Autonomous Cost Optimization Platform

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    Reclaim waste in real time

    Pepperdata instructs the scheduler to remove capacity from overprovisioned applications

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    Maximize resource utilization continuously

    Pepperdata intelligently increases resource utilization by evaluating actual instead of allocated resource utilization

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    Optimize autoscaling second-by-second

    Pepperdata ensures new instances are added only when existing instances are fully utilized

Additive to All Existing Approaches

After you’ve implemented nearly four tools from your toolbox, turn on Pepperdata.
We’ll still save you money.

Visibility tools

Cost observability dashboards

Spot instances

Reserved instances

Savings Plans

Manual tuning

Configuration Tweaks

Instance rightsizing

Container rightsizing

Pod Rightsizing

Cloud Autoscalers

Cloud-provided cost management tools

Reduce Operational Costs, Maximize Savings


Increased CPU utilization compared to the AWS autoscaler


Autoscaling cost savings over the default EKS autoscaler


Instance hours reduction

Run more workloads with Capacity Optimizer

Customers Love Pepperdata

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“Pepperdata lets us see inside our ephemeral clusters even after they’ve been deleted.”

Being able to see the memory, cpu, io and other cluster metrics help us to appropriately size the clusters and tune our jobs.
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gartner peer insights

Chief Data Architect, DPI

“The Missing Link In Large Scale YARN Cluster Management”

Getting up and running effectively took a little time, but now that we use of the product for ongoing monitoring and operations it’s hard to understand how we were getting by without it.

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Sr. Software Engineer , Cloud Infrastructure

“Best for spark application monitor”

Easy to navigate for all metrics related to spark job, capture all yarn-related metrics. we can search by application id easily. multiple realm is also useful for EMR spark

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Consultant, 08/28/2022

“Pepperdata helps us in optimizing our day to day tasks.”

Its easy to go through the UI and get the stats of the tasks and see the errors and optimize them accordingly. Review collected by and hosted on

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Associate Software Engineer, 08/23/2022

“Pepperdata & Big Data Positives”

Pepperdata has been essential for my team. We use Apache data aggregation tools at scale; Pepperdata helps us to monitor memory and CPU usage with easy-to-read visualizations, warnings, and metrics.

Try Us for Free for 15 Days


Step 1:

Install Pepperdata’s bootstrap script on your cluster


Step 2:

Login to your customer dashboard to visualize your cluster’s waste and savings


Step 3:

Start saving immediately—up to 38%


How is Pepperdata able to reclaim waste in the cloud that other alternatives cannot?

Pepperdata Capacity Optimizer is a radical new way to minimize the inherent waste of big data and Kubernetes systems in the cloud and increase utilization in on-premises environments. By instructing the YARN or Kubernetes scheduler to consider the actual resource utilization instead of allocated resources, Capacity Optimizer takes advantage of unused resources to schedule additional jobs. Capacity Optimizer is thus able to reclaim waste, maximize resource utilization, and optimize autoscaling in the cloud and on premises. In the cloud, Capacity Optimizer lowers the monthly cloud bills for some of the largest and most complex environments in the world. On premises, Capacity Optimizer helps you extend the life of your infrastructure investment. Capacity Optimizer operates autonomously, continuously, and in real time in both YARN and Kubernetes environments.

If I already use my cloud’s autoscaler, why do I need Pepperdata?

Pepperdata makes your current cloud autoscaler work better. Cloud autoscaling is implemented based on resource allocation. Cloud autoscalers add more instances when the scheduler cannot add more applications to the cluster because all the existing resources have already been allocated. Once the configured resource utilization is achieved, the autoscaler adds more instances. Pepperdata enables the scheduler or cluster manager to schedule workloads based on resource utilization instead of resource allocation. Pepperdata not only maximizes the utilization of each of the existing instances, it also ensures that the new instances are added only when the existing instances are fully utilized in an autoscaling environment. Pepperdata manages the autoscaling behavior of the cloud platforms so that you don’t have to.

What workloads can Pepperdata optimize?

Pepperdata works with some of the world’s largest and most complex, multi-tenant, and highly-scaled computing environments in the world, including two of the Fortune 10 and others in the Fortune 100 and 500. Pepperdata supports most big data analytics and querying technologies on premises and in the cloud (e.g. Amazon EMR, Amazon EKS), including Spark, MapReduce, Tez, Hive, Impala, Presto/Trino, along with AI/ML and ETL workloads. In Kubernetes environments, Pepperdata supports all batch workloads and microservices.

How long does it take to get up and running with Pepperdata?

Pepperdata typically installs within an hour on most enterprise environments. Within a few hours after that, you will start to see waste and cost savings on your Pepperdata-provided dashboard. You should start to see the hard cost savings on your next cloud bill.

How can I justify the cost of purchasing Pepperdata to my management team?

Pepperdata typically pays for itself in hard cloud cost savings within a few months of installing. One of the largest companies in the world recently installed Pepperdata on a single cluster and shaved 28% off their cloud cost. In the case of this customer, that cost savings translates to over $400,000 in reduced cloud costs per year—for a single cluster.

In addition, with Pepperdata, you will also enjoy the soft cost savings of reduced personnel costs. With Pepperdata, you won’t need dedicated engineers constantly monitoring your systems. In addition, your finance personnel will no longer need to corral your engineering teams to implement recommendations. With Pepperdata, your development teams can be freed from the tedium of tweaking and tuning code to focus on high-value, innovative activities to grow your business.

Does Pepperdata work with other cloud cost optimization solutions like Granulate, Cast.AI, Densify, and cloud vendor-provided tools?

Yes, Pepperdata is complementary and accretive to all other solutions in the marketplace. Continue to do what you’re doing to optimize your cloud operations, using your existing tooling and processes. Then implement Pepperdata on top of it to achieve an additional cloud cost reduction.

Can’t I just hire another engineer to do what Pepperdata does?

If you use a handful of instances in the cloud, an engineer might help you optimize that workload. However, with larger-scale operations, it is impossible to do what Capacity Optimizer does. Pepperdata Capacity Optimizer works directly with the native YARN or Kubernetes scheduler to make hundreds and thousands of decisions in real time, around the clock. Capacity Optimizer operates in the background, autonomously and continuously, optimizing your cloud or on-premises environment in a way that far exceeds what even the most diligent engineer would be able to accomplish.

How safe, secure, and reliable is Pepperdata?

Pepperdata is built upon the same safe, secure, reliable platform that has been deployed to some of the most demanding enterprises for over a decade, including global banks and Fortune 10 companies. We would be happy to provide you a security white paper and engage with your teams on any questions they have about security and reliability.

Can I try Pepperdata for free in my environment?

Yes! We welcome the opportunity to bring the same cost savings we see with leading enterprises into your environment. Book a meeting with us to get up and running with a free trial.

How is Pepperdata priced?

Pepperdata’s pricing is based on your usage. Book a meeting with us to get up and running with a free trial.

Take a free 15-day trial to see what Big Data success looks like

Pepperdata products provide complete visibility and automation for your big data environment. Get the observability, automated tuning, recommendations, and alerting you need to efficiently and autonomously optimize big data environments at scale.