Digital Transformation Drives Mainframe’s Future

Amazon’s Jeff Bezos on Cloud Computing

By G C Network | June 18, 2008

Amazon’s Jeff Bezos on Cloud Computing How and when Amazon began its cloud computing effort.Why Amazon has become an innovator with Amazon Web Services and how it relates to their…

Dataline, IBM, Google, Northrop Grumman on Cloud Computing

By G C Network | June 17, 2008

My company, Dataline LLC, in cooperation with IBM, Google and Northrop Grumman Mission Systems, is sponsoring an educational series entitled “Cloud Computing in a Netcentric Environment“. The series will be…

EMC Studies Cloud Computing Security

By G C Network | June 17, 2008

Storage firm EMC has joined the Daoli Trusted Infrastructure Project which conducts research into “trust and assurance” in cloud computing environments. The team’s research will focus on cloud computing, trusted…

The Cloud Computing Marketplace

By G C Network | June 17, 2008

For explaination and details see Understanding the Cloud Computing/SaaS/PaaS markets: a Map of the Players in the Industry by Peter Laird, Kent Dickson, and Steve Bobrowski from Oracle. Update: Please…

Key cloud computing concerns by CXO’s

By G C Network | June 16, 2008

Key cloud computing concerns by CXO’s attending the Enterprise 2.0 Conference in Boston were addresed in a June 9th panel of executives from Google, Amazon Web Services (AWS), and Salesforce.com.…

IBM Cloud Computing Center

By G C Network | June 13, 2008

On June 5th, IBM announced it will establish the first Cloud Computing Center for software companies in China, which will be situated at the new Wuxi Tai Hu New Town…

EUCALYPTUS – An Open Source Cloud Computing Platform

By G C Network | June 13, 2008

Elastic Utility Computing Architecture for Linking Your Programs To Useful Systems (EUCALYPTUS) is a new project that seems to be trying to put an “open source” flavor to cloud computing.…

The Honorable John G. Grimes Speaks about Cloud Computing

By G C Network | June 12, 2008

Today I had the pleasure of hearing The Honorable John G. Grimes, Assistant Secretary of Defense for Networks and Information Intergration and Department of Defense CIO, speak on some key…

Amazon leads Google into the cloud (So what else is new)

By G C Network | June 12, 2008

In this May 1, 2008 Globe and Mail Update article, Mathew Ingram provides an excellent comparison of Amazon and Google’s cloud computing initiatives. Bottom line: Amazon leads the pack with…

Web 2.0 Expo – What is Cloud Computing?

By G C Network | June 11, 2008

For some interesting views, take a look at these video interviews on what is cloud computing. These were done during the recent Web 2.0 Expo, April 22-25 in San Francisco,…

 

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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