Table of Contents: What is Spark Performance Tuning? The Challenge of Apache Spark Performance Tuning Choosing the Partition and Executor Size Real-Time Cost Optimization Solution for Spark Performance Tuning Case Study: How Extole...
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...
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...
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...
It’s never been easier to take a risk-free spin of Pepperdata in your testing or production environment. Within a few days, you’ll understand exactly how much waste is in your system and exactly what you can do to eliminate it once and...
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...
“Why is Spark So Slow?” 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...
Read the case study to discover how Pepperdata improved this client’s big data infrastructure processes and slashed their cloud costs.
Read the case study to discover how Pepperdata improved this client’s big data infrastructure processes and slashed their cloud costs.
Here at Pepperdata, we’ve been on a number of sales calls lately where there’s a sense of incredulity on the other side of the video screen. How does Pepperdata extract as much as 50 percent in cost savings from some of the most...
The Pepperdata 2021 HiBench Benchmark Report demonstrates the effect Pepperdata Capacity Optimizer has when implemented on top of an AWS Custom Auto Scaling Policy. The benchmarking work in this report uses HiBench, an industry-standard ...
You’ve optimized your Amazon EMR or Amazon EKS platform, but there’s likely still waste in your applications. Quantify and eliminate that waste with Pepperdata....
Apply the “Sauce” and Reduce the Cost: Right Now, for Free, and Without Any Sales Pitches Pepperdata’s cost slashing capabilities are legendary: for the last decade, we’ve been doing just that for some of the largest and most demanding...
No matter how complicated your monthly cloud bill, all spend in the cloud is premised on a very simple formula: Cost = Usage x Rate In simple terms, at any given moment, your cloud cost is determined by how much of a given resource...
Explore the differentiators between Pepperdata Capacity Optimizer Classic and Next Gen to help you decide which version best suits your app environment....
Pepperdata Capacity Optimizer Next Gen reduces cloud costs for both microservices and Spark workloads continuously, autonomously, and in real time....
IT spend on big data systems in 2023 is forecasted to be $222 billion (Statista.com: Information spending on data center systems worldwide from 2012 to 2023). Actual monetary cost is just one parameter: infrastructure resources,...
Cloud FinOps is rapidly becoming popular among organizations in today’s digital age due to its ability to help manage financial operations more efficiently. This is because it allows organizations to track, measure, and optimize...
Autoscaling in Kubernetes, or in any cloud environment, is essential for enterprises as it enables users to automatically add and remove instances to meet the demands of the workload. It’s an effective cloud cost optimization approach,...
Reduce cost by up to 38% in the cloud and increase throughput on-premise with zero code changes and no manual intervention.
Reduce your Amazon EMR costs by up to 50% with zero code changes.
Reduce your Amazon EMR costs by up to 50% with zero code changes.
Read the datasheet to learn how Pepperdata reduces cost by 40% and resources for big data workloads on Amazon EKS.
Read the case study to discover how Pepperdata improved this client’s big data infrastructure processes and slashed their cloud costs.
Bill shock stemming from surprisingly high cloud bills remains a persistent concern for enterprises that have migrated to the cloud. Cloud service providers often market the cloud as a highly effective means to lower operational costs....
Magnite, the biggest independent sell-side advertising solution, empowers publishers with their innovative monetization technology. Trusted by the world’s foremost agencies and brands, Magnite’s advertising technology...
Site reliability engineering (SRE) is fast becoming an essential aspect of modern IT operations, particularly in highly scaled, big data environments. As businesses and industries shift to the digital and embrace new IT infrastructures...
Despite its ability to handle large data sets and perform resource-intensive computing processes, Spark can struggle to perform at an optimum level. When this happens, companies are at risk of inefficiently utilizing their compute, spend...
Today, we have some exciting news to share: Pepperdata Capacity Optimizer now supports Azure Kubernetes Service (AKS). This means users of AKS are able to automatically optimize their workloads running on the Azure Kubernetes Service....
You’d probably struggle to find a big data practitioner who’s never heard of Apache Spark or used big data with Spark. We’d even go so far as to say it’s near impossible—and that’s for good reason. Spark is well known because it’s...
Are you sure your Hive queries are performing at their best? You might be surprised. Apache Hive is the most prevalent query engine used in many of the largest enterprise environments today, but that doesn’t mean it works...
Cloud computing is one of the great technologies of our era. As such, enterprises everywhere are in a hurry to migrate to the cloud. However, one of the less-talked-about trends of our time is cloud repatriation: the process of...
Thinking about using Google Dataproc as your cloud vendor? We can see why. Google Dataproc is a powerful tool for analytics and data processing, but to get the most out of it you have to ensure you use it properly. We’re going to...
Autoscaling from cloud service providers offers valuable elasticity for big data deployments. But, based on workload peak needs, it also leads to wasted resources and inflated costs. You need a way to optimize your resource utilization a...
Our “Pepperdata Profiles” series shines a light on our talented individuals and explores employee experiences. This month, we talked with Kirk Lewis, a Pepperdata field engineer. Kirk discussed what is unique about the Pepperdata...
Our “Pepperdata Profiles” series shines a light on our talented individuals and explores employee experiences. This week, we talked to Kimoon Kim, a veteran Pepperdata software engineer. Kimoon elaborates on how Pepperdata products...
Our “Pepperdata Profiles” series shines a light on our talented individuals and explores employee experiences. This week, we talked to Jeremy Hay, who has been central to the company’s front-end development for six years. What,...
Financial services organizations are challenged to deliver effective big data and digital strategies at two levels. On one hand, each line of business needs to address their unique operational requirements and client expectations. On...
Our “Pepperdata Profiles” series shines a light on our talented individuals and explores employee experiences. This week, we talked to Ruchi Garg, an experienced product manager who is passionate about her work and the world of...
As any good leader knows, a team is only as good as its people. And at Pepperdata, we have some of the very best. Our “Pepperdata Profiles” series shines a light on our talented individuals and explores employee experiences. This week,...
Large, multi-tenant enterprise and cloud big data systems are complex. As these platforms scale, it becomes very difficult to maintain visibility across your entire big data stack, from the hardware up to the application level. Before yo...
Apache Hive is the most prevalent query engine used in many of the largest enterprise environments today. To get the most out of the engine, it’s important to perform Hive performance tuning. But before we dive into that, let’s cover...
Apache Spark™ has quickly become an open-source framework, and the only unified analytics engine, that combines large-scale data processing with state-of-the-art machine learning and AI algorithms. However, Apache Spark™...
Apache Spark™ is a full-fledged data engineering toolkit that enables you to operate on large data sets without worrying about the underlying infrastructure. It achieves high performance for both batch and streaming data, using...
Chad and I founded Pepperdata to help every company benefit from the same kinds of massive data systems we'd built and used at places like Inktomi, Yahoo, and Bing. I managed Yahoo's web search engineering team – the first commercial...
Looking for a safe, proven method to reduce waste and cost by up to 47% and maximize value for your cloud environment? Sign up now for a free Cost Optimization Proof-of-Value to see how Pepperdata Capacity Optimizer can help you start saving immediately.
