Automating Analysis of z/OS Alerts

jerrystreet

By Jerry Streetz/OS Alert

You are nowhere near your workstation, and you receive an urgent text that z/OS has an unexpected increase in CPU utilization. While the alert is beneficial, it would be more helpful if you had all the information you needed to diagnose the issue in hand. We discussed the pains of bad alerts in part 1 of this blog. The remainder of this blog discusses how you can integrate your z/OS alerting with the rich artificial intelligence of IntelliMagic Vision.

Rather than just another alarm in a sea of alarms, you should be able to expect more from your alerts. Especially with something as important as your z/OS, alerts should provide actionable recommendations to the problems they are alerting you to. IntelliMagic Vision does just that. IntelliMagic Vision can be configured to send detailed root cause analysis reports based on pre-defined z/OS alerts allowing you to understand the impact and urgency of the alert and guiding subsequent investigation.

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Making Use of Artificial Intelligence for IT Operations Analytics / AIOps

Brent PhillipsBy Brent PhillipsArtificial Intelligence for IT Operations Analytics

Enterprise computing systems and storage operations teams have a difficult job: manage the IT infrastructure so that application availability is always efficiently maintained. But this is virtually impossible due to the complexity and disparity of the meta-data and reporting tools for all the various infrastructure components. A lack of information is not the problem, rather the great need is to derive meaningful intelligence out of all the information.

But the cloud, for example, will not work for all applications due to performance and security requirements. And outsourcing doesn’t make infrastructure performance problems go away, in fact it can make them harder to resolve. So most enterprise organizations will still benefit from and require deep infrastructure performance analysis capabilities.

In recent years, a new class of products initially called IT Operations Analytics (ITOA) have come on the market with the design objective of providing a single interface into all the data generated from disparate devices, and more importantly, helping interpret what it really means for performance, availability, and efficiency.

The idea is to employ the computer to do more of the work of deriving meaningful intelligence out of all the data. If designed correctly, this is a type of artificial intelligence which is done by the machine and enables human IT operations teams to be more effective. In 2017 Gartner coined the term AIOps which is a nice nomenclature for the capability.

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AI and z/OS Performance and Capacity Analysis: 2018 Predictions

Brent PhillipsBy Brent Phillips2018 Predictions on AI and z/OS Performance and Capacity Analysis

2018 is gearing up to be a watershed year for z/OS performance and capacity professionals.

Industry analysts have been talking for some years now about Artificial Intelligence (AI) and the role it will play in our work. But what that truly means, and its value in day-to-day operations has not yet been understood or realized by most professionals in this field.

There are many different types of AI, but not all are useful in making the computer do the kind of infrastructure performance and availability health assessment work that is no longer feasible for human analysts to proactively do every day. But when properly designed and deployed, it has proven very effective to implement automated, AI-driven decision making about what all the data means for identifying current or near-term performance problems and their root-causes.

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What is AIOps? The Benefits Explained

By Morgan Oats

August 2017 ushered in a new term heralded by Gartner in the form of AIOps: Artificial Intelligence for IT Operations. The term has certainly generated a lot of market hype, but what exactly is AIOps, and how can it help support your business operations?

Gartner’s official definition for AIOps is:

“AIOps platforms utilize big data, modern machine learning and other advanced analytics technologies to directly and indirectly enhance IT operations (monitoring, automation and service desk) functions with proactive, personal and dynamic insight. AIOps platforms enable the concurrent use of multiple data sources, data collection methods, analytical (real-time and deep) technologies, and presentation technologies.”

AIOps: Artificial Intelligence for IT Operations

Source: Gartner [https://blogs.gartner.com/andrew-lerner/2017/08/09/aiops-platforms/]

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Bridging the z/OS Mainframe Performance & Capacity Skills Gap

Brent PhillipsBy Brent Phillips

Bridging the mainframe skills gap

Many, if not most organizations that depend on mainframes are experiencing the effects of the mainframe skills gap, or shortage. This gap is a result of the largely baby-boomer workforce that is now retiring without a new generation of experts in place who have the same capabilities. At the same time, the scale, complexity, and change in the mainframe environment continues to accelerate.

Performance and capacity teams are a mission-critical function, and this performance skills gap represents a great risk to ongoing operations. It demands both immediate attention and a new, more effective approach to bridging the gap.

In our connected and technology-dependent world, deep performance and capacity management skills are essential. Applications and back-end transactions are often accessed throughout the day and night, causing less workload predictability.

Simultaneously, the infrastructure as well as the performance and configuration data analysis required to maintain availability is even more complex than it used to be. New features such as Pervasive Encryption and hardware data compression (zEDC) must be measured and monitored to ensure they do not impact required service levels. New cross-platform applications with Web front-ends and mainframe transaction back-ends are now common and create new requirements for predictive and prescriptive monitoring of TCP/IP, MQ, and other network parts of the infrastructure.

This dynamic environment, coupled with the shortage of performance and capacity experts, represents a significant risk to mainframe operations and affects most of the world’s largest organizations. The mainframe performance skills gap is in fact, one of the significant issues causing IT executives to question the future role of the mainframe within their organization.

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