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Cloud Infrastructure Services Market Size 2024-2028
The cloud infrastructure services market size is forecast to increase by USD 109.2 billion at a CAGR of 9.4% between 2023 and 2028. The market is experiencing significant growth, driven by the shift from capital expenditure (CAPEX) to operational expenditure (OPEX) models. This trend allows businesses to reduce upfront costs and invest in other areas of their operations. Another key trend is the increasing adoption of hybrid cloud storage systems, which offer the benefits of both public and private clouds. However, challenges remain, including latency in cloud networks, security concerns, and the need for seamless integration between different cloud platforms. To address these challenges, cloud infrastructure service providers are investing in advanced technologies such as artificial intelligence and machine learning to improve network performance and enhance security features. Overall, the market is expected to continue growing as more businesses adopt cloud solutions to optimize their IT infrastructure and improve operational efficiency.
What will be the Size of the Market During the Forecast Period?
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Cloud infrastructure services refer to the hardware and software components required to build, deploy, and manage cloud architectures, including private cloud, public cloud, and hybrid clouds. These services encompass computing resources such as servers and storage devices, as well as networking and management software. Cloud architecture relies on virtualization technologies like hypervisors and virtual machine monitors to create and manage virtual servers and machines. Cloud services offer flexibility and scalability, enabling businesses to quickly deploy and manage resources as needed.
Moreover, cloud computing resources can be scaled up or down based on demand, while storage can be easily expanded or contracted. Networking is crucial for cloud infrastructure, ensuring seamless communication between servers, virtual machines, and users. Security is a top priority in cloud infrastructure, with intelligent monitoring and management software providing real-time threat detection and response. Deployment software streamlines the process of launching and managing applications in the cloud, while cloud management software provides a centralized interface for managing and monitoring cloud resources. Overall, cloud infrastructure services enable businesses to build and deploy applications and services more efficiently and cost-effectively than traditional on-premises solutions.
Market Segmentation
The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.
Deployment
Public cloud
Private cloud
Hybrid cloud
Geography
North America
US
APAC
China
Japan
Europe
Germany
UK
South America
Middle East and Africa
By Deployment Insights
The public cloud segment is estimated to witness significant growth during the forecast period. In the dynamic business landscape of 2023, the public cloud segment holds a significant share of The market. This dominance can be attributed to the expanding IT, BFSI, education, healthcare, and retail sectors, which require cloud infrastructure for valuable business insights. The increasing number of Small and Medium Enterprises (SMEs) in emerging economies, such as China, India, Brazil, Indonesia, and Mexico, is driving the demand for public cloud services. These organizations seek cost-effective solutions for their business needs. Cloud infrastructure service providers offer virtualization technology, enabling organizations to deploy software applications on a shared backend infrastructure, ensuring flexibility and scalability. Public cloud computing and storage devices are accessible via the internet, making it a preferred choice for businesses seeking to reduce capital expenditures and focus on their core competencies.
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The public cloud segment was valued at USD 99.90 billion in 2018 and showed a gradual increase during the forecast period.
Regional Insights
North America is estimated to contribute 34% to the growth of the global market during the forecast period. Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.
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In the global market for cloud infrastructure services, North America held the largest market share in 2023. The region's dominance can be attributed to the rising demand for computing services, leading to an expansion of data centers and storage spaces. Cloud infra
This nowCOAST time-enabled map service provides map depicting the latest surface weather and marine weather observations at observing sites using the international station model. The station model is method for representing information collected at an observing station using symbols and numbers. The station model depicts current weather conditions, cloud cover, wind speed, wind direction, visibility, air temperature, dew point temperature, sea surface water temperature, significant wave height, air pressure adjusted to mean sea level, and the change in air pressure over the last 3 hours. The circle in the model is centered over the latitude and longitude coordinates of the station. The total cloud cover is expressed as a fraction of cloud covering the sky and is indicated by the amount of circle filled in. (Cloud cover is not presently displayed due to a problem with the source data. Present weather information is also not available for display at this time.) Wind speed and direction are represented by a wind barb whose line extends from the cover cloud circle towards the direction from which the wind is blowing. The short lines or flags coming off the end of the long line are called barbs. The barb indicates the wind speed in knots. Each normal barb represents 10 knots, while short barbs indicate 5 knots. A flag represents 50 knots. If there is no wind barb depicted, an outer circle around the cloud cover symbol indicates calm winds. The map of observations are updated in the nowCOAST map service approximately every 10 minutes. However, since the reporting frequency varies by network or station, the observation at a particular station may have not updated and may not update until after the next hour. For more detailed information about the update schedule, please see: http://new.nowcoast.noaa.gov/help/#section=updateschedule
Background InformationThe maps of near-real-time surface weather and ocean observations are based on non-restricted data obtained from the NWS Family of Services courtesy of NESDIS/OPSD and also the NWS Meteorological Assimilation Data Ingest System (MADIS). The data includes observations from terrestrial and maritime observing from the U.S.A. and other countries. For terrestrial networks, the platforms including but not limited to ASOS, AWOS, RAWS, non-automated stations, U.S. Climate Reference Networks, many U.S. Geological Survey Stations via NWS HADS, several state DOT Road Weather Information Systems, and U.S. Historical Climatology Network-Modernization. For over maritime areas, the platforms include NOS/CO-OPS National Water Level Observation Network (NWLON), NOS/CO-OPS Physical Oceanographic Observing Network (PORTS), NWS/NDBC Fixed Buoys, NDBC Coastal-Marine Automated Network (C-MAN), drifting buoys, ferries, Regional Ocean Observing System (ROOS) coastal stations and buoys, and ships participating in the Voluntary Ship Observing (VOS) Program. Observations from MADIS are updated approximately every 10 minutes in the map service and those from NESDIS are updated every hour. However, not all stations report that frequently. Many stations only report once per hour sometime between 15 minutes before the hour and 30 minutes past the hour. For these stations, new observations will not appear until 22 minutes past top of the hour for land-based stations and 32 minutes past the top of the hour for maritime stations.
Time InformationThis map is time-enabled, meaning that each individual layer contains time-varying data and can be utilized by clients capable of making map requests that include a time component.
This particular service can be queried with or without the use of a time component. If the time parameter is specified in a request, the data or imagery most relevant to the provided time value, if any, will be returned. If the time parameter is not specified in a request, the latest data or imagery valid for the present system time will be returned to the client. If the time parameter is not specified and no data or imagery is available for the present time, no data will be returned.
In addition to ArcGIS Server REST access, time-enabled OGC WMS 1.3.0 access is also provided by this service.
Due to software limitations, the time extent of the service and map layers displayed below does not provide the most up-to-date start and end times of available data. Instead, users have three options for determining the latest time information about the service:
This nowCOAST time-enabled map service provides map depicting the latest surface weather and marine weather observations at observing sites using the international station model. The station model is method for representing information collected at an observing station using symbols and numbers. The station model depicts current weather conditions, cloud cover, wind speed, wind direction, visibility, air temperature, dew point temperature, sea surface water temperature, significant wave height, air pressure adjusted to mean sea level, and the change in air pressure over the last 3 hours. The circle in the model is centered over the latitude and longitude coordinates of the station. The total cloud cover is expressed as a fraction of cloud covering the sky and is indicated by the amount of circle filled in. (Cloud cover is not presently displayed due to a problem with the source data. Present weather information is also not available for display at this time.) Wind speed and direction are represented by a wind barb whose line extends from the cover cloud circle towards the direction from which the wind is blowing. The short lines or flags coming off the end of the long line are called barbs. The barb indicates the wind speed in knots. Each normal barb represents 10 knots, while short barbs indicate 5 knots. A flag represents 50 knots. If there is no wind barb depicted, an outer circle around the cloud cover symbol indicates calm winds. The map of observations are updated in the nowCOAST map service approximately every 10 minutes. However, since the reporting frequency varies by network or station, the observation at a particular station may have not updated and may not update until after the next hour. For more detailed information about the update schedule, please see: http://new.nowcoast.noaa.gov/help/#section=updateschedule
Background InformationThe maps of near-real-time surface weather and ocean observations are based on non-restricted data obtained from the NWS Family of Services courtesy of NESDIS/OPSD and also the NWS Meteorological Assimilation Data Ingest System (MADIS). The data includes observations from terrestrial and maritime observing from the U.S.A. and other countries. For terrestrial networks, the platforms including but not limited to ASOS, AWOS, RAWS, non-automated stations, U.S. Climate Reference Networks, many U.S. Geological Survey Stations via NWS HADS, several state DOT Road Weather Information Systems, and U.S. Historical Climatology Network-Modernization. For over maritime areas, the platforms include NOS/CO-OPS National Water Level Observation Network (NWLON), NOS/CO-OPS Physical Oceanographic Observing Network (PORTS), NWS/NDBC Fixed Buoys, NDBC Coastal-Marine Automated Network (C-MAN), drifting buoys, ferries, Regional Ocean Observing System (ROOS) coastal stations and buoys, and ships participating in the Voluntary Ship Observing (VOS) Program. Observations from MADIS are updated approximately every 10 minutes in the map service and those from NESDIS are updated every hour. However, not all stations report that frequently. Many stations only report once per hour sometime between 15 minutes before the hour and 30 minutes past the hour. For these stations, new observations will not appear until 22 minutes past top of the hour for land-based stations and 32 minutes past the top of the hour for maritime stations.
Time InformationThis map is time-enabled, meaning that each individual layer contains time-varying data and can be utilized by clients capable of making map requests that include a time component.
This particular service can be queried with or without the use of a time component. If the time parameter is specified in a request, the data or imagery most relevant to the provided time value, if any, will be returned. If the time parameter is not specified in a request, the latest data or imagery valid for the present system time will be returned to the client. If the time parameter is not specified and no data or imagery is available for the present time, no data will be returned.
In addition to ArcGIS Server REST access, time-enabled OGC WMS 1.3.0 access is also provided by this service.
Due to software limitations, the time extent of the service and map layers displayed below does not provide the most up-to-date start and end times of available data. Instead, users have three options for determining the latest time information about the service:
According to our latest research, the global Road Weather Information System Cloud market size in 2024 stands at USD 1.45 billion, with a robust compound annual growth rate (CAGR) of 11.2% projected from 2025 to 2033. By 2033, the market is anticipated to reach a value of USD 3.98 billion. This exceptional growth is driven by the increasing need for real-time weather data integration in road safety management, rapid urbanization, and a rising emphasis on smart infrastructure across multiple regions. As per our latest research, the adoption of cloud-based Road Weather Information Systems (RWIS) is accelerating due to advancements in sensor technologies, enhanced connectivity, and the demand for scalable, cost-effective solutions in the transportation sector.
A key growth factor for the Road Weather Information System Cloud market is the surge in government investments aimed at modernizing transportation infrastructure. Many countries are prioritizing road safety and traffic efficiency, leading to the deployment of advanced weather monitoring and traffic management systems. These initiatives are heavily reliant on cloud-based RWIS platforms, which offer seamless integration with other smart city technologies and enable centralized data management. The ability to collect, process, and analyze vast amounts of real-time weather and road condition data is crucial for proactive decision-making, especially in regions prone to severe weather events. As governments continue to allocate budgets towards intelligent transportation systems, the demand for RWIS cloud solutions is set to rise exponentially.
Another significant driver is the technological evolution in sensor networks and Internet of Things (IoT) integration. Modern RWIS deployments utilize a wide array of sensors for temperature, humidity, wind speed, precipitation, and road surface conditions, all connected to cloud platforms for real-time analytics. The scalability and flexibility offered by cloud infrastructure allow for the rapid expansion of RWIS networks without the constraints of traditional on-premises systems. Additionally, cloud-based RWIS solutions facilitate seamless data sharing and collaboration among various stakeholders, including transportation departments, meteorological agencies, and commercial fleets. This interconnected ecosystem enhances the accuracy of weather forecasts, optimizes maintenance planning, and minimizes traffic disruptions, thereby improving overall road safety and operational efficiency.
The increasing focus on sustainability and environmental impact is also shaping the Road Weather Information System Cloud market. Cloud-based RWIS platforms support predictive maintenance and efficient resource allocation, which contribute to reduced energy consumption and lower carbon emissions from road operations. By enabling timely interventions such as anti-icing, snow removal, and hazard warnings, these systems help prevent accidents and minimize traffic congestion, resulting in more sustainable transportation networks. Furthermore, the integration of machine learning and artificial intelligence in cloud-based RWIS solutions is unlocking new possibilities for predictive analytics and automated decision-making, further boosting market growth. As environmental regulations become stricter and public awareness of climate change grows, the adoption of cloud-enabled RWIS is expected to accelerate.
On the regional front, North America remains the dominant market for Road Weather Information System Cloud solutions, driven by substantial investments in intelligent transportation systems and a high incidence of adverse weather conditions. Europe follows closely, with a strong emphasis on road safety and regulatory compliance. The Asia Pacific region, however, is emerging as the fastest-growing market, fueled by rapid urbanization, expanding highway networks, and increasing government initiatives in smart city development. Latin America and the Middle East & Africa are also witnessing steady growth, albeit at a slower pace, as infrastructure modernization gains momentum. Each region presents unique opportunities and challenges, with varying levels of technology adoption and regulatory frameworks influencing market dynamics.
This nowCOAST time-enabled map service provides map depicting the latest surface weather and marine weather observations at observing sites using the international station model. The station model is method for representing information collected at an observing station using symbols and numbers. The station model depicts current weather conditions, cloud cover, wind speed, wind direction, visibility, air temperature, dew point temperature, sea surface water temperature, significant wave height, air pressure adjusted to mean sea level, and the change in air pressure over the last 3 hours. The circle in the model is centered over the latitude and longitude coordinates of the station. The total cloud cover is expressed as a fraction of cloud covering the sky and is indicated by the amount of circle filled in. (Cloud cover is not presently displayed due to a problem with the source data. Present weather information is also not available for display at this time.) Wind speed and direction are represented by a wind barb whose line extends from the cover cloud circle towards the direction from which the wind is blowing. The short lines or flags coming off the end of the long line are called barbs. The barb indicates the wind speed in knots. Each normal barb represents 10 knots, while short barbs indicate 5 knots. A flag represents 50 knots. If there is no wind barb depicted, an outer circle around the cloud cover symbol indicates calm winds. The map of observations are updated in the nowCOAST map service approximately every 10 minutes. However, since the reporting frequency varies by network or station, the observation at a particular station may have not updated and may not update until after the next hour. For more detailed information about the update schedule, please see: http://new.nowcoast.noaa.gov/help/#section=updateschedule
Background InformationThe maps of near-real-time surface weather and ocean observations are based on non-restricted data obtained from the NWS Family of Services courtesy of NESDIS/OPSD and also the NWS Meteorological Assimilation Data Ingest System (MADIS). The data includes observations from terrestrial and maritime observing from the U.S.A. and other countries. For terrestrial networks, the platforms including but not limited to ASOS, AWOS, RAWS, non-automated stations, U.S. Climate Reference Networks, many U.S. Geological Survey Stations via NWS HADS, several state DOT Road Weather Information Systems, and U.S. Historical Climatology Network-Modernization. For over maritime areas, the platforms include NOS/CO-OPS National Water Level Observation Network (NWLON), NOS/CO-OPS Physical Oceanographic Observing Network (PORTS), NWS/NDBC Fixed Buoys, NDBC Coastal-Marine Automated Network (C-MAN), drifting buoys, ferries, Regional Ocean Observing System (ROOS) coastal stations and buoys, and ships participating in the Voluntary Ship Observing (VOS) Program. Observations from MADIS are updated approximately every 10 minutes in the map service and those from NESDIS are updated every hour. However, not all stations report that frequently. Many stations only report once per hour sometime between 15 minutes before the hour and 30 minutes past the hour. For these stations, new observations will not appear until 22 minutes past top of the hour for land-based stations and 32 minutes past the top of the hour for maritime stations.
Time InformationThis map is time-enabled, meaning that each individual layer contains time-varying data and can be utilized by clients capable of making map requests that include a time component.
This particular service can be queried with or without the use of a time component. If the time parameter is specified in a request, the data or imagery most relevant to the provided time value, if any, will be returned. If the time parameter is not specified in a request, the latest data or imagery valid for the present system time will be returned to the client. If the time parameter is not specified and no data or imagery is available for the present time, no data will be returned.
In addition to ArcGIS Server REST access, time-enabled OGC WMS 1.3.0 access is also provided by this service.
Due to software limitations, the time extent of the service and map layers displayed below does not provide the most up-to-date start and end times of available data. Instead, users have three options for determining the latest time information about the service:
This nowCOAST time-enabled map service provides map depicting the latest surface weather and marine weather observations at observing sites using the international station model. The station model is method for representing information collected at an observing station using symbols and numbers. The station model depicts current weather conditions, cloud cover, wind speed, wind direction, visibility, air temperature, dew point temperature, sea surface water temperature, significant wave height, air pressure adjusted to mean sea level, and the change in air pressure over the last 3 hours. The circle in the model is centered over the latitude and longitude coordinates of the station. The total cloud cover is expressed as a fraction of cloud covering the sky and is indicated by the amount of circle filled in. (Cloud cover is not presently displayed due to a problem with the source data. Present weather information is also not available for display at this time.) Wind speed and direction are represented by a wind barb whose line extends from the cover cloud circle towards the direction from which the wind is blowing. The short lines or flags coming off the end of the long line are called barbs. The barb indicates the wind speed in knots. Each normal barb represents 10 knots, while short barbs indicate 5 knots. A flag represents 50 knots. If there is no wind barb depicted, an outer circle around the cloud cover symbol indicates calm winds. The map of observations are updated in the nowCOAST map service approximately every 10 minutes. However, since the reporting frequency varies by network or station, the observation at a particular station may have not updated and may not update until after the next hour. For more detailed information about the update schedule, please see: http://new.nowcoast.noaa.gov/help/#section=updateschedule
Background InformationThe maps of near-real-time surface weather and ocean observations are based on non-restricted data obtained from the NWS Family of Services courtesy of NESDIS/OPSD and also the NWS Meteorological Assimilation Data Ingest System (MADIS). The data includes observations from terrestrial and maritime observing from the U.S.A. and other countries. For terrestrial networks, the platforms including but not limited to ASOS, AWOS, RAWS, non-automated stations, U.S. Climate Reference Networks, many U.S. Geological Survey Stations via NWS HADS, several state DOT Road Weather Information Systems, and U.S. Historical Climatology Network-Modernization. For over maritime areas, the platforms include NOS/CO-OPS National Water Level Observation Network (NWLON), NOS/CO-OPS Physical Oceanographic Observing Network (PORTS), NWS/NDBC Fixed Buoys, NDBC Coastal-Marine Automated Network (C-MAN), drifting buoys, ferries, Regional Ocean Observing System (ROOS) coastal stations and buoys, and ships participating in the Voluntary Ship Observing (VOS) Program. Observations from MADIS are updated approximately every 10 minutes in the map service and those from NESDIS are updated every hour. However, not all stations report that frequently. Many stations only report once per hour sometime between 15 minutes before the hour and 30 minutes past the hour. For these stations, new observations will not appear until 22 minutes past top of the hour for land-based stations and 32 minutes past the top of the hour for maritime stations.
Time InformationThis map is time-enabled, meaning that each individual layer contains time-varying data and can be utilized by clients capable of making map requests that include a time component.
This particular service can be queried with or without the use of a time component. If the time parameter is specified in a request, the data or imagery most relevant to the provided time value, if any, will be returned. If the time parameter is not specified in a request, the latest data or imagery valid for the present system time will be returned to the client. If the time parameter is not specified and no data or imagery is available for the present time, no data will be returned.
In addition to ArcGIS Server REST access, time-enabled OGC WMS 1.3.0 access is also provided by this service.
Due to software limitations, the time extent of the service and map layers displayed below does not provide the most up-to-date start and end times of available data. Instead, users have three options for determining the latest time information about the service:
According to our latest research, the global Real-Time Targeting Cloud at the Edge market size reached USD 3.62 billion in 2024, registering a robust growth trajectory. The market is anticipated to expand at a CAGR of 19.4% during the forecast period, with the market size projected to reach USD 15.33 billion by 2033. This rapid expansion is primarily driven by the increasing demand for ultra-low latency data processing, the proliferation of IoT devices, and the growing need for real-time analytics across various industries. The integration of edge computing with cloud-based targeting solutions is revolutionizing how enterprises deliver personalized experiences, optimize operations, and ensure data security at the network's edge.
One of the primary growth factors propelling the Real-Time Targeting Cloud at the Edge market is the escalating adoption of IoT and smart devices across industries such as manufacturing, healthcare, and retail. These devices generate massive volumes of data that require real-time processing and analysis to enable instant decision-making. Edge computing, in tandem with cloud-based targeting, allows organizations to process data closer to the source, significantly reducing latency and bandwidth usage. As a result, enterprises can deliver hyper-personalized content, offers, and services to end-users, enhancing customer engagement and operational efficiency. Furthermore, the increasing focus on digital transformation and automation is compelling organizations to invest in advanced edge-cloud architectures, further fueling market growth.
Another significant driver is the surge in demand for real-time analytics and targeted advertising, particularly in sectors such as advertising & marketing, retail, and telecommunications. Businesses are leveraging real-time targeting solutions at the edge to analyze consumer behavior, preferences, and location data instantaneously. This enables them to deliver contextually relevant advertisements and promotions, improving conversion rates and maximizing ROI. The evolution of 5G networks and advancements in AI and machine learning algorithms are further augmenting the capabilities of real-time targeting cloud at the edge, enabling seamless, high-speed data transmission and sophisticated analytics at scale. These technological advancements are expected to open new avenues for market expansion in the coming years.
Security and data privacy concerns are also playing a pivotal role in shaping the market landscape. With stringent data protection regulations such as GDPR and CCPA, organizations are increasingly prioritizing solutions that enable secure data processing and storage at the edge. Real-Time Targeting Cloud at the Edge offers enhanced security by minimizing data transfer to centralized data centers and enabling localized data governance. This not only reduces the risk of data breaches but also ensures compliance with regional and industry-specific regulations. The growing emphasis on secure and compliant data processing is expected to drive the adoption of edge-cloud targeting solutions, particularly among enterprises handling sensitive customer information.
From a regional perspective, North America currently dominates the Real-Time Targeting Cloud at the Edge market, accounting for the largest share in 2024. The region's leadership can be attributed to the presence of major technology players, early adoption of advanced digital solutions, and significant investments in IoT and edge computing infrastructure. Asia Pacific is emerging as the fastest-growing region, driven by rapid industrialization, increasing internet penetration, and a burgeoning e-commerce sector. Europe also holds a substantial share, supported by robust regulatory frameworks and growing demand for digital transformation across various industries. The Middle East & Africa and Latin America are witnessing steady growth, fueled by rising investments in smart city projects and digital infrastructure.
The Real-Time
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Cloud Integration Software Market Size and Trends
The cloud integration software market size is forecast to increase by USD 9.31 billion, at a CAGR of 12.4% between 2023 and 2028. The market is experiencing significant growth due to the increasing adoption of cloud-based solutions among large enterprises in various industries, including IT and telecom, healthcare, and manufacturing. This trend is driven by the need for digital transformation and the proliferation of interconnected devices. Hybrid environments are becoming increasingly common, leading to a demand for cloud-integrated solutions that can seamlessly connect on-premises systems with cloud applications. Moreover, pre-configured integration packages are gaining popularity due to their ease of use and quick implementation. However, concerns about data security remain a challenge, as organizations must ensure that their data is protected while being transferred and stored in the cloud. The market is expected to continue growing as businesses seek to streamline their operations and improve efficiency through the use of advanced integration technologies. In summary, the market is witnessing strong growth due to the increasing adoption of cloud solutions by large enterprises in various industries, the need for hybrid environments, and the popularity of pre-configured integration packages. However, data security concerns remain a challenge that must be addressed.
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The market is witnessing significant growth as businesses increasingly adopt cloud-based solutions to address the challenges of connecting disparate applications within their IT environment. With the rise of remote work models and distributed teams, the need for scalable storage solutions and real-time data connectivity has become crucial. Cloud integration software enables seamless data transfer between on-premises applications and cloud-based applications. It facilitates the interoperability of various systems, ensuring that data remains consistent and up-to-date across the organization. This is particularly important in industries such as e-commerce, banking, and others that rely on real-time data processing and analysis. The integration of cloud-based applications with edge computing and serverless architectures is also gaining traction. These technologies enable businesses to process data closer to the source, reducing latency and improving overall performance. Moreover, artificial intelligence (AI) and machine learning (ML) repositories can be integrated with cloud-based systems, enabling advanced analytics and automation of workflows.
Cloud migration is another key driver of the market. As more businesses move their operations to the cloud, they require integration solutions to connect their legacy systems with their new cloud-based infrastructure. This ensures a smooth transition and minimizes disruptions to business operations. In the market, cloud integration software is becoming an essential component of digital transformation initiatives. It enables businesses to leverage the benefits of cloud computing while ensuring that their IT systems remain interconnected and functional. The use of automated workflows and real-time data connectivity further enhances operational efficiency and productivity. The market is expected to continue its growth trajectory, driven by the increasing adoption of cloud-based solutions and the need for seamless data integration across various systems and applications. With the continued evolution of technology, cloud integration software will play a critical role in enabling businesses to adapt and thrive in an increasingly digital world.
Market Segmentation
The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2024-2028, as well as historical data from 2018 - 2022 for the following segments.
Deployment
SaaS
IaaS
Paas
Geography
North America
Canada
US
Europe
Germany
UK
France
APAC
China
India
Japan
South Korea
South America
Middle East and Africa
By Deployment Insights
The SaaS segment is estimated to witness significant growth during the forecast period. The market is expected to experience significant growth, with SaaS (Software as a Service) being the leading segment. SaaS is a software delivery model where cloud providers host applications and grant access to users via the Internet. This model is popular among various sectors including large enterprises, healthcare, manufacturing, and IT and telecommunications, due to its affordability and scalability.
Get a glance at the market share of various segments Download the PDF Sample
The SaaS segment was valued at USD 4.97 billion in 2018. The SaaS industry's expansion is driven by digital transformation initiatives, the increasing numb
According to our latest research, the global Cloud-Based HD Map Distribution market size reached USD 2.42 billion in 2024, demonstrating robust growth driven by increasing adoption of autonomous and connected vehicle technologies. The market is projected to expand at a remarkable CAGR of 18.7% from 2025 to 2033, reaching an estimated USD 12.05 billion by 2033. This growth is propelled by the surging demand for real-time, high-definition mapping solutions that support next-generation mobility applications, including autonomous vehicles, advanced driver-assistance systems (ADAS), and dynamic fleet management. As per our latest research, the rising integration of cloud computing with high-definition mapping platforms is transforming the automotive and mobility sectors, enabling seamless, scalable, and up-to-date distribution of critical map data.
One of the primary growth factors for the Cloud-Based HD Map Distribution market is the accelerating development and deployment of autonomous vehicles across global markets. High-definition (HD) maps are a foundational technology for self-driving cars, providing centimeter-level accuracy and detailed information about road geometry, lane markings, traffic signs, and surrounding infrastructure. The cloud-based distribution of these maps ensures that autonomous vehicles receive the most current data, enabling safe navigation and real-time response to changing road conditions. As automotive OEMs and technology companies intensify their investments in autonomous driving, the demand for scalable, cloud-delivered HD mapping solutions is set to rise dramatically, further fueling market expansion.
Another significant driver is the proliferation of connected vehicles and the increasing adoption of advanced driver-assistance systems (ADAS). Cloud-based HD maps are essential for enabling features such as lane-keeping assistance, adaptive cruise control, and predictive route planning. These systems rely on precise, real-time map data to enhance situational awareness and improve driver safety. The shift towards connected mobility ecosystems, where vehicles continuously exchange data with the cloud and other infrastructure, underscores the importance of reliable and high-speed map distribution platforms. Additionally, the growth of shared mobility services and the emergence of smart cities are creating new opportunities for cloud-based HD map providers to deliver tailored solutions for diverse end-users.
The rapid advancements in cloud computing infrastructure and the increasing availability of high-speed internet networks are also contributing to the growth of the Cloud-Based HD Map Distribution market. Cloud platforms offer unparalleled scalability, flexibility, and cost-efficiency, enabling map service providers to update, store, and distribute massive volumes of HD map data in real time. The integration of artificial intelligence and machine learning with cloud-based mapping platforms further enhances the accuracy and predictive capabilities of HD maps. As cloud adoption becomes mainstream in the automotive and transportation industries, it is expected to unlock new business models and revenue streams for both established players and emerging startups in the HD map distribution ecosystem.
From a regional perspective, North America currently leads the global Cloud-Based HD Map Distribution market, supported by significant investments in autonomous vehicle research, a mature connected vehicle ecosystem, and the presence of major technology and automotive companies. Europe follows closely, driven by stringent safety regulations, smart mobility initiatives, and collaborations between OEMs and mapping technology providers. The Asia Pacific region is poised for the fastest growth during the forecast period, fueled by rapid urbanization, government support for smart transportation infrastructure, and the expansion of automotive manufacturing hubs. Latin America and the Middle East & Africa are also witnessing increased adoption of cloud-based HD mapping solutions, primarily in logistics and fleet management applications.
Ambee’s global weather dataset provides a continuum of data that flows seamlessly from the year 1995 to present and into the forecast with forward forecast views ranging from one hour all the way out to 46 days. All data is available in both hourly and daily format and daily data includes min. and max. values, and daily averages.
The Ambee global weather dataset was developed using direct observations, sensors, satellite imagery, reanalysis model outputs, and more, to deliver a global dataset that is harmonized and calibrated for use across any analytics or modeling workload.
Parameters include core atmospheric variables such as temperature, feels like temperature, humidity, dew point, wind speed and direction, precipitation, both rain and snow, cloud cover, visibility, solar radiation, UV index, and pressure. Additional derived fields are available upon request.
Gaps in data are intelligently filled using companion datasets and climatological data. cross-station substitution, and meteorological context modeling. All values are passed through Ambee’s multi-stage quality pipeline to ensure long-term temporal integrity and cross-region comparability.
This dataset is ideal for machine learning training, demand forecasting, infrastructure planning, ESG reporting, and climate-related risk modeling. Clients across pharmaceuticals, retail, agriculture, and finance use Ambee’s global weather data to optimize operations, mitigate weather risk, and create predictive and prescriptive models to improve overall business performance.
As per our latest research, the global cloud-based database security market size reached USD 7.4 billion in 2024, reflecting robust demand across diverse industries. The market is poised to grow at a compelling CAGR of 17.2% from 2025 to 2033, with the market size forecasted to reach USD 25.7 billion by 2033. This strong growth trajectory is primarily driven by the increasing adoption of cloud infrastructure, the proliferation of data-centric business models, and escalating concerns over cyber threats targeting sensitive and mission-critical data.
A major growth factor for the cloud-based database security market is the exponential rise in cloud adoption across enterprises of all sizes. Organizations are migrating their workloads and databases to the cloud to leverage scalability, cost-efficiency, and agility. However, this migration has also amplified the exposure of databases to sophisticated cyberattacks, prompting a surge in demand for advanced cloud-based security solutions. The increasing frequency of data breaches, ransomware attacks, and compliance requirements such as GDPR, HIPAA, and CCPA have made database security a board-level priority. Consequently, businesses are investing in comprehensive security frameworks that encompass threat detection, access control, encryption, and compliance management, thereby fueling market growth.
Another significant driver is the rapid digital transformation initiatives undertaken by sectors such as BFSI, healthcare, retail, and government. The surge in digital transactions, electronic health records, and online retailing has led to an unprecedented volume of sensitive data being stored and processed in cloud databases. This data is a lucrative target for cybercriminals, necessitating robust security measures. Innovations in artificial intelligence (AI), machine learning (ML), and automation are being integrated into cloud-based database security solutions, enabling real-time threat intelligence, anomaly detection, and automated response mechanisms. These advancements are not only enhancing the efficacy of security protocols but also reducing manual intervention and operational costs.
Furthermore, the evolving regulatory landscape is compelling organizations to adopt cloud-based database security solutions. Governments and regulatory bodies worldwide are imposing stringent data protection laws, mandating businesses to implement advanced security controls and maintain audit trails. Non-compliance can result in hefty fines, reputational damage, and loss of customer trust. As a result, companies are increasingly opting for cloud-native security platforms that offer centralized visibility, automated compliance reporting, and seamless integration with existing IT infrastructure. The growing awareness about the shared responsibility model in cloud security is also encouraging enterprises to proactively secure their databases, driving sustained market expansion.
From a regional perspective, North America currently dominates the cloud-based database security market, accounting for the largest share in 2024, followed by Europe and Asia Pacific. The region's leadership is attributed to the high concentration of cloud service providers, early adoption of advanced technologies, and stringent regulatory frameworks. However, Asia Pacific is expected to exhibit the fastest growth during the forecast period, driven by rapid digitalization, expanding IT infrastructure, and increasing investments in cybersecurity. Latin America and the Middle East & Africa are also witnessing steady growth, fueled by rising awareness and government initiatives to bolster data security.
The component segment of the cloud-based database security market is bifurcated into software and services. Software solutions encompass a wide array of security tools, including database activity monitoring, data encryption, access management, and vulnerability assessment.
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This application is intended for informational purposes only and is not an operational product. The tool provides the capability to access, view and interact with satellite imagery, and shows the latest view of Earth as it appears from space.For additional imagery from NOAA's GOES East and GOES West satellites, please visit our Imagery and Data page or our cooperative institute partners at CIRA and CIMSS.This website should not be used to support operational observation, forecasting, emergency, or disaster mitigation operations, either public or private. In addition, we do not provide weather forecasts on this site — that is the mission of the National Weather Service. Please contact them for any forecast questions or issues. Using the MapsWhat does the Layering Options icon mean?The Layering Options widget provides a list of operational layers and their symbols, and allows you to turn individual layers on and off. The order in which layers appear in this widget corresponds to the layer order in the map. The top layer ‘checked’ will indicate what you are viewing in the map, and you may be unable to view the layers below.Layers with expansion arrows indicate that they contain sublayers or subtypes.What does the Time Slider icon do?The Time Slider widget enables you to view temporal layers in a map, and play the animation to see how the data changes over time. Using this widget, you can control the animation of the data with buttons to play and pause, go to the previous time period, and go to the next time period.Do these maps work on mobile devices and different browsers?Yes!Why are there black stripes / missing data on the map?NOAA Satellite Maps is for informational purposes only and is not an operational product; there are times when data is not available.Why does the imagery load slowly?This map viewer does not load pre-generated web-ready graphics and animations like many satellite imagery apps you may be used to seeing. Instead, it downloads geospatial data from our data servers through a Map Service, and the app in your browser renders the imagery in real-time. Each pixel needs to be rendered and geolocated on the web map for it to load.How can I get the raw data and download the GIS World File for the images I choose?The geospatial data Map Service for the NOAA Satellite Maps GOES satellite imagery is located on our Satellite Maps ArcGIS REST Web Service ( available here ).We support open information sharing and integration through this RESTful Service, which can be used by a multitude of GIS software packages and web map applications (both open and licensed).Data is for display purposes only, and should not be used operationally.Are there any restrictions on using this imagery?NOAA supports an open data policy and we encourage publication of imagery from NOAA Satellite Maps; when doing so, please cite it as "NOAA" and also consider including a permalink (such as this one) to allow others to explore the imagery.For acknowledgment in scientific journals, please use:We acknowledge the use of imagery from the NOAA Satellite Maps application: LINKThis imagery is not copyrighted. You may use this material for educational or informational purposes, including photo collections, textbooks, public exhibits, computer graphical simulations and internet web pages. This general permission extends to personal web pages. About this satellite imageryWhat am I looking at in these maps?In this map you are seeing the past 24 hours (updated approximately every 10 minutes) of the Western Hemisphere and Pacific Ocean, as seen by the NOAA GOES East (GOES-16) and GOES West (GOES-18) satellites. In this map you can also view four different ‘layers’. The views show ‘GeoColor’, ‘infrared’, and ‘water vapor’.This maps shows the coverage area of the GOES East and GOES West satellites. GOES East, which orbits the Earth from 75.2 degrees west longitude, provides a continuous view of the Western Hemisphere, from the West Coast of Africa to North and South America. GOES West, which orbits the Earth at 137.2 degrees west longitude, sees western North and South America and the central and eastern Pacific Ocean all the way to New Zealand.What does the GOES GeoColor imagery show?The 'Merged GeoColor’ map shows the coverage area of the GOES East and GOES West satellites and includes the entire Western Hemisphere and most of the Pacific Ocean. This imagery uses a combination of visible and infrared channels and is updated approximately every 15 minutes in real time. GeoColor imagery approximates how the human eye would see Earth from space during daylight hours, and is created by combining several of the spectral channels from the Advanced Baseline Imager (ABI) – the primary instrument on the GOES satellites. The wavelengths of reflected sunlight from the red and blue portions of the spectrum are merged with a simulated green wavelength component, creating RGB (red-green-blue) imagery. At night, infrared imagery shows high clouds as white and low clouds and fog as light blue. The static city lights background basemap is derived from a single composite image from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day Night Band. For example, temporary power outages will not be visible. Learn more.What does the GOES infrared map show?The 'GOES infrared' map displays heat radiating off of clouds and the surface of the Earth and is updated every 15 minutes in near real time. Higher clouds colorized in orange often correspond to more active weather systems. This infrared band is one of 12 channels on the Advanced Baseline Imager, the primary instrument on both the GOES East and West satellites. on the GOES the multiple GOES East ABI sensor’s infrared bands, and is updated every 15 minutes in real time. Infrared satellite imagery can be "colorized" or "color-enhanced" to bring out details in cloud patterns. These color enhancements are useful to meteorologists because they signify “brightness temperatures,” which are approximately the temperature of the radiating body, whether it be a cloud or the Earth’s surface. In this imagery, yellow and orange areas signify taller/colder clouds, which often correlate with more active weather systems. Blue areas are usually “clear sky,” while pale white areas typically indicate low-level clouds. During a hurricane, cloud top temperatures will be higher (and colder), and therefore appear dark red. This imagery is derived from band #13 on the GOES East and GOES West Advanced Baseline Imager.How does infrared satellite imagery work?The infrared (IR) band detects radiation that is emitted by the Earth’s surface, atmosphere and clouds, in the “infrared window” portion of the spectrum. The radiation has a wavelength near 10.3 micrometers, and the term “window” means that it passes through the atmosphere with relatively little absorption by gases such as water vapor. It is useful for estimating the emitting temperature of the Earth’s surface and cloud tops. A major advantage of the IR band is that it can sense energy at night, so this imagery is available 24 hours a day.What do the colors on the infrared map represent?In this imagery, yellow and orange areas signify taller/colder clouds, which often correlate with more active weather systems. Blue areas are clear sky, while pale white areas indicate low-level clouds, or potentially frozen surfaces. Learn more about this weather imagery.What does the GOES water vapor map layer show?The GOES ‘water vapor’ map displays the concentration and location of clouds and water vapor in the atmosphere and shows data from both the GOES East and GOES West satellites. Imagery is updated approximately every 15 minutes in real time. Water vapor imagery, which is useful for determining locations of moisture and atmospheric circulations, is created using a wavelength of energy sensitive to the content of water vapor in the atmosphere. In this imagery, green-blue and white areas indicate the presence of high water vapor or moisture content, whereas dark orange and brown areas indicate little or no moisture present. This imagery is derived from band #10 on the GOES East and GOES West Advanced Baseline Imager.What do the colors on the water vapor map represent?In this imagery, green-blue and white areas indicate the presence of high water vapor or moisture content, whereas dark orange and brown areas indicate less moisture present. Learn more about this water vapor imagery.About the satellitesWhat are the GOES satellites?NOAA’s most sophisticated Geostationary Operational Environmental Satellites (GOES), known as the GOES-R Series, provide advanced imagery and atmospheric measurements of Earth’s Western Hemisphere, real-time mapping of lightning activity, and improved monitoring of solar activity and space weather.The first satellite in the series, GOES-R, now known as GOES-16, was launched in 2016 and is currently operational as NOAA’s GOES East satellite. In 2018, NOAA launched another satellite in the series, GOES-T, which joined GOES-16 in orbit as GOES-18. GOES-17 became operational as GOES West in January 2023.Together, GOES East and GOES West provide coverage of the Western Hemisphere and most of the Pacific Ocean, from the west coast of Africa all the way to New Zealand. Each satellite orbits the Earth from about 22,200 miles away.
This nowCOAST time-enabled map service provides map depicting the latest surface weather and marine weather observations at observing sites using the international station model. The station model is method for representing information collected at an observing station using symbols and numbers. The station model depicts current weather conditions, cloud cover, wind speed, wind direction, visibility, air temperature, dew point temperature, sea surface water temperature, significant wave height, air pressure adjusted to mean sea level, and the change in air pressure over the last 3 hours. The circle in the model is centered over the latitude and longitude coordinates of the station. The total cloud cover is expressed as a fraction of cloud covering the sky and is indicated by the amount of circle filled in. (Cloud cover is not presently displayed due to a problem with the source data. Present weather information is also not available for display at this time.) Wind speed and direction are represented by a wind barb whose line extends from the cover cloud circle towards the direction from which the wind is blowing. The short lines or flags coming off the end of the long line are called barbs. The barb indicates the wind speed in knots. Each normal barb represents 10 knots, while short barbs indicate 5 knots. A flag represents 50 knots. If there is no wind barb depicted, an outer circle around the cloud cover symbol indicates calm winds. The map of observations are updated in the nowCOAST map service approximately every 10 minutes. However, since the reporting frequency varies by network or station, the observation at a particular station may have not updated and may not update until after the next hour. For more detailed information about the update schedule, please see: http://new.nowcoast.noaa.gov/help/#section=updateschedule
Background InformationThe maps of near-real-time surface weather and ocean observations are based on non-restricted data obtained from the NWS Family of Services courtesy of NESDIS/OPSD and also the NWS Meteorological Assimilation Data Ingest System (MADIS). The data includes observations from terrestrial and maritime observing from the U.S.A. and other countries. For terrestrial networks, the platforms including but not limited to ASOS, AWOS, RAWS, non-automated stations, U.S. Climate Reference Networks, many U.S. Geological Survey Stations via NWS HADS, several state DOT Road Weather Information Systems, and U.S. Historical Climatology Network-Modernization. For over maritime areas, the platforms include NOS/CO-OPS National Water Level Observation Network (NWLON), NOS/CO-OPS Physical Oceanographic Observing Network (PORTS), NWS/NDBC Fixed Buoys, NDBC Coastal-Marine Automated Network (C-MAN), drifting buoys, ferries, Regional Ocean Observing System (ROOS) coastal stations and buoys, and ships participating in the Voluntary Ship Observing (VOS) Program. Observations from MADIS are updated approximately every 10 minutes in the map service and those from NESDIS are updated every hour. However, not all stations report that frequently. Many stations only report once per hour sometime between 15 minutes before the hour and 30 minutes past the hour. For these stations, new observations will not appear until 22 minutes past top of the hour for land-based stations and 32 minutes past the top of the hour for maritime stations.
Time InformationThis map is time-enabled, meaning that each individual layer contains time-varying data and can be utilized by clients capable of making map requests that include a time component.
This particular service can be queried with or without the use of a time component. If the time parameter is specified in a request, the data or imagery most relevant to the provided time value, if any, will be returned. If the time parameter is not specified in a request, the latest data or imagery valid for the present system time will be returned to the client. If the time parameter is not specified and no data or imagery is available for the present time, no data will be returned.
In addition to ArcGIS Server REST access, time-enabled OGC WMS 1.3.0 access is also provided by this service.
Due to software limitations, the time extent of the service and map layers displayed below does not provide the most up-to-date start and end times of available data. Instead, users have three options for determining the latest time information about the service:
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This upload contains the same data as published in our previous zenodo dataset upload. Unlike our previous upload, this version contains data after transferring the DICOMs directly from the Siemens Skyra 3T to our Linux machine (as done in real-time experiments). The purpose of this separate upload is to serve as sample data for our real-time cloud software, for a specific sample project. The brain data are contributed by author S.A.N. and are authorized for non-anonymized distribution.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
These products are a subset of the ECMWF real-time forecast data and are made available to the public free of charge. They are based on the medium-range (high-resolution and ensemble) and seasonal forecast models. Products are available at 0.4 degrees resolution in GRIB2 format unless stated otherwise.
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The global cloud-based mapping service market size was valued at approximately USD 3.5 billion in 2023 and is projected to reach around USD 8.9 billion by 2032, exhibiting a compound annual growth rate (CAGR) of 11.2% during the forecast period. This remarkable growth is primarily driven by the increasing demand for real-time data access and navigation services across various sectors. Businesses and governments worldwide are increasingly leveraging cloud-based mapping services to optimize operations, improve customer experience, and enhance decision-making processes. The seamless integration of advanced technologies such as Artificial Intelligence (AI) and Internet of Things (IoT) in mapping services is further boosting this market's expansion.
The integration of AI with cloud-based mapping services is one of the key growth factors for this market. AI technologies enhance the capabilities of cloud-based mapping services by providing intelligent insights and predictive analytics. For instance, AI can analyze traffic patterns and predict congestion, offering alternative routes and optimal travel paths. This is particularly beneficial for the transportation and logistics sectors, where time is of the essence. Furthermore, AI-driven mapping services can assist businesses in understanding consumer behavior and preferences, allowing for targeted marketing strategies and improved customer engagement. The ability of AI to process massive datasets quickly and accurately makes it a valuable tool in the cloud-based mapping service industry.
Another significant factor contributing to market growth is the rising adoption of IoT devices. IoT devices generate a vast amount of location-based data that can be effectively managed and utilized through cloud-based mapping services. These services enable businesses to track and monitor assets, vehicles, and personnel in real-time, leading to improved operational efficiency and reduced costs. For example, in the logistics sector, companies can use cloud-based mapping services to optimize delivery routes and monitor vehicle conditions, thereby minimizing fuel consumption and enhancing customer satisfaction. The continuous evolution and proliferation of IoT devices are expected to drive further demand for cloud-based mapping services in the coming years.
The increasing reliance on mobile devices and the proliferation of high-speed internet connectivity are also significant growth drivers for the cloud-based mapping service market. With the widespread use of smartphones and tablets, consumers and businesses alike are accessing mapping services on-the-go, necessitating reliable cloud-based solutions. The availability of high-speed internet ensures seamless connectivity and real-time updates, enhancing user experience. This trend is particularly prominent in urban areas, where demand for navigation and location-based services is high. As mobile technology continues to evolve and internet infrastructure improves worldwide, the cloud-based mapping service market is poised for substantial growth.
The rise of URL Shortening Services has become increasingly relevant in the context of cloud-based mapping services. These services allow users to condense lengthy URLs into shorter, more manageable links, which is particularly useful for sharing location-based information. In industries such as logistics and transportation, where quick access to precise location data is crucial, URL shortening can streamline communication and improve efficiency. By integrating URL shortening with mapping services, businesses can enhance their digital marketing strategies and facilitate easier sharing of maps and navigation routes. This integration not only improves user experience but also supports the growing demand for seamless digital interactions in the mapping service market.
The cloud-based mapping service market is segmented into several service types, each offering unique features and benefits to users. Mapping and navigation services are perhaps the most widely recognized and utilized among these. They provide users with detailed maps, directions, and navigation assistance, which are crucial for both consumers and businesses. These services cater to a wide array of applications, from personal navigation to complex logistics operations. As the demand for precise, real-time navigation grows, mapping and navigation services continue to be at the forefront of the cloud-based mapping industry. Their integrat
This nowCOAST time-enabled map service provides map depicting the latest surface weather and marine weather observations at observing sites using the international station model. The station model is method for representing information collected at an observing station using symbols and numbers. The station model depicts current weather conditions, cloud cover, wind speed, wind direction, visibility, air temperature, dew point temperature, sea surface water temperature, significant wave height, air pressure adjusted to mean sea level, and the change in air pressure over the last 3 hours. The circle in the model is centered over the latitude and longitude coordinates of the station. The total cloud cover is expressed as a fraction of cloud covering the sky and is indicated by the amount of circle filled in. (Cloud cover is not presently displayed due to a problem with the source data. Present weather information is also not available for display at this time.) Wind speed and direction are represented by a wind barb whose line extends from the cover cloud circle towards the direction from which the wind is blowing. The short lines or flags coming off the end of the long line are called barbs. The barb indicates the wind speed in knots. Each normal barb represents 10 knots, while short barbs indicate 5 knots. A flag represents 50 knots. If there is no wind barb depicted, an outer circle around the cloud cover symbol indicates calm winds. The map of observations are updated in the nowCOAST map service approximately every 10 minutes. However, since the reporting frequency varies by network or station, the observation at a particular station may have not updated and may not update until after the next hour. For more detailed information about the update schedule, please see: http://new.nowcoast.noaa.gov/help/#section=updateschedule
Background InformationThe maps of near-real-time surface weather and ocean observations are based on non-restricted data obtained from the NWS Family of Services courtesy of NESDIS/OPSD and also the NWS Meteorological Assimilation Data Ingest System (MADIS). The data includes observations from terrestrial and maritime observing from the U.S.A. and other countries. For terrestrial networks, the platforms including but not limited to ASOS, AWOS, RAWS, non-automated stations, U.S. Climate Reference Networks, many U.S. Geological Survey Stations via NWS HADS, several state DOT Road Weather Information Systems, and U.S. Historical Climatology Network-Modernization. For over maritime areas, the platforms include NOS/CO-OPS National Water Level Observation Network (NWLON), NOS/CO-OPS Physical Oceanographic Observing Network (PORTS), NWS/NDBC Fixed Buoys, NDBC Coastal-Marine Automated Network (C-MAN), drifting buoys, ferries, Regional Ocean Observing System (ROOS) coastal stations and buoys, and ships participating in the Voluntary Ship Observing (VOS) Program. Observations from MADIS are updated approximately every 10 minutes in the map service and those from NESDIS are updated every hour. However, not all stations report that frequently. Many stations only report once per hour sometime between 15 minutes before the hour and 30 minutes past the hour. For these stations, new observations will not appear until 22 minutes past top of the hour for land-based stations and 32 minutes past the top of the hour for maritime stations.
Time InformationThis map is time-enabled, meaning that each individual layer contains time-varying data and can be utilized by clients capable of making map requests that include a time component.
This particular service can be queried with or without the use of a time component. If the time parameter is specified in a request, the data or imagery most relevant to the provided time value, if any, will be returned. If the time parameter is not specified in a request, the latest data or imagery valid for the present system time will be returned to the client. If the time parameter is not specified and no data or imagery is available for the present time, no data will be returned.
In addition to ArcGIS Server REST access, time-enabled OGC WMS 1.3.0 access is also provided by this service.
Due to software limitations, the time extent of the service and map layers displayed below does not provide the most up-to-date start and end times of available data. Instead, users have three options for determining the latest time information about the service:
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This upload contains the same data as published in our previous zenodo dataset upload. Unlike our previous upload, this version contains data after transferring the DICOMs directly from the Siemens Skyra 3T to our Linux machine (as done in real-time experiments). The purpose of this separate upload is to serve as sample data for our real-time cloud software, for the rtAttenPenn project. A previous version of this same data was uploaded for a different rt-cloud sample project (zenodo link here). For the current sample project, we are additionally including a T1w anatomical scan for real-time registration. All brain data are contributed by author S.A.N. and are authorized for non-anonymized distribution.
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According to our latest research, the Industry Cloud Platform market size reached USD 17.8 billion in 2024, driven by increasing demand for vertical-specific cloud solutions across global enterprises. The market is experiencing robust expansion, registering a CAGR of 23.5% from 2025 to 2033. By 2033, the global Industry Cloud Platform market is projected to attain a value of USD 130.9 billion, reflecting the sector’s rapid adoption and integration across industries. This remarkable growth is underpinned by the surge in digital transformation initiatives, the need for scalable IT infrastructure, and the proliferation of industry-tailored cloud ecosystems. As per our latest research, these factors collectively position industry cloud platforms as a pivotal enabler of operational efficiency and innovation for organizations worldwide.
A primary growth factor for the Industry Cloud Platform market is the increasing emphasis on vertical-specific cloud solutions that address unique regulatory, operational, and security requirements. Unlike generic cloud services, industry cloud platforms are engineered to deliver specialized capabilities, data models, and compliance protocols tailored for sectors such as healthcare, BFSI, manufacturing, and retail. This verticalization enables organizations to accelerate digital transformation initiatives, streamline workflows, and enhance agility. The healthcare sector, for instance, benefits from industry cloud platforms by ensuring HIPAA compliance, secure patient data management, and seamless integration with electronic health records. Similarly, financial institutions leverage these platforms to meet stringent regulatory standards, drive innovation in digital banking, and optimize risk management. The ability of industry cloud platforms to provide sector-specific value propositions is a key driver fueling their widespread adoption and market expansion.
Another significant growth catalyst is the escalating demand for scalable and flexible IT infrastructure to support evolving business models, particularly in the wake of the COVID-19 pandemic. Organizations across all industry verticals are increasingly migrating mission-critical applications and workloads to the cloud to achieve operational resilience, cost optimization, and business continuity. Industry cloud platforms, with their robust architectures and customizable solutions, empower enterprises to rapidly deploy new services, scale resources on demand, and respond to market changes with agility. This shift towards cloud-native operations is further amplified by the rise of hybrid and multi-cloud strategies, which enable organizations to balance performance, security, and compliance while minimizing vendor lock-in. The growing adoption of these deployment models is expected to sustain the momentum of the Industry Cloud Platform market over the forecast period.
The proliferation of advanced technologies such as artificial intelligence, machine learning, Internet of Things (IoT), and blockchain is also contributing to the growth of the Industry Cloud Platform market. These technologies are increasingly being embedded into industry cloud solutions to deliver intelligent automation, predictive analytics, and real-time insights tailored to specific business processes. For example, manufacturing companies are leveraging AI-powered industry cloud platforms to optimize supply chain operations, improve quality control, and enable predictive maintenance. Retailers are utilizing cloud-based analytics to enhance customer experience, personalize offerings, and streamline inventory management. As organizations continue to embrace digital innovation, the integration of emerging technologies within industry cloud platforms is expected to unlock new opportunities, drive competitive differentiation, and accelerate market growth.
From a regional perspective, North America currently dominates the Industry Cloud Platform market, accounting for the largest revenue share in 2024. This leadership is attributed to the presence of major cloud service providers, early adoption of digital technologies, and strong investments in cloud infrastructure across key industry verticals. However, Asia Pacific is emerging as the fastest-growing region, driven by rapid industrialization, government-led digitalization initiatives, and the burgeoning demand for cloud solutions among SMEs. Europe also demonstrates significant growth potential, particularly in sectors such as manufacturing, healthcare, and BFSI, where regulatory complianc
According to our latest research, the global Deployable Edge Cloud market size reached USD 5.3 billion in 2024, reflecting robust momentum driven by digital transformation across industries. The market is forecasted to reach USD 29.7 billion by 2033, expanding at an impressive CAGR of 21.1% during the forecast period. This exceptional growth is primarily fueled by the increasing adoption of edge computing for real-time data processing, the proliferation of IoT devices, and the critical need for low-latency applications in sectors such as manufacturing, healthcare, and smart cities. As per our latest research, these factors are collectively reshaping the landscape of cloud computing, propelling the rapid expansion of the Deployable Edge Cloud market worldwide.
The primary growth driver for the Deployable Edge Cloud market is the exponential rise in connected devices and the corresponding surge in data generation at the network’s edge. Enterprises across industries are leveraging edge cloud solutions to process data closer to the source, thereby reducing latency, enhancing security, and improving overall operational efficiency. The proliferation of IoT sensors in manufacturing, smart city infrastructure, and autonomous vehicles is creating a pressing demand for scalable, real-time data analytics, which only edge cloud architectures can deliver effectively. Furthermore, the need for uninterrupted service delivery and compliance with stringent data sovereignty regulations is compelling organizations to adopt deployable edge cloud platforms, which offer localized computing power and storage, thereby addressing both performance and regulatory requirements.
Another significant growth factor is the rapid digitalization of critical sectors, including healthcare, transportation, and energy. In healthcare, for example, the deployment of edge cloud solutions enables real-time patient monitoring, supports telemedicine, and facilitates the secure and efficient handling of sensitive medical data. Similarly, in transportation and logistics, edge cloud platforms are essential for enabling autonomous vehicles, intelligent traffic management, and real-time supply chain optimization. The energy and utilities sector is also witnessing increased adoption of deployable edge cloud solutions to support smart grid operations, predictive maintenance, and decentralized energy management. These sector-specific applications are not only accelerating market growth but also fostering innovation and the development of tailored edge cloud offerings.
The evolution of 5G networks is another crucial factor bolstering the Deployable Edge Cloud market. The ultra-low latency and high bandwidth capabilities of 5G are unlocking new possibilities for edge computing, particularly in applications that require instantaneous data processing, such as augmented reality, virtual reality, and industrial automation. Telecom operators are actively investing in edge cloud infrastructure to monetize 5G services, enabling new business models and revenue streams. The convergence of edge cloud with emerging technologies like artificial intelligence and machine learning is further amplifying its value proposition, as organizations seek to deploy intelligent applications at the edge for enhanced decision-making and automation.
From a regional perspective, North America currently leads the Deployable Edge Cloud market, underpinned by significant investments in digital infrastructure, a mature cloud ecosystem, and early adoption of advanced technologies across multiple industries. The Asia Pacific region is expected to register the fastest growth over the forecast period, driven by rapid urbanization, expanding IoT deployments, and government initiatives promoting smart city projects. Europe is also witnessing substantial growth, fueled by stringent data privacy regulations and increasing demand for localized data processing solutions. The Middle East & Africa and Latin America are emerging as promising markets, supported by ongoing digital transformation initiatives and investments in next-generation connectivity solutions.
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Cloud Infrastructure Services Market Size 2024-2028
The cloud infrastructure services market size is forecast to increase by USD 109.2 billion at a CAGR of 9.4% between 2023 and 2028. The market is experiencing significant growth, driven by the shift from capital expenditure (CAPEX) to operational expenditure (OPEX) models. This trend allows businesses to reduce upfront costs and invest in other areas of their operations. Another key trend is the increasing adoption of hybrid cloud storage systems, which offer the benefits of both public and private clouds. However, challenges remain, including latency in cloud networks, security concerns, and the need for seamless integration between different cloud platforms. To address these challenges, cloud infrastructure service providers are investing in advanced technologies such as artificial intelligence and machine learning to improve network performance and enhance security features. Overall, the market is expected to continue growing as more businesses adopt cloud solutions to optimize their IT infrastructure and improve operational efficiency.
What will be the Size of the Market During the Forecast Period?
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Cloud infrastructure services refer to the hardware and software components required to build, deploy, and manage cloud architectures, including private cloud, public cloud, and hybrid clouds. These services encompass computing resources such as servers and storage devices, as well as networking and management software. Cloud architecture relies on virtualization technologies like hypervisors and virtual machine monitors to create and manage virtual servers and machines. Cloud services offer flexibility and scalability, enabling businesses to quickly deploy and manage resources as needed.
Moreover, cloud computing resources can be scaled up or down based on demand, while storage can be easily expanded or contracted. Networking is crucial for cloud infrastructure, ensuring seamless communication between servers, virtual machines, and users. Security is a top priority in cloud infrastructure, with intelligent monitoring and management software providing real-time threat detection and response. Deployment software streamlines the process of launching and managing applications in the cloud, while cloud management software provides a centralized interface for managing and monitoring cloud resources. Overall, cloud infrastructure services enable businesses to build and deploy applications and services more efficiently and cost-effectively than traditional on-premises solutions.
Market Segmentation
The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.
Deployment
Public cloud
Private cloud
Hybrid cloud
Geography
North America
US
APAC
China
Japan
Europe
Germany
UK
South America
Middle East and Africa
By Deployment Insights
The public cloud segment is estimated to witness significant growth during the forecast period. In the dynamic business landscape of 2023, the public cloud segment holds a significant share of The market. This dominance can be attributed to the expanding IT, BFSI, education, healthcare, and retail sectors, which require cloud infrastructure for valuable business insights. The increasing number of Small and Medium Enterprises (SMEs) in emerging economies, such as China, India, Brazil, Indonesia, and Mexico, is driving the demand for public cloud services. These organizations seek cost-effective solutions for their business needs. Cloud infrastructure service providers offer virtualization technology, enabling organizations to deploy software applications on a shared backend infrastructure, ensuring flexibility and scalability. Public cloud computing and storage devices are accessible via the internet, making it a preferred choice for businesses seeking to reduce capital expenditures and focus on their core competencies.
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The public cloud segment was valued at USD 99.90 billion in 2018 and showed a gradual increase during the forecast period.
Regional Insights
North America is estimated to contribute 34% to the growth of the global market during the forecast period. Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.
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In the global market for cloud infrastructure services, North America held the largest market share in 2023. The region's dominance can be attributed to the rising demand for computing services, leading to an expansion of data centers and storage spaces. Cloud infra