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The latest News and Information on Observabilty for complex systems and related technologies.

Climbing the Security Pyramid: From Awareness to Automation with AI and Observability

Modern threats don't wait. They move fast, hide deep, and often strike without warning. That's why old-school security isn't enough anymore. You need more than firewalls and login rules. You need layers. You need clarity. And most of all, you need speed. This is where the security pyramid comes in. It shows how smart security stacks-from the ground up. It starts with awareness and ends with advanced tools like automation and AI. In this article, we'll break it down step by step-and show how observability and automation help you climb it.

The Fast Path to More Useful Telemetry

Over and over, we’ve seen that teams who invest in adding rich, relevant context to their telemetry end up debugging faster and collaborating more effectively during incidents. Getting meaningful context added can feel like a big cross-team project, but some of the highest-leverage improvements don’t require app code changes or coordination across services.

Observability as Code: Why You Should You Use OaC

Key takeaways In the fast-moving world of CI/CD pipelines, microservice architectures, and container orchestration, software changes rapidly. What exists in a codebase today might be gone next week. At this scale and speed, it’s impossible for development teams to manually track every line of code and every new piece of functionality.

Uptrace v2.0: The Future of Observability is Here

The Uptrace team is thrilled to announce the release of v2.0—our biggest update yet! This release represents a complete reimagining of how observability data should be stored, queried, and managed. With multi-project support, revolutionary JSON-based storage, powerful data transformations, and a host of developer-friendly features, Uptrace v2.0 is designed to scale with your growing infrastructure needs.

Elastic named a Leader in the 2025 Gartner Magic Quadrant for Observability Platforms

Observability has an investigation problem, and dashboards and alerts aren’t enough for solving problems in today’s complex systems. AI-driven capabilities, powerful analytics, and the ability to scale are essential to drive real-time investigations while keeping costs low. We think this is why Elastic has been named a Leader in the 2025 Gartner Magic Quadrant for Observability Platforms for the second time.

How to improve your observability

Coroot was designed to solve the problem of time-consuming root cause analysis. It handles the full observability journey - from collecting telemetry automatically with zero code setup (thanks, eBPF!) to simplifying the role of SREs and DevOps everywhere with instant root cause analysis powered by AI. We also strongly believe that simple observability should be an innovation everyone can afford to benefit from: which is why our software is open source!

Datadog named Leader in 2025 Gartner Magic Quadrant for Observability Platforms

We are thrilled to announce that, for the fifth consecutive year, Datadog has been named a Leader in the 2025 Gartner Magic Quadrant for Observability Platforms. We believe that this recognition reflects our continued focus on helping customers observe, secure, and act on everything that matters across their technology stack.

What Are Traces? A Developer's Guide to Distributed Tracing

One of the most common challenges in modern software engineering today is understanding how requests flow through applications. As system architectures shift to favor widely distributed, cloud-native designs, keeping track of how an application processes user actions is more difficult than ever. A single user action may trigger events processed in dozens of backend services. Traces are helping software developers today with this challenge.

The Inconvenient Truth About AI Ethics in Observability

Let's be honest: most conversations about AI ethics sound like they're happening in a boardroom, not an ops room. But here's the thing, when you're using AI to make sense of your telemetry data, ethics isn't some abstract concept. It's the difference between insights you can trust and algorithmic noise that leads you down the wrong path. The uncomfortable reality? Your AI is only as ethical as the messiest, most biased piece of telemetry data you feed it. And if you think your data is clean, well...