Tag: Observability
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How to Monitor Virtual Machines with Middleware
Virtual machine (VM) monitoring tracks CPU, memory, disk, and network performance in real time, allowing infrastructure teams to detect and resolve issues before they affect users. 📖 New to infrastructure monitoring? Read our foundational guide → What Is Infrastructure Monitoring? This guide covers how to deploy Middleware’s OpenTelemetry-based monitoring across VMs on AWS, Azure, and…
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Frontend Performance Metrics: Bridging the Gap from Browser to Backend with RUM and Tracing
Frontend performance metrics measure how quickly and smoothly a web or mobile application behaves for users. This includes load time, interactivity, and visual stability across different devices, browsers, and app environments. Frontend performance metrics often show that something is wrong, but they fail to explain who is affected, how it impacts users, and where the…
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How a SaaS Team Scaled End-to-End Browser Tests with Middleware Synthetic Monitoring
An EdTech platform with 200k users learned a hard lesson in reactive monitoring. After a Friday deployment, their status page was green, but their checkout was dead for iOS 14 users. It took two hours to diagnose while revenue leaked. By pivoting from manual regression to a Synthetic-First Observability Strategy with Middleware, they cut detection…
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Best 9 ServiceNow (Lightstep) Alternatives for Observability in 2026
Lightstep is officially discontinued, leaving teams to find a reliable replacement. This guide compares the best Lightstep alternatives in 2026
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Best 9 Distributed Tracing Tools in 2026
Distributed tracing tools track requests as they move across services, helping teams identify where slowdowns, failures, and bottlenecks occur in modern distributed systems. Modern applications don’t run in one place. A single user request can pass through multiple services, APIs, and databases before returning a response. When something slows down or breaks, it’s not enough…
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The Complete Guide to Observability Pipelines
You know that moment when something breaks in production? Alerts go off, you open logs, and it’s just… noise. Different formats, useless messages, missing context, and the one thing you need isn’t there. That’s the current state of telemetry for most teams. An observability pipeline sits between your data sources and your monitoring tools. It…
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Grafana Tempo: Simplifying Distributed Tracing at Scale
Learn how Grafana Tempo simplifies distributed tracing at scale using object storage and how to get started with TraceQL, Helm, and Grafana
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Mastering Your Data Flow: Introducing the Middleware Observability Pipeline
Middleware Observability Pipeline helps teams cut noise, reduce costs, and protect data by filtering, enriching, and controlling telemetry before storage.
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Real-Time Anomaly Detection in AI Models
Learn how real-time anomaly detection works in AI systems. Identify data drift, model performance issues, LLM failures, and GPU anomalies using metrics, traces, and logs with observability platforms like Middleware.
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Continuous Profiling: What It is and How it Works
Continuous profiling helps you detect CPU, memory, and performance issues in production by continuously analyzing real code behavior.
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Observability Predictions for 2026
Discover the top observability trends for 2026, including proactive AIOps, OTel adoption, cost-aware telemetry, and deeper, intelligent insights.
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Resolve Root Cause Issues with Middleware Before User Impact
Predict and resolve issues before users feel the impact. Middleware’s AI-powered observability delivers instant root-cause insights, faster fixes, and fewer incidents.
