Mainframe and IBM i Observability: Why It Matters to IT
In decades past, IT systems were relatively self-contained. Inputs, outputs, and integration points were clearly defined and comparatively few. Today’s systems, however, are highly interconnected and constantly in flux. Data flows from edge devices to core applications and back again. A myriad of data analytics tools provide up-to-the-minute insights to decision-makers throughout the organization.
Naturally, the highly interconnected nature of modern systems opens the door to plenty of new possibilities, but it also creates some new challenges. With so many moving parts, it can be difficult to zero in on the root cause of an unexpected problem. Observability helps IT teams to achieve mastery over this complexity.
How Observability Differs from Monitoring
Observability is emerging as a relatively new paradigm in IT. As such, some different definitions are circulating in the marketplace, each with its particular nuances. Precisely defines observability as “the ability to measure the internal states of a system by examining its outputs,” including things like log files and alerts. Observability helps IT professionals to link causes and effects within a highly complex and interactive chain of events.
Monitoring, in contrast, is more limited in scope because it typically involves tracking parameters to alert IT staff to metrics that fall outside the norm or could potentially trigger compliance issues. Monitoring is necessary, but by itself, it offers a fairly limited view of reality.
The concept of observability extends beyond the edges of isolated systems, giving IT teams a view of the entire system landscape. Observability allows teams to oversee modern systems more effectively and efficiently by zeroing in on the root causes of specific states or behaviors.
This has some very real business benefits. According to research from Splunk, companies on the leading edge of observability are 2.1 times as likely to detect problems in internally developed systems in just minutes. They also report a 69% faster mean time to resolution for unplanned downtime or performance degradation.
Observability leaders, according to the Splunk study, reported an average downtime cause for internal applications of $2.5 million annually, compared to nearly $24 million for those just getting started.
Observability Accelerates Root Cause Analysis
In today’s highly interconnected systems, pinpointing the root cause of a problem can be especially difficult because there are so many things happening at once. A small change upstream can have unintended consequences to systems or applications of which the author may not even be aware.
A seemingly minor change to a source database, for example, can impact an executive dashboard or AI training model. In a best-case scenario, the problem will be apparent right away. In a worst-case situation, decision-makers could rely on the erroneous data for some time before discovering the problem.
Observability is critical because it shifts the focus of IT visibility to a more proactive, holistic perspective. It provides the information that IT teams need to get ahead of problems when they occur.
eBook
IT Operations Checklist for z/OS Mainframes
Read this eBook for a comprehensive start to ensuring the health, availability, and security of your z/OS mainframe systems. Explore how new technologies have emerged that enable you to capture mainframe information and quickly move it to an open-system based analytics platform to be integrated, correlated, analyzed, and visualized.
Observability for Mainframe & IBM i Systems
Organizations that run mainframe and IBM i systems must develop an observability strategy that fully incorporates those core elements of their IT environment. In most organizations, mainframes are still treated as somewhat of a standalone operation. They come with their own databases, programming languages, security protocols, and interfaces, requiring a unique set of skills.
But mainframes and IBM i systems aren’t going anywhere anytime soon. They’re secure, reliable, and efficient. While there’s a good deal of talk about modernization, many organizations are opting for pragmatic improvements that enable them to continue leveraging the power of the mainframe to handle mission-critical workloads.
These systems tend to be computationally intensive, often processing hundreds of thousands if not millions of transactions per day or even per minute. That generally comes with some very high expectations for availability, every second of every hour of every day. Today’s consumers expect to be able to get an accurate bank account balance from their mobile device, whether it’s the middle of the workday or 3 a.m. Given those high stakes, companies simply cannot afford to overlook mainframes and IBM i systems when they’re devising an observability strategy.
Getting Access to the Right Information
To drive better insights and agility, IT teams need access to the logs, metrics, and traces that originate on their mainframe & IBM i systems. It can be difficult to make sense of all that information, given the sheer volume of data available.
Moreover, that information needs to be available as part of the comprehensive view of the IT landscape. The concept of observability is about understanding the complex and dynamic relationships of various interconnected systems. You can’t achieve that if your mainframe or IBM i system is still functioning as a silo.
Precisely Ironstream makes it possible to integrate mainframe and IBM i systems into leading IT analytics and operations platforms like Splunk IT Service Intelligence, ServiceNow, Elastic, Kafka, and Microsoft System Center. Precisely Ironstream enables an enterprise-wide view, supporting true observability of the entire IT landscape. That, in turn, allows IT teams to get ahead of issues and resolve them proactively, often before customers or other stakeholders are even aware of a potential problem.
One leading global bank is using Ironstream to manage hundreds of applications and critical business services that serve millions of customers worldwide. The bank is using Splunk IT Service Intelligence to present a “Glass Table” view showing the health status, performance, and trends for their most mission-critical systems. Having initially focused on payment card systems, the bank is now expanding its use of Ironstream and Splunk to include other critical functions.
To learn more about ensuring the health, availability, and security of your mainframe systems, check out Precisely’s free ebook today, IT Operations Checklist for z/OS Mainframes.