|By Jose Castano||
|July 7, 2014 08:00 AM EDT||
Technology is moving at a blistering pace. In today's era of data-centric, complex environments where the lines between business and technology are becoming increasingly blurred, organizations are moving beyond virtualization to cloud computing to meet new challenges and keep up with the pace of change. Critical investments are needed to keep companies competitive, and chief among these technologies is cloud computing. In fact, Gartner expects cloud computing to become the bulk of new IT expenditure by 2016. The bottom line is, if you're not already looking at cloud as an essential investment, you're risking your survival into the next era of computing.
The emerging cloud-based model of computing requires systems that can provide very fast response times to huge volumes of requests. And, mission critical services such as healthcare, finance, transportation, public utilities, and other industries require very high levels of availability, security and other industrial-strength capabilities. Those attributes, qualities and requirements make the mainframe the ideal platform for such mission critical cloud-based workloads.
Cloud computing is a modern extension of a concept first developed nearly 50 years ago with the mainframe. The inherent spirit behind mainframe based computing was to serve users in remote locations at the same time, on a pay-as-you-go basis. The mainframe was introduced as the most robust, scalable system ever built, and with continued innovation the system has maintained its leadership status as one of the platforms of choice to handle today's complex workloads including sophisticated public, private and hybrid cloud computing environments. At its core, the mainframe was designed around three key traits - virtualization, standardization and provisioning. Not coincidentally, these are the foundational requirements for true cloud implementation.
Most enterprises today started their cloud journey with low-risk applications and high agility requirements. This approach allows customers to ease into cloud computing, learn and adjust their management of the cloud, and build the confidence to introduce more demanding applications. The applications tend to use web technologies and architectures that can be scaled on commodity infrastructures, using load balancing and service cloning. Batch workloads that fit with commodity infrastructures are another popular workload on clouds.
For private, public or hybrid clouds, the mainframe can provide the following key requirements:
- Scalability - users need to scale quickly and efficiently both up and down with complete confidence and zero loss of availability.
- Reliability - a cloud computing environment that is always accessible with guaranteed application performance, limited to no downtime with provisions for rapid recovery from failure.
- Multi-Tenancy - allowing multiple users to access software applications on the same system, concurrently and securely, critical for cloud service providers hosting many organizations in a single cloud infrastructure and for enterprises deploying private clouds to manage growth through acquisitions to host multiple companies in the same infrastructure;
- Cost Efficiency - consolidating a distributed x86 cloud environment onto one mainframe creates a simplified, more efficient environment with reductions in floor space and power requirements, and higher return on investment over the life of the platform;
- Security - the mainframe has unmatched system security with ensured isolation and protection of each virtual server environment.
Companies across various industries are gaining these advantages and efficiencies by consolidating cloud environments on a mainframe, such as:
By consolidating cloud on a mainframe private cloud solution that replaced thousands of standalone servers for its daily business activities like policy verification, claims processing, and generating customer quotations, Nationwide Insurance has saved 80% in energy and facility costs. The consolidation saved the company roughly $15 million over three years and will only continue to efficiently keep costs down in the future. Additionally, this solution gives them the capacity, processing speeds and reliability to increase the pace of innovation across its products and channels as it continues to grow.
By leveraging the cloud capabilities offered by the mainframe, Marist College was able to extend its business analytics technology to its academic community including researchers and students, while extracting even more value from its IT investments. By providing its analytics technology via cloud, the college has been able to expose analytics tools to a wide variety of programs, including technical disciplines and also business, liberal arts and communications programs so students learn how to apply it to their fields of study. Marist has also realized significant financial benefits, saving roughly $350,000 by using the cloud to support the college's ERP system.
The mainframe, with its shared platform, integration, and secure design attributes combined with continuous innovation, has enabled organizations to stay ahead of changing market dynamics with a solution that embodies efficiency, economics and agility - a resilient solution for today's cloud environment.
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Jul. 29, 2014 03:27 PM EDT Reads: 556
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Jul. 29, 2014 11:45 AM EDT Reads: 1,521
There will be 50 billion Internet connected devices by 2020. Today, every manufacturer has a propriety protocol and an app. How do we securely integrate these "things" into our lives and businesses in a way that we can easily control and manage? Even better, how do we integrate these "things" so that they control and manage each other so our lives become more convenient or our businesses become more profitable and/or safe? We have heard that the best interface is no interface. In his session at Internet of @ThingsExpo, Chris Matthieu, Co-Founder & CTO at Octoblu, Inc., will discuss how these devices generate enough data to learn our behaviors and simplify/improve our lives. What if we could connect everything to everything? I'm not only talking about connecting things to things but also systems, cloud services, and people. Add in a little machine learning and artificial intelligence and now we have something interesting...
Jul. 29, 2014 10:45 AM EDT Reads: 629
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Jul. 29, 2014 10:00 AM EDT Reads: 1,621
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Jul. 29, 2014 09:45 AM EDT Reads: 981
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Jul. 29, 2014 09:00 AM EDT Reads: 1,097
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Jul. 28, 2014 01:30 AM EDT Reads: 2,061
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Jul. 27, 2014 11:45 PM EDT Reads: 2,618
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Jul. 27, 2014 11:45 PM EDT Reads: 2,647
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Jul. 27, 2014 11:00 PM EDT Reads: 2,215
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Jul. 27, 2014 09:00 PM EDT Reads: 2,341
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Jul. 21, 2014 11:17 AM EDT Reads: 1,978
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Jul. 20, 2014 03:00 PM EDT Reads: 1,776
There are 182 billion emails sent every day, generating a lot of data about how recipients and ISPs respond. Many marketers take a more-is-better approach to stats, preferring to have the ability to slice and dice their email lists based numerous arbitrary stats. However, fundamentally what really matters is whether or not sending an email to a particular recipient will generate value. Data Scientists can design high-level insights such as engagement prediction models and content clusters that allow marketers to cut through the noise and design their campaigns around strong, predictive signals, rather than arbitrary statistics. SendGrid sends up to half a billion emails a day for customers such as Pinterest and GitHub. All this email adds up to more text than produced in the entire twitterverse. We track events like clicks, opens and deliveries to help improve deliverability for our customers – adding up to over 50 billion useful events every month. While SendGrid data covers only abo...
Jul. 20, 2014 02:00 PM EDT Reads: 2,452
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Jul. 20, 2014 09:15 AM EDT Reads: 1,958
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