
Centreon announced a strategic collaboration agreement with Amazon Web Services (AWS) to support its new Software as a Service (SaaS) monitoring platform, Centreon Cloud.
Centreon Cloud will bring more value and an optimized time-to-market delivery for global customers and managed service providers with a robust, market-proven, agile, and cost-effective monitoring solution.
Centreon Cloud is a new SaaS IT Monitoring Platform giving organizations, no matter their size, maximum flexibility for their monitoring projects. After a successful Beta phase during which Centreon fine-tuned technical and operational details with selected customers, Centreon Cloud has entered a six-month Controlled Availability phase and has been commercially available in selected regions as of March 1, 2022. This SaaS offering will become generally available to all markets later this year. AWS teams have been working with Centreon from the beginning to provide guidance in designing a Cloud Native solution and selecting appropriate services offering an optimal cost/security/performance combination.
Marc-Antoine Hostier, Centreon COO said, “The market, and many of our existing customers, are embracing a Cloud-First strategy. This means that we not only need to monitor cloud infrastructures, but also need to have a monitoring platform that runs in the cloud itself. Today, with Centreon Cloud, we are responding to a growing market demand for full SaaS monitoring solutions and support our customers in their digitalization and migration strategies to the cloud, whether they are Cloud-First, Multi-Cloud or Hybrid. Being ready for tomorrow's infrastructure, today, is what we offer with Centreon Cloud."
The Centreon Cloud platform will serve clients by automatically discovering and monitoring Cloud Infrastructure within minutes, with zero-config alerting and no-code connectivity and integrations to 700+ asset types. At the same time, it can monitor on-premises legacy and edge equipment, providing a unique Cloud-to-Edge visibility. The benefit for customers will add tremendous value across the industry.
Julien Mathis, Centreon CEO and Co-Founder said, “Our customers choose Centreon because our solutions allow them to easily monitor 100% of their infrastructure, whether it's cloud, legacy, edge, or at the edge of the network, with unparalleled integration flexibility. Now they have the choice to subscribe to Centreon Cloud, so that they can focus on their core business and let us provide a turnkey service.”
Centreon has achieved another milestone on its journey as an AWS Partner Network member. By completing the Foundational Technical (FTR) and the Well Architected (WAR) Reviews for Centreon Cloud, Centreon has now reached the Validated stage of the AWS Partner Network Software Path.
Julien Mathis, CEO-Co-founder and Marc-Antoine Hostier, COO at Centreon both continued, "... With this strategic AWS relationship, we enter a new phase of growth for Centreon. With AWS, we are delivering Centreon Cloud, our SaaS monitoring platform. The APN program also allows us valuable access to the deep expertise of AWS and its partners, which is crucial for our international growth."
The Latest
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 ...
Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...
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 ...
If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...