Operations | Monitoring | ITSM | DevOps | Cloud

OpenTelemetry instrumentation is the foundation of modern microservices observability, but getting it right in production requires more than just enabling auto-instrumentation. This guide covers production-tested OpenTelemetry best practices that help engineering teams achieve reliable distributed tracing, control observability costs, and extract maximum value from their telemetry data.

Organizations are increasingly using agentic AI applications powered by large language models (LLMs) to automate analysis, decision-making, and operational workflows. As these AI agents take on more responsibility, they gain access to internal tools and services and can interact with them in unintended ways.

When to use JavaScript or CSS in frontend projects is a matter of continued debate among many frontend developers. JavaScript is often the default choice for frontend development, as it offers a robust collection of libraries custom-made for creating advanced UI features, such as data-based visualizations or complex animations. But JavaScript also comes with tradeoffs, particularly when it comes to performance, accessibility, and code complexity.

Event-driven systems are great at decoupling services, but they also make incidents harder to untangle. A single user request can turn into dozens (or thousands) of messages, multiple consumers, retries, and delayed acknowledgments. If your tracing only tells you that a message was sent or received, you still have to guess which upstream request produced the message, whether a batch publish fanned out cleanly, and where queue time is accumulating.

Exponential smoothing is a time series forecasting method that uses an exponentially weighted average of past observations to predict future values. In other words, it assigns greater weight to recent observations than to older ones, allowing the forecast to adapt to changing data trends. In this post, we’ll look at the basics of exponential smoothing, including how it works, its types, and how to implement it in Python.

By incorporating observability tools into your stack, you can better understand how your complex infrastructure operates, reduce downtime, and empower developers to identify and fix problems quickly. However, it now takes considerably more work, time, and money to build the best observability tools for your infrastructure and applications. According to a Splunk survey, over half of the firms polled employ eight or more observability tools.

ATS Group and Galileo are pleased to announce the appointment of Andy Wojnarek as Chief Technology Officer. Andy’s appointment reflects the evolution of a technical leadership role he has developed over more than 16 years with the company, grounded in hands-on expertise, cross-functional influence, and a sustained focus on solving complex infrastructure and observability challenges for clients.

Driving down the highway, you usually glance intermittently at your speedometer to ensure that you stay within the speed limit, or whatever window above the speed limit you’re willing to drive. While monitoring your speed mitigates the risk of a ticket, you still need to look out for various threats on the road, like cars going through stop signs. By observing your surroundings, you take in real-time information that can help prevent a crash.

DNS Spy now offers complete brand protection with WHOIS History & Monitoring and Phishing Sentinel—automatically tracking domain registration changes and detecting phishing variants before they become security incidents.