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Mezmo Adds Stateful Processing in Telemetry Pipelines

Mezmo announced new capabilities that help companies understand, optimize, and respond more quickly to their telemetry data.

Mezmo’s Telemetry Pipeline can now trigger stateful alerts in stream. It detects data variations and compares data in motion to metrics thresholds to send alerts based on predefined parameters so users can take swift action to remediate issues and prevent costly overages.

Now you can process terabytes — even petabytes — of data originating from multiple sources and address unexpected events or issues such as misconfigurations that can cause data spikes and excessive overages. Automated in-stream alerts (stateful) allow the data to be actionable and minimize the cost of indexing in expensive observability tools. This workflow provides cost-effective control of telemetry data while offering new and immediate business insights by moving data logic into the pipeline. With Mezmo Telemetry Pipeline, teams can now access various insights and alerts without completely depending on metrics inside observability platforms and act on data aberrations quickly.

“Mezmo delivers advanced capabilities that help SRE, ITOps, and security teams more effectively manage their data and more quickly discover when there is a problem so they can remediate it fast, without wasting time or money,” said Tucker Callaway, CEO, Mezmo. “While other telemetry pipelines focus on data movement and control, Mezmo takes a data engineering approach to make telemetry pipelines more intelligent. New alerting capabilities are another innovative step in shifting logic into the pipeline and making data more actionable.”

Here are some examples of in-stream alerts:

- Threshold Alerts: Mezmo Telemetry Pipeline will analyze data and alert on any metric derived from unstructured logs or rollup of a metric based on user-defined thresholds. For example, Mezmo will alert when data volume reaches a specific threshold or when an application has exceeded a predefined number of errors.

- Change Alerts: Mezmo Telemetry Pipeline will compare the absolute or relative percentage change in value between the current and prior intervals for a metric and alert when a metric change is above or below the user-defined threshold. This will help customers detect sudden surges in data volume and enable them to throttle the data from certain sources to automatically prevent overages.

- Absence Alerts: Mezmo Telemetry Pipeline can also be configured to alert when something expected doesn’t happen, for instance, when an expected report is not created.

As part of the recent update, Mezmo now ingests data from more sources, making the platform a more comprehensive solution for telemetry data management. Newly added sources include HTTP endpoints, syslog endpoints, and full support of OpenTelemetry Protocol.

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Mezmo Adds Stateful Processing in Telemetry Pipelines

Mezmo announced new capabilities that help companies understand, optimize, and respond more quickly to their telemetry data.

Mezmo’s Telemetry Pipeline can now trigger stateful alerts in stream. It detects data variations and compares data in motion to metrics thresholds to send alerts based on predefined parameters so users can take swift action to remediate issues and prevent costly overages.

Now you can process terabytes — even petabytes — of data originating from multiple sources and address unexpected events or issues such as misconfigurations that can cause data spikes and excessive overages. Automated in-stream alerts (stateful) allow the data to be actionable and minimize the cost of indexing in expensive observability tools. This workflow provides cost-effective control of telemetry data while offering new and immediate business insights by moving data logic into the pipeline. With Mezmo Telemetry Pipeline, teams can now access various insights and alerts without completely depending on metrics inside observability platforms and act on data aberrations quickly.

“Mezmo delivers advanced capabilities that help SRE, ITOps, and security teams more effectively manage their data and more quickly discover when there is a problem so they can remediate it fast, without wasting time or money,” said Tucker Callaway, CEO, Mezmo. “While other telemetry pipelines focus on data movement and control, Mezmo takes a data engineering approach to make telemetry pipelines more intelligent. New alerting capabilities are another innovative step in shifting logic into the pipeline and making data more actionable.”

Here are some examples of in-stream alerts:

- Threshold Alerts: Mezmo Telemetry Pipeline will analyze data and alert on any metric derived from unstructured logs or rollup of a metric based on user-defined thresholds. For example, Mezmo will alert when data volume reaches a specific threshold or when an application has exceeded a predefined number of errors.

- Change Alerts: Mezmo Telemetry Pipeline will compare the absolute or relative percentage change in value between the current and prior intervals for a metric and alert when a metric change is above or below the user-defined threshold. This will help customers detect sudden surges in data volume and enable them to throttle the data from certain sources to automatically prevent overages.

- Absence Alerts: Mezmo Telemetry Pipeline can also be configured to alert when something expected doesn’t happen, for instance, when an expected report is not created.

As part of the recent update, Mezmo now ingests data from more sources, making the platform a more comprehensive solution for telemetry data management. Newly added sources include HTTP endpoints, syslog endpoints, and full support of OpenTelemetry Protocol.

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Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...

Seamless shopping is a basic demand of today's boundaryless consumer — one with little patience for friction, limited tolerance for disconnected experiences and minimal hesitation in switching brands. Customers expect intuitive, highly personalized experiences and the ability to move effortlessly across physical and digital channels within the same journey. Failure to deliver can cost dearly ...

If your best engineers spend their days sorting tickets and resetting access, you are wasting talent. New global data shows that employees in the IT sector rank among the least motivated across industries. They're under a lot of pressure from many angles. Pressure to upskill and uncertainty around what agentic AI means for job security is creating anxiety. Meanwhile, these roles often function like an on-call job and require many repetitive tasks ...