Improve Cloudera Performance With Datadog

Monitor Cloudera & All Layers of Your Data Analytics Stack

Easily analyze the health of your Cloudera clusters and improve overall cluster performance with dedicated dashboards for critical components - including HDFS, YARN, Namenode, Spark, Zookeeper, Hive, and Apache Impala
Create custom alerts for key metrics such as CPU usage, memory usage, and disk utilization; get notified on any issues before they become critical
Optimize resource allocation and improve capacity planning; easily identify underutilized or overutilized nodes

Identify critical issues quickly with real-time service maps, AI-powered synthetic monitors, and alerts on latency, yarn application, and queue-size metrics
Resolve detected problems faster with infrastructure metrics, distributed request traces, and logs all within one platform
Conduct root cause analysis quickly and troubleshoot performance issues before a real user is impacted with full-stack correlation

Gain a comprehensive understanding of your data usage and workloads with 700+ vendor-backed integrations including Oracle, Hadoop, Hive, Cassandra, AWS Kinesis, and Apache Spark
Discover in-depth insights into your entire data architecture with customizable, drag-and-drop dashboards available out-of-the-box for all of Datadog’s integrations
Monitor the health of all your on-premise servers, cloud services, containers, databases, applications, and more in one place

Easily verify that your streaming architecture is highly available through dashboard reporting, synthetic tests, and App Analytics
Track all key service-level indicator metrics in real time with Datadog, including availability, response times, reliability, error rates, and throughput
Automatically detect unanticipated outliers, anomalies, and errors with Watchdog
Proactively prevent outages and errors by alerting on metric forecasts or specific data thresholds
Eliminate false-positives and receive smarter alerts that account for daily, weekly, and seasonal fluctuations or cascading event failures