In this episode of Techsplainers, we explore network observability, a proactive approach to understanding and managing complex network environments. Unlike traditional monitoring, which focuses on predefined metrics, network observability provides real-time visibility into network health and performance across on-premises, hybrid, and multicloud infrastructures. We break down its five pillars—metrics, logs, traces, context, and correlation—and explain how they work together to deliver actionable insights. You will also learn about key capabilities, such as intelligent alerting, topology mapping, and continuous performance analysis, as well as the benefits of observability for security, cloud migration, and cost optimization. Whether you are an IT professional or a tech enthusiast, this episode will help you understand why network observability is critical for resilience and efficiency in today’s digital world. Find more information at https://www.ibm.com/think/podcasts/techsplainersNarrated by PJ Hagerty
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Observability vs. monitoring
In this episode of Techsplainers, we explore the key differences between observability and monitoring and why both are critical for managing complex IT environments. Monitoring focuses on tracking predefined metrics and alerting teams when something goes wrong, while observability goes further by providing context and insights into why issues occur and how to fix them. We discuss how observability evolved from traditional application performance monitoring, the role of telemetry data (including logs, metrics, and traces), and how these tools work together to optimize performance. You will also learn about the benefits of observability for dynamic, cloud-native architectures and how AI-driven features enable predictive analytics and proactive issue resolution. This episode will help you understand how monitoring and observability create a powerful framework for reliability and scalability.Find more information at https://www.ibm.com/think/podcasts/techsplainersNarrated by PJ Hagerty
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Three pillars of observability
In this episode of Techsplainers, we break down the three pillars of observability: metrics, logs, and traces. We'll explain how they provide the foundation for understanding complex cloud-native systems. Discover what each pillar does, why they matter, and how they complement each other to deliver actionable insights for DevOps teams. We also explore system events, distributed tracing, and emerging capabilities like continuous profiling, which offer deeper visibility into application performance. Whether you are a developer, IT professional, or tech enthusiast, this episode will help you understand how observability accelerates troubleshooting, optimizes performance, and supports modern digital transformation. Find more information at https://www.ibm.com/think/podcasts/techsplainersNarrated by PJ Hagerty
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What is observability?
This episode of Techsplainers takes a deep dive into observability, a cornerstone of modern DevOps and cloud-native environments. We break down what observability really means—going beyond traditional monitoring to provide full-stack visibility into complex systems. You’ll learn about its three pillars: logs, traces, and metrics, and how they work together to deliver actionable insights. The discussion explores how observability empowers teams to troubleshoot faster, optimize performance, and improve user experience. We also examine cutting-edge innovations like AI-driven observability, predictive analytics, and causal AI, which are transforming how organizations prevent issues before they occur. Real-world benefits, common use cases, and the role of observability in accelerating DevOps pipelines round out this comprehensive guide to one of today’s most critical tech practices.Find more information at https://www.ibm.com/think/podcasts/techsplainersNarrated by PJ Hagerty
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What is data quality management?
This episode of Techsplainers explains data quality management (DQM)—a set of practices that ensure data is accurate, complete, consistent, timely, unique, and valid. Learn why high-quality data is critical for business intelligence, regulatory compliance, and AI performance, and explore key techniques like data profiling, cleansing, validation, and monitoring.Find more information at https://www.ibm.com/think/podcasts/techsplainersNarrated by Matt Finio
Introducing the Techsplainers by IBM podcast, your new podcast for quick, powerful takes on today’s most important AI and tech topics. Each episode brings you bite-sized learning designed to fit your day, whether you’re driving, exercising, or just curious for something new. This is just the beginning. Tune in every weekday at 6 AM ET for fresh insights, new voices, and smarter learning.
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