Sumo Logic announced several new and enhanced solutions:
- Updated Application Observability solution - Sumo Logic’s Application Observability solutions enables customers to rapidly monitor, diagnose and troubleshoot applications and infrastructure across any architecture, technology or environments. The solution integrates to over 200 applications and infrastructure out of the box. With the additional support for open source Prometheus and Telegraf technologies, it extends support to hundreds of new sources and environments. In addition, support for Open Telemetry enables the collection and correlation of traces with relevant logs and metrics. Lastly, new dashboards along with topology and entity models provide intuitive workflows and allow for cross-linking to automate troubleshooting playbooks.
- New General Availability of Kubernetes Observability solution - Sumo Logic’s Kubernetes Observability solutions provides rich monitoring, diagnosing and troubleshooting capabilities for Kubernetes based microservices applications, by giving enterprises a unified platform for all application and infrastructure telemetry. This solution automatically instruments and discovers Kubernetes topology and entities, automatically collects logs, metrics, traces and metadata to automatically create preconfigured dashboards and alerts.
- New General Availability of AWS Observability solution - The Sumo Logic AWS Observability solution for AWS takes a cross-cutting approach to managing reliability of AWS based applications and underlying AWS services by easily and automatically ingesting, collecting, unifying and analyzing telemetry data from popular AWS services like Application Load Balancer, Amazon Elastic Compute Cloud (EC2), Amazon Relational Database (RDS), AWS Lambda, Amazon DynamoDB and Amazon API Gateway in order to quickly detect anomalous events, determine timeline and scale of anomalies, and enable rapid root cause analysis through machine learning aided technology.
- Multi-cloud Observability solution - The Sumo Logic Multi-cloud Observability solution provides monitoring and troubleshooting capabilities to manage the reliability of applications across AWS, Microsoft Azure, Google Cloud Platform (GCP) and hybrid cloud environments. The solutions provide out-of-the-box integrations and content to a variety of AWS, Azure and GCP and traditional on-premise infrastructures.
- Web and Edge Observability solution - As modern applications continue to rely on multi-edge networks and services like content delivery networks (CDNs), load-balancers and more, to deliver exceptional customer experience, managing the availability and performance of these infrastructures is critical. The Sumo Logic Web and Edge Observability solution provides monitoring, diagnosis and troubleshooting capabilities for these critical edge-networks such as Akamai, CloudFlare and Fastly as well as similar services provided by hyperscale cloud providers such as AWS, Azure and GCP.
- General Availability of SDO - Sumo Logic today announced the general availability of its Software Development Optimization (SDO) solution, a new business intelligence offering that integrates and analyzes data from multiple DevOps tools to give developers real-time insights into software development pipelines. The solution was developed in partnership with various key ecosystem partners and provides engineering organizations of all sizes and maturity, the ability to benchmark and optimize their software development and delivery performance against industry standard DORA metrics to better understand the health of their innovation cycles. With SDO, data across disparate DevOps tools is captured in real-time and automatically enriched, normalized and correlated across the entire DevOps lifecycle. By unifying fragmented data sets generated by software development and delivery tools, DevOps, engineering and business leaders gain the continuous intelligence needed for data-driven decisions to drive faster innovation cycles and better team collaboration that lead to reliable, performant and secure customer experiences.
The Sumo Logic SDO solution is free to existing customers and has already been adopted by a number of customers and also comes with out of the box integrations to Jira, GitHub, Jenkins, Bitbucket, PagerDuty and OpsGenie and can also be easily extended to other popular tools like Azure DevOps, GitLab, CircleCI and more.
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.