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Sumo Logic Announces New Observability Capabilities

Sumo Logic has expanded the breadth and depth of its observability solution with new real-time data sources and integrations to provide deeper insights and value including:

Advanced Analytics for Comprehensive Alert Response - new Alert Response feature enables users to move beyond manual issue diagnostics and troubleshooting to analytics-guided issue resolution. Using domain agnostic analytics and machine learning, Alert Response understands the context of all of the inbound data points, making the troubleshooting process easier for observers.

Sensu Go - as part of its recent acquisition of Sensu, Sensu Go is now part of the Sumo Logic Continuous Intelligence Platform to empower enterprises and developers to quickly get real-time insights from unstructured data for troubleshooting, performance improvement and security across their dynamic infrastructure. With the addition of Sensu Go, enterprises now have access to native Monitoring-as-Code capabilities to help fill gaps in their observability pipeline and accelerate troubleshooting, diagnosis and self-healing from bare-metal to Kubernetes.

Sensu Plus - For Sensu customers who want an integrated analytics engine to produce insights from their observability pipeline data, Sumo Logic is launching Sensu Plus. With simple node based pricing customers now have access to a single integrated solution for checks based monitoring as code.

Coverage across the entire application stack is critical to managing the application, and out-of-the box integrations are key to achieve this and include:

- Cloud Services - Azure Event Hub Collection, Azure Append Blob Collection, AWS Lambda Extensions, AWS Lambda Logs APIs, Azure WebApp, Windows JSON, MS SQL Server

- App Infrastructure - Memcached, Elasticsearch, ActiveMQ, RabbitMQ, Nginx and Nginx Plus, Cassandra, HAProxy, Catchpoint, Kafka, MySQL, F5, Varnish, Tomcat, MongoDB, Apache, Redis, PostgreSQL, ServiceNow ServiceGraph Connector

- Sumo Logic Solutions - Software Development Optimization for Jira Cloud, Kubernetes, Tracing, Real User Monitoring (RUM), GlobaI Intelligence services for NGINX, AWS CloudTrail, Apache and Tomcat

In addition, Sumo Logic delivers an open, flexible, community-driven approach to collecting data through new innovations for OpenTelemetry projects including:

Sumo Logic OpenTelemetry Distro and Ecosystem Support - now in beta, Sumo Logic’s Open Telemetry Distro is a next-generation agent based collector that provides customers with a single agent to collect all of their critical telemetry data including logs, metrics and traces based on a widely supported open source standard. In addition, Sumo Logic now supports AWS OpenTelemetry Distro to help with the collection of observability signals, making it even easier for the customers to run their workloads on AWS, as well as Red Hat OpenShift Operator through the Red Hat Marketplace. In support of developers Sumo Logic has also increased the capabilities of Sumo Logic Free to include Sensu’s checks based monitoring as code and OpenTelemetry Distro alongside existing analytics capabilities.

Orchestration powered by Open Integration Framework - Integrates with the Sumo Logic Continuous Intelligence Platform, as well as hundreds of security and IT tools and technologies and orchestrate using Sumo Logic’s Open Integration Framework, providing security and IT teams with varying levels to create custom integrations with low-code.

Sumo Logic Open Source Programs Office - As a consumer of open source, Sumo Logic understands the responsibility to contribute back to the community and the projects that matter to developers. In support of this, the company intends to standardize how it contributes to, supports, and sponsors open source with the launch of an Open Source Programs Office. Through this initiative, Sumo Logic will work to increase its engagement with the open source community and to provide transparency into the company’s work and priorities.

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.

Sumo Logic Announces New Observability Capabilities

Sumo Logic has expanded the breadth and depth of its observability solution with new real-time data sources and integrations to provide deeper insights and value including:

Advanced Analytics for Comprehensive Alert Response - new Alert Response feature enables users to move beyond manual issue diagnostics and troubleshooting to analytics-guided issue resolution. Using domain agnostic analytics and machine learning, Alert Response understands the context of all of the inbound data points, making the troubleshooting process easier for observers.

Sensu Go - as part of its recent acquisition of Sensu, Sensu Go is now part of the Sumo Logic Continuous Intelligence Platform to empower enterprises and developers to quickly get real-time insights from unstructured data for troubleshooting, performance improvement and security across their dynamic infrastructure. With the addition of Sensu Go, enterprises now have access to native Monitoring-as-Code capabilities to help fill gaps in their observability pipeline and accelerate troubleshooting, diagnosis and self-healing from bare-metal to Kubernetes.

Sensu Plus - For Sensu customers who want an integrated analytics engine to produce insights from their observability pipeline data, Sumo Logic is launching Sensu Plus. With simple node based pricing customers now have access to a single integrated solution for checks based monitoring as code.

Coverage across the entire application stack is critical to managing the application, and out-of-the box integrations are key to achieve this and include:

- Cloud Services - Azure Event Hub Collection, Azure Append Blob Collection, AWS Lambda Extensions, AWS Lambda Logs APIs, Azure WebApp, Windows JSON, MS SQL Server

- App Infrastructure - Memcached, Elasticsearch, ActiveMQ, RabbitMQ, Nginx and Nginx Plus, Cassandra, HAProxy, Catchpoint, Kafka, MySQL, F5, Varnish, Tomcat, MongoDB, Apache, Redis, PostgreSQL, ServiceNow ServiceGraph Connector

- Sumo Logic Solutions - Software Development Optimization for Jira Cloud, Kubernetes, Tracing, Real User Monitoring (RUM), GlobaI Intelligence services for NGINX, AWS CloudTrail, Apache and Tomcat

In addition, Sumo Logic delivers an open, flexible, community-driven approach to collecting data through new innovations for OpenTelemetry projects including:

Sumo Logic OpenTelemetry Distro and Ecosystem Support - now in beta, Sumo Logic’s Open Telemetry Distro is a next-generation agent based collector that provides customers with a single agent to collect all of their critical telemetry data including logs, metrics and traces based on a widely supported open source standard. In addition, Sumo Logic now supports AWS OpenTelemetry Distro to help with the collection of observability signals, making it even easier for the customers to run their workloads on AWS, as well as Red Hat OpenShift Operator through the Red Hat Marketplace. In support of developers Sumo Logic has also increased the capabilities of Sumo Logic Free to include Sensu’s checks based monitoring as code and OpenTelemetry Distro alongside existing analytics capabilities.

Orchestration powered by Open Integration Framework - Integrates with the Sumo Logic Continuous Intelligence Platform, as well as hundreds of security and IT tools and technologies and orchestrate using Sumo Logic’s Open Integration Framework, providing security and IT teams with varying levels to create custom integrations with low-code.

Sumo Logic Open Source Programs Office - As a consumer of open source, Sumo Logic understands the responsibility to contribute back to the community and the projects that matter to developers. In support of this, the company intends to standardize how it contributes to, supports, and sponsors open source with the launch of an Open Source Programs Office. Through this initiative, Sumo Logic will work to increase its engagement with the open source community and to provide transparency into the company’s work and priorities.

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.