Digital Transformation Drives Mainframe’s Future

Cloud Computing and the Process Integration Era

By G C Network | December 17, 2008

The Industry Advisory Council (IAC) is a non-profit, non-partisan organization dedicated to fostering improved communications and understanding between government and industry. through its affiliation with the American Council for Technology…

The Tactical Cloud

By G C Network | December 16, 2008

When cloud computing first came in vogue, there was a rather serious discussion about the private cloud concept. The whole idea of cloud computing seemed to argue against implementing such…

“Cloud Musings” Now on SYS-CON Media “Cloud Computing Journal” !!

By G C Network | December 15, 2008

I’m happy to announce that a recent “Cloud Musings” article, “Commercial vs Federal Cloud Computing ” has been reposted on SYS-CON Media’s “Cloud Computing Journal“. Thank you SYS-CON for making…

How to make clouds interoperable and standard !!

By G C Network | December 12, 2008

This has been a huge part of my life over the past few weeks! This is my personal view. WARNING: DON’T EXPECT THE ANSWER TO BE FOUND BELOW !!! There…

The Tension between Public and Private Clouds

By G C Network | December 11, 2008

Last week, during discussion on cloud interoperability and standards in Israel, I saw for the first time a real dichotomy in the value of public (external) and private (internal) clouds.…

Cloud Computing for Continuity of Operations (COOP)

By G C Network | December 10, 2008

Recently, I’ve been focusing on cloud computing for COOP. The way I looked at it, many government agencies are already using commercial shared facilities as COOP sites and that the…

NCOIC Plenary Session

By G C Network | December 9, 2008

Hopping a plane to the west coast today to attend the NCOIC Plenary in Costa Mesa, California. First day “Cloud Computing for Net-Centric Operations” agenda includes: David Ryan, Chief Architect…

Dataline named “Top 100 Cloud Computing Company”

By G C Network | December 9, 2008

SYS-CON’s Cloud Computing Journal included Dataline in its expanded list of the most active players in the cloud ecosystem. In adding Dataline to the “Top 100” list, Jeremy Geelan noted…

Autoscaling into the cloud- Good or Bad?

By G C Network | December 8, 2008

I always thought saw the ability to autoscale into a cloud infrastructure as a good thing. George Reese presented a differing view on the O’Reilly blog recently. “Auto-scaling is the…

Cloudera must be reading the script!

By G C Network | December 4, 2008

“Cloud computing leapt out as the most obvious way to address enterprise large data problems” – Ken Pierce, IT Specialist, DIA-DS/C4ISR “We view Hadoop as the key enabler…[in] optimizing the…

 

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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