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Sumo Logic Releases 11 New Google Cloud Platform Applications

Sumo Logic announced the release of 11 new Google Cloud Platform (GCP) applications as well as an integration with Google Cloud’s open source machine learning library, TensorFlow, to provide customers with flexible and scalable enterprise-grade cloud choices that deliver real-time business, operational and security insights into modern applications and infrastructure.

Sumo Logic is one of the first in the industry to release a comprehensive set of applications for GCP that enable real-time collection and analytics of machine data emitted by all major GCP services. Sumo Logic will also leverage TensorFlow machine learning libraries to augment existing machine learning analytics to enable customers to perform powerful analytics and apply advanced machine learning to data generated by their modern applications to improve operational, security and business outcomes.

“As today’s modern businesses continue to look for ways to differentiate themselves and deliver a seamless experience to their customers, the demand for secure, customizable solutions that support multiple cloud platforms is growing,” said Bruno Kurtic, founding VP of Product and Strategy, Sumo Logic. “The Sumo Logic platform is purpose-built to provide flexible and scalable enterprise-class support for all major cloud platforms — including AWS, Azure and GCP — to detect, troubleshoot and help rapidly investigate operational and security incidents to give users real-time actionable intelligence. This latest release further reinforces our longstanding commitment to deliver continuous intelligence for our customers’ businesses, regardless of where their modern applications and infrastructure data reside.”

The new GCP apps are now available via the Sumo Logic App Catalog, and include support for:

- Google App Engine Understand platform activity, incoming requests, applications, HTTP status codes, and latency and response times in your App Engine to get ahead of serious issues before they affect users.

- Google BigQuery: Proactively manage and troubleshoot your Google BigQuery data warehouse for deep operation insights, query optimization and enhanced user activity.

- Google Cloud Audit: Empower your audit and compliance needs by monitoring and tracking user, administrative and authentication activity for a real-time analysis of all audit streams across GCP.

- Google Cloud Functions: Leverage pre-configured dashboards and searches for deeper visibility into the overall usage, executions, operations, latency, errors, outliers and failures of your Google Cloud Functions environment.

- Google Cloud Identity & Access Management (IAM): Monitor Google Cloud IAM project activities, operations, role activities, role and policy changes, and IAM messages to analyze changes, share critical data and secure your environment.

- Google Cloud Load Balancing: Use pre-configured dashboards to monitor load balancing activity and get full insight into request locations and volume, response codes, and request and response data by load balancer.

- Google Cloud SQL: Easy-to-deploy pre-configured Sumo Logic dashboards provide insight into created and deleted resources, messages, authorization failures, user activities and error logs for all Google Cloud SQL activity.

- Google Cloud Storage: Continuously monitor and troubleshoot activity in Google Cloud Storage for insights into request locations, bucket and object operations, user activities, errors, and bucket statistics.

- Google Compute Engine: Monitor your infrastructure to visualize the activities, users, and message severity of your Google Compute Engine, the Infrastructure as a Service (IaaS) component of Google Cloud Platform.

- Google Kubernetes Engine: Gain node-level and pod-level monitoring information for deeper operational insights, container optimization, and security and compliance of your Kubernetes environment to better manage potential risks and threats.

- Google Virtual Private Cloud (VPC): Leverage interactive, customizable dashboards with outlier detection to trace unusual traffic patterns and suspicious activity for VPC flows and gain real-time insights and analytics into network activity for GCP-generated log data.

“The Sumo Logic platform integrates directly with GCP services to collect audit and operational data in real-time and provides operational and security monitoring tools used by a variety of enterprise customers,” said Vineet Bhan, Head of Security Partnerships, Google Cloud. “We look forward to continued collaboration with Sumo Logic.”

With expanded GCP support, Sumo Logic enables GCP customers to improve monitoring, detection and alerting on operational issues, accelerate troubleshooting and root cause analysis, help with compliance regulations such as PCI, HIPAA, SOX, GDPR, and deliver real-time, threat-aware security analytics that facilitate powerful security incident investigations for their applications and GCP infrastructure — all with the goal of improving operational and security visibility to deliver the ultimate customer experience.

The addition of Google Cloud’s open source TensorFlow libraries to Sumo Logic’s powerful machine learning engine enables customers to deploy more custom machine learning algorithms directly to their data. This allows customers to gain deeper insights from their machine data, a critical data set for companies focused on improving how they serve their customers, understanding user behavior and leveraging all data sets to differentiate from competition.

The GCP apps and TensorFlow integration are available now to Sumo Logic customers.

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Sumo Logic Releases 11 New Google Cloud Platform Applications

Sumo Logic announced the release of 11 new Google Cloud Platform (GCP) applications as well as an integration with Google Cloud’s open source machine learning library, TensorFlow, to provide customers with flexible and scalable enterprise-grade cloud choices that deliver real-time business, operational and security insights into modern applications and infrastructure.

Sumo Logic is one of the first in the industry to release a comprehensive set of applications for GCP that enable real-time collection and analytics of machine data emitted by all major GCP services. Sumo Logic will also leverage TensorFlow machine learning libraries to augment existing machine learning analytics to enable customers to perform powerful analytics and apply advanced machine learning to data generated by their modern applications to improve operational, security and business outcomes.

“As today’s modern businesses continue to look for ways to differentiate themselves and deliver a seamless experience to their customers, the demand for secure, customizable solutions that support multiple cloud platforms is growing,” said Bruno Kurtic, founding VP of Product and Strategy, Sumo Logic. “The Sumo Logic platform is purpose-built to provide flexible and scalable enterprise-class support for all major cloud platforms — including AWS, Azure and GCP — to detect, troubleshoot and help rapidly investigate operational and security incidents to give users real-time actionable intelligence. This latest release further reinforces our longstanding commitment to deliver continuous intelligence for our customers’ businesses, regardless of where their modern applications and infrastructure data reside.”

The new GCP apps are now available via the Sumo Logic App Catalog, and include support for:

- Google App Engine Understand platform activity, incoming requests, applications, HTTP status codes, and latency and response times in your App Engine to get ahead of serious issues before they affect users.

- Google BigQuery: Proactively manage and troubleshoot your Google BigQuery data warehouse for deep operation insights, query optimization and enhanced user activity.

- Google Cloud Audit: Empower your audit and compliance needs by monitoring and tracking user, administrative and authentication activity for a real-time analysis of all audit streams across GCP.

- Google Cloud Functions: Leverage pre-configured dashboards and searches for deeper visibility into the overall usage, executions, operations, latency, errors, outliers and failures of your Google Cloud Functions environment.

- Google Cloud Identity & Access Management (IAM): Monitor Google Cloud IAM project activities, operations, role activities, role and policy changes, and IAM messages to analyze changes, share critical data and secure your environment.

- Google Cloud Load Balancing: Use pre-configured dashboards to monitor load balancing activity and get full insight into request locations and volume, response codes, and request and response data by load balancer.

- Google Cloud SQL: Easy-to-deploy pre-configured Sumo Logic dashboards provide insight into created and deleted resources, messages, authorization failures, user activities and error logs for all Google Cloud SQL activity.

- Google Cloud Storage: Continuously monitor and troubleshoot activity in Google Cloud Storage for insights into request locations, bucket and object operations, user activities, errors, and bucket statistics.

- Google Compute Engine: Monitor your infrastructure to visualize the activities, users, and message severity of your Google Compute Engine, the Infrastructure as a Service (IaaS) component of Google Cloud Platform.

- Google Kubernetes Engine: Gain node-level and pod-level monitoring information for deeper operational insights, container optimization, and security and compliance of your Kubernetes environment to better manage potential risks and threats.

- Google Virtual Private Cloud (VPC): Leverage interactive, customizable dashboards with outlier detection to trace unusual traffic patterns and suspicious activity for VPC flows and gain real-time insights and analytics into network activity for GCP-generated log data.

“The Sumo Logic platform integrates directly with GCP services to collect audit and operational data in real-time and provides operational and security monitoring tools used by a variety of enterprise customers,” said Vineet Bhan, Head of Security Partnerships, Google Cloud. “We look forward to continued collaboration with Sumo Logic.”

With expanded GCP support, Sumo Logic enables GCP customers to improve monitoring, detection and alerting on operational issues, accelerate troubleshooting and root cause analysis, help with compliance regulations such as PCI, HIPAA, SOX, GDPR, and deliver real-time, threat-aware security analytics that facilitate powerful security incident investigations for their applications and GCP infrastructure — all with the goal of improving operational and security visibility to deliver the ultimate customer experience.

The addition of Google Cloud’s open source TensorFlow libraries to Sumo Logic’s powerful machine learning engine enables customers to deploy more custom machine learning algorithms directly to their data. This allows customers to gain deeper insights from their machine data, a critical data set for companies focused on improving how they serve their customers, understanding user behavior and leveraging all data sets to differentiate from competition.

The GCP apps and TensorFlow integration are available now to Sumo Logic customers.

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.