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Sumo Logic Releases New Applications and Integrations for Microsoft Azure

Sumo Logic released new Sumo Logic applications for Microsoft Azure services, as well as new native integrations with Azure Monitor and Blob Storage, to provide customers with deep visibility, improved troubleshooting and enhanced security and compliance across their modern applications and cloud infrastructure.

“Speed of innovation and agility are critical for success in today’s digital economy and leading enterprises are aggressively building customer-facing applications in the public cloud,” said Bruno Kurtic, founding VP of Product and Strategy, Sumo Logic. “Our goal is to provide our customers with the most flexible and scalable machine data analytics platform to fit the unique needs of their digital business, enabling them to build, run and secure applications across all major cloud providers. This latest release of native Azure integrations and applications is another step forward in our overall commitment to delivering a comprehensive platform built for modern applications and cloud infrastructures.”

Sumo Logic already provides a cloud-native suite of applications that integrates into Azure environments to simplify the management and monitoring of Azure services, including Azure Audit Log, Azure Network Watcher and Azure Web Apps. By leveraging the Sumo Logic platform, customers are able to migrate to Azure faster and with higher confidence, gain better real-time operational and security visibility into their cloud and hybrid workloads to identify issues and expedite root-cause analysis, and strengthen security and compliance by easily monitoring user access, platform configurations and changes, and generate audit trails to demonstrate compliance for the Payment Card Industry Data Security Standard (PCI DSS), Health Insurance Portability and Accountability Act (HIPAA), the General Data Protection Regulation (GDPR) and more.

With this latest release, Sumo Logic now also supports Azure SQL Database, a managed relational cloud database service, and Azure Active Directory, a cloud-based directory and identity management service that provides directory services, application access management and identity protection, to provide an even deeper layer of operational, security and business insights.

The new Sumo Logic Apps for Azure are now available via the Sumo Logic App Catalog:

- Azure SQL Database: Monitor activity in Azure SQL Database with Sumo Logic and gain insights into resource utilization, blocking queries, database wait events, errors, runtime execution stats and other database analytics through pre-configured dashboards.

- Azure Active Directory: Monitor Azure Active Directory activity and leverage dashboards to provide insight into role, user and group management, successful and failed sign-in events, directory management, and application management data to better understand users’ experiences.

Furthermore, with native integrations for Microsoft Azure Monitor and Blob Storage, Sumo Logic offers out-of-the-box solutions that completely eliminate the dependency on virtual machines (VMs) and require zero maintenance for customers. The Sumo Logic platform uses advanced analytics and machine learning algorithms to read and analyze terabytes of audit log and active directory data, enabling customers to instantly turn their data into real-time operational insights, audit reports and powerful visualization tools.

“As we continue to meet and exceed the needs of our robust community, we’re excited to have Sumo Logic’s machine data analytics platform on Microsoft Azure to help customers secure and manage their applications across cloud environments,” said Sajan Parihar, director, Microsoft Azure Platform at Microsoft Corp. “Sumo Logic shares our same commitment to delivering the most flexible, scalable and secure solutions for new and emerging technologies across the full application stack.”

The Azure apps and integrations are available now to Sumo Logic customers.

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Sumo Logic Releases New Applications and Integrations for Microsoft Azure

Sumo Logic released new Sumo Logic applications for Microsoft Azure services, as well as new native integrations with Azure Monitor and Blob Storage, to provide customers with deep visibility, improved troubleshooting and enhanced security and compliance across their modern applications and cloud infrastructure.

“Speed of innovation and agility are critical for success in today’s digital economy and leading enterprises are aggressively building customer-facing applications in the public cloud,” said Bruno Kurtic, founding VP of Product and Strategy, Sumo Logic. “Our goal is to provide our customers with the most flexible and scalable machine data analytics platform to fit the unique needs of their digital business, enabling them to build, run and secure applications across all major cloud providers. This latest release of native Azure integrations and applications is another step forward in our overall commitment to delivering a comprehensive platform built for modern applications and cloud infrastructures.”

Sumo Logic already provides a cloud-native suite of applications that integrates into Azure environments to simplify the management and monitoring of Azure services, including Azure Audit Log, Azure Network Watcher and Azure Web Apps. By leveraging the Sumo Logic platform, customers are able to migrate to Azure faster and with higher confidence, gain better real-time operational and security visibility into their cloud and hybrid workloads to identify issues and expedite root-cause analysis, and strengthen security and compliance by easily monitoring user access, platform configurations and changes, and generate audit trails to demonstrate compliance for the Payment Card Industry Data Security Standard (PCI DSS), Health Insurance Portability and Accountability Act (HIPAA), the General Data Protection Regulation (GDPR) and more.

With this latest release, Sumo Logic now also supports Azure SQL Database, a managed relational cloud database service, and Azure Active Directory, a cloud-based directory and identity management service that provides directory services, application access management and identity protection, to provide an even deeper layer of operational, security and business insights.

The new Sumo Logic Apps for Azure are now available via the Sumo Logic App Catalog:

- Azure SQL Database: Monitor activity in Azure SQL Database with Sumo Logic and gain insights into resource utilization, blocking queries, database wait events, errors, runtime execution stats and other database analytics through pre-configured dashboards.

- Azure Active Directory: Monitor Azure Active Directory activity and leverage dashboards to provide insight into role, user and group management, successful and failed sign-in events, directory management, and application management data to better understand users’ experiences.

Furthermore, with native integrations for Microsoft Azure Monitor and Blob Storage, Sumo Logic offers out-of-the-box solutions that completely eliminate the dependency on virtual machines (VMs) and require zero maintenance for customers. The Sumo Logic platform uses advanced analytics and machine learning algorithms to read and analyze terabytes of audit log and active directory data, enabling customers to instantly turn their data into real-time operational insights, audit reports and powerful visualization tools.

“As we continue to meet and exceed the needs of our robust community, we’re excited to have Sumo Logic’s machine data analytics platform on Microsoft Azure to help customers secure and manage their applications across cloud environments,” said Sajan Parihar, director, Microsoft Azure Platform at Microsoft Corp. “Sumo Logic shares our same commitment to delivering the most flexible, scalable and secure solutions for new and emerging technologies across the full application stack.”

The Azure apps and integrations are available now to Sumo Logic customers.

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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.