components function in a dynamic yet uniform manner through a single graphical interface with a customizable dashboard view, automating workflows, integrating third-party applications and providing dynamic and intelligent monitoring across an enterprise’s network infrastructure with robust reporting capabilities. Data-driven observability takes this networking management and monitoring functionality to a new level. Contextualization utilizes AI to generate enriched and correlated (versus isolated) data that provides a richer, real-time view of the network environment, spanning components, access points and devices. With full-stack observability in place, organizations benefit from more meaningful data, actionable insights and reduced time to resolution through faster triaging and escalation. Additionally, AI technology enables enhanced automation of these functions, leveraging predictive analytics and event correlation techniques. The improved automated workflows enable more accurate and efficient data management, minimize alert fatigue and reduce the need for manual intervention. Much like a ballet where the harmony of performers depends on synchronized movement, a network operates smoothly when all components interact fluidly. A single disruption can cause cascading effects, alerting multiple systems and triggering redundant tickets. Contextualization helps stitch these signals together, presenting a holistic view that quickly identifies the root issue. Key Advantages Contextualized network management platforms delivered through a single pane of glass offer many advantages that include reduced ticket volumes and MTTR, as well as enhanced control and visibility that is provided through a centralized dashboard. First and foremost, it simplifies network management in an increasingly complex and distributed enterprise network environment. Secondly, it reduces network vulnerabilities to security breaches through enhanced threat detection and remediation capabilities. Additionally, it enables more efficient and optimized performance, helping reduce costs, conserve scarce IT resources and improve productivity. The consolidated view of applications also helps ensure enhanced control and reduced opportunity for error. This relates to the expanding array of use cases across cloud, security and third-party middle-mile monitoring. The improved automation capabilities also enable realtime response times and faster incident resolution. These improvements are further strengthened by more advanced event correlation techniques, which enable pre-emptive and proactive problem remediation. In addition, access to data, along with its integrity and meaningfulness, is also improved, driving more efficient and effective decision-making. Finally, holistic observability delivered through a single pane of glass helps ensure operational stability and continuous business, improving both the user and customer experience. Use Cases Data-driven observability through a single pane of glass has numerous applications across network management, cybersecurity, business intelligence, supply chain management and overall IT operations management. The operation Number of Network-related Tools in Use Source: Uptime Institute; 2022 Source: Auvik 10% 2% 26% 62% 5% 2% 44% 49% 4% 8% 20% 68% 4% 29% 67% 12% 36% 52% 12% 2% 35% 51% 6% 1% 31% 62% 7% 1% 44% 48% 10% 3% 26% 61% Corporate IT IT MSP 1-100 employees 101-500 employees 501-1000 employees 1000+ employees 0-4 years 5-9 years 10+ years Less than 10 CORPORATE VS SERVICE PROVIDER ORGANIZATION SIZE ORGANIZATION OPERATIONAL YEARS Between 10-20 More than 20+ Don’t know 19 SUMMER 2025 | CHANNELVISION
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