Monitor Kafka Streams Health Metrics in Confluent Cloud

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    "url": "https://www.confluent.io/blog/monitor-kafka-streams-health-metrics",
    "title": "Monitor Kafka Streams Health Metrics in Confluent Cloud",
    "excerpt": "Monitor Kafka Streams health metrics in Confluent Cloud.\n\nIt's 3 a.m., and an alert fires: Your critical Kafka Streams application is lagging. The frantic troubleshooting begins. Is it a consumer group rebalance? You start searching through application logs across multiple pods. Is it a problem with the Apache Kafka(R) cluster itself? You switch to your cluster monitoring dashboards to check broker health. Or is there a silent bottleneck hidden deep in your application code? Without the right instrumentation, you're flying blind. After 30 minutes of digging through disparate tools, you're still just guessing.\n\nConfluent Enterprise has heard this story from countless developers and operators. That's why Confluent Enterprise is excited to announce the launch of key Kafka Streams application health metrics directly in the Confluent Cloud Console. Now, you can quickly understand application state, identify potential bottlenecks, and monitor state store health without writing custom instrumentation code. This means less time firefighting, faster mean time to resolution (MTTR) for production incidents, and more developer cycles spent building features that drive your business. The best part? All you need to do is upgrade your Kafka Streams client library to any version above 4.0.\n\nInstantly see your application's health and pinpoint problem instances.\n\nThe new Kafka Streams page...",
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curl https://signals.autobound.ai/v1/signals/13d058e8-3710-445c-bcb7-a5c5778b8ef6 \
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curl -X POST https://signals.autobound.ai/v1/companies/enrich \
  -H "X-API-KEY: $AUTOBOUND_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"domain":"confluent.io","limit":20}'