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Epsagon Expands Applied Observability Platform

Epsagon announced Azure Kubernetes Service (AKS) support, as well as a Microsoft Azure Partnership and solution availability in the Azure Marketplace to serve the fast-growing number of enterprises using Azure Cloud and multi-cloud architectures.

In addition, Epsagon is expanding its core platform with enhanced automation and correlation capabilities as well as deep container and Kubernetes monitoring, alerting and troubleshooting for both Azure and AWS public clouds. This update is part of an overall strategy for the company to extend and apply Epsagon’s observability advantages—including automation of manual tasks, rapid and easy troubleshooting and issue resolution, greater developer velocity and faster time to business value—equally across serverless, container and Kubernetes environments and to Azure as well as AWS cloud infrastructures.

Now, Epsagon is extending the same level of seamless, automated observability and rich context that it pioneered for serverless environments to enterprises leveraging Azure as part or all of their cloud infrastructure, and the growing number of companies using container and Kubernetes technologies.

“Businesses are entering a Cloud 2.0 era where hyper-growth in data volume, more widespread adoption of hybrid container and serverless environments, and multi-cloud microservice architectures are driving complexity that makes application management ever more difficult,” said Nitzan Shapira, CEO at Epsagon. “Organizations need to be able to make sense of the terabytes of valuable data collected and understand, immediately, how to use this data to make wise operational and business-level decisions. Epsagon’s advances in observability, monitoring and troubleshooting get to the heart of this challenge.”

In addition to support for AWS Cloud and multiple AWS services, companies leveraging Azure for either part or all of their infrastructure can immediately and fully utilize Epsagon's observability platform for automated monitoring and troubleshooting of Azure Kubernetes Service (AKS) environments. With the new AKS cluster monitoring view, users and teams can understand:

- Cluster-level metrics over time for a specific cluster

- Nodes, pods, containers and deployments associated with the specific cluster

Already an AWS Advanced Technology Partner, Epsagon has made the same improvements as for Azure to its dashboard for AWS ECS, Amazon’s containerized orchestration tool, and for AWS EKS, Amazon Elastic Kubernetes Service.

Epsagon has also added to its platform:

- High-level infrastructure monitoring dashboards with compute service metrics

- Custom monitoring dashboards to understand the overall health of an application

- Expanded monitoring with auto alerting and alerting on more metrics (including trace, user-defined and AWS resource metrics)

Through its improved observability offering, Epsagon allows users to analyze trends or spikes for more accurate troubleshooting across both serverless and container environments. Users can see three sources of data: service performance metrics, service metrics from the cloud infrastructure provider and custom business metrics. With metrics from the cloud provider, in particular, users can feel comfortable using Epsagon as their single platform for monitoring and troubleshooting microservices.

With Epsagon’s automated correlation of metrics, logs, traces and payloads in a single pane of glass, users not only see immediately when something goes wrong in their environment, they also gain a full and instant understanding of the root cause of the problem. Users can see high-level metrics, drill down to specific traces and analyze correlated metrics, logs and payloads for containers as well as serverless. They can correlate a trace to relevant logs, to compute metrics and to resource metrics, and they can jump seamlessly from a node to highly visual dashboards.

“Because Epsagon’s end-to-end observability platform provides a complete picture of their environment at full depth in an elegant, simple-to-use platform, teams now can confidently use this single platform instead of relying on their existing, loosely integrated mixture of APM, logging, monitoring and troubleshooting tools,” Shapira said.

Epsagon’s newest capabilities are available today.

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Epsagon Expands Applied Observability Platform

Epsagon announced Azure Kubernetes Service (AKS) support, as well as a Microsoft Azure Partnership and solution availability in the Azure Marketplace to serve the fast-growing number of enterprises using Azure Cloud and multi-cloud architectures.

In addition, Epsagon is expanding its core platform with enhanced automation and correlation capabilities as well as deep container and Kubernetes monitoring, alerting and troubleshooting for both Azure and AWS public clouds. This update is part of an overall strategy for the company to extend and apply Epsagon’s observability advantages—including automation of manual tasks, rapid and easy troubleshooting and issue resolution, greater developer velocity and faster time to business value—equally across serverless, container and Kubernetes environments and to Azure as well as AWS cloud infrastructures.

Now, Epsagon is extending the same level of seamless, automated observability and rich context that it pioneered for serverless environments to enterprises leveraging Azure as part or all of their cloud infrastructure, and the growing number of companies using container and Kubernetes technologies.

“Businesses are entering a Cloud 2.0 era where hyper-growth in data volume, more widespread adoption of hybrid container and serverless environments, and multi-cloud microservice architectures are driving complexity that makes application management ever more difficult,” said Nitzan Shapira, CEO at Epsagon. “Organizations need to be able to make sense of the terabytes of valuable data collected and understand, immediately, how to use this data to make wise operational and business-level decisions. Epsagon’s advances in observability, monitoring and troubleshooting get to the heart of this challenge.”

In addition to support for AWS Cloud and multiple AWS services, companies leveraging Azure for either part or all of their infrastructure can immediately and fully utilize Epsagon's observability platform for automated monitoring and troubleshooting of Azure Kubernetes Service (AKS) environments. With the new AKS cluster monitoring view, users and teams can understand:

- Cluster-level metrics over time for a specific cluster

- Nodes, pods, containers and deployments associated with the specific cluster

Already an AWS Advanced Technology Partner, Epsagon has made the same improvements as for Azure to its dashboard for AWS ECS, Amazon’s containerized orchestration tool, and for AWS EKS, Amazon Elastic Kubernetes Service.

Epsagon has also added to its platform:

- High-level infrastructure monitoring dashboards with compute service metrics

- Custom monitoring dashboards to understand the overall health of an application

- Expanded monitoring with auto alerting and alerting on more metrics (including trace, user-defined and AWS resource metrics)

Through its improved observability offering, Epsagon allows users to analyze trends or spikes for more accurate troubleshooting across both serverless and container environments. Users can see three sources of data: service performance metrics, service metrics from the cloud infrastructure provider and custom business metrics. With metrics from the cloud provider, in particular, users can feel comfortable using Epsagon as their single platform for monitoring and troubleshooting microservices.

With Epsagon’s automated correlation of metrics, logs, traces and payloads in a single pane of glass, users not only see immediately when something goes wrong in their environment, they also gain a full and instant understanding of the root cause of the problem. Users can see high-level metrics, drill down to specific traces and analyze correlated metrics, logs and payloads for containers as well as serverless. They can correlate a trace to relevant logs, to compute metrics and to resource metrics, and they can jump seamlessly from a node to highly visual dashboards.

“Because Epsagon’s end-to-end observability platform provides a complete picture of their environment at full depth in an elegant, simple-to-use platform, teams now can confidently use this single platform instead of relying on their existing, loosely integrated mixture of APM, logging, monitoring and troubleshooting tools,” Shapira said.

Epsagon’s newest capabilities are available today.

The Latest

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

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 ...