Keeping the Trains Running: Effective Troubleshooting for Hadoop
The road to success with Hadoop can certainly take time, but even when a cluster is up and running, there are hurdles to overcome. How can your organization avoid common pitfalls, or even relatively uncommon challenges? Register for Episode II of the 2016 Tech Lab with world-renowned Data Scientist Dez Blanchfield, as he demonstrates how to identify and resolve some of the more vexing issues with parallel computing.
He’ll be joined by Chad Carson of Pepperdata, a platform designed to provide increased visibility, control and capacity for critical Hadoop workloads. Carson will discuss the Pepperdata instance that Blanchfield has loaded onto the InsideAnalysis Tech Lab cluster. An extended roundtable discussion will ensue, and attendees will be encouraged to ask probing questions to better understand how clusters can be optimized at machine speed.
The Perils & Pitfalls of Distributed Computing - How to Get Your Operations Back on Track
Hadoop is hard. It’s certainly not plug-and-play, in part because it’s being used in ways that were not envisioned during its design. And once a cluster is deployed, keeping it running smoothly can be a real challenge. As with any distributed computing system, Hadoop’s complexity renders manual tuning largely ineffective. And as the environment gets more complex (adding multiple tenants, mixed workloads, etc), manual efforts to manage and control cluster activity only get less practical. Although software tools exist to help improve performance, they are often suggestion-based, still relying on Hadoop operators to make manual changes to configuration. Automated adjustments at the speed of compute are the only answer.
Watch the inaugural 2016 Tech Lab Webcast to hear from Hadoop visionary and Data Scientist Dez Blanchfield, as he explains why automation is the key to making clusters hum. He’ll be joined by Kirk Lewis and Alex Pierce of Pepperdata, who will demonstrate why distributed computing brings its own set of challenges that extend beyond the kind of tuning often used in the database world. He’ll also share real-world success stories of optimizing Hadoop in real time. This event will kick off a series of Webcasts in 2016 as Blanchfield takes Pepperdata into the Lab and tests it against all manner of workloads.