Operations | Monitoring | ITSM | DevOps | Cloud

Your Easiest 2026 Resolution: Simplify the Collection Layer and Move to OTel Without the Agent Sprawl

This is blog 2 in our New Year, New Resolution Series on OTel migrations. Read the first post, "New Year, New Telemetry: Resolve to Stop Breaking Dashboards", here. Most New Year’s resolutions fail because they require a "big bang" change. If your 2026 mandate is to migrate to OpenTelemetry (OTel), the traditional approach is the definition of friction.

New Year, New Telemetry: Resolve to Stop Breaking Dashboards

It's 2026. Your New Year's resolution was to finally migrate to OpenTelemetry. But you're staring at dozens of dashboards that depend on your current data format, and that migration deadline is looming... Sound familiar? If you're an SRE or Platform Engineer facing a top-down OTel mandate, you're not alone. The challenge isn't just about adopting a new standard—it's about doing so without disrupting the observability systems your team depends on every day.

The Observability Stack is Collapsing: Why Context-First Data is the Only Path to AI-Powered Root Cause Analysis

By Bill Balnave, VP of Customer Success at Mezmo The core promise of modern observability is simple: cut Mean Time To Resolution (MTTR). Yet, despite a boom in tooling and investment over the last four years, the data tells a sobering story: our industry is actually getting worse at finding and resolving issues. Dashboards, once our trusted guide, have become the starting point for a chaotic "dashboard hunt" that rarely leads to the definitive root cause.

Mezmo + Catchpoint deliver observability SREs can rely on

For SREs juggling multiple services, third-party dependencies, and constant alerts, a critical service slowdown can quickly turn into chaos. APM Dashboards may show everything is fine, yet users are still experiencing problems. That gap—between application telemetry and real-world performance—can turn a five-minute fix into a two-hour war room. ‍

Mezmo's AI-powered Site Reliability Engineering (SRE) agent for Root Cause Analysis (RCA)

We are thrilled to announce the availability of Mezmo’s AI-powered Site Reliability Engineering (SRE) agent for Root Cause Analysis (RCA)—a truly transformative leap forward for engineering and operations teams included in your existing subscription at no additional charge. We are paving the way for a new era of observability, moving beyond passive, reactive monitoring to a world of proactive AI-driven observability.

What is Active Telemetry

Active Telemetry is the evolution in how organizations collect, process, and use observability data. In traditional observability, telemetry is passive: systems emit logs, metrics, and traces that are stored and visualized after the fact. This model worked when systems were simpler and changes were predictable. But in today’s world with distributed microservices, Kubernetes, and AI workloads, passive telemetry can’t keep up. Active Telemetry changes that.

Paving the way for a new era: Mezmo's Active Telemetry

The world of software development has fundamentally changed. We've moved from monthly releases to continuous delivery measured in minutes, and the rise of AI means velocity is no longer just a goal—it's a requirement for survival. But this relentless speed has exposed a critical flaw in how we approach observability. The industry relies on a "store first, ask questions later" model where you collect every log, metric, and trace, and then hope to find the root cause when something breaks.

The Answer to SRE Agent Failures: Context Engineering

AI agents for SREs were supposed to slash mean time to resolution and eliminate alert fatigue. Instead, most teams got expensive, unreliable tools that burn through tokens without delivering insights. But what if the problem isn't the AI models themselves? Recent benchmarking reveals the real bottleneck: context engineering. When we tested our context engineering approach against conventional methods, the results were dramatic: Scroll down for our benchmark results to see the full comparison.

Empowering an MCP server with a telemetry pipeline

This blog was authored by Jason Bloomberg, Managing Director, Intellyx BV ‍ Observability depends upon telemetry – the data streaming from various applications, services, and systems that indicate their internal state in real-time. Various tools consume such telemetry to enable both operational and cybersecurity tasks.