Centreon has reinvented its partner program.
In order to seize growth opportunity, Centreon has embraced a partner-first strategy internationally. By investing in partners, Centreon expects to increase their revenue and geographic coverage, while continuing to provide support from their current operations across Europe, North and Latin America.
“The need for Always-On IT is booming and customers from all regions want to benefit from our leading monitoring platform”, explains Eryk Markiewicz, CMO at Centreon. “This reinvented partner program not only brings the value of Centreon even closer to customers but enriches the partner and customer experience with increased access to technical tooling, sales support and marketing programs.”
In a world that runs on IT, the opportunity for Centreon partners is to support the Always-On business needs of customers. Centreon is focusing on and investing in enabling their partners to seize on this market potential, and the extensive need for services to support business-critical operations.
Onboarding, Technical and Sales Enablement and Certification are available through the Centreon Academy for Partners using a cutting-edge LMS (Learning Management System), and Sales, Marketing and Services processes are managed with a rich PRM (Partner Relationship Management) platform giving them access to sales tools, technical training and market insights.
In addition to these new systems, all our partners have access to our dedicated, partner-facing teams, including monitoring technical experts and pre-sales resources.
” Partners continue to play an invaluable role at Centreon”, says Marc-Antoine Hostier, Chief Revenue Officer at Centreon, ”but we are accelerating our investments to become the best company to do business with in our space. We are actively recruiting VARs and SIs in EMEA, Americas, and Asia-Pacific, and will extend our partner program to more partner types such as Distributors, GOSIs and Consulting Firms in 2021.”
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 ...