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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