Digital Transformation Drives Mainframe’s Future

My views on “Classification of Cloud Computing Stakeholders”

By G C Network | July 12, 2008

In “Cloudy Times”, Markus Klems is having a good discussion on how cloud computing stakeholders classify the various infrastructure options. I then thought that it would be good for me…

The Implemetation of Network-Centric Warfare

By G C Network | July 12, 2008

The Implemetation of Network-Centric Warfare “Warfare is about human behavior in a context of organized violence directed toward political ends. So, network-centric warfare (NCW) is about human behavior within a…

Personal Views on DISA, HP and RACE

By G C Network | July 11, 2008

DISA and HP are clearly on the path towards cloud computing. At it’s core, net-centric operations requires the effective delivery of information to forward forces and the translation of that…

DISA selects HP for RACE

By G C Network | July 10, 2008

Byte and Switch reported today that the Department of Defense (DoD) has confirmed that HP will help the Defense Information Systems Agency (DISA) deploy a major cloud computing infrastructure. Grid…

Speakers for First SOA-R Event Announced

By G C Network | July 10, 2008

Scheduled speakers and topics for the first SOA-R Cloud Computing Education event are: Steve Armentrout, Parabon, President & CEO Grid to Cloud Computing Greg Boss, IBM, Lead Cloud Solution Architect…

Cloud Computing Offerings – A Taxonomy

By G C Network | July 9, 2008

From “The various level of cloud computing” by Ross Cooney Applications in the cloud: Software as a Service (SaaS). Examples include gmail, yahoo mail, Hotmail, the various search engines, wikipedia,…

Cloud Computing Guides (updated 8/10/08)

By G C Network | July 9, 2008

InfoWorld Special Report on Cloud Computing InformationWeek Guide to Cloud Computing InfoWorld Cloud Computing Strategy Guide Cloud Computing Product Guide A Brief History of Cloud Computing Business Week CEO Guide…

Microsoft announcing Cloud Computing offering

By G C Network | July 8, 2008

According to Information Week, Microsoft plans to make three important business software offerings — Exchange, Office Communications, and SharePoint — available in SaaS versions for business this year, but it’s…

Intel new CIO to examine Cloud Computing

By G C Network | July 7, 2008

In a ComputerworldUK article, incoming Intel CIO Diane Bryant says that she will network with fellow information chiefs, examine cloud computing and advocate using the chip giant’s internal operations as…

Cloud Computing for National Security

By G C Network | July 3, 2008

As the national security community considers cloud computing as an IT infrastructure option, it is surely looking at the value of the cloud in an information sharing world. Implementation of…

 

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

( Thank you. If you enjoyed this article, get free updates by email or RSS – © Copyright Kevin L. Jackson 2017)

Follow me at https://Twitter.com/Kevin_Jackson
Posted in

G C Network