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Elastic Announces General Availability of Elastic Distributions of OpenTelemetry

SREs and developers now have access to a production-ready OTel ecosystem

Elastic announced the general availability of Elastic Distributions of OpenTelemetry (EDOT), a fully open distribution of the OpenTelemetry (OTel) collector and software development kits (SDKs) for code instrumentation. 

EDOT provides site reliability engineers (SREs) and developers with a stable, production-tested OTel ecosystem backed by enterprise-grade support to provide faster, more reliable infrastructure and application monitoring.

According to EMA Research, over 73% of IT decision-makers and practitioners are currently using OpenTelemetry or plan to implement OpenTelemetry in their environment, but cite a lack of vendor or community support as a top barrier to OpenTelemetry adoption. To address this, EDOT users receive production-ready OTel with expert-backed support. They also benefit by avoiding vendor lock-in and proprietary add-ons, all without schema conversion.

“Enterprises adopting OpenTelemetry often struggle with unreliable support, leading to operational risks and downtime and increased troubleshooting efforts,” said Santosh Krishnan, general manager of Observability and Security at Elastic. “EDOT delivers enterprise-grade support backed by OpenTelemetry experts, helping organizations confidently adopt and scale OpenTelemetry without operational disruptions or added maintenance burden.”

EDOT is available to all Elastic customers. Some available components include EDOT Java and EDOT Python. Read the Elastic blog for a full list of EDOT components that are now generally available.

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Elastic Announces General Availability of Elastic Distributions of OpenTelemetry

SREs and developers now have access to a production-ready OTel ecosystem

Elastic announced the general availability of Elastic Distributions of OpenTelemetry (EDOT), a fully open distribution of the OpenTelemetry (OTel) collector and software development kits (SDKs) for code instrumentation. 

EDOT provides site reliability engineers (SREs) and developers with a stable, production-tested OTel ecosystem backed by enterprise-grade support to provide faster, more reliable infrastructure and application monitoring.

According to EMA Research, over 73% of IT decision-makers and practitioners are currently using OpenTelemetry or plan to implement OpenTelemetry in their environment, but cite a lack of vendor or community support as a top barrier to OpenTelemetry adoption. To address this, EDOT users receive production-ready OTel with expert-backed support. They also benefit by avoiding vendor lock-in and proprietary add-ons, all without schema conversion.

“Enterprises adopting OpenTelemetry often struggle with unreliable support, leading to operational risks and downtime and increased troubleshooting efforts,” said Santosh Krishnan, general manager of Observability and Security at Elastic. “EDOT delivers enterprise-grade support backed by OpenTelemetry experts, helping organizations confidently adopt and scale OpenTelemetry without operational disruptions or added maintenance burden.”

EDOT is available to all Elastic customers. Some available components include EDOT Java and EDOT Python. Read the Elastic blog for a full list of EDOT components that are now generally available.

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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 ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...

Many organizations assumed their infrastructure strategy was settled. It had been implemented, optimized and built into long-term plans. Recent changes in technology and vendor consolidation are forcing a second look. Cloud outages and licensing changes have exposed how much dependency exists on a small number of platforms. As a result, organizations are reevaluating whether those decisions still hold up under current conditions ...

Edge AI is strategically embedded in core IT and infrastructure spending across industries, according to the 2026 Edge AI Survey from ZEDEDA. The research shows that 83% of C-suite and IT executive respondents say edge AI is important to their core business strategy ...

As AI adoption accelerates, operational complexity — not model intelligence — is becoming the primary barrier to reliable AI at scale, according to the State of AI Engineering 2026 from Datadog ... The report highlights a compounding complexity challenge as AI systems scale ... Around 5% of AI model requests fail in production, with nearly 60% of those failures caused by capacity limits ...

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

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