Live Webinar March 1st 2016 1:00 PM – 2:00 PM EST
Duration: 1 Hour Credits: 1 PDU Category C Free
Presented by : O’Reilly

Distributed computing platforms such as Hadoop have created a unique class of performance problems. Issues such as resource contention, jobs running late, and the inability to troubleshoot prohibit organizations from realizing the full value of their investment.

The existing tools on the market today are insufficient to address these performance gaps.

Schedulers and monitoring tools are essential to get jobs on the cluster and to see what is happening (at the node level), but they offer no active control of jobs once they are running, and don’t go deep enough so you can understand what is happening at the job, user, or task level.

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 Sean as he surveys some of these “best practices” and offer up some new ways to address the performance gap.

Sean will 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, Sean will 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.

This webcast is the first of four in a series exploring the Hadoop performance paradigm. In this series, Sean will discuss some specific limitations of distributed computing, and how to overcome them to increase ROI.

Presenter: Sean Suchter, (LinkedIn profile) CEO & Co-Founder—Pepperdata, has been working with Hadoop & distributed systems for more than 15 years. Sean was the founding GM of Microsoft’s SV Search Technology Center, where he led the integration of Facebook and Twitter content into Bing search. Previously Sean managed the Yahoo Search Technology Team, the first production user of Hadoop. Sean joined Yahoo through the acquisition of Inktomi. He holds a B.S. in Engineering and Applied Science from Caltech.

PDU Category C (PMBOK 5) documentation details:
Process Groups: Planning, Monitoring & Controlling
Knowledge Areas: 4 – Integration 6 – Time 8 – Quality

• 5.2 Collect Requirements
• 5.3 Define Scope
• 6.2 Define Activities
• 8.4 Control Quality

As a Category C ‘Self Directed Learning Activity’ remember to document your learning experience and its relationship to project management for your ‘PDU Audit Trail Folder’

Click to register for:
Overcome Limitations Of Distributed Computing With Real-Time Intelligence