Mezmo

Tired of every incident turning into a 3-hour team huddle? Mezmo’s AI SRE agent finds the "why" instantly, cutting the guesswork and giving you back your night.

There is a lot of noise about AI SREs and "autonomous operations." But as an intelligent person, you're looking past the hype to the actual, messy reality of running cloud-native systems. Feeding raw logs into an LLM for a root cause analysis is like giving a detective a pile of unsorted papers and expecting a solved case. It’s expensive, unreliable, and prone to hallucinations. The core problem: garbage in, garbage out The most significant bottleneck in incident response today isn't the model's intelligence; it's the data's quality. SREs and developers spend hours on: Filtering Noise: Dealing with duplicative, low-value telemetry. Context Switching: Jumping between logs, traces, and metrics to manually piece together a timeline. Prompt Engineering: Trying to get a generic LLM to understand their unique, complex stack. The result is RCAs that take hours and cost a fortune in token usage. The breakthrough: Agentic SREs and the MCP The real shift isn't just using AI, but building an intelligent context layer for the AI. This is what most refer to as Context Engineering. A true Agentic SRE doesn't just read data; it refines it as it deduplicates, validates, and aggregates, before the model ever sees it. This targeted approach transforms the workflow: Cost Reduction: We're seeing token costs drop by 90%+ because the agent isn't wading through noise. Speed: RCA time compresses from hours to minutes. Reliability: The results are based on high-fidelity signals, virtually eliminating AI "flakiness." This move from passive storage to Active Telemetry—where the data itself is prepared for intelligent consumption—marks a fundamental shift. It means engineers stop being data janitors and start being system architects. This is an exciting time to be in this space—things are changing so quickly. Mezmo is stoked to pave the path to the future for how every successful engineering team should be managing complexity and scale—while also reducing their costs. Want to see our Agentic SRE in action? Book some time with us: https://lnkd.in/eA9D7AZu #SRE #AgenticAI #Observability #ContextEngineering #CloudNative #Mezmo

The world of monitoring and observability is evolving quickly. We’ve had dashboarding and graphs forever, but those tools were only ever as good as the time invested in them. As tech stacks grow in both variance and data volumes, monitoring systems have to keep up to provide lasting value. With the rise of AI, new ways of addressing this situation present themselves. The catch? AI tools are only as good as the context they are given. We can throw everything at an LLM and hope with clever prompting that the LLMs accurately determine signal from noise and derive valid potential root cause analysis. This is a new and very expensive bottleneck, because context size = token count. Can we do better? AI engineers here at Mezmo have written our MCP to dramatically improve the quality of context provided to your LLM. By increasing the precision of log data we reduce AI processing costs, reduce time-to-result, and increase the odds of accurate root cause analysis. Using an agent connected to our own logs (via our MCP), to our own documentation, and to our tooling repos, AI has produced some fantastic internal insights and eased some operational burdens for SREs at Mezmo at minimal incremental cost. It can for you too. Managing costs is a major part of platform leadership. If your team is drowning in data volumes or token costs, see how Mezmo can leverage AI to help you: https://lnkd.in/gRyNzZPV #PlatformEngineering #SRE #Mezmo #AI

Discover the transformative power of telemetry pipelines and how they are used to manage application performance.

This Gartner Market Guide details trends driving rapid adoption of telemetry pipelines.

This Gartner report explains how pipelines transform noisy, inconsistent data into clear, actionable insights, and highlights how Mezmo helps you take control.