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Sumo Logic Consolidates Collection Agents with OpenTelemetry

Sumo Logic has taken steps to remove complexity from data collection, improved normalization of data, and consolidated collection agents with OpenTelemetry.

Sumo Logic was purpose-built to manage and analyze data from any source. Today, Sumo Logic extends that legacy by adopting OpenTelemetry as its de facto collection strategy to remove complexity in the collection and normalization of data. With Sumo Logic Distro for OT, a native OTel solution, customers no longer face vendor lock-in and can apply Sumo Logic flexibility and analytics to their vendor of choice.

"Sumo Logic has made a commitment to its customers and the community to develop and deliver on OTel-native collection so that customers can realize value, quickly,” said Erez Barak, VP of Product Development for Observability, Sumo Logic. “The enhancements announced today will make it possible for Sumo Logic to deliver choice and flexibility while continuing to provide comprehensive infrastructure and application monitoring. The best OTel-native experiences run on Sumo Logic."

With nearly 30 apps related to database, server, or infrastructure monitoring powered by OTel, Sumo Logic Distro for OT provides a single collector for telemetry. Now, with support for Windows, customers using Sumo Logic Distro for OT can gather logs, metrics, and traces from Windows, Linux and MacOS operating systems, which can be configured utilizing the new onboarding workflows.

Sumo Logic’s unified agent makes it easier to consolidate into one platform for observability use cases instead of disparate monitoring tools for logs or APM. Through a single app installation workflow for logs, metrics and traces, Sumo Logic makes it easier for developers to harness data and takes the complexity out of deploying OpenTelemetry as a collection strategy.

Sumo Logic also reduces the number of manual steps in the data onboarding process. Each step - Collector Setup, Source Configuration, Dashboard Setup - is now folded into a single workflow allowing users to onboard data in under 5 minutes. By standardizing on OTel-native collection, developers get a simplified installation to onboard data and set up data collection on Sumo Logic.

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Sumo Logic Consolidates Collection Agents with OpenTelemetry

Sumo Logic has taken steps to remove complexity from data collection, improved normalization of data, and consolidated collection agents with OpenTelemetry.

Sumo Logic was purpose-built to manage and analyze data from any source. Today, Sumo Logic extends that legacy by adopting OpenTelemetry as its de facto collection strategy to remove complexity in the collection and normalization of data. With Sumo Logic Distro for OT, a native OTel solution, customers no longer face vendor lock-in and can apply Sumo Logic flexibility and analytics to their vendor of choice.

"Sumo Logic has made a commitment to its customers and the community to develop and deliver on OTel-native collection so that customers can realize value, quickly,” said Erez Barak, VP of Product Development for Observability, Sumo Logic. “The enhancements announced today will make it possible for Sumo Logic to deliver choice and flexibility while continuing to provide comprehensive infrastructure and application monitoring. The best OTel-native experiences run on Sumo Logic."

With nearly 30 apps related to database, server, or infrastructure monitoring powered by OTel, Sumo Logic Distro for OT provides a single collector for telemetry. Now, with support for Windows, customers using Sumo Logic Distro for OT can gather logs, metrics, and traces from Windows, Linux and MacOS operating systems, which can be configured utilizing the new onboarding workflows.

Sumo Logic’s unified agent makes it easier to consolidate into one platform for observability use cases instead of disparate monitoring tools for logs or APM. Through a single app installation workflow for logs, metrics and traces, Sumo Logic makes it easier for developers to harness data and takes the complexity out of deploying OpenTelemetry as a collection strategy.

Sumo Logic also reduces the number of manual steps in the data onboarding process. Each step - Collector Setup, Source Configuration, Dashboard Setup - is now folded into a single workflow allowing users to onboard data in under 5 minutes. By standardizing on OTel-native collection, developers get a simplified installation to onboard data and set up data collection on Sumo Logic.

The Latest

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...