Not surprisingly, since the release of my new book, Visible Ops – Private Cloud,
I have been talking with a lot of people about how to deploy private
cloud, where to start, what to avoid, etc. So far, the most common
question has been, “What type of existing workloads are organizations
putting into private cloud environments today - and what are they avoiding?”
So I thought I would jot down some of my answers, specifically related to '
cloud-migrant' services, as opposed to 'cloud-native' services - and without getting too hung up on whether the use cases are 100% cloud or not!
One recurrent use case is to provide dynamic desktop allocation,
especially for education and projects use cases. A number of schools,
universities, training centers, and even some larger enterprises, have
adopted private cloud to allocate servers, clients, applications and
data for reusable desktop systems.
This seems especially prevalent for short-term learning facilities,
repeatable one-off classroom systems, training/demo labs at conventions
(or user groups), and contractor setup. It is also similar to the
executive briefing centers and 'demos on demand' that many software
sales organizations (like CA Technologies) use.
Another service-based use case I have seen in several universities is
self-service access for students and faculty, using pooled resources,
not only for application services but also for full VDI desktop
allocation.
I have seen this in other enterprises too - most notably for
home-source process workers (e.g. call center, data entry) - but mostly
as a proof-of-concept, not a large-scale production deployment.
However, most cloud-migrant workloads I see deployed to private
clouds today still tend to be server-based. Most of these are at 'Phase
1' in the Visible Ops Private Cloud - a reorientation of virtualization
deployments to pilot a private cloud that works, proving results,
gaining skills, and hopefully measuring opportunities. It is still
focused on servers, not services, but provides a vital part of the
learning curve toward private cloud.
For example:
- Dev/test/QA servers - 3-tier LAMP stacks (app/Db/WS), but also LAMP
components, IDEs, source code management tools, etc. (which often
results in applications that run on a private cloud in production)
- Collaboration servers - especially SharePoint, but also Web-based
collaboration services like team chat servers, content repositories,
blogs, wikis, and project management tools
- Engineering servers – I have seen a number of engineering firms move
their design project systems (especially CAD tools) into private clouds
so engineers can fire up new design projects on-demand
- Web servers - popular for marketing teams who can fire up their own
Web servers, especially for short-term and/or localized promotions &
campaigns
- Analytics servers - short-term number crunching of 'big data'
(including BI applications) in medical research, social marketing,
pharmaceutical research, higher education, financial, logistics, etc
The workloads that are less suited to private cloud deployment are harder to identify, because it requires positive evidence of absence,
so my thoughts here are much more anecdotal. I do see CIOs push back on
migrating ‘core’ applications, even to private clouds, citing lack of
confidence, performance concerns, potential security and compliance
issues, and lack of ROI. I would not agree these are always good reasons, but they can be, and are certainly understandable.
In my opinion, private cloud is not ideally suited to relatively
large, static, predictable, and resource-saturating workloads - think
ERP or Data Warehouse. After all, used internally such applications are
almost never deployed ‘on demand’; they are rarely if ever
‘multi-tenant’; they have no real benefit from an ‘infinitely scalable’
infrastructure; and are mostly viewed as a cost of doing business,
without any 'resource measurement' or chargeback.
(btw, there are certainly good arguments to deploy these applications on a public cloud, as 'cloud-native' services using SaaS, to outsource them to a non-cloud third-party, or to just virtualize them - even with 1:1 virtualization
- without the other trappings of cloud. Such alternatives could deliver
better cost savings, higher up-time, faster DR, and other benefits.
However, I think the upside of putting such applications in a private cloud is less apparent.)
That said, I do think that we will see more and more strategic
services - as opposed to project servers - deployed in both private and
public cloud as it matures. In fact, recent IDC data
suggests CIOs that are adopting private cloud will migrate many core
applications in the coming years. Moreover, some of the more advanced
customers I talk with are already doing this, although they are by far
in the minority.
Either way, I will be very interested to see how this all pans out.
What do you think? What have I missed? What types of workloads do you
see being deployed in a private cloud? What are CIOs passing over in
their evaluations? Are they right, or wrong? What criteria should they
use?
Please feel free to continue the discussion in the comments below, or hit me up on Twitter with your ideas.