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Pepperdata

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  • Effectively Manage Multi-tenant Hadoop for the Enterprise Effectively Manage Multi-tenant Hadoop for the Enterprise Sean Suchter, CTO of Pepperdata Recorded: Nov 14 2016 39 mins
    As the Hadoop market matures and new applications and use cases for Big Data emerge, organizations are dealing with more complex environments than ever before. In days past, deployments often focused on single, batch-oriented workloads, and if you wanted to run multiple workloads at the same time, you needed to split your clusters. With Hadoop 2 and YARN, organizations are able to run multiple workloads on the same cluster. But, in multi-tenant environments, resource contention can become a daily problem and low-priority, ad-hoc jobs can sometimes monopolize hardware resource that is needed for high-priority workloads.

    Pepperdata is the first and only software that guarantees service levels in multi-tenant Hadoop environments. We have helped dozens of companies of all industries and all sizes to effectively manage and scale their multi-tenant environments, guaranteeing service levels and improving overall cluster performance.

    Join us for this webcast to hear best practices for running multi-tenant environments and how you can improve visibility, performance, and overall management of your big data environment.
  • Improve Amazon EMR Performance up to 4X Improve Amazon EMR Performance up to 4X Vinod Nair, Product Manager at Pepperdata Recorded: Oct 13 2016 36 mins
    Are you currently running Amazon EMR but lacking the visibility and measurement of how your cluster is performing? Pepperdata for Amazon EMR enables users of Amazon Elastic MapReduce to run jobs up to four times faster and simultaneously reduce costs. Users can see over 300 metrics even after the cluster has been terminated, so users have a historical view of performance.

    Register for our webinar to learn how Amazon EMR can help streamline your big data projects, and how Pepperdata can help you get the most value from your investment.
  • Ensure Quality of Service in Multi-tenant Hadoop Environments Ensure Quality of Service in Multi-tenant Hadoop Environments Sean Suchter of Pepperdata and Andy Oram of O'Reilly Media Recorded: Aug 3 2016 44 mins
    This webcast will show you how Pepperdata can help your organization guarantee quality of service in multi-tenant Hadoop environments by eliminating resource contention and guaranteeing service levels for high-priority jobs. Run HBase, MapReduce, Spark, Hive, and more all on a single cluster without worrying about jobs stomping on each other. We'll show you how Pepperdata automates cluster optimization to reduce time and cost, and keep your Hadoop humming happily.
  • Keeping the Trains Running: Effective Troubleshooting for Hadoop Keeping the Trains Running: Effective Troubleshooting for Hadoop Sean Suchter, CEO of Pepperdata and Dez Blanchfield, Data Scientist at the Bloor Group Recorded: May 4 2016 67 mins
    When something goes wrong on your Hadoop cluster – a missed job, sudden performance slow downs, or massive spike in IO – are you able to pinpoint the exact cause of the issue? Most times, it can take hours or days (or maybe the cause will never be discovered). Join us for this webinar to see how Pepperdata reduces troubleshooting times by 90% and can prevent most performance problems from ever happening in the first place.
  • Overcome the limitations of distributed computing with real-time intelligence Overcome the limitations of distributed computing with real-time intelligence Sean Suchter, CEO and co-founder of Pepperdata Recorded: Mar 2 2016 49 mins
    Most Hadoop admins have learned a set of “best practices” to address and mitigate this performance dilemma, such as manual tuning, cluster isolation, or adding new hardware, but most of these remedies are not sustainable long-term solutions. Join us for this webcast as we survey some of these “best practices” and offer up some new ways to address the performance gap. We’ll also tell you the warning signs to look out for, so you can assess the health and production readiness of your cluster.

    In this webcast, we’ll examine:

    the reality of what the current tools in the ecosystem do before and after a job has run,
    the most common “best practice” approaches to improve performance and the positive and negative outcomes of each, and
    a new approach to performance gains-how to use software to fill the gap of human capability.
  • Optimizing Big Data Clusters in Production - Performance, Capability, and Cost Optimizing Big Data Clusters in Production - Performance, Capability, and Cost Sean Suchter, Pepperdata Co-founder and CEO and Mike Matchett, Sr. Analyst at Taneja Group Recorded: Nov 18 2015 54 mins
    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.
  • Real-time Hadoop and IoT Real-time Hadoop and IoT Sean Suchter, Pepperdata and Bill Peterson, MapR Recorded: Oct 29 2015 53 mins
    When your business requires information be available in realtime, you can't rely on self-tuning to get you the performance you need. Hadoop addresses a lot of big data challenges, but it can't always guarantee that your priority jobs will complete on time.

    Join Pepperdata and MapR for this webcast to learn how you can use technology to go beyond the capabilities of human interaction. Hear REAL LIFE USE CASES of customers who have leveraged the right tools to address the volumes, decisions, and interactions required of IoT.
  • Big Data in Healthcare: How to accelerate your Hadoop & big data operations Big Data in Healthcare: How to accelerate your Hadoop & big data operations Sean Suchter, CEO & Co-founder of Pepperdata. Charles Boicey, Clinical & Information Technology Expert Recorded: Aug 20 2015 54 mins
    Attend our webinar to hear experts in the field of Big Data and Healthcare discuss the emergence of Hadoop and other Big Data technologies and how to make sure you're taking full advantage. LIVE QUESTIONS ARE ENCOURAGED. Topics we will cover:
    - How healthcare organizations are using big data
    - What tools & skill sets do you need once you are up and running
    - How to enforce SLAs in production to make sure your critical tasks are always completed

    We will have an active Q&A session and encourage questions from the audience - join us to guide the discussion!
  • Real-time Cluster Optimization for Hadoop and more Real-time Cluster Optimization for Hadoop and more Brock Alston, Pepperdata and Alex Pierce, Pepperdata Recorded: Jul 14 2015 39 mins
    You've deployed Hadoop. But now what? Are you spending a lot of time putting out fires on your production cluster? Are you able to identify the root cause of issues? Are your users complaining about jobs running more slowly or experiencing resource contention?

    This webcast will talk about the most common challenges for Enterprises running Hadoop in production, and will show you how you can use simple visibility and management tools to get:

    – Fine-grained visibility in your production cluster
    – Enforced SLA’s and enabled multi-tenancy
    – Increased throughput between 30 and 50%