Digital Transformation Drives Mainframe’s Future

DISA Chief Technologist States Plan for Cloud

By G C Network | September 23, 2008

In an interview reported on in this month’s Military Information Technology magazine, David Mihelcic, DISA Chief Technology Officer, has laid out his goal for the agency’s cloud computing initiative. As…

Google, GeoEye, Twitter. What a Combination!

By G C Network | September 23, 2008

On September 9th, Bob Lozano posted his kudos to GeoEye for a successful launch of GeoEye-1. (Hey Bob! Where’s that post on your “cloud failure” last week?) According to their…

RightScale goes Transcloud

By G C Network | September 22, 2008

Over the weekend, Maureen O’Gara of SYS-CON media reported that RightScale is now offering a “first in industry” capability to provide application management across multiple cloud infrastructures. It now offers…

A Bill to Outlaw Cloud Computing…..

By G C Network | September 19, 2008

… is what we may see if we don’t educate our lawmakers now! That seemed to be one of the main point at last week’s Google workshop in DC. Berin…

NCOIC and Cloud Computing

By G C Network | September 18, 2008

Yesterday the Network Centric Operations Industry Consortium (NCOIC) had a very good session on cloud computing during their plenary session in Falls Church, VA. Led by NCOIC’s Bob Marcus, speakers…

Military Information Technology Cloud Computing Collaboration

By G C Network | September 17, 2008

Today, we’re happy to announce what we believe to be an industry first. “Military Information Technology Magazine“, as the publication of record for the defense information technology community, is collaborating…

Is 99.999% reliability good enough?

By G C Network | September 16, 2008

According to Reuven Cohen in his recent post, Cloud Failure: The Myth of Nines , the whole concept of reliability may be meaningless. “In the case of a physical failure…

You Probably Use Cloud Computing Already.

By G C Network | September 15, 2008

56% of internet users use webmail services such as Hotmail, Gmail, or Yahoo! Mail. 34% store personal photos online. 29% use online applications such as Google Documents or Adobe Photoshop…

20 Real-Life Challenges of Cloud Computing

By G C Network | September 12, 2008

Nikita Ivanov of GridGain offers some excellent insight into the nuts and bolts of getting the cloud to work. Definitely worth a read. To summarize: Most likely you do NOT…

3Tera Announces Global Cloud Services

By G C Network | September 11, 2008

Last week, 3Tera has announced the availability of global cloud services, based on their AppLogic grid operating system. 3Tera is currently running data centers in seven countries (United States, Japan,…

 

Digital Transformation is amplifying mainframe as mission critical to business growth more than ever before. With 70% of the world’s corporate data and over half of the world’s enterprise applications running on mainframe computers, they are at the core of just about every transaction. A single transaction can, in fact, drive up to 100 system interactions. The continued increase in mainframe transaction volumes, growing on average 7-8% a year for 78% of customers,  has even led to a new buzzword: The Connected Mainframe.
According to IDC’s research, connected mainframe solutions generate almost $200 million in additional revenue per year while simultaneously improving staff productivity and cutting operational costs. Over 50% of the benefit value ciomes from higher transaction volumes, new services, and business expansion. Businesses rely on mainframes to:
  • Perform large-scale transaction processing (thousands of transactions per second)
  • Support thousands of users and application programs concurrently accessing numerous resources
  • Manage terabytes of information in databases
  • Handle large-bandwidth communication

 

 

The growth of transaction volumes and diversity of applications connecting into the mainframes can lead to significant operational challenges. With more mobile to mainframe applications tio manage and more data to transact, including eventually blockchain data, organizations need to improve their mainframe operations model drastically. Reactive approaches to mainframe management just can’t keep up with the velocity of change and dramatic growth. Enterprises are losing an average $21.8 million per year from outages and 87% of these enterprises expect this downtime cost to increase in the future. An astounding 66% of enterprises surveyed admit that digital transformation initiatives are being held back by unplanned downtime.
Improving the enterprise’s ability to support increased mainframe workloads is why machine learning, augmented intelligence, and predictive analytics are critical to the CA Mainframe Operational Intelligence solution. Embedded operational intelligence proactively detects abnormal patterns of operation by ingesting operational data from numerous sources. This helps to anticipate and avoid problems through:
  • Detecting anomalies quickly and delivering proactive warnings of abnormal patterns
  • Using advancedvisualization and analysis that accelerates issue triage and root-cause analysis
  • Deploying multiple data collectors that work synergistically to provide broad visibility, more in-depth insights and increased accuracy of predictions
  • Delivering dynamic alerts that improve mean time to resolution (MTTR)
  • Combining simplified visualization of time-series data with deep-dive analysis tools
  • Clustering alerts automatically to correlate related alerts and symptoms
  • Removing irrelevant data points from reports to provide more actionable insights

 

CA Mainframe Operational Intelligence consumes data from multiple CA solutions and directly from the IBM® z Systems® environment through SMF records. Raw alerts from performance, network and storage resource management tools are automatically correlated to surface specific issues and provide predictive insights for each issue. With machine learning and intelligence, wide data sets lead to more accurate predictions, and better relationship and pattern analysis. This insight also includes drill-down and probabilities which can also trigger automated problem remediation. This capability is uniquely embedded into the management environment to more proactively optimize mainframe performance and availability with fewer resources.
This modern approach to operational management will help organizations on-board new IT staff to manage the mainframe moving forward, while also protecting limited mainframe experts to focus on essential tasks. Using machine learning and advanced analytics, your entire team can now acton potential issues much earlier, isolate the real root-cause faster and ultimately remediate issues before they become revenue-impacting incidents.

 

( This content is being syndicated through multiple channels. The opinions expressed are solely those of the author and do not represent the views of GovCloud Network, GovCloud Network Partners or any other corporation or organization.)

 

Cloud Musings

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