Watch the video to discover how to transform unpredictable outages into predictable ones by creating Availability Intelligence out of the RMF and SMF data using built-in expert domain knowledge.
Your z/OS mainframe is known for superior reliability. In fact, the “z” in z Systems even stands for “Zero Downtime”
That means your users on z have never experienced outages, right? Of course they have!
The z/OS operating system may indeed have zero unplanned downtime. But every shop still experiences issues on z that impact at least some end-users.
And they are expensive – $686,000 dollars per hour of downtime for large companies according to a recent Aberdeen Group survey.
Outages can be classified as either Predictable or Unpredictable
Today, you probably think of most incidents that disrupt availability as unpredictable.
Why is this? If it could have been predicted, you would have indeed avoided it, right? And if you did not avoid it, then it is normal to think of it as “unpredictable”. But what if many of these currently unpredictable incidents could be moved to the predictable category?
How would that impact your customers, your employees, your IT staff?
How would it reduce emergency hardware purchases?
How can you effect this shift?
z/OS mainframes already generate far richer measurement data than any other enterprise computing platform. But this data is vastly underutilized.
First, because the extreme quantity of data makes it difficult and time consuming to find what is important;
And second, because understanding what the data means is very difficult.
To see what it means about risk to continuous availability for your end-users, the data needs to be interpreted with specific knowledge about the capabilities of your hardware configuration.
Your existing RMF and SMF reporting that has been in use for many years is simply unable to create this kind of intelligence from the data.
Unlocking the potential of the performance and configuration data lets you protect availability for your production users in new way. But this requires a new approach.
It requires automatic, daily interpretation using built-in expert domain knowledge.
Expert domain knowledge about the infrastructure is the key to discovering upcoming problems in the data and is far more effective at it than even Analytics solutions that spot correlations or anomalies in the data.
Built-in expert domain knowledge is what transforms the data into intelligence about your workloads on your infrastructure.
Where are the bottlenecks developing?
When are your workloads likely to saturate certain components and introduce unacceptable delays?
What can you do to avoid an outage?
This Availability Intelligence gives insight that is “sooner than real time” because you see upcoming problems before your real-time monitors can even detect any service disruption.
And for incidents that are truly the result of unpredictable events, it provides insight that dramatically reduces the Mean Time To Resolution.
IntelliMagic Vision produces this Availability Intelligence for your z/OS infrastructure from processors down to the physical disks, and other mission critical z/OS resources as well, such as virtual tape and the replication infrastructure.
Some of the largest mainframe shops in the world are using IntelliMagic Vision every day, as are small and mid-sized shops.
But you don’t have to take our word or even their word for it. Using your historical data we can show you the warning we would have provided before your last incident. Just send us your data, and you can see for yourself.
You can install our software on site. But this problem of how to generate valuable intelligence out of the data, is one that lends itself very well to the Software as a Service model.
In as little as 24 hours after starting to send us your data, you can start receiving valuable intelligence about specific threats to availability in your infrastructure.
And this services option also gives you access to deep experts to consult with you about risks and remediation strategies.
No long term, expensive contract is required.
Intellimagic Vision will provide you with the Availability Intelligence you need to outsmart unavailability incidents by avoiding outages and solving problems faster.
For more information, please contact us at intellimagic.com
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To help enhance the value you can derive from that SMF data, IntelliMagic Vision provides two complementary types of automated anomaly detection: health insights and change detection.
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Change Detection and Health Assessments (based on pre-defined best practice conditions) play complementary roles, but there can be scenarios where they both flag issues. This use case with CICS Max Tasks is one such example.
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