Infrastructure Monitoring Market by Type (Agent-Based Monitoring, Agentless Monitoring), Component (Services, Solutions), Technology, End-User Vertical - Global Forecast 2025-2032
Description
The Infrastructure Monitoring Market was valued at USD 4.51 billion in 2024 and is projected to grow to USD 4.76 billion in 2025, with a CAGR of 6.13%, reaching USD 7.26 billion by 2032.
An authoritative orientation to modern infrastructure monitoring that explains the convergence of observability, resilience practices, and cross-functional operational priorities
The infrastructure monitoring domain is evolving rapidly as enterprises adopt hybrid architectures, distributed applications, and automated operation models. This introduction frames the current environment, clarifies core monitoring paradigms, and highlights why disciplined observability has become strategic for uptime, cost control, and compliance. The interplay of legacy on-premises systems with cloud-native services is creating a heterogenous estate that demands more sophisticated telemetry collection, correlation, and analytics.
As digital services grow in criticality, teams are shifting from reactive incident response to proactive resilience engineering. This shift prioritizes end-to-end visibility across application stacks and the underlying infrastructure, enabling faster root-cause identification and more precise remediation. In parallel, organizations are rethinking roles and processes, integrating monitoring outputs into DevOps and SRE practices to close the loop between development, deployment, and operations.
Security, regulatory obligations, and sustainability targets are adding new dimensions to monitoring requirements. Observability platforms are expected to not only signal performance degradations but also surface compliance deviations and inefficiencies in resource utilization. Consequently, decision-makers must consider monitoring as a strategic capability that informs investment trade-offs, drives operational maturity, and supports risk management across the enterprise.
How advancements in telemetry processing, AI-driven observability, and converged IT/OT practices are redefining what effective infrastructure monitoring must deliver
The landscape of infrastructure monitoring is experiencing transformative shifts driven by advances in telemetry, analytics, and cloud adoption. First, the proliferation of distributed architectures has increased the volume, variety, and velocity of telemetry, which in turn has made traditional siloed tooling insufficient; modern platforms must ingest diverse data types and present them in a normalized, correlated view to enable effective decision-making. As a result, vendors and adopters are focusing on high-cardinality event processing and scalable storage models that preserve fidelity without sacrificing performance.
Second, artificial intelligence and machine learning techniques have begun to augment human operators by surfacing anomalous patterns, prioritizing incidents, and recommending remediation steps. These capabilities are moving from experimental pilots into production workflows, reducing noise and accelerating mean time to resolution. At the same time, organizations are balancing automation with governance to ensure model outputs are explainable and auditable for stakeholders.
Third, the rise of converged IT and OT environments blurs the boundary between traditional enterprise IT monitoring and industrial monitoring. This trend is prompting integration of network, server, storage, database, and specialized control system telemetry into unified observability fabrics. Finally, cost discipline and sustainability goals are incentivizing more granular monitoring of resource consumption and environmental metrics, creating demand for features that tie performance to operational expenses and carbon footprint. Collectively, these shifts are redefining vendor roadmaps and buyer expectations, making extensibility, interoperability, and data governance central selection criteria.
Detailed assessment of how evolving United States tariff measures in 2025 reshape procurement choices, supply chain resilience, and observability architecture strategies
United States tariff policy developments in 2025 have introduced nuanced but material considerations for infrastructure monitoring programs that rely on global supply chains and hardware-dependent deployments. Tariffs that affect networking equipment, server components, and storage arrays increase the complexity of procurement decisions and create longer lead times for hardware refresh cycles. Consequently, organizations are prioritizing strategies that reduce dependence on bespoke hardware, accelerate adoption of software-defined alternatives, and extend the life of existing assets through enhanced predictive maintenance.
In addition, tariffs can amplify supply volatility, prompting procurement teams to diversify vendors and geographic sourcing to mitigate single-country exposure. This shift increases the need for vendor-agnostic monitoring solutions capable of operating across heterogeneous environments without requiring bespoke integrations for each hardware variant. Observability architectures that emphasize open instrumentation standards and vendor-neutral telemetry collectors are better positioned to absorb the operational shock of changing supplier landscapes.
Finally, tariffs influence total cost of ownership dynamics and capital allocation timing, which affects project prioritization for monitoring modernization. Organizations are likely to explore cloud-native observability options and managed services to reduce upfront capital demands and to convert fixed costs into more flexible operational expenses. In this context, monitoring leaders should revisit procurement policies, validate compatibility across alternative suppliers, and strengthen lifecycle management practices to maintain service continuity under shifting tariff regimes.
Actionable segmentation insights that connect monitoring approaches, component responsibilities, technology footprints, and vertical-specific observability priorities
Understanding segmentation is essential to align capability investments with operational objectives and to design an observability roadmap that addresses diverse technical requirements. Based on Type, monitoring approaches are broadly characterized by agent-based monitoring, which installs telemetry collectors on endpoints to gather granular process and application-level data, and agentless monitoring, which relies on external protocols and APIs to infer system health while minimizing endpoint footprint. Each approach has trade-offs: agent-based deployments provide depth of insight but introduce management overhead, whereas agentless methods lower operational burden but may miss fine-grained internal signals.
Based on Component, solutions and services frame the ecosystem where solutions include capabilities such as application performance monitoring, cloud monitoring, database monitoring, network monitoring, server monitoring, and storage monitoring, while services encompass managed and professional offerings that support deployment, tuning, and ongoing operation. This dual view highlights the importance of consuming monitoring as a combination of technology and services; organizations with constrained operational teams often favor managed services to accelerate value realization, while enterprises with strong internal expertise invest in professional services to tailor monitoring to complex architectures.
Based on Technology, wired and wireless modalities define observability needs for connectivity and edge scenarios, influencing telemetry collection methods and signal reliability considerations. Wireless deployments introduce latency and intermittent connectivity patterns that require robust buffering and resumable ingestion. Based on End-User Vertical, sector-specific requirements vary substantially: aerospace and defense impose stringent security and compliance constraints; automotive demands high availability and real-time telemetry for connected vehicle platforms; construction and manufacturing emphasize industrial protocol visibility and on-site OT integrations; oil and gas, and power generation necessitate resilience and safety-oriented monitoring frameworks. Crosscutting these dimensions, buyers must assess interoperability, regulatory constraints, and domain-specific telemetry sources to develop an effective monitoring strategy.
Practical regional intelligence that decodes adoption trends, regulatory impacts, and deployment choices across the Americas, EMEA, and Asia-Pacific landscapes
Regional dynamics shape both technology adoption patterns and procurement strategies, and practitioners must consider geographic nuances when designing monitoring programs. In the Americas, large enterprise adopters emphasize integrated observability platforms that support cloud migration and DevOps practices, with a strong appetite for managed services to streamline operations. This region also has a mature vendor ecosystem and a high rate of experimentation with AI-driven incident management, which accelerates feature adoption and integration standards.
In Europe, Middle East & Africa, regulatory diversity and data residency considerations drive a preference for solutions that offer flexible deployment models, including on-premises and private cloud options. Organizations here often prioritize data protection, encryption, and audit capabilities, and they require vendors to demonstrate compliance with local frameworks. In addition, regional infrastructure variability creates demand for solutions that can adapt to constrained connectivity and hybrid topologies.
In Asia-Pacific, heterogeneous infrastructure profiles and rapid digitalization across industries spur demand for scalable, cost-efficient monitoring. Many markets in this region combine legacy systems with aggressive cloud adoption, creating unique interoperability challenges and an increased need for professional services to configure and integrate monitoring across multiple environments. Taken together, regional differences inform vendor selection, service packaging, and the sequence of capability rollouts to ensure alignment with local operational realities and regulatory obligations.
Key company and ecosystem dynamics that reveal how provider capabilities, partnerships, and services influence technology selection and operational success
Competitive dynamics among technology providers and service firms influence solution roadmaps and buyer negotiations, and organizations should evaluate vendors across capability, openness, and delivery models. Leading solution providers are differentiating through platform extensibility, robust integrations, and investments in machine learning to reduce operational noise and accelerate incident triage. At the same time, a healthy ecosystem of specialists and managed service providers fills gaps in deployment expertise, integration services, and vertical adaptations for industrial and regulated environments.
Interoperability with third-party tooling and adherence to open telemetry standards are becoming key evaluation criteria, enabling buyers to avoid vendor lock-in and to reuse existing instrumentation across newer platforms. Partnerships between infrastructure, cloud, and network vendors also shape the value proposition, as integrated stacks reduce integration risk and simplify support models. For enterprise buyers, the ideal sourcing strategy often combines a strong core platform with targeted specialist services to cover edge cases and domain-specific telemetry requirements.
Finally, procurement and governance practices matter as much as product capabilities. Companies that structure vendor relationships around outcome-based metrics, clear service-level objectives, and continuous improvement pathways tend to realize faster operational benefits. Therefore, assessing provider track records, customer references, and service orchestration capabilities is crucial when selecting partners to support monitoring transformation.
High-impact, executable recommendations for leaders to accelerate observability maturity, secure operations, and align monitoring investments with strategic priorities
Leaders should adopt a clear set of pragmatic actions to accelerate monitoring maturity and to derive measurable operational outcomes. Begin by defining prioritized use cases that align with business objectives, focusing on high-impact scenarios such as incident reduction, mean time to repair improvement, and regulatory reporting. This clarity allows teams to select tooling and service models that deliver immediate value while creating a foundation for broader observability expansion.
Next, standardize instrumentation across teams by adopting common telemetry schemas and leveraging vendor-neutral collection agents or protocols where possible to preserve flexibility. Establish governance for data retention, access controls, and cost allocation to ensure observability outputs remain usable and secure. In parallel, invest in upskilling initiatives that bridge the gap between development, operations, and security, and formalize runbooks and escalation procedures so that insights translate into repeatable operational responses.
Finally, reassess procurement strategies in light of supply chain dynamics and tariff-related uncertainties by validating multi-supplier compatibility and prioritizing software-defined alternatives. Consider hybrid delivery models that combine managed services for operational continuity with in-house expertise to maintain strategic control. By sequencing these actions-use case prioritization, instrumentation standardization, capability development, and procurement resilience-organizations can achieve sustained improvements in service reliability and operational efficiency.
Transparent, practitioner-validated research methodology integrating technical synthesis, stakeholder interviews, and cross-sectional analysis to ensure rigorous insight provenance
The research methodology underpinning these insights combines a structured review of technical literature, synthesis of public policy analyses, and qualitative engagement with industry practitioners to capture practical implementation experiences. Primary inputs included interviews with infrastructure architects, operations leads, and procurement specialists across multiple sectors to surface real-world challenges and mitigation strategies. These practitioner insights were complemented by secondary source analysis of vendor technical documentation, standards initiatives, and regulatory guidance to ensure a comprehensive view of capability requirements and compliance drivers.
Analysts applied a cross-sectional approach to identify recurring patterns across deployment models, technological modalities, and vertical demands. This entailed mapping telemetry flows, evaluating integration points, and assessing service delivery models for scalability and security implications. Careful attention was given to distinguishing tactical operational practices from strategic architectural choices, and to validating assumptions through peer review with experienced monitoring professionals.
Throughout the process, emphasis was placed on transparency of reasoning and traceability of conclusions so that recommendations are actionable and defensible. The methodology balances practitioner experience with technical validation to provide a reliable foundation for decision-makers planning monitoring transformations or vendor selections.
Concluding synthesis that reinforces observability as a strategic capability and summarizes the practical pathways to operational resilience and governance excellence
In conclusion, infrastructure monitoring has moved from a supporting IT function to a strategic capability that underpins resilience, regulatory compliance, and operational efficiency. The interplay of distributed architectures, AI-assisted analytics, and regional policy dynamics requires a thoughtful, multi-dimensional approach to observability design. Organizations that prioritize use-case clarity, embrace open instrumentation practices, and align procurement to supply chain realities will be better positioned to extract continuous value from monitoring investments.
Moreover, the transition to outcome-focused provider relationships and the selective use of managed services can accelerate time to value while preserving strategic control over critical telemetry and governance. As complexity increases, so do the returns to disciplined telemetry management, cross-functional workflows, and investment in people and processes. Executives and technical leaders who take a coordinated approach will strengthen operational resilience, reduce incident impact, and support digital initiatives with the visibility and control required for sustainable growth.
Note: PDF & Excel + Online Access - 1 Year
An authoritative orientation to modern infrastructure monitoring that explains the convergence of observability, resilience practices, and cross-functional operational priorities
The infrastructure monitoring domain is evolving rapidly as enterprises adopt hybrid architectures, distributed applications, and automated operation models. This introduction frames the current environment, clarifies core monitoring paradigms, and highlights why disciplined observability has become strategic for uptime, cost control, and compliance. The interplay of legacy on-premises systems with cloud-native services is creating a heterogenous estate that demands more sophisticated telemetry collection, correlation, and analytics.
As digital services grow in criticality, teams are shifting from reactive incident response to proactive resilience engineering. This shift prioritizes end-to-end visibility across application stacks and the underlying infrastructure, enabling faster root-cause identification and more precise remediation. In parallel, organizations are rethinking roles and processes, integrating monitoring outputs into DevOps and SRE practices to close the loop between development, deployment, and operations.
Security, regulatory obligations, and sustainability targets are adding new dimensions to monitoring requirements. Observability platforms are expected to not only signal performance degradations but also surface compliance deviations and inefficiencies in resource utilization. Consequently, decision-makers must consider monitoring as a strategic capability that informs investment trade-offs, drives operational maturity, and supports risk management across the enterprise.
How advancements in telemetry processing, AI-driven observability, and converged IT/OT practices are redefining what effective infrastructure monitoring must deliver
The landscape of infrastructure monitoring is experiencing transformative shifts driven by advances in telemetry, analytics, and cloud adoption. First, the proliferation of distributed architectures has increased the volume, variety, and velocity of telemetry, which in turn has made traditional siloed tooling insufficient; modern platforms must ingest diverse data types and present them in a normalized, correlated view to enable effective decision-making. As a result, vendors and adopters are focusing on high-cardinality event processing and scalable storage models that preserve fidelity without sacrificing performance.
Second, artificial intelligence and machine learning techniques have begun to augment human operators by surfacing anomalous patterns, prioritizing incidents, and recommending remediation steps. These capabilities are moving from experimental pilots into production workflows, reducing noise and accelerating mean time to resolution. At the same time, organizations are balancing automation with governance to ensure model outputs are explainable and auditable for stakeholders.
Third, the rise of converged IT and OT environments blurs the boundary between traditional enterprise IT monitoring and industrial monitoring. This trend is prompting integration of network, server, storage, database, and specialized control system telemetry into unified observability fabrics. Finally, cost discipline and sustainability goals are incentivizing more granular monitoring of resource consumption and environmental metrics, creating demand for features that tie performance to operational expenses and carbon footprint. Collectively, these shifts are redefining vendor roadmaps and buyer expectations, making extensibility, interoperability, and data governance central selection criteria.
Detailed assessment of how evolving United States tariff measures in 2025 reshape procurement choices, supply chain resilience, and observability architecture strategies
United States tariff policy developments in 2025 have introduced nuanced but material considerations for infrastructure monitoring programs that rely on global supply chains and hardware-dependent deployments. Tariffs that affect networking equipment, server components, and storage arrays increase the complexity of procurement decisions and create longer lead times for hardware refresh cycles. Consequently, organizations are prioritizing strategies that reduce dependence on bespoke hardware, accelerate adoption of software-defined alternatives, and extend the life of existing assets through enhanced predictive maintenance.
In addition, tariffs can amplify supply volatility, prompting procurement teams to diversify vendors and geographic sourcing to mitigate single-country exposure. This shift increases the need for vendor-agnostic monitoring solutions capable of operating across heterogeneous environments without requiring bespoke integrations for each hardware variant. Observability architectures that emphasize open instrumentation standards and vendor-neutral telemetry collectors are better positioned to absorb the operational shock of changing supplier landscapes.
Finally, tariffs influence total cost of ownership dynamics and capital allocation timing, which affects project prioritization for monitoring modernization. Organizations are likely to explore cloud-native observability options and managed services to reduce upfront capital demands and to convert fixed costs into more flexible operational expenses. In this context, monitoring leaders should revisit procurement policies, validate compatibility across alternative suppliers, and strengthen lifecycle management practices to maintain service continuity under shifting tariff regimes.
Actionable segmentation insights that connect monitoring approaches, component responsibilities, technology footprints, and vertical-specific observability priorities
Understanding segmentation is essential to align capability investments with operational objectives and to design an observability roadmap that addresses diverse technical requirements. Based on Type, monitoring approaches are broadly characterized by agent-based monitoring, which installs telemetry collectors on endpoints to gather granular process and application-level data, and agentless monitoring, which relies on external protocols and APIs to infer system health while minimizing endpoint footprint. Each approach has trade-offs: agent-based deployments provide depth of insight but introduce management overhead, whereas agentless methods lower operational burden but may miss fine-grained internal signals.
Based on Component, solutions and services frame the ecosystem where solutions include capabilities such as application performance monitoring, cloud monitoring, database monitoring, network monitoring, server monitoring, and storage monitoring, while services encompass managed and professional offerings that support deployment, tuning, and ongoing operation. This dual view highlights the importance of consuming monitoring as a combination of technology and services; organizations with constrained operational teams often favor managed services to accelerate value realization, while enterprises with strong internal expertise invest in professional services to tailor monitoring to complex architectures.
Based on Technology, wired and wireless modalities define observability needs for connectivity and edge scenarios, influencing telemetry collection methods and signal reliability considerations. Wireless deployments introduce latency and intermittent connectivity patterns that require robust buffering and resumable ingestion. Based on End-User Vertical, sector-specific requirements vary substantially: aerospace and defense impose stringent security and compliance constraints; automotive demands high availability and real-time telemetry for connected vehicle platforms; construction and manufacturing emphasize industrial protocol visibility and on-site OT integrations; oil and gas, and power generation necessitate resilience and safety-oriented monitoring frameworks. Crosscutting these dimensions, buyers must assess interoperability, regulatory constraints, and domain-specific telemetry sources to develop an effective monitoring strategy.
Practical regional intelligence that decodes adoption trends, regulatory impacts, and deployment choices across the Americas, EMEA, and Asia-Pacific landscapes
Regional dynamics shape both technology adoption patterns and procurement strategies, and practitioners must consider geographic nuances when designing monitoring programs. In the Americas, large enterprise adopters emphasize integrated observability platforms that support cloud migration and DevOps practices, with a strong appetite for managed services to streamline operations. This region also has a mature vendor ecosystem and a high rate of experimentation with AI-driven incident management, which accelerates feature adoption and integration standards.
In Europe, Middle East & Africa, regulatory diversity and data residency considerations drive a preference for solutions that offer flexible deployment models, including on-premises and private cloud options. Organizations here often prioritize data protection, encryption, and audit capabilities, and they require vendors to demonstrate compliance with local frameworks. In addition, regional infrastructure variability creates demand for solutions that can adapt to constrained connectivity and hybrid topologies.
In Asia-Pacific, heterogeneous infrastructure profiles and rapid digitalization across industries spur demand for scalable, cost-efficient monitoring. Many markets in this region combine legacy systems with aggressive cloud adoption, creating unique interoperability challenges and an increased need for professional services to configure and integrate monitoring across multiple environments. Taken together, regional differences inform vendor selection, service packaging, and the sequence of capability rollouts to ensure alignment with local operational realities and regulatory obligations.
Key company and ecosystem dynamics that reveal how provider capabilities, partnerships, and services influence technology selection and operational success
Competitive dynamics among technology providers and service firms influence solution roadmaps and buyer negotiations, and organizations should evaluate vendors across capability, openness, and delivery models. Leading solution providers are differentiating through platform extensibility, robust integrations, and investments in machine learning to reduce operational noise and accelerate incident triage. At the same time, a healthy ecosystem of specialists and managed service providers fills gaps in deployment expertise, integration services, and vertical adaptations for industrial and regulated environments.
Interoperability with third-party tooling and adherence to open telemetry standards are becoming key evaluation criteria, enabling buyers to avoid vendor lock-in and to reuse existing instrumentation across newer platforms. Partnerships between infrastructure, cloud, and network vendors also shape the value proposition, as integrated stacks reduce integration risk and simplify support models. For enterprise buyers, the ideal sourcing strategy often combines a strong core platform with targeted specialist services to cover edge cases and domain-specific telemetry requirements.
Finally, procurement and governance practices matter as much as product capabilities. Companies that structure vendor relationships around outcome-based metrics, clear service-level objectives, and continuous improvement pathways tend to realize faster operational benefits. Therefore, assessing provider track records, customer references, and service orchestration capabilities is crucial when selecting partners to support monitoring transformation.
High-impact, executable recommendations for leaders to accelerate observability maturity, secure operations, and align monitoring investments with strategic priorities
Leaders should adopt a clear set of pragmatic actions to accelerate monitoring maturity and to derive measurable operational outcomes. Begin by defining prioritized use cases that align with business objectives, focusing on high-impact scenarios such as incident reduction, mean time to repair improvement, and regulatory reporting. This clarity allows teams to select tooling and service models that deliver immediate value while creating a foundation for broader observability expansion.
Next, standardize instrumentation across teams by adopting common telemetry schemas and leveraging vendor-neutral collection agents or protocols where possible to preserve flexibility. Establish governance for data retention, access controls, and cost allocation to ensure observability outputs remain usable and secure. In parallel, invest in upskilling initiatives that bridge the gap between development, operations, and security, and formalize runbooks and escalation procedures so that insights translate into repeatable operational responses.
Finally, reassess procurement strategies in light of supply chain dynamics and tariff-related uncertainties by validating multi-supplier compatibility and prioritizing software-defined alternatives. Consider hybrid delivery models that combine managed services for operational continuity with in-house expertise to maintain strategic control. By sequencing these actions-use case prioritization, instrumentation standardization, capability development, and procurement resilience-organizations can achieve sustained improvements in service reliability and operational efficiency.
Transparent, practitioner-validated research methodology integrating technical synthesis, stakeholder interviews, and cross-sectional analysis to ensure rigorous insight provenance
The research methodology underpinning these insights combines a structured review of technical literature, synthesis of public policy analyses, and qualitative engagement with industry practitioners to capture practical implementation experiences. Primary inputs included interviews with infrastructure architects, operations leads, and procurement specialists across multiple sectors to surface real-world challenges and mitigation strategies. These practitioner insights were complemented by secondary source analysis of vendor technical documentation, standards initiatives, and regulatory guidance to ensure a comprehensive view of capability requirements and compliance drivers.
Analysts applied a cross-sectional approach to identify recurring patterns across deployment models, technological modalities, and vertical demands. This entailed mapping telemetry flows, evaluating integration points, and assessing service delivery models for scalability and security implications. Careful attention was given to distinguishing tactical operational practices from strategic architectural choices, and to validating assumptions through peer review with experienced monitoring professionals.
Throughout the process, emphasis was placed on transparency of reasoning and traceability of conclusions so that recommendations are actionable and defensible. The methodology balances practitioner experience with technical validation to provide a reliable foundation for decision-makers planning monitoring transformations or vendor selections.
Concluding synthesis that reinforces observability as a strategic capability and summarizes the practical pathways to operational resilience and governance excellence
In conclusion, infrastructure monitoring has moved from a supporting IT function to a strategic capability that underpins resilience, regulatory compliance, and operational efficiency. The interplay of distributed architectures, AI-assisted analytics, and regional policy dynamics requires a thoughtful, multi-dimensional approach to observability design. Organizations that prioritize use-case clarity, embrace open instrumentation practices, and align procurement to supply chain realities will be better positioned to extract continuous value from monitoring investments.
Moreover, the transition to outcome-focused provider relationships and the selective use of managed services can accelerate time to value while preserving strategic control over critical telemetry and governance. As complexity increases, so do the returns to disciplined telemetry management, cross-functional workflows, and investment in people and processes. Executives and technical leaders who take a coordinated approach will strengthen operational resilience, reduce incident impact, and support digital initiatives with the visibility and control required for sustainable growth.
Note: PDF & Excel + Online Access - 1 Year
Table of Contents
181 Pages
- 1. Preface
- 1.1. Objectives of the Study
- 1.2. Market Segmentation & Coverage
- 1.3. Years Considered for the Study
- 1.4. Currency
- 1.5. Language
- 1.6. Stakeholders
- 2. Research Methodology
- 3. Executive Summary
- 4. Market Overview
- 5. Market Insights
- 5.1. Integration of artificial intelligence and machine learning for predictive infrastructure problem detection and resolution
- 5.2. Adoption of unified observability platforms combining logs, metrics and distributed tracing for faster incident response
- 5.3. Implementation of edge computing monitoring solutions for distributed industrial and large-scale IoT environments
- 5.4. Expansion of cloud-native monitoring to oversee containerized microservices across hybrid multi-cloud deployments
- 5.5. Integration of security telemetry with infrastructure monitoring for unified threat detection and regulatory compliance visibility
- 5.6. Deployment of synthetic transaction testing to proactively assess application performance and end-user digital experience
- 5.7. Adoption of low-code monitoring configuration tools for rapid setup, customization and workflow automation by operations teams
- 6. Cumulative Impact of United States Tariffs 2025
- 7. Cumulative Impact of Artificial Intelligence 2025
- 8. Infrastructure Monitoring Market, by Type
- 8.1. Agent-Based Monitoring
- 8.2. Agentless Monitoring
- 9. Infrastructure Monitoring Market, by Component
- 9.1. Services
- 9.1.1. Managed
- 9.1.2. Professional
- 9.2. Solutions
- 9.2.1. Application Performance Monitoring (APM)
- 9.2.2. Cloud Monitoring
- 9.2.3. Database Monitoring
- 9.2.4. Network Monitoring
- 9.2.5. Server Monitoring
- 9.2.6. Storage Monitoring
- 10. Infrastructure Monitoring Market, by Technology
- 10.1. Wired
- 10.2. Wireless
- 11. Infrastructure Monitoring Market, by End-User Vertical
- 11.1. Aerospace & Defense
- 11.2. Automotive
- 11.3. Construction
- 11.4. Manufacturing
- 11.5. Oil & Gas
- 11.6. Power Generation
- 12. Infrastructure Monitoring Market, by Region
- 12.1. Americas
- 12.1.1. North America
- 12.1.2. Latin America
- 12.2. Europe, Middle East & Africa
- 12.2.1. Europe
- 12.2.2. Middle East
- 12.2.3. Africa
- 12.3. Asia-Pacific
- 13. Infrastructure Monitoring Market, by Group
- 13.1. ASEAN
- 13.2. GCC
- 13.3. European Union
- 13.4. BRICS
- 13.5. G7
- 13.6. NATO
- 14. Infrastructure Monitoring Market, by Country
- 14.1. United States
- 14.2. Canada
- 14.3. Mexico
- 14.4. Brazil
- 14.5. United Kingdom
- 14.6. Germany
- 14.7. France
- 14.8. Russia
- 14.9. Italy
- 14.10. Spain
- 14.11. China
- 14.12. India
- 14.13. Japan
- 14.14. Australia
- 14.15. South Korea
- 15. Competitive Landscape
- 15.1. Market Share Analysis, 2024
- 15.2. FPNV Positioning Matrix, 2024
- 15.3. Competitive Analysis
- 15.3.1. Auvik Networks Inc.
- 15.3.2. BMC Software, Inc.
- 15.3.3. Broadcom, Inc.
- 15.3.4. Cisco Systems, Inc.
- 15.3.5. Datadog
- 15.3.6. Dynatrace Inc.
- 15.3.7. eG Innovations
- 15.3.8. Grafana Labs
- 15.3.9. Hewlett Packard Enterprise Company
- 15.3.10. Icinga GmbH
- 15.3.11. International Business Machines Corporation
- 15.3.12. Kentik, Inc.
- 15.3.13. LogicMonitor Inc.
- 15.3.14. Microsoft Corporation
- 15.3.15. Nagios Enterprises, LLC
- 15.3.16. NEW RELIC INC.
- 15.3.17. Opsview Ltd.
- 15.3.18. Paessler GmbH
- 15.3.19. Progress Software Corporation
- 15.3.20. Prometheus by The Linux Foundation
- 15.3.21. ScienceLogic, Inc.
- 15.3.22. SolarWinds Worldwide, LLC
- 15.3.23. Splunk LLC
- 15.3.24. Sumo Logic, Inc.
- 15.3.25. Zabbix LLC
- 15.3.26. Zoho Corporation Pvt. Ltd.
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