managed Kafka in your own cloud

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What “Kafka monitoring & Observability” Usually Involves

Effective Kafka monitoring means tracking broker, topic, producer, and consumer metrics, plus logs and traces, usually across several tools

Key Metrics

Key Metrics

Key Metrics

Throughput, latency, consumer lag, broker CPU/memory/disk, offline/under‑replicated partitions, leader elections, topic/partition health
You want Kafka as a Platform Inside Your Own Cloud Boundary

You want Kafka as a Platform Inside Your Own Cloud Boundary

Typical Tools

Typical Tools

Typical Tools

Prometheus + Grafana, Datadog, OpenTelemetry, vendor consoles (Confluent Control Center, Redpanda Console, Kafdrop, Kafka UI, etc.)

Work to Wire It

Work to Wire It

Work to Wire It

Exporter configs, dashboards per cluster, alert thresholds, and integration with incident tooling

You end up with great graphs, but a lot of bespoke work
to make them meaningful for your streaming use cases

You end up with great graphs, but a lot of bespoke work to make them meaningful for your streaming use cases

How Condense Changes Kafka Monitoring

Condense runs on Kafka but exposes observability around the
thing you actually ship: pipelines and real‑time applications

Condense runs on Kafka but exposes observability around the thing you actually ship: pipelines and real‑time applications

Condense runs on Kafka but exposes observability around the thing you actually ship: pipelines and real‑time applications

CondenseDIY Kafka Monitoring Stack
FocusPipelines, connectors, and cluster health.​Brokers, topics, raw metrics per node.​
ToolsObservability built into Condense UI.​Prometheus, Grafana, Datadog, Kafka UIs, etc.​
SetupPre‑configured views and alerting patterns.​Exporters, dashboards, alerts per environment.​

When Condense is Better Than “Just Another Kafka Monitoring Tool”

// You’re monitoring clusters but still firefighting pipelines”

You can see broker and consumer lag metrics but still spend time correlating which topics
and apps are affected; Condense attaches metrics directly to pipelines and connectors.​
You can see broker and consumer lag metrics but still spend time correlating which topics and apps are affected; Condense attaches metrics directly to pipelines and connectors.​

// Each team built its own Kafka dashboard UI

Platform, data, and app teams each maintain separate dashboards and alert
rules; Condense centralizes pipeline and cluster observability in one place.​
Platform, data, and app teams each maintain separate dashboards and alert rules; Condense centralizes pipeline and cluster observability in one place.​

// You want observability to be part of the streaming platform, not bolted on

Instead of treating Kafka monitoring as a separate project, Condense
ships it as part of how pipelines are designed, deployed, and governed.​
Instead of treating Kafka monitoring as a separate project, Condense ships it as part of how pipelines are designed, deployed, and governed.​

Frequently Asked Questions (FAQs)

Does Condense replace Prometheus/Grafana/Datadog?
Condense provides Kafka and pipeline‑level observability out of the box and can coexist with tools like Prometheus, Grafana, or Datadog; many teams export Condense metrics into their existing stack for centralized SRE views while product teams use Condense’s UI for pipeline‑centric insight.
Does Condense replace Prometheus/Grafana/Datadog?
Condense provides Kafka and pipeline‑level observability out of the box and can coexist with tools like Prometheus, Grafana, or Datadog; many teams export Condense metrics into their existing stack for centralized SRE views while product teams use Condense’s UI for pipeline‑centric insight.
Does Condense replace Prometheus/Grafana/Datadog?
Condense provides Kafka and pipeline‑level observability out of the box and can coexist with tools like Prometheus, Grafana, or Datadog; many teams export Condense metrics into their existing stack for centralized SRE views while product teams use Condense’s UI for pipeline‑centric insight.
Can Condense alert us before consumer lag or failures impact SLAs?

Yes. Condense supports alerting on critical metrics such as consumer lag, error rates, and throughput drops on key pipelines so teams can intervene before incidents violate SLOs.
Can Condense alert us before consumer lag or failures impact SLAs?

Yes. Condense supports alerting on critical metrics such as consumer lag, error rates, and throughput drops on key pipelines so teams can intervene before incidents violate SLOs.
Can Condense alert us before consumer lag or failures impact SLAs?

Yes. Condense supports alerting on critical metrics such as consumer lag, error rates, and throughput drops on key pipelines so teams can intervene before incidents violate SLOs.
Where does Condense run for observability data?

All metrics are collected from Kafka and the Condense platform running in your own cloud accounts (BYOC), respecting your network, security, and data‑residency policies
Where does Condense run for observability data?

All metrics are collected from Kafka and the Condense platform running in your own cloud accounts (BYOC), respecting your network, security, and data‑residency policies
Where does Condense run for observability data?

All metrics are collected from Kafka and the Condense platform running in your own cloud accounts (BYOC), respecting your network, security, and data‑residency policies
What Kafka metrics can I see in Condense?

You can expose core Kafka metrics (throughput, latency, consumer lag, under‑replicated/offline partitions, broker resource usage) mapped to clusters, topics, and pipelines, plus platform‑specific metrics like pipeline deployment status and connector health.
What Kafka metrics can I see in Condense?

You can expose core Kafka metrics (throughput, latency, consumer lag, under‑replicated/offline partitions, broker resource usage) mapped to clusters, topics, and pipelines, plus platform‑specific metrics like pipeline deployment status and connector health.
What Kafka metrics can I see in Condense?

You can expose core Kafka metrics (throughput, latency, consumer lag, under‑replicated/offline partitions, broker resource usage) mapped to clusters, topics, and pipelines, plus platform‑specific metrics like pipeline deployment status and connector health.