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Hadoop engineering support services primer

As the focus has shifted to production deployment of Hadoop based applications, there is an increasing need to have good practices around the production support process. While this may be a BAU transition process for large organizations, the startups and new product orgs. may want to catch up on standard and best implementations. Let’s put across a small primer on what you need while setting up a Hadoop production support system.



People:


            In a typical software product org and/or startup, the first focus and strength is usually skilled people. However, there is a need to segregate your high skilled force among the product/project development and support activities. At best, you need the following skills as part of support org. structure:

-          Hadoop stack Administrator

-          Support professional with MapReduce and essential application knowledge

-          Data scientist (definition of skills may vary specific to your app)

-          Account Manager (multi-variant customer facing role)



Process:


            While process terms may sound slightly offbeat or cliché to ‘hackers’, a service management setup demands it as a basic commandment. To begin with, identify type of issue reported as:

-          Incident, Problem, Service Request

-          Product enhancement

Further, establish how your team can get access to stacks:

-          Logs

-          Remote login rights

At the onset, while taking an issue report, collect basic hygiene information from the customer, including

-          stack details with product versions

-          trigger for issue, if known

-          any new deployment or upgrade info in the cluster

-          data sample, if possible

Further, devise a process on how to:

-          Escalate ticket internally

-          Advise customer on escalation process for:

o       Hierarchical escalation within your organization

o       Cross team escalation for integrated stacks

o       ‘War room’ escalations for major revenue impact incidents



Technology:


            Technology is not limited to just your product and the associated hardware. For a production support system, some must-have include:

-          Voice Call response and recording

-          Ticket management portal for accepting, assigning and transferring tickets

It may be nice to have

-          Self service portal for customers

-          FAQ or answer forum (like MapR) to help customer figures out a few issues themselves



Metrics:


            No support team can be spared on this. You just ought to have a sound metrics system for your team on:

-          Turn Around Time

-          Effort

-          Cost

-          Post production defects

-          Productivity per person



Billing:


            The bread and butter step, this has a few catches when it comes to Hadoop stacks. Your account manager (aka VP) needs to have a clear cut contract on support cost per node or similarly defined unit along with billing milestones. So, you need to keep watching each month for:

-          Any contract deviations (e.g. from inclusions in fixed AMC)

-          Number of supported nodes that your contract stated

-          Any ticket which needs to be billed as Enhancement and not as problem.





While many of these may inspire from a usual service management desk, there are key peculiarities with node based billing combined along with evolutionary nature of MapReduce product ecosystem. Due to the integrated nature of Hadoop technology stack which may have unsupported open source along with evolving NoSQL database combined with enterprise legacy suites, each organization needs to evolve a resilient production support system. It is best advised to review the key constituents holistically and devise a production support organization system.



For any help in setting up a production support setup further, you may drop a query to scale [at] hadoopsphere.com .





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 top image source: freedigitalphotos.net

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