Operations | Monitoring | ITSM | DevOps | Cloud

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

The Fourth Pillar of Observability

Your application is only as reliable as the infrastructure it runs on. Most commonly, that means Kubernetes is doing the job by managing fleets of containers, scaling services on demand, and keeping workloads distributed across nodes. Traditional dashboards weren’t built to scale with this reality. They give you snapshots of raw metrics. They don’t scale to multi-cluster environments. They don’t map relationships between resources.

Bridging the Gap: Legacy Systems and Modern Observability

Technology moves quickly and while the spotlight has shifted to dynamic, cloud-based systems, many organizations have legacy applications and infrastructure that they must maintain. In this fireside chat, Datadog’s Matt Moore (Principal Observability Strategist) will host James Flores (Enterprise Systems Engineer) at Australian Community Media to discuss their journey of modernization and bridging legacy systems with the cloud using a bit of ingenuity and observability.

Actionable insights into the end-user experience: an overview of Grafana Cloud Frontend Observability dashboards

One of the biggest challenges in frontend development is identifying when and why users encounter performance issues, whether it’s slow page loads, JavaScript errors, or failed HTTP requests. With Grafana Cloud Frontend Observability — a hosted service for real user monitoring (RUM) — you get immediate, clear, and actionable insights into the end-user experience of your web applications.
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How to Reduce Continuous Monitoring Costs

Continuous monitoring is a crucial practice in the fields of DevOps, cybersecurity, and compliance. It involves the proactive and ongoing process of observing, assessing, and collecting data from various systems, applications, and infrastructure components in real-time or near real-time. Continuous monitoring is closely related to observability, which goes beyond simple monitoring to provide a deep understanding of complex and dynamic systems.

Tech Talk - Aligning Observability Costs with Business Value Practical Strategies

Learn how to tackle the challenges of growing telemetry data and optimize your observability model to maximize value while minimizing costs. This session will explore strategies to reduce log ingestion, centralize pipeline management, and gain visibility into metric usage to identify waste.

Full-Circle Observability: Using SigNoz to monitor a LangChain agent that queries SigNoz MCP

In Part 1 of this series, we explored how to instrument a LangChain trip planner agent with OpenTelemetry and send telemetry data to SigNoz. By tracing each step of the planning process: LLM reasoning, tool calls for flights, hotels, weather, and activities, and the final itinerary response, we saw how observability turns a black-box agent workflow into a transparent, debuggable system.

LangChain Observability: How to Monitor LLM Apps with OpenTelemetry (With Demo App)

LangChain has become one of the most popular frameworks for building LLM-powered applications, making it easier to create agents that can reason, plan, and take actions. But like any production-grade AI app, LangChain agents can run into performance bottlenecks, hallucinations, or tool call failures. And without proper LangChain observability, it’s hard to know where things break down.