Digital Transformation Drives Mainframe’s Future

Strategies And Technologies for Cloud Computing Interoperability (SATCCI)

By G C Network | March 4, 2009

As I alluded to in an earlier post, a major cloud computing interoperability event will be held in conjunction with the Object Management Group (OMG) March Technical Meeting on March…

Government Cloud Computing E-zine Launched

By G C Network | March 3, 2009

Today marks the launch of a new electronic magazine dedicated to addressing cloud computing within the government space. Over the last year during my personal exploration of this marketspace, I’ve…

NCOIC Plenary: Cloud Computing Working Group

By G C Network | March 2, 2009

Last week, I had the pleasure of participating in the NCOIC Cloud Computing Working Group. Led by Cisco Systems Distinguished Engineer, Mr. Krishna Sankar of Cisco Systems, the meeting purpose…

2nd Government Cloud Computing Survey – A Sneak Peek

By G C Network | February 25, 2009

This month, we’re in the middle of collecting data for our 2nd Government Cloud Computing Survey. to peek your curiosity (an to entice your participation) here is a sneak peek…

Government could save billions with cloud computing

By G C Network | February 23, 2009

In a recent study, published by MeriTalk, Red Hat and DLT Solutions, the Federal government could save $6.6 billion by using cloud computing or software-as-a-service. “Looking at 30 federal agencies,…

Cloud Games at FOSE 2009

By G C Network | February 19, 2009

ONLINE REGISTRATION NOW AVAILABLE Booz Allen Hamilton is launching its Cloud Computing Wargame (CCW)T at FOSE March 10-12, 2009 in Washington, DC. The CCW is designed to simulate the major…

IBM and Amazon

By G C Network | February 16, 2009

According to the Amazon Web Services (AWS) site, you can now use DB2, Informix, WebSphere sMash, WebSphere Portal Server or Lotus Web Content Management on Amazon’s EC2 cloud. “This relationship…

A Berkeley View of Cloud Computing

By G C Network | February 13, 2009

Yesterday, Berkeley released their View of Cloud Computing with a view that cloud computing provides an elasticity of resources, without paying a premium for large scale, that is unprecedented in…

Cloud Economic Models

By G C Network | February 11, 2009

One of the most important drivers of cloud computing in the Federal space is its perceived “compelling” economic value. Some initial insight on the economic argument is now available on…

Cloud Computing In Government: From Google Apps To Nuclear Warfare

By G C Network | February 10, 2009

Today, I want to thank John Foley of InformationWeek for an enjoyable interview and his excellent post, Cloud Computing In Government: From Google Apps To Nuclear Warfare. Our discussion covered…

 

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.)

 

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