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Elastic Expands Cloud Security Capabilities for AWS

Elastic announced expanded capabilities for Elastic Security including Cloud Security Posture Management (CSPM) for AWS, container workload security, and cloud vulnerability management.

Building on the previously released Kubernetes security posture management (KSPM) and Cloud Workload Protection Platform (CWPP) capabilities, Elastic now delivers a comprehensive security analytics solution that includes complete Cloud Native Application Protection for AWS.

According to Gartner, more than 85% of organizations are moving to a cloud-first model and 95% of new digital workloads are being deployed on cloud-native platforms. However, 99% of cloud failures will be the customer’s fault due to mistakes like cloud misconfigurations. Research from Elastic Security Labs found that nearly 1 in 3 (33%) attacks in the cloud leverage credential access, indicating that users often overestimate the security of their cloud environments and fail to configure and protect them adequately.

“Many companies have a fragmented approach to cloud security, as security and devops teams pivot between multiple dashboards,” said Ken Buckler, Research Analyst - Security and Risk Management, Enterprise Management Associates. “Unified visibility across all cloud resources, as well as on-premises systems, is critical to quickly identify and stop security threats at scale, especially when attackers repeatedly cross boundaries between cloud and on-premise in attempts to evade detection. With Elastic Security, organizations can streamline their cloud security operations by establishing real-time, unified visibility across their environments in a single interface.”

Elastic’s comprehensive suite of cloud security capabilities includes:

- Cloud Workload Protection (generally available) — Expands on existing runtime security for traditional endpoints, enabling cloud security teams to gain deep visibility into the entire runtime workload including standalone Linux workloads, virtual machines, and infrastructure hosted in AWS, Google Cloud, and Microsoft Azure.

- Container Workload Protection (beta) — Provides cloud security teams deep visibility into container workloads in managed Kubernetes environments with pre-execution runtime analysis for workloads running in Amazon EKS, GKE, and AKS environments.

- Cloud Security Posture Management (beta) — Enables cloud security teams to continuously detect and remediate misconfigurations across workloads in AWS and Amazon EKS in real-time with Center for Information Security (CIS) benchmark controls, out-of-the-box integrations, and posture management dashboards and reports.

- Cloud Vulnerability Management (beta) — Uncovers cloud-native vulnerabilities in AWS EC2 workloads with minimal resource utilization on workloads and enumerating vulnerabilities with risk context to help cloud security teams identify and respond to potential risk.

“Elastic Security is a unified security solution offering SIEM, endpoint, and cloud security capabilities—rooted in data management and analytics—that enables customers to protect, investigate and respond to threats across their entire infrastructure,” said Santosh Krishnan, General Manager of Elastic Security, Elastic. “The expansion of Elastic Security’s comprehensive cloud security capabilities provides organizations with the power they need to modernize their cloud security operations, improve attack surface visibility, reduce vendor complexity, and accelerate remediation.”

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Elastic Expands Cloud Security Capabilities for AWS

Elastic announced expanded capabilities for Elastic Security including Cloud Security Posture Management (CSPM) for AWS, container workload security, and cloud vulnerability management.

Building on the previously released Kubernetes security posture management (KSPM) and Cloud Workload Protection Platform (CWPP) capabilities, Elastic now delivers a comprehensive security analytics solution that includes complete Cloud Native Application Protection for AWS.

According to Gartner, more than 85% of organizations are moving to a cloud-first model and 95% of new digital workloads are being deployed on cloud-native platforms. However, 99% of cloud failures will be the customer’s fault due to mistakes like cloud misconfigurations. Research from Elastic Security Labs found that nearly 1 in 3 (33%) attacks in the cloud leverage credential access, indicating that users often overestimate the security of their cloud environments and fail to configure and protect them adequately.

“Many companies have a fragmented approach to cloud security, as security and devops teams pivot between multiple dashboards,” said Ken Buckler, Research Analyst - Security and Risk Management, Enterprise Management Associates. “Unified visibility across all cloud resources, as well as on-premises systems, is critical to quickly identify and stop security threats at scale, especially when attackers repeatedly cross boundaries between cloud and on-premise in attempts to evade detection. With Elastic Security, organizations can streamline their cloud security operations by establishing real-time, unified visibility across their environments in a single interface.”

Elastic’s comprehensive suite of cloud security capabilities includes:

- Cloud Workload Protection (generally available) — Expands on existing runtime security for traditional endpoints, enabling cloud security teams to gain deep visibility into the entire runtime workload including standalone Linux workloads, virtual machines, and infrastructure hosted in AWS, Google Cloud, and Microsoft Azure.

- Container Workload Protection (beta) — Provides cloud security teams deep visibility into container workloads in managed Kubernetes environments with pre-execution runtime analysis for workloads running in Amazon EKS, GKE, and AKS environments.

- Cloud Security Posture Management (beta) — Enables cloud security teams to continuously detect and remediate misconfigurations across workloads in AWS and Amazon EKS in real-time with Center for Information Security (CIS) benchmark controls, out-of-the-box integrations, and posture management dashboards and reports.

- Cloud Vulnerability Management (beta) — Uncovers cloud-native vulnerabilities in AWS EC2 workloads with minimal resource utilization on workloads and enumerating vulnerabilities with risk context to help cloud security teams identify and respond to potential risk.

“Elastic Security is a unified security solution offering SIEM, endpoint, and cloud security capabilities—rooted in data management and analytics—that enables customers to protect, investigate and respond to threats across their entire infrastructure,” said Santosh Krishnan, General Manager of Elastic Security, Elastic. “The expansion of Elastic Security’s comprehensive cloud security capabilities provides organizations with the power they need to modernize their cloud security operations, improve attack surface visibility, reduce vendor complexity, and accelerate remediation.”

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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.