Introduction

Organizations are drawn to the promise of AIOps to maintain resiliency by leveraging AI-driven intelligence and automation for quick and accurate decisions.  AIOps uses artificial intelligence to simplify IT operations management through acceleration and automation of problem resolution in complex modern IT environments.

A recent blog by Sanjay Chandru sets the stage for guiding you on Best practices for taking a hybrid approach to AIOps. A key capability that empowers IBM Z IT ops teams and accelerates your journey to AIOps is accurately detecting issues and anomalies across hybrid cloud infrastructure and applications.  We will focus on monitoring and observability delivering faster resolution with full-stack monitoring for early detection of Z incidents.

As IT systems become more dynamic and connected, new monitoring approaches are needed to maintain operational resiliency. Observability is a new approach that augments rule-based monitoring by measuring to understand the internal states of a system from external outputs.

Observability focuses on being prepared by instrumenting all applications and infrastructure components to monitor a critical set of KPI’s for health of the applications and infrastructure. By applying AI / ML, analysis of long-term trends can detect potential problems. The teams can be alerted to perform root cause analysis and decide on a resolution.

Observability does not replace monitoring – rather it enables better resource and application performance monitoring across the hybrid application.

Customer challenges

The growing complexity of new application architectures involving open mainframe services, challenges monitors to capture even more metrics and provide better insights into these new workloads. Failure to modernize monitoring and observability exposes customers potentially avoidable outages.

A basic monitoring challenge is adding more metrics and collection points balanced against the undesired side effect of increased overhead to the monitored environment.

Another challenge lies in effectively using the thousands of metrics with open tooling for analysis in context of modern hybrid cloud applications due to lack of integration through API’s or due to complex data format translation processes.

A pervasive challenge is in attracting and retaining the skills and expertise to address these ever-changing complex architectures. Modern monitoring and observability needs to be simple enough for IT staff to understand and execute even complex tasks with confidence and speed.

Continue reading on Planet Mainframe

ATTENTION: Log4j / Log4Shell Threat

DataKinetics products do not use or include any Java libraries.

Users of tableBASE, tableBASE VTS, and tableBASE Online are not vulnerable to the Log4j / Log4Shell threat.