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Logentries Delivers Real-Time Log Management and Analytics Integration for Google Cloud Platform

Logentries announced a real-time integration with Google Cloud Platform.

The Logentries log management and analytics service integrates with Google Cloud Logging to offer Google Cloud Platform customers’ an easily configurable choice for log management and advanced analytics including anomaly detection.

The new integration leverages the Google Cloud Publisher-Subscriber (Pub-Sub) API, which provides reliable, many-to-many, asynchronous messaging between Google Cloud Platform and Logentries, for easy communication between services.

“We understand that Log Management and Analytics is a critical customer need and are excited to offer Google customers a choice to easily send logs to a key provider like Logentries,” said Deepak Tiwari, Product Manager, Google Cloud. “Many of Google Compute Engine customers already use Logentries for advanced log analysis. This integration enables customers to use Logentries for Google App Engine and services like Cloud Dataflow as well and makes it even easier to get started. At Google, we are committed to creating an open ecosystem with easy path of integration for partners, and Logentries provides a great example of a leading partner.”

Today’s distributed, cloud-based environments produce billions of machine-generated data, making separate tools for monitoring, alerting, troubleshooting and analyzing data across systems, applications and end users completely unmanageable. Organizations need a single tool to monitor, alert and analyze multiple data sources using one shared data format.

The Logentries and Google Cloud Platform integration provides a meaningful choice for real-time event monitoring, alerting, advanced analytics, and data visualizations to Google customers for a better understanding of their system and application activity and performance. With this visibility, users can monitor and alert on critical activity and exceptions across their apps, including anomaly detection, inactivity alerting, and end user experience metrics.

In addition to data from applications and VMs, logs collected from Google Cloud Platform also contain metadata with every log entry, giving users valuable information, including the exact time any log entry was created, the origins (resource or instance) of each entry along with its security level. With the integration between Logentries and Google Cloud Platform, users can easily:

- Build data visualizations with streaming log data from apps hosted on Google Cloud Platform and VMs hosted on Google Compute Engine.

- Receive real-time alerts on events, inactivity and anomaly detection from Google App Engine and Google Compute Engine.

- Correlate events from Google App Engine with Google Compute Engine to help identify the root cause of issues.

“The Google Cloud Pub/Sub API is a powerful service for routing messages from multiple cloud and third party resources at scale,” explained Trevor Parsons, Co-founder and Chief Scientist of Logentries. “With the new Logentries integration Google customers are now able to generate powerful correlations, visualizations and alerts from disparate sources of application and system-level data – all in real time.”

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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 ...

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Logentries Delivers Real-Time Log Management and Analytics Integration for Google Cloud Platform

Logentries announced a real-time integration with Google Cloud Platform.

The Logentries log management and analytics service integrates with Google Cloud Logging to offer Google Cloud Platform customers’ an easily configurable choice for log management and advanced analytics including anomaly detection.

The new integration leverages the Google Cloud Publisher-Subscriber (Pub-Sub) API, which provides reliable, many-to-many, asynchronous messaging between Google Cloud Platform and Logentries, for easy communication between services.

“We understand that Log Management and Analytics is a critical customer need and are excited to offer Google customers a choice to easily send logs to a key provider like Logentries,” said Deepak Tiwari, Product Manager, Google Cloud. “Many of Google Compute Engine customers already use Logentries for advanced log analysis. This integration enables customers to use Logentries for Google App Engine and services like Cloud Dataflow as well and makes it even easier to get started. At Google, we are committed to creating an open ecosystem with easy path of integration for partners, and Logentries provides a great example of a leading partner.”

Today’s distributed, cloud-based environments produce billions of machine-generated data, making separate tools for monitoring, alerting, troubleshooting and analyzing data across systems, applications and end users completely unmanageable. Organizations need a single tool to monitor, alert and analyze multiple data sources using one shared data format.

The Logentries and Google Cloud Platform integration provides a meaningful choice for real-time event monitoring, alerting, advanced analytics, and data visualizations to Google customers for a better understanding of their system and application activity and performance. With this visibility, users can monitor and alert on critical activity and exceptions across their apps, including anomaly detection, inactivity alerting, and end user experience metrics.

In addition to data from applications and VMs, logs collected from Google Cloud Platform also contain metadata with every log entry, giving users valuable information, including the exact time any log entry was created, the origins (resource or instance) of each entry along with its security level. With the integration between Logentries and Google Cloud Platform, users can easily:

- Build data visualizations with streaming log data from apps hosted on Google Cloud Platform and VMs hosted on Google Compute Engine.

- Receive real-time alerts on events, inactivity and anomaly detection from Google App Engine and Google Compute Engine.

- Correlate events from Google App Engine with Google Compute Engine to help identify the root cause of issues.

“The Google Cloud Pub/Sub API is a powerful service for routing messages from multiple cloud and third party resources at scale,” explained Trevor Parsons, Co-founder and Chief Scientist of Logentries. “With the new Logentries integration Google customers are now able to generate powerful correlations, visualizations and alerts from disparate sources of application and system-level data – all in real time.”

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.