Effective Multi-Tenant Distributed Systems

Challenges and Solutions when Running Complex Environments

Effective Multi-Tenant Distributed Systems

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Organizations are eager to capitalize on real-time data analysis, move beyond batch processing for time-critical insights, and excel at big data in a predictable, reliable way. But performance has been an issue for distributed systems like Hadoop, especially when the use cases of a single cluster become multi-tenant or multi-workload. The worst part? You may not even know you have a performance issue.

In this report, Chad Carson and Sean Suchter from Pepperdata describe the performance challenges of running multi-tenant distributed computing environments, especially within a Hadoop context. After examining pros and cons of current solutions for these problems, you’ll learn how to use real-time, intelligent software that tracks and dynamically adjusts each application’s usage of physical hardware. Get ahead of your Hadoop operations for faster, better decision-making and faster, better business returns.

With this report, you’ll explore:

  • How Hadoop and other multi-tenant distributed systems work, and why performance matters
  • Business-visible symptoms of performance problems: late jobs, inconsistent runtimes, and underutilized hardware
  • Scheduling challenges in multi-tenant systems
  • Symptoms and solutions for CPU performance limitations
  • Physical and virtual limits of node memory—and what happens when you run out
  • Identifying and solving performance problems due to disk and network performance limits and other typical bottlenecks
  • Solutions for monitoring performance and accurately allocating cluster costs among users and business units

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Chad Carson

Chad Carson

Chad Carson led teams at Microsoft, Yahoo, and Inktomi, using huge amounts of data building web-scale products, including social search at Bing and sponsored search ranking and optimization at Yahoo. Before getting into web search, Chad worked on computer vision and image retrieval, earning a Ph.D. in EECS from UC Berkeley.

Sean Suchter

Sean Suchter

Sean has been working with Hadoop and distributed systems for more than 15 years. He was the founding GM of Microsoft’s Silicon Valley Search Technology Center, where he led the integration of Facebook and Twitter content into Bing search. Prior to Microsoft, 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.