Data-Driven Customer Support

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Data-Driven Customer Support

Adam Warrington| Senior Manager of Internal Systems Engineering Sean Spediacci| Product Marketing


Your Speakers

Adam WarringtonSenior Manager of Internal Systems Engineering


Looking Internally for Support


Supporting distributed systems is complex

Issues can be related or root cause might be the same

Looking for ways to work at scale as company continues to grow

Problem Statement


The Way It Used To Be

Engineers, solution architects, and training team were used for Support

Looking for ways automation can give insight into problems, so issues can be solved quicker

Asking customers to pull information is non-trivial

The whole team Time to resolution A manual process


The Support Tools Team

Internal Tools Team• Adam Warrington• Ari Rabkin• AB Srinivasan• Adam Weber• Jacob Schmitz• Manoj Mohan• Krista Mizusaki

Mission Statement: Build data driven software that reduces our time to solve on support cases while increasing customer satisfaction


Keeping The Tools Team Close

The tools team was kept close to the new full time support engineers

Support engineers provide the feedback loop that allows us to build these applications

Looking for ways to work at scale as company continues to grow


The Applications


Customer Support Interface (CSI)Data IngestionOur internal EDH ingests 10 data sources that are support specific. We have access to over 230TB of data and it is growing each month.

Data VisualizationOur goal is to visualize all data that is useful to a support engineer in a useful way. CSI is a java web application that sits on top of the EDH

Tools exist within CSIAll support tools exist as a function or feature within CSI. This includes all the tools we are about to go over (e.g. Diagnostic Bundles, Validations, Monocle, and Clues)


Diagnostic Bundles

Cloudera ManagerOne of the original problems in supporting Hadoop was seeing into the customer environment. Cloudera Manager has the ability to send a snapshot using diagnostic bundles.

What are they used forSupport engineers are able to dive into these bundles to get a granular view of the scenario and quickly solve issues using our tools.


Validations

Getting ahead of the issuesA “Validation” is a set of known issue rules that a diagnostic bundle passes through before it becomes an issue for our customers

What they are used forWhen a diagnostic bundle is sent to Cloudera, the information is run through our library of known issue signatures, and checked automatically. If it hits a “critical” signature, it is automatically escalated to our proactive support team


Monocle

Making specialized knowledge searchableSearching all of the data sources within CSI we are able to create a single index of both internal and open source knowledge for a one stop Hadoop engine.

What is it used forNo longer making support engineers have to “Google” for information. Our internal search platform is the most powerful Hadoop support engine for all their needs.


Support Lab Environment

Reproducing issuesOur support engineers need to be able to launch a environment similar to the customer who is experiencing an issue. Private cloud environment, using OpenStack, where we can launch a cluster that closely matches the customer’s.

Keeping Focused on our CustomersThis capability allows us to hand off the issue to engineering after confirming the bug in the software. This keeps engineers focused on the software and support focused on our customers


Demo


What Does this Mean For Customers?

Solving Customer

Issues Quickly

Issue Clarification

Understanding Customer

Environment

Deep Dive into Issue

Searching for Related Issues

Reproduce Customer

Environment


Future Plans

Clues (Beta)

Expanding Validations rules

Expand Support Labs Functionality

Improvements to Diagnostic

Bundles


Thank [email protected]@cloudera.com

mailto:[email protected]

mailto:[email protected]

Data-Driven Customer Support

Software

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