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Sumo Logic Introduces OpenTelemetry Distro Collector

Sumo Logic marks a new milestone in innovation for Sumo Logic Observability with Sumo Logic OpenTelemetry Distro Collector (OT Distro).

The OT Distro Collector is designed to simplify and democratize the collection of logs, metrics, traces, and metadata from modern cloud applications. With this announcement, Sumo Logic further embraces open source and establishes OpenTelemetry as its future standard to collect all machine data, breaking from the legacy model of using proprietary agents to gather critical application and infrastructure telemetry.

Most organizations have multiple tools for data collection and no single framework or standard way of capturing critical signals for observability, leading to increased costs and overhead. By adopting OpenTelemetry, site reliability engineering (SRE) teams can define and own their global collection strategy, without fear of vendor lock-in. The unified collection of logs, metrics and traces available in the OT Distro Collector eliminates the need to manage multiple agents, further removing complexity from data collection.

“Full-stack observability is absolutely necessary to manage modern applications. At its core, observability is a data analytics problem. As the industry standardizes on OpenTelemetry for data collection, it will put the focus back where it should be - on a great SRE experience with great data analytics,” said Erez Barak, VP of Product Development for Observability, Sumo Logic. “This release of Sumo Logic OT Distro Collector is the first step towards what will ultimately become the sole collector on our unified continuous intelligence platform. With it, our customers can ingest telemetry from all domains - logs, metrics, traces, and metadata - and deliver reliable and secure digital experiences at scale.”

The initial release of Sumo Logic OT Distro Collector is available today and supports:

- Architectures, including x86/x64 and ARM

- Operating systems, including Mac OS, Linux

- Orchestration platforms, including Kubernetes

In addition to the standard OpenTelemetry capabilities listed, the OT Distro Collector also includes support for automatic collector registration, heartbeat reporting (in advance of full OpAmp support), as well as a built-in Telegraf support, allowing customers to leverage the Telegraf catalog of input plugins. These unique additions simplify the migration to an OpenTelemetry based approach while using a vendor-supported agent.

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Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

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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.

Sumo Logic Introduces OpenTelemetry Distro Collector

Sumo Logic marks a new milestone in innovation for Sumo Logic Observability with Sumo Logic OpenTelemetry Distro Collector (OT Distro).

The OT Distro Collector is designed to simplify and democratize the collection of logs, metrics, traces, and metadata from modern cloud applications. With this announcement, Sumo Logic further embraces open source and establishes OpenTelemetry as its future standard to collect all machine data, breaking from the legacy model of using proprietary agents to gather critical application and infrastructure telemetry.

Most organizations have multiple tools for data collection and no single framework or standard way of capturing critical signals for observability, leading to increased costs and overhead. By adopting OpenTelemetry, site reliability engineering (SRE) teams can define and own their global collection strategy, without fear of vendor lock-in. The unified collection of logs, metrics and traces available in the OT Distro Collector eliminates the need to manage multiple agents, further removing complexity from data collection.

“Full-stack observability is absolutely necessary to manage modern applications. At its core, observability is a data analytics problem. As the industry standardizes on OpenTelemetry for data collection, it will put the focus back where it should be - on a great SRE experience with great data analytics,” said Erez Barak, VP of Product Development for Observability, Sumo Logic. “This release of Sumo Logic OT Distro Collector is the first step towards what will ultimately become the sole collector on our unified continuous intelligence platform. With it, our customers can ingest telemetry from all domains - logs, metrics, traces, and metadata - and deliver reliable and secure digital experiences at scale.”

The initial release of Sumo Logic OT Distro Collector is available today and supports:

- Architectures, including x86/x64 and ARM

- Operating systems, including Mac OS, Linux

- Orchestration platforms, including Kubernetes

In addition to the standard OpenTelemetry capabilities listed, the OT Distro Collector also includes support for automatic collector registration, heartbeat reporting (in advance of full OpAmp support), as well as a built-in Telegraf support, allowing customers to leverage the Telegraf catalog of input plugins. These unique additions simplify the migration to an OpenTelemetry based approach while using a vendor-supported agent.

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

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.