Mainframe observability with Elastic and Kyndryl

Before diving further into the details of mainframe observability, it is crucial to understand what a mainframe is and why it holds such significant value in today's digital landscape. 

A mainframe is a large, high-performance computer that can process and manage vast amounts of data quickly and securely. Mainframes are designed to be reliable, secure, and robust, and they are capable of running critical applications and handling massive volumes of data and transactions. This makes them the backbone of many large-scale businesses, particularly in sectors like the financial services industry, healthcare, retail, and manufacturing. Their processing power, coupled with high levels of security, make them indispensable in environments where large-scale transaction processing is essential. The ability to handle such substantial workload while ensuring an unprecedented level of uptime makes the mainframe a vital component of modern IT infrastructure. 

The Elastic-Kyndryl solution addresses the inherent challenges of managing and observing these complex systems, thereby enhancing their overall operational efficiency.

Business needs have undergone a radical transformation. Efficient monitoring, performance tuning, and continuous service improvement are no longer an added advantage but a necessity. They are at the center of a business's ability to identify and seize optimization and improvement opportunities, thus ensuring efficiency and the provision of uninterrupted services for businesses and end users. At the center of this evolution lies the Elastic-Kyndryl solution.

Mainframes — despite being potent machines responsible for handling data and transactions for numerous businesses — present significant challenges without an adequate capability to observe and analyze their performance and operations. These challenges span identifying and resolving performance issues, gaining visibility into resource usage, and predicting and averting system failures. If left unaddressed, these challenges can culminate in service disruptions, inefficient resource utilization, and increased operational costs.

The Elastic-Kyndryl mainframe observability solution brings transformative change in the world of mainframe observability. It offers a comprehensive approach by leveraging Elastic technology at its core, enabling the ingestion of System Management Facility (SMF30) and Syslog data into Elastic's sophisticated analytics environment. This ability provides the power to identify programs and jobs consuming substantial resources and showing extended run times.

Through the comparison of day-to-day run times of batches over months, deviations can be detected, thereby enabling necessary performance adjustments. Insightful and actionable data is then generated via customized dashboards.

Batch job analytics is an integral component of the Elastic-Kyndryl solution and introduces a robust and intuitive tool that learns job behavior, including job schedules, message sequences, job sequence/dependency, typical time taken/duration between messages, and resource usage patterns.

It carries the capacity to detect anomalies and deliver early warnings and alerts, ensuring potential issues are dealt with before they impact system performance. Additionally, it provides a unified visualization of logs, performance metrics, utilization metrics, tickets, events, and more and offers both real-time and historical views.

A unique attribute of batch job analytics is its agnosticism toward the Batch job or Scheduling tool and its scalability to support large environments running hundreds and thousands of jobs per day that extend beyond mainframe data sources and data types.

The journey of implementing the Elastic-Kyndryl solution includes several steps. It begins with setting up the connector to ingest SMF and Syslog data from the mainframe into the Elastic environment. Following this, the batch job analytics features are configured to meet the organization's specific needs. Next, the necessary dashboards are set up and offer meaningful insights. Finally, the solution is seamlessly integrated with the organization's existing IT infrastructure.

Implementing the Elastic-Kyndryl mainframe observability solution can lead to significant business benefits. It has the potential to prevent batch window overruns, enhance batch performance, reduce Mean Time To Resolution (MTTR), decrease dependency on Mainframe Infrastructure and Operations teams, and optimize system resources. These facets collectively can contribute to significant cost savings. Ultimately, it paves the path for continuous service improvement and boosts end-user satisfaction.

Our mainframe observability solution brings industry-specific advantages to the table. In the financial services industry, the solution's capacity to efficiently monitor and optimize mainframe-heavy systems can drive drastic improvements in operational efficiency, cost savings, and service quality. In addition, it helps these organizations in meeting regulatory requirements and managing risks more effectively.

In the healthcare sector, where patient data security and system uptime are of paramount importance, the solution offers the much-needed visibility and predictive capabilities to ensure system reliability and compliance with data security regulations.

The retail and manufacturing industries can also benefit from the solution's ability to identify performance bottlenecks and optimize resource usage, thereby driving improved operational efficiency and cost savings.

In conclusion, our solution built by Elastic and Kyndryl is set to redefine mainframe observability across diverse industries. Learn more about the Elastic-Kyndryl partnership.