Data Observability: MultiCloud, GenAI Make Challenges Harder

The New Stack Podcast

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Peak Travel

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How a Destination Goes Viral 20:33

לפני 7 ימים20:33

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20:33

Have you ever opened Instagram to see a bunch of people posting from the same place — Lisbon? The Amalfi Coast? Charleston? Japan? It’s no coincidence that every year, it feels like everyone is going on the exact same trips. In this episode, we’re going to pull back the curtain on the travel media industry and show you how a place becomes a viral destination. Learn about your ad choices: dovetail.prx.org/ad-choices…

לפני שנה 23:14

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Rohit Choudhary, co-founder and CEO of Acceldata, placed an early bet on data observability, which has proven prescient. In a New Stack Makers podcast episode, Choudhary discussed three key insights that shaped his vision: First, the exponential growth of data in enterprises, further amplified by generative AI and large language models. Second, the rise of a multicloud and multitechnology environment, with a majority of companies adopting hybrid or multiple cloud strategies. Third, a shortage of engineering talent to manage increasingly complex data systems.

As data becomes more essential across industries, challenges in data observability have intensified. Choudhary highlights the complexity of tracking where data is produced, used, and its compliance requirements, especially with the surge in unstructured data. He emphasized that data's operational role in business decisions, marketing, and operations heightens the need for better traceability. Moving forward, traceability and the ability to manage the growing volume of alerts will become areas of hyper-focus for enterprises.

Learn more from The New Stack about data observability:

What Is Data Observability and Why Does It Matter?

The Looming Crisis in the Observability Market

The Growth of Observability Data Is Out of Control!

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#Tech #News #Tech News #Technology #Thenewstack #New Stack #Development #DevOps #Joab Jackson #Alex Williams #Software Engineering #Heather Joslyn #Cloud Native #Software Development #Kubernetes #Open Source #Darry Taft

Data Observability: MultiCloud, GenAI Make Challenges Harder

The New Stack Podcast

113 subscribers

published לפני שנה

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MP3•בית הפרקים

Learn more from The New Stack about data observability:

What Is Data Observability and Why Does It Matter?

The Looming Crisis in the Observability Market

The Growth of Observability Data Is Out of Control!

Join our community of newsletter subscribers to stay on top of the news and at the top of your game.

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Platform engineering was meant to ease the burdens of Devs and Ops by reducing cognitive load and repetitive tasks. However, building internal development platforms (IDPs) has proven challenging. Despite this, Gartner predicts that by 2026, 80% of software engineering organizations will have a platform team. In a recent New Stack Makers episode, Mallory Haigh of Humanitec and Nathen Harvey of Google discussed the current state and future of platform engineering. Haigh emphasized that many organizations rush to build IDPs without understanding why they need them, leading to ineffective implementations. She noted that platform engineering is 10% technical and 90% cultural change, requiring deep introspection and strategic planning. AI-driven automation, particularly agentic AI, is expected to shape platform engineering’s future. Haigh highlighted how AI can enhance platform orchestration and optimize GPU resource management. Harvey compared platform engineering to generative AI—both aim to reduce toil and improve efficiency. As AI adoption grows, platform teams must ensure their infrastructure supports these advancements. Learn more from The New Stack about platform engineering: Platform Engineering on the Brink: Breakthrough or Bust? Platform Engineers Must Have Strong Opinions The Missing Piece in Platform Engineering: Recognizing Producers Join our community of newsletter subscribers to stay on top of the news and at the top of your game.…

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The New Stack Podcast

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Observability is expensive because traditional tools weren’t designed for the complexity and scale of modern cloud-native systems, explains Christine Yen, CEO of Honeycomb.io. Logging tools, while flexible, were optimized for manual, human-scale data reading. This approach struggles with the massive scale of today’s software, making logging slow and resource-intensive. Monitoring tools, with their dashboards and metrics, prioritized speed over flexibility, which doesn’t align with the dynamic nature of containerized microservices. Similarly, traditional APM tools relied on “magical” setups tailored for consistent application environments like Rails, but they falter in modern polyglot infrastructures with diverse frameworks. Additionally, observability costs are rising due to evolving demands from DevOps, platform engineering, and site reliability engineering (SRE). Practices like service-level objectives (SLOs) emphasize end-user experience, pushing teams to track meaningful metrics. However, outdated observability tools often hinder this, forcing teams to cut back on crucial data. Yen highlights the potential of AI and innovations like OpenTelemetry to address these challenges. Learn more from The New Stack about the latest trends in observability: Honeycomb.io’s Austin Parker: OpenTelemetry In-Depth Observability in 2025: OpenTelemetry and AI to Fill In Gaps Observability and AI: New Connections at KubeCon Join our community of newsletter subscribers to stay on top of the news and at the top of your game .…

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The New Stack Podcast

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Heroku has open-sourced its Twelve-Factor App methodology, initially created in 2011 to help developers build portable, resilient cloud applications. Heroku CTO Gail Frederick announced this shift at KubeCon + CloudNativeCon North America, explaining the move aims to involve the community in modernizing the framework. While the methodology inspired a generation of cloud developers, certain factors are now outdated, such as the focus on logs as event streams. Frederick highlighted the need for updates to address current practices like telemetry and metrics visualization, reflecting the rise of OpenTelemetry. The updated Twelve-Factor methodology will expand to accommodate modern cloud-native realities, such as deploying interconnected systems of apps with diverse backing services. Planned enhancements include supporting documents, reference architectures, and code examples illustrating the principles in action. Success will be measured by its applicability to use cases involving edge computing, IoT, serverless, and distributed systems. Heroku views this open-source effort as an opportunity to redefine best practices for the next era of cloud development. Learn more from The New Stack about Heroku: How Heroku Is Positioned To Help Ops Engineers in the GenAI Era The Data Stack Journey: Lessons from Architecting Stacks at Heroku and Mattermost Join our community of newsletter subscribers to stay on top of the news and at the top of your game .…

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The New Stack Podcast

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The New Stack Podcast

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Why Are So Many Developers Out of Work in 2024? 21:10

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