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Items Tagged: Pepperdata

news / Blog

Visualizing (and Optimizing) Cluster Performance

Clusters are the scale-out way to go in today's data center. Why not try to architect an infrastructure that can grow linearly in capacity and/or performance? Well, one problem is that operations can get quite complex especially when you start mixing workloads and tenants on the same cluster. In vanilla big data solutions everyone can compete, and not always fairly, for the same resources. This is a growing problem in production environments where big data apps are starting to underpin key business-impacting processes. Pepperdata was formed to help deliver consistent big data application performance. They lay in their solution into Big Data clusters (i.e. YARN/Hadoop, Spark...) and then can dynamically optimize runtime operations - tuning and tweaking at sub-second intervals to help guarantee required QoS to key workloads....

  • Premiered: 09/29/15
  • Author: Mike Matchett
Topic(s): Pepperdata Big Data Cluster Management Chargeback Hadoop Spark Performance Optimization
Resources

Optimizing Big Data Clusters in Production - Performance, Capability, and Cost

Come join us as we learn how to tackle and manage big data application performance. First, Taneja Group Sr. Analyst Mike Matchett will present his take on how enterprise IT is now being challenged to support big data applications in real production environments. He'll discuss why too many enterprises haven't been as successful as they should in taking advantage of their big data opportunities - in many cases losing out to competitors. He'll explore what agile IT/devops really needs to do to not only effectively host, but deliver top-notch, consistent big data performance with the smallest infrastructure cost. 
Then Sean Suchter, co-founder and CEO at Pepperdata will present their compelling approach to solving big data cluster performance challenges. He'll demonstrate how Pepperdata's dynamic run-time optimizations can guarantee consistent performance SLA's in a shared multi-tenant Hadoop cluster. Because Pepperdata delivers detailed visibility into Hadoop cluster activity , the software becomes invaluable for cluster troubleshooting, reporting/chargeback, capacity planning, and other management and optimization requirements. With Pepperdata, IT can now effectively, efficiently, and reliably support all the business-empowering big data applications of an organization. This webcast will be 45 minutes with time reserved for Q+A.

Speakers:
Mike Matchett - Senior Analyst & Consultant; Taneja Group (host)
Sean Suchter - Co-founder and CEO, Pepperdata

  • Premiered: 11/18/15
  • Location: OnDemand
  • Speaker(s): Mike Matchett, Taneja Group; Sean Suchter, Pepperdata
Topic(s): TBA Topic(s): Mike Matchett Topic(s): TBA Topic(s): Pepperdata Topic(s): TBA Topic(s): Big Data Topic(s): TBA Topic(s): Hadoop Topic(s): TBA Topic(s): cluster Topic(s): TBA Topic(s): Optimization
news

Can your cluster management tools pass muster?

The right designs and cluster management tools ensure your clusters don't become a cluster, er, failure.

  • Premiered: 11/17/15
  • Author: Mike Matchett
  • Published: TechTarget: Search Data Center
Topic(s): TBA cluster TBA Cluster Management TBA Cluster Server TBA Storage TBA Cloud TBA Public Cloud TBA Private Cloud TBA Virtual Infrastructure TBA Virtualization TBA hyperconvergence TBA hyper-convergence TBA software-defined TBA software-defined storage TBA SDS TBA Big Data TBA scale-up TBA CAPEX TBA IT infrastructure TBA OPEX TBA Hypervisor TBA Migration TBA QoS TBA Virtual Machine TBA VM TBA VMWare TBA VMware VVOLs TBA VVOLs TBA Virtual Volumes TBA cloud infrastructure TBA OpenStack
Profiles/Reports

Now Big Data Works for Every Enterprise: Pepperdata Adds Missing Performance QoS to Hadoop

While a few well-publicized web 2.0 companies are taking great advantage of foundational big data solution that they have themselves created (e.g. Hadoop), most traditional enterprise IT shops are still thinking about how to practically deploy their first business-impacting big data applications – or have dived in and are now struggling mightily to effectively manage a large Hadoop cluster in the middle of their production data center. This has led to the common perception that realistic big data business value may yet be just out of reach for most organizations – especially those that need to run lean and mean on both staffing and resources.   

This new big data ecosystem consists of scale-out platforms, cutting-edge open source solutions, and massive storage that is inherently difficult for traditional IT shops to optimally manage in production – especially with still evolving ecosystem management capabilities. In addition, most organizations need to run large clusters supporting multiple users and applications to control both capital and operational costs. Yet there are no native ways to guarantee, control, or even gain visibility into workload-level performance within Hadoop. Even if there wasn’t a real high-end skills and deep expertise gap for most, there still isn’t any practical way that additional experts could tweak and tune mixed Hadoop workload environments to meet production performance SLA’s.

At the same time, the competitive game of mining of value from big data has moved from day-long batch ELT/ETL jobs feeding downstream BI systems, to more user interactive queries and business process “real time” applications. Live performance matters as much now in big data as it does in any other data center solution. Ensuring multi-tenant workload performance within Hadoop is why Pepperdata, a cluster performance optimization solution, is critical to the success of enterprise big data initiatives.

In this report we’ll look deeper into today’s Hadoop deployment challenges and learn how performance optimization capabilities are not only necessary for big data success in enterprise production environments, but can open up new opportunities to mine additional business value. We’ll look at Pepperdata’s unique performance solution that enables successful Hadoop adoption for the common enterprise. We’ll also examine how it inherently provides deep visibility and reporting into who is doing what/when for troubleshooting, chargeback and other management needs. Because Pepperdata’s function is essential and unique, not to mention its compelling net value, it should be a checklist item in any data center Hadoop implementation.

To read this full report please click here.

Publish date: 12/17/15
news

Concurrent app management tools work on Hadoop and Spark

If Hadoop and Spark are to sneak into the enterprise, they will need to be manageable. With Driven, Concurrent Inc. takes a stab at the problem.

  • Premiered: 12/09/15
  • Author: Taneja Group
  • Published: TechTarget: Search Data Management
Topic(s): TBA Hadoop TBA Spark TBA Driven TBA Concurrent TBA manageability TBA Big Data TBA Performance TBA Performance Management TBA Mike Matchett TBA Hive TBA MapReduce TBA SLA TBA service level agreement TBA software TBA high-fidelity TBA HiFi TBA cluster TBA Pepperdata TBA Oracle TBA IBM TBA CA
news

Mobile gaming company plays new Hadoop cluster management card

Chartboost, which operates a platform for mobile games, turned to new cluster management software in an effort to overcome problems in controlling the use of its Hadoop processing resources.

  • Premiered: 01/05/16
  • Author: Taneja Group
  • Published: TechTarget: Search Data Management
Topic(s): TBA Chartboost TBA mobile TBA cluster TBA Cluster Management TBA Hadoop TBA processing TBA data processing TBA analytics TBA Big Data TBA MapReduce TBA Hive TBA Spark TBA Optimization TBA Cloudera TBA AWS TBA Amazon TBA Cloud TBA YARN TBA Pepperdata TBA Memory TBA CPU TBA Application TBA Concurrent TBA SLA TBA service-level agreement TBA HBase TBA application performance TBA application performance management TBA Mike Matchett
news / Blog

Big Data Enterprise Maturity

It's time to look at big data again. Last week I was at Cloudera's growing and vibrant annual analyst event to hear the latest from the folks who know what's what. Then this week Strata (conference for data scientists) brings lots of public big data vendor announcements. A noticeable shift this year is less focus on how to apply big data and more about maturing enterprise features intended to ease wider data center level adoption. A good example is the "mixed big data workload QoS" cluster optimizating solution from Pepperdata.

  • Premiered: 03/29/16
  • Author: Mike Matchett
Topic(s): Cloudera Pepperdata Big Data
news

Pepperdata offers a free health check for Hadoop users

Enterprises are falling over themselves to gain a competitive advantage using sophisticated tools like Hadoop, But as powerful as this technology is, Hadoop-based projects can quickly become a nightmare when performance problems work their way into complex Big Data operations.

  • Premiered: 06/27/16
  • Author: Taneja Group
  • Published: Silicon Angle
Topic(s): TBA Mike Matchett TBA Pepperdata TBA Hadoop TBA Big Data TBA cluster TBA hadoop cluster TBA ROI TBA scalability TBA scalable