My users are happy: Having clearly identified and targeted my end users (did I focus on business application owners, trusted business IT folks, IT solutions team, or my administrators?), I can see that the adoption of the cloud automation is growing. This does not mean they are able to do everything they want in my first cloud deployment, but it means they are getting value out of it and I can see the anticipated number of physical and virtual servers provisioned. I also see deprovisioning occurring. After a few months I might still see three times to the provisioning going on as deprovisioning. I also have other teams beyond the first deployment angling for their turn.
IT Operations / the Cloud Command Center are cautiously monitoring the people, processes and technology: Let’s face it, getting into production was intense and we had to make tradeoffs. We did not get everything we wanted in the first deployment. We cut the tape and users jumped in the cloud pool. We got lots of feedback. We tweaked one or two things; we got even more feedback. We breathed a sigh of relief. We looked forward to chapter two and built long lists of what we wanted. We adjusted our roadmap. We reviewed the success, learnings and failures with our management. We identified and quantified the ROI. We realized that we had lots of work to do. Our Data Center operational processes were so spread out among our staff. We had to think very clearly about managing the change from routine to strategic and how our workforce needed to transition to new roles.
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Tags: intelligent automation, orchestration, private cloud
Author’s Note: I have no kids. I have friends with kids, who used to be in diapers. The kids were in diapers, not the friends. I’ve changed a few in my day, but not nearly as many as my friends have. And yes this has some sort of relevance to this story…
In every trade show or conference there’s someone talking about Big Data. They talk about algorithms, CPUs, memory, software stacks, cabling, racks, ROI, TCO, nodes, names, federation, centralization, organization until you get “the pitch.” I’m not really interested in the pitch for why someone’s product is better than the other, I’m more interested in the “What is the Problem that you’re trying to solve?” This to me gets to the root of Big Data,or the consolidation of a set of diverse data sources with a multitude of data types for which you’re attempting to determine relationships and patterns amongst it. Phew. Got it?
Me neither, but I like to think in examples and this is where it dawned on me in the grocery store.
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Tags: Big Data, data center, retail
In my first blog post, I highlighted some of the benefits being seen by customers using Cisco Unified Computing System™ (UCS) from Case Studies. In posts two, three, and four, I discussed reduction in cabling, provisioning times, and power & cooling in more detail. Today’s post will highlight three customers and their reduction in operating costs where, to quote Ben Franklin, “A penny saved is a penny earned.”
EDIF Holding SPA– “We have reduced our operating costs by 75 percent while renewing the technology in our IT infrastructure, and we can now offer better continuity of service and a faster response to our customers.” Samuele Cerquetti, CIO
Seven Corners Inc.– “The system paid for itself in less than a year by recouping the more than $1 million the company had been losing annually due to network outages. The company also achieved a $475,000 reduction in operating costs within the first six months of buildout and saved $84,000 instantly by not having to renew software licenses on a number of virtualized servers.”
Avago Technologies – “Ordinarily, expanding from two to three data centers would be expected to increase operational costs by 50 percent. ‘Our operational costs will actually decrease by 40 percent when we expand from two to three data centers.’” Shreyas Shah, Senior Director, Global Information Technology
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Tags: blades, data center, Servers, UCS, unified computing, unified computing system
It’s close to 11 p.m. on the last day of the quarter in a large corporation. IT gets an urgent request to postpone a closing of the books process because there’s a large order stuck in the CRM system.
This means that the order won’t hit the books and be recorded as a booking. The customer won’t get her order, the salesperson won’t get paid, and finance will show a missing number.
This generates an urgent call to the team that manages the workload automation platform: Hold the closing workflow! Stop the presses!
The admins have to get to their console to find the job and pause it. Not a huge deal, except there are thousands of jobs to be run and hundreds of business people calling on a regular basis, at all kind of hours.
Some customers have created help desks for their workload automation teams or they may even off-shore the call center to serve these kinds of requests.
No more. Introducing self-service for workload automation.
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Tags: data center, intelligent automation, job scheduling, orchestration, Tidal Enterprise Scheduler, unified management, workload automation