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Pepperdata

Reduce Cloud Costs and Recover Application Waste | Pepperdata Capacity Optimizer

Pepperdata has saved companies over $200M over the last decade by reclaiming application waste and increasing your hardware utilization to reduce costs in the cloud. It completely eliminates the need for manual tuning, applying recommendations, or changing application code: it's autonomous, real-time cost optimization.

You Can Solve the Application Waste Problem

If you’re like most companies running large-scale data intensive workloads in the cloud, you’ve realized that you have significant quantities of waste in your environment. Smart organizations implement a host of FinOps activities to ameliorate or address this waste and the cost it incurs, things such as: … and the list goes on. These are infrastructure-level optimizations.

Pay-As-You-Go with Pepperdata Real-Time Cost Optimization

Gartner, Inc. estimates that worldwide spending on public cloud services is forecast to grow 20.4% to total $678.8 billion in 2024. With many organizations incorporating FinOps practices to govern how they spend their money in the cloud, Real-Time Cost Optimization is essential to saving money. In particular, as the market for Generative AI workloads continues to explode, organizations will need to consider a range of cost-savings models to extract optimal efficiency.

A Quick Guide to Get You Started with Spark on Kubernetes (K8s)

Apache Spark versus Kubernetes? Or both? The past few years have seen a dramatic increase in companies deploying Spark on Kubernetes (K8s). This isn’t surprising, considering the benefits that K8s brings to the table. Adopting Kubernetes can help improve resource utilization and reduce cloud expenses, a key initiative in many organizations given today’s economic climate.

How Extole Discovered and Saved 30% By Reducing Application Waste

Not every application has wasted capacity in it—or do they? Watch Ben Smith, VP Technical Operations at Extole, discuss how he discovered that there's around 30% of application waste within every running app, and how Extole went about saving that wasted capacity.

Pepperdata Reduces the Cost of Amazon EMR on EKS by 42.5%

With Kubernetes emerging as the de facto operating system of the cloud, capable of running almost anything, it’s not a surprise that many enterprises are rapidly porting their Apache Spark workloads to Kubernetes. This includes migrating Amazon EMR workloads to Amazon EKS to gain the additional deployment and scaling benefits of a fully managed service like Amazon EKS.

Why is Spark So Slow? 5 Ways to Optimize Spark Today

When Apache Spark works well, it works really well. Sometimes, though, users find themselves asking this frustrating question. Spark is such a popular large-scale data processing framework because it is capable of performing more computations and carrying out more stream processing than many other data processing solutions. Compared to popular conventional systems like MapReduce, Spark is 10-100x faster.

Pepperdata Capacity Optimizer Next Gen: How Pepperdata Can Save 30% Off Your Cloud Bill

Pepperdata Capacity Optimizer Next Gen is the only cost optimization solution for both Apache Spark and microservices that can save you between 30–47% on your cloud bill. No matter if you try to manually tune your applications on your own, an estimated one-third of what is spent every day on cloud computing resources is wasted. While you might have cost-optimized your infrastructure with things like savings plans, spot and reserved instances, that doesn’t address the waste inherent in your applications.