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The world of advanced research and academia often provides a glimpse into the future of technology, with today's cutting-edge challenges frequently becoming tomorrow's mainstream enterprise concerns. A recent example is the New England Research Cloud (NERC), part of the Massachusetts Open Cloud (MOC) Alliance and operated by Harvard and Boston University. NERC serves numerous institutions across New England.

Built on Red Hat OpenShift, NERC includes several clusters (test, production and infrastructure), each with specific user access limitations. These constraints initially restricted access to crucial observability data—metrics, logs and traces—which is valuable for research and teaching, independent of the applications, models or data generating it. 

To address the issue and support demanding artificial intelligence/machine learning (AI/ML) workloads, NERC recently implemented a dedicated observability cluster. As highlighted in the Red Hat Research Quarterly, this development is more than an academic exercise; it’s a clear signal of an emerging essential for any organization serious about innovation within complex IT environments.

NERC researchers, much like enterprise teams pushing boundaries with AI/ML and other distributed, cloud-native applications, recognized an acute need. They required deep, real-time insights into system performance and health to manage resource-intensive experiments and accelerate discovery. This mirrors the escalating challenges enterprises face: the growing complexity of modern workloads deployed across hybrid cloud, datacenter and edge environments. These workloads, often comprised of containerized and virtualized components with dynamic scaling needs, render traditional monitoring insufficient due to the sheer scale of the environments and the volume of data involved.

From research cloud to enterprise strategy

The core truth is that the "cutting-edge" requirements of NERC—managing intricate workloads, ensuring performance and enabling data-driven decisions—are rapidly becoming the baseline needs for competitive enterprises. Fragmented visibility across hybrid environments is a common pain point, and a reactive approach to issue resolution is no longer tenable.

This is where a strategic approach to observability, like what is included within Red Hat OpenShift, becomes crucial. Red Hat OpenShift observability provides a set of capabilities designed for these modern complexities, offering insights into applications and infrastructure across any footprint. It’s about providing real-time visibility and analysis of metrics, logs and traces to help teams quickly diagnose and troubleshoot issues, often before they impact end users. On top of that, the Red Hat observability stack is fine-tuned for large-scale deployments, horizontally scalable, handling large volumes of logs from thousands of pods across many clusters without becoming a resource hog. This unified multicluster observability integrated with Red Hat Advanced Cluster Management for Kubernetes enables research teams to correlate logs and metrics within the same dashboards. They can easily switch between viewing a metric graph and drilling down into the relevant logs at that specific time, speeding up troubleshooting and performance tuning.

4 benefits of observability

  1. Fostering true innovation: Just as NERC empowers researchers, robust observability allows your development teams to experiment and deploy new features with greater confidence. When you can clearly see how applications are performing and how changes impact the system, innovation cycles can accelerate.
  2. Proactive problem solving: Instead of reacting to outages, a comprehensive observability solution facilitates proactive insights and performance optimization. Red Hat OpenShift observability, augmented by Red Hat Insights, helps predict risks and recommend actions.
  3. Data-driven decisions: The ability to collect, visualize and analyze telemetry data empowers teams to move beyond guesswork. This means optimizing resource allocation, improving capacity planning and enhancing application reliability and user experience.
  4. Controlling complexity: With capabilities designed for multicluster and multitenant deployments, and an API-first architecture for extensibility, OpenShift's approach helps manage the inherent complexity of modern IT estates.

The NERC example isn't an isolated case; it’s a practical demonstration of needs that are becoming universal. By looking at how such research platforms address their observability challenges with solutions like Red Hat OpenShift, enterprises can glean valuable lessons for their own journey. Investing in a comprehensive, integrated observability strategy isn’t just about better monitoring; it's about building a resilient, agile and innovative future for your business.

Take the next step

Ready to explore observability at the edge? Visit the redhat.com/observability and documentation pages to learn more, and get started with the latest observability tools in Red Hat OpenShift.

The Observability: Monitor, measure and analyze your application page also contains information to help you learn about and implement observability capabilities.

Be sure to subscribe to the Red Hat Research Quarterly to learn about the latest open source research topics.

We value your feedback! Share your thoughts and suggestions using the Red Hat OpenShift feedback form

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Red Hat OpenShift Data Foundation | Versión de prueba del producto

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Sobre el autor

Dan Bettinger is a tech marketing innovator who has carved a unique path through the evolving landscape of cloud computing, blockchain, and DevOps. Currently serving as Principal Product Marketing Manager for OpenShift at Red Hat, Dan's career highlights include spearheading J.P. Morgan's groundbreaking blockchain network and hosting the IBM Cloud Podcast, where he reached thousands of listeners per episode.

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