Cloudera Performance Monitoring: Troubleshoot and Optimize Using AI

Cloudera coverage

CDP Private Cloud

CDP Public Cloud

Legacy CDH

Legacy HDP

Spark

Hive

Impala

MapReduce

HBase

Kafka

YARN

HDFS

Ozone

Tez

Oozie

NiFi

——— The reality of running Cloudera

Powerful. Unforgiving.
^{And the people who knew it best are moving on.}

The stack hasn't gotten simpler. The team that ran it has gotten smaller. And the failures keep coming.

Failures hide in long logs

A Spark job fails at 3 AM. Hours of YARN log archaeology before anyone knows why — let alone how to prevent it next time.

Waste compounds quietly

Storage and compute leak in a hundred small places. Nobody notices until the hardware renewal quote arrives.

Expertise is leaving the building

The engineers who knew the stack are retiring or moving to cloud-native roles. Tribal knowledge walks out the door.

Proud member of the Cloudera Connect partner program

——— What Unravel does for Cloudera

Three things, ^{done deeply.}

Built on a decade of Hadoop, Spark, and Impala telemetry. Tuned for the realities of running Cloudera in 2026.

Automatic root cause

Why a job failed. Why a query slowed. In minutes.

Full execution graph — every stage, container, and config
Auto-detection, no rule-writing or model training
Findings tied to specific lines of code or settings
Every engine in the Cloudera stack, one workflow

Waste reduction

Rightsize what's oversized. Reclaim what's unused.

Continuous — not a quarterly audit
Quantified in TB and dollars before you act
Owner and team attribution on every finding
Compute, storage, and data lifecycle in one view

Reliability at scale

Catch failures before users do.

Predictive, not just after-the-fact alerts
SLA-first, with breach attribution to root cause
Trend analysis catches slow drift before it breaks
Built for the realities of multi-tenant clusters

——— Root cause, automatically

Stop digging through ^{YARN logs.}

Unravel reads the full execution graph and tells you exactly why a job failed or slowed — across every engine, without anyone writing a rule.

Auto-diagnosed failure modes

Across every Cloudera engine.

Data skew

Executor OOM

Shuffle spill

GC pressure

Bad joins

Container kills

Stage retries

Stale statistics

Full scans

Memory limits

Queue starvation

Slow stages

Cluster throttle

Misconfigured executors

——— Waste reduction

Reclaim what Cloudera _{quietly leaks.}

Clusters running on headroom that never gets used. Tables nobody has touched in months. Queues fighting for the same slots. Unravel surfaces it, sizes it, and gives you a path to fix it.

^30–50%

Cluster rightsizing

Match cluster and YARN queue capacity to actual workload patterns. Most environments are oversized by a third or more.

^{Cold data}

Identified and quantified

Hot / warm / cold classification across HDFS, Ozone, and cloud storage. Know what to archive, tier, or delete.

^{Queues tuned}

Eliminate starvation

Balance multi-tenant workloads. Catch queues hogging slots and pipelines waiting on capacity they'll never get.

^Forecasted

Plan with data, not gut feel

Capacity projections grounded in usage trends. Make hardware refresh and scale-up decisions defensible.

——— One pane. Every deployment.

Whether you're on-prem, in CDP Public Cloud,
^{or somewhere in between.}

Unravel runs across CDP Private Cloud, CDP Public Cloud, and legacy CDH/HDP — in a single view. Same diagnoses. Same waste signals. Same SLA tracking. No matter where the workload lives.

CDP Private Cloud

Full on-prem depth

End-to-end coverage from cluster down to executor. The visibility your data center has always needed.

CDP Public Cloud

Native cloud support

Same depth across AWS, Azure, and GCP deployments. Including Data Engineering, Data Warehouse, and DataFlow.

Legacy CDH & HDP

Not left behind

Continued depth for clusters not yet on CDP. Operate them with confidence while you plan what's next.

——— Where Cloudera teams use Unravel

Four jobs we do ^{every day.}

The recurring work that Cloudera teams hand off to Unravel — and stop spending evenings on.

Recommended resources

Diagnose failures in minutes. Surface waste before it compounds. Hold SLAs across CDP Private Cloud, Public Cloud, and legacy clusters — from one place.