The Mezmo blog

Explore how Jev's structured decision models can help SRE teams evaluate evidence, choose next steps, and build more reliable autonomous operations.

A Mezmo AI Investigation is a root cause analysis record AURA produces when a Pipeline node alert fires, with evidence, a confidence score, and a root cause.

Walk through OpenTelemetry trace analysis in Mezmo, from service maps and anomalous traces to AI-powered investigations and root cause analysis.

Build a working AI SRE agent that investigates Kubernetes incidents using real cluster state and Prometheus metrics, with least-privilege tool access.

AURA engineer Mike Shearer explains why production agents need persistent context, server-side execution, orchestration, and measurable evaluation.

Context engineering helps SREs and AI agents reason over telemetry by designing structure, lineage, and intent into every signal for modern operations.

AURA is Mezmo's open-source SRE agent that runs in your infrastructure to investigate incidents, ground findings in real telemetry, and keep actions reviewable

Tony Rogers explains how Mezmo tests AURA with internal benchmarks, trace inspection, and workflow validation to make agentic SRE reliable before production

Mezmo SRE Eric Lake connected AURA to GitHub runbooks via MCP, auto-generates missing ones, and stores investigation memory across incidents.

Single SRE agents hit a ceiling fast. See how AURA's orchestration mode routes work across scoped agents to cut tool overload and context confusion.

Context engineering is the deliberate design of telemetry, metadata, and feedback loops so AI agents reason accurately over production systems during incidents

Mezmo PM Henry Andrews on why AURA uses Rust, TOML configs, and OpenTelemetry to make MCP-native agent workflows inspectable and production-ready for SRE teams.

We put AURA behind a Slack bot, connected it to PagerDuty, Prometheus, and Mezmo via MCP, and pointed it at our own production environment. Here's what worked.

56% of teams have zero agents in production. The five steps that move SREs and platform engineers from agent demo to autonomous ops with AURA and Mezmo.

Learn how AURA helps SRE and platform teams turn incident investigations into draft runbooks using grounded context, MCP tools, and human review.

Explore six production use cases for AURA, Mezmo's open-source, MCP-native agent harness, from drop-in chat agents to runbook-grounded RCA.

AURA was built to be an open-source standard for production AI, designed to connect your models so you can trust what you see.

SaaS is changing for the better. Now, organizations can build, deploy, and scale faster than ever — it’s our job to provide the System of Context.

Grok Patterns are reactive. Real evolution is shifting from manual parsing to AI-assisted systems for improved understanding and observability.

Take back the power and control of your observability strategy. With OpenTelemetry and Mezmo, break free from vendor lock-in and cut your costs today.

The latest Mezmo AI SRE update adds streaming progress, log aggregation, and visualization tools to make observability faster and more intuitive.

Don’t let legacy agents cause problems during your OpenTelemetry migration. Mezmo makes migrating to OpenTelemetry and unlocking the true potential of AI easy.

More dashboards haven't cut MTTR. See why context-first data is the only path to AI-powered root cause analysis that lowers tokens and cost.

Mezmo and Catchpoint pair internal telemetry with external performance insight and agentic SRE analysis to surface real root causes and shrink MTTR.

Mezmo's new AI SRE agent is here. Get instant root cause analysis, 90% faster MTTR, and proactive observability, included in your subscription at no extra cost.

Active Telemetry turns logs, metrics, and traces into AI ready signals in real time to cut noise, reduce spend, speed MTTR, and enable agentic ops.

Mezmo’s AI SRE delivers root cause analysis fast with agentic workflows, Active Telemetry, and an MCP Server, cutting costs by 90% and MTTR by up to 80%.

Discover Mezmo's Active Telemetry—a proactive approach that delivers real-time, high-fidelity data developers, SREs, and AI agents need to move faster.

AI SRE agents overpromise but underdeliver due to missing context. Learn why raw telemetry breaks them — and how Mezmo’s Context Engine fixes it

AI agents are only as good as their context. Learn how Mezmo's telemetry pipeline supplies the real-time data that powers AI-driven observability.

Skip the manual log hunt. The Mezmo MCP Server delivers context-rich data to AI agents, enabling instant root cause analysis and proactive workflows.

Eliminate tool friction and boost productivity. The Mezmo MCP Server delivers seamless access to observability data across your dev ecosystem.

Boost efficiency with Mezmo’s new AI chatbot. Get instant answers, context-aware help for pipelines, and smarter workflows, all directly in the platform.

Engineering teams don’t need more telemetry data. Discover how Mezmo’s MCP Server brings AI-ready context to observability and accelerates root cause analysis.

It’s time to ditch the oil analogy. Discover why modern data infrastructure looks more like a dynamic power grid than a pipeline, and what that means for SREs.

Learn how Mezmo helps platform teams streamline OpenTelemetry, manage compliance, and cut observability costs in Dynatrace, all from one control plane.

Cut MTTR by replaying full-fidelity logs on demand. Learn how Mezmo + Dynatrace accelerate root cause analysis with real-time data and zero delay.

Learn how Mezmo helps reduce your Dynatrace bill by filtering noisy logs, managing cardinality, and sending only high-value data to the platform.

Learn how to reduce observability costs without sacrificing visibility. Explore four key cost drivers and how Mezmo helps teams take control.

Most teams still collect everything, all the time. Learn how synthetic monitoring can trigger responsive telemetry pipelines to cut cost and noise.

Your AI is only as ethical as your data. Learn why messy telemetry creates bias, and how to build trust with transparency, security, and human oversight.

Observability is evolving, not ending. Learn how AI-first pipelines cut costs, speed insights, and transform ops into a strategic advantage.

From cost control to real-time insights, telemetry pipelines help engineers cut noise, enrich data, and build smarter observability into every tool.

Mezmo filters noise, enriches logs, and pinpoints root causes fast—so you can resolve incidents quickly and avoid sleepless nights.

Observability costs start upstream in your pipeline. Learn how smarter telemetry pipelines cut data volume and noise, and ready you for agentic ops.

Why modern telemetry stacks miss the mark on MTTR, and how smarter signals plus synthetic monitoring help teams detect, debug, and resolve faster.

Mezmo’s new pricing model simplifies observability, reduces costs, and gives teams full control over how they process, analyze, and retain telemetry data.

Struggling with rising Datadog costs? Learn smart Datadog cost optimization strategies to reduce log ingestion and keep value high without vendor lock-in.

Telemetry toil and data overload slow teams down. Learn why rapid pipelining and early data processing outperform retention policies for observability.

Telemetry Pipeline 101: what makes a good pipeline, why it matters for DevOps, and how it cuts data bloat so you get insight without the budget burn.

Explore the 2024 DORA Report's insights on DevOps performance metrics and the nuanced impact of AI on software delivery.

Learn the differences between SLOs, SLAs, and SLIs, and how Mezmo helps optimize system performance for reliability, compliance, and operational success.

Learn how data profiling can combat burnout by streamlining telemetry data analysis, reduce mental toil, and focus on critical projects.

Unlock the full potential of OpenTelemetry (OTel) with Mezmo by simplifying Telemetry data collection and enhanced system monitoring.

Learn more about open-source telemetry pipeline solutions, their common use cases, and how Mezmo’s offering stands out from the crowd.

Discover how Mezmo leverages Vector's capabilities to enhance telemetry data management, ensuring efficient data collection and actionable insights.

For teams working with sensitive medical or financial data, Mezmo Edge processes telemetry in your own environment to meet PCI, GDPR, and CCPA needs.

Separate signal from noise: learn how to derive valuable metrics from logs with the Mezmo Telemetry Pipeline for clearer, data-driven decisions.

Metrics and log-to-metrics processors can play a crucial role in an organization’s decision-making process when analyzing its data.

Organizations can gather, process, and enhance the value of their data with these six steps to implement a telemetry pipeline.

Observability pipelines make SRE lives easier by enabling better management, value, and insights from data for less cost.

At KubeCon 2022, we received some key industry insights on observability data, and the results were enlightening. Check out what we found.

Observability Pipelines centralize your telemetry data for transformation, correlation, and routing for teams. Here's how to find the one that meets your needs.

Telemetry pipelines save more than time. See how they keep observability costs down even as your organization generates ever more data.

Introducing Mezmo for OpenTelemetry: Reduce your MTTD and MTTR by making log data more actionable through the power of Mezmo and OpenTelemetry.

Learn the basics of observability data and the need for an observability data pipeline to centralize and enrich your data.

Log data is a pillar of observability — understand 5 of the top metrics for DevOps teams to monitor in order to achieve true observability.

Which Kubernetes signals matter most? A guide to the top Kubernetes metrics and logs you need for true end-to-end monitoring of your clusters.

Log alerts allow organizations to gain insight into critical events like server warnings, performance loss, and business insight necessary for productivity.

Splunk promises one-stop observability, but cost, complex setup, and speed hold it back. Compare 12 alternatives on features, scale, and price.

As organizations evolve, so do their data needs. How they log, monitor, and use metrics evolves as well, changing the future of DevOps observability.

A practical guide to regular expressions and grep: what regex is, why it matters, and how to use it to search and parse text and log data.

Compare Kibana, Grafana, Prometheus, and Mezmo as data visualization tools, and learn which fits your monitoring, troubleshooting, and security needs.

Elastic Stack can be a free solution, but that doesn't mean it won't cost your organization. When scaled, the costs can rise immensely.