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Akuity Launches New AI Capabilities

Akuity announced that it has launched major new AI capabilities that let users detect degraded states across applications, triage incidents and automate fixes on the Akuity platform in minutes. 

The platform provides enterprise-ready continuous delivery and promotion capabilities for Kubernetes and is built on the fundamentals of Argo CD, the third most-adopted open source project in the CNCF behind Kubernetes and OpenTelemetry.

Companies use the Akuity platform to deploy, promote and monitor across their Kubernetes clusters leveraging GitOps best practices:

  • Deploy: Akuity’s advanced hybrid, agent-based model, built on a rearchitected Argo CD, is 100x more scalable than the open source project, delivers better security and enables companies to manage thousands of clusters from a single control plane.
  • Promote: Akuity’s promotion capabilities are built on top of Kargo, an open source continuous promotion orchestration layer, removing the need for custom scripts and providing safer deployments with enforced processes and guardrails.
  • Monitor: Akuity’s multi-cluster Kubernetes dashboards let teams view all Kubernetes resources, facilitating issue detection and troubleshooting without requiring developers to switch between different tools.

Akuity co-founder and CEO and Argo CD co-creator Hong Wang said: “Developers spend a majority of their time on manual tasks, such as identifying CVEs and remediating issues. Built on the context and insights from Kubernetes clusters, Akuity’s new AI capabilities enable developers to detect, troubleshoot and remediate issues with a few clicks. Issues that may have taken days and multiple developers to resolve can now be fixed in minutes.”

The new AI capabilities build on the power of Akuity Intelligence, enabling developers to go beyond manual troubleshooting to AI-powered remediation. Developers can now leverage Akuity’s AI in the Argo CD UI they trust and:

  • Detect incidents as soon as workloads drift from a healthy state and remediates them quickly, reducing MTTD and MTTR
  • Centralize incident context with logs, events, metrics and deployment history, eliminating tool-switching
  • Increase autonomy with runbooks so incidents can be resolved without waking on-call engineers
  • Maintain team awareness with real-time Slack updates on incident status and actions taken
  • Provide enterprise control with approval gates, scoped permissions and full audit trails, giving organizations confidence in automation

The new release is generally available today and as a free trial.

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Akuity Launches New AI Capabilities

Akuity announced that it has launched major new AI capabilities that let users detect degraded states across applications, triage incidents and automate fixes on the Akuity platform in minutes. 

The platform provides enterprise-ready continuous delivery and promotion capabilities for Kubernetes and is built on the fundamentals of Argo CD, the third most-adopted open source project in the CNCF behind Kubernetes and OpenTelemetry.

Companies use the Akuity platform to deploy, promote and monitor across their Kubernetes clusters leveraging GitOps best practices:

  • Deploy: Akuity’s advanced hybrid, agent-based model, built on a rearchitected Argo CD, is 100x more scalable than the open source project, delivers better security and enables companies to manage thousands of clusters from a single control plane.
  • Promote: Akuity’s promotion capabilities are built on top of Kargo, an open source continuous promotion orchestration layer, removing the need for custom scripts and providing safer deployments with enforced processes and guardrails.
  • Monitor: Akuity’s multi-cluster Kubernetes dashboards let teams view all Kubernetes resources, facilitating issue detection and troubleshooting without requiring developers to switch between different tools.

Akuity co-founder and CEO and Argo CD co-creator Hong Wang said: “Developers spend a majority of their time on manual tasks, such as identifying CVEs and remediating issues. Built on the context and insights from Kubernetes clusters, Akuity’s new AI capabilities enable developers to detect, troubleshoot and remediate issues with a few clicks. Issues that may have taken days and multiple developers to resolve can now be fixed in minutes.”

The new AI capabilities build on the power of Akuity Intelligence, enabling developers to go beyond manual troubleshooting to AI-powered remediation. Developers can now leverage Akuity’s AI in the Argo CD UI they trust and:

  • Detect incidents as soon as workloads drift from a healthy state and remediates them quickly, reducing MTTD and MTTR
  • Centralize incident context with logs, events, metrics and deployment history, eliminating tool-switching
  • Increase autonomy with runbooks so incidents can be resolved without waking on-call engineers
  • Maintain team awareness with real-time Slack updates on incident status and actions taken
  • Provide enterprise control with approval gates, scoped permissions and full audit trails, giving organizations confidence in automation

The new release is generally available today and as a free trial.

The Latest

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...

40% of organizations deploying AI will implement dedicated AI observability tools by 2028 to monitor model performance, bias and outputs, according to Gartner ...

Until AI-powered engineering tools have live visibility of how code behaves at runtime, they cannot be trusted to autonomously ensure reliable systems, according to the State of AI-Powered Engineering Report 2026 report from Lightrun. The report reveals that a major volume of manual work is required when AI-generated code is deployed: 43% of AI-generated code requires manual debugging in production, even after passing QA or staging tests. Furthermore, an average of three manual redeploy cycles are required to verify a single AI-suggested code fix in production ...

Many organizations describe AI as strategic, but they do not manage it strategically. When AI plans are disconnected from strategy, detached from organizational learning, and protected from serious assumptions testing, the problem is no longer technical immaturity; it is a failure of management discipline ... Executives too often tell organizations to "use AI" before they define what AI is supposed to change. The problem deepens in organizations where strategy isn't well articulated in the first place ...

Across the enterprise technology landscape, a quiet crisis is playing out. Organizations have run hundreds, sometimes thousands, of generative AI pilots. Leadership has celebrated the proof of concept (POCs) ... Industry experience points to a sobering reality: only 5-10% of AI POCs that progress to the pilot stage successfully reach scaled production. The remaining 90% fail because the enterprise environment around them was never ready to absorb them, not the AI models ...

Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...

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Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors. On one hand, they are being asked to push digital transformation ... On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far. In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats ...

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...