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The latest News and Information on Application Performance Monitoring and related technologies.

New Dashboards and Reports for Kubernetes Monitoring

This is just a quick blog to draw attention to some new and enhanced monitoring dashboards and reports we have added to eG Enterprise in our latest release (v7.5) to provide quick and powerful overviews when monitoring a range of Kubernetes technologies. As with all our dashboards, color-coded overlays provide guided drilldown for help desk operators and administrators.

Datadog Feature Flags, track Claude costs, migrate historical logs, and more | This Month in Datadog

See how you can reduce risk during feature rollouts in September’s This Month in Datadog. This episode, we spotlight Datadog Feature Flags, which combines advanced targeting with built-in observability, and guardrails to make rollouts safer and more controlled. Plus, we cover: This Month in Datadog brings you the latest updates on our newest product features, announcements, resources, and events.

From Logs to Insights: Accelerate Customer-Impact Analysis with Datadog Sheets

Datadog Sheets helps you move from log exploration to actionable insights quickly and with no code required. In this demo, see how to enrich logs with Salesforce data, build pivot tables, uncover customer impact trends, and build shareable reporting, all within Datadog.

Top 11 Java APM Tools: A Comprehensive Comparison

Are your Java applications running at their optimal performance, or is there room for improvement to make them faster and more efficient? With so many services depending on Java, keeping applications responsive and reliable is a core part of modern software engineering. This blog walks you through the leading Java Application Performance Monitoring (APM) tools, with a clear comparison to help you choose the right option for your needs.

OpenMetrics vs OpenTelemetry - A guide on understanding these two specifications

OpenMetrics and OpenTelemetry are popular standards for instrumenting cloud-native applications. Both projects are part of the Cloud Native Computing Foundation (CNCF) and aim to simplify how we generate, collect and monitor services in a modern cloud-native distributed application environment. Let's have a look at how both the standards are aiming to help solve the observability conundrum.

LLM Observability in the Wild - Why OpenTelemetry should be the Standard

A few days ago I hosted a live conversation with Pranav, co-founder of Chatwoot, about issues his team was running into with LLM observability. The short version: building, debugging, and improving AI agents in production gets messy fast. There's multiple competing standards for default libraries for LLM observability. And many such libraries like OpenInference which claim to be based on OpenTelemetry don't strictly adhere to it's conventions.

An overview of Context Propagation in OpenTelemetry

To effectively manage modern applications, you need to understand how they work on the inside. Distributed tracing is the key to this, providing a detailed picture of a request's journey across every service. OpenTelemetry has emerged as the industry-standard framework for implementing tracing and achieving true observability in complex, distributed systems. In this article, we embark on a journey to explore the core concept of context propagation within Open Telemetry.

OpenTelemetry and Jaeger | Key Features & Differences [2025]

OpenTelemetry is a broader, vendor-neutral framework for generating and collecting telemetry data (logs, metrics, traces), offering flexible backend integration. Jaeger, on the other hand, is focused on distributed tracing in microservices. Earlier Jaeger had its own SDKs based on OpenTracing APIs for instrumenting applications, but now Jaeger recommends using OpenTelemetry instrumentation and SDKs. Warning The original Jaeger client SDKs (based on OpenTracing) are archived and no longer maintained.

Key APM Metrics You Must Track

Application Performance Monitoring (APM) helps you understand how your software runs in production. When you track the right metrics, you see how requests move through your system, where slowdowns happen, and how resources are being used. With this knowledge, you can spot issues early and keep your applications reliable for your users. In this blog, we discuss the key APM metrics to monitor, grouped into categories, and why each one matters for performance and user experience.

New Relic's CCU-based pricing is creating unpredictable costs, pushing teams to sample heavily

We talked to 7 companies in August 2025 who were looking to switch from New Relic. One engineering director said they're paying $1,000 a month and only ingesting 10% of their traces. Teams are defaulting to aggressive sampling, some at 1%, others at 10%, to manage costs.