Digital Transformation Drives Mainframe’s Future

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This afternoon I had a very interesting discussion with Mr. Jeffrey Kaplan, Managing Director of THINKstrategies and founder of the Cloud Computing Showplace. His firm is focused entirely on the…

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Implementation of Cloud Computing Solutions in Federal Agencies: Part 4 – Cloud Computing for Defense and Intelligence

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By G C Network | September 13, 2011

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Implementation of Cloud Computing Solutions in Federal Agencies : Part 2 – Challenges of Cloud Computing

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Implementation of Cloud Computing Solutions in Federal Agencies : Part 1-Introduction

By G C Network | September 8, 2011

(This post first appeared on “Cloud Musings on Forbes”. This series provides the content of a whitepaper I recently authored. A copy of the complete whitepaper is available at NJVC.com…

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   With GSA now issuing ATOs and Amazon launching it’s own government specific cloud, IaaS for government agencies is now a reality.  This next step in this “Cloud First” march…

On The Frontlines: GovCloud and Cybersecurity

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My friends at Trezza Media recently published a couple of great online documents on GovCloud and Cyber. Your should especially check out the “Cloud Chopping Made Easy” by David McClure…

GovCloud Is Now For Real !!

By G C Network | July 3, 2011

On Friday July 1, Infrastructure-as-a-Services for the US federal government became a reality with Authority to Operate (ATO) approval for the following vendors: Web Hosting CGI Federal Computer Literacy World…

The Economic Impact of GovCloud

By G C Network | June 26, 2011

What a month! June has really been busy!! Just now getting around to doing a post about CloudExpo 2011 in New York.With over 5000 delegates in attendance, it was just…

 

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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