Category Archives: Cloud Computing
Global Healthcare Cloud Computing Market Expected to Grow at a CAGR of 25.1& Over the Forecast Period, 2018-2023 – ResearchAndMarkets.com – Yahoo…
The "Global Healthcare Cloud Computing Market, Forecast to 2023" report has been added to ResearchAndMarkets.com's offering.
Global healthcare cloud market revenue is expected to surge at a compound annual growth rate of 25.1% from 2018 to 2023.
Cloud computing in healthcare is gaining momentum as a variety of factors create a significant need for the value propositions that a successful cloud implementation promises to offer.
Cloud computing involves the use of external suppliers of infrastructure, platforms, and software. As a result, former capital expenses or owned software systems are transitioned to a service offered by a cloud provider or participants within a cloud service provider's ecosystem. This study focuses on cloud services that are used by providers and other healthcare stakeholders seeking to manage clinical and business workflows and reduce certain costs associated with the data-rich global healthcare environment.
This study reviews the significant drivers that are propelling cloud computing in healthcare. For example, the data flow resulting from digital health systems will transform healthcare into a Big Data environment. This trend will include data from telehealth and increasingly from consumer-generated remote monitoring systems. There is a consistent view across the industry that healthcare providers are eager to take advantage of the cloud, but this is offset by the reality that careful planning and diligence must be performed in order to ensure that the configuration of the selected cloud implementation is the correct path forward. Also challenging is the fact that providers are finding it difficult to staff the IT cloud management experts needed to ensure a smooth transition from in-house systems. The transition to usage-based cloud services must be well planned to avoid the potential for higher-than-anticipated costs. For example, the migration of data from internal data centers to cloud services can be complicated, depending on the systems involved. There is also the ever-present need to maintain data security and patient privacy.
Cloud computing offers a compelling financial proposition for healthcare providers. By utilizing the infrastructure of a cloud service provider, healthcare providers should be able to achieve increased scalability and reduce their IT costs. In addition, the use of software-as-a-service will relieve medical staff from time-intensive management of various software-related maintenance and update functions.
The study also reviews the potential for the healthcare cloud to accelerate the deployment of emerging technologies such as artificial intelligence, blockchain, and advanced data analytics.
The evolving healthcare cloud will increase the potential for data system interoperability across the healthcare industry. Perhaps the most exciting aspect of the cloud will be the growth of a new generation of ecosystems that will revolutionize the way that clinical and operational data can be used to support improved patient outcomes and customer relationship management. Although a great deal of media attention is devoted to tracking familiar cloud market leaders such as Amazon AWS, Microsoft Azure, and Google Cloud, this report will identify and summarize the activities of key participants of the emerging healthcare cloud ecosystem. This dynamic ecosystem will be the catalyst of new growth opportunities for specialized service suppliers across the global healthcare industry.
Key Issues Addressed
Key Topics Covered:
1. Executive Summary
2. Analysis of the Growth Environment
3. Visioning Scenarios
4. The Cloud-based Healthcare Ecosystem
5. Growth Pipeline
6. Competitive Landscape
7. Notable Healthcare Cloud Companies
8. Leading Cloud Solution Suppliers
9. Specialized Healthcare Cloud Services
10. System Integrators Participating in the Healthcare Cloud
11. Regional Outlook
Companies Mentioned
For more information about this report visit https://www.researchandmarkets.com/r/16h2fp
View source version on businesswire.com: https://www.businesswire.com/news/home/20200225005496/en/
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Architecting a Cloud-to-Edge Computing Strategy As data-hungry devices and apps clamor for speed – IoT World Today
As data-hungry devices and apps clamor for speed and bandwidth, public clouds alone bring too much latency. Enter cloud-to-edge architectures.
After a decade dominated by the growing reliance on centralized third-party public cloud services, the deployment of edge computing systems and Internet of Things (IoT) devices represents a partial pendulum swing back to decentralized data management. Large cloud service providers, however, are eager to extend services from the cloud to the edge. As a result, organizations face decisions on how tightly to tie evolving architecture to a single service provider.
Cloud computing services such as Amazon Web Services (AWS) and Microsoft Azure allowed large corporations to ease dependence on large, costly private data centers. They also enabled emerging companies to rapidly scale up to compete with larger competitors even if they lacked the time or financial resources to build their own computing infrastructure.
But as organizations seek to capitalize on a growing torrent of data from edge devices and servers, they cant afford to be constrained by the latency and bandwidth limitations inherent in transmitting data up to a cloud service. In critical situations, operational control requires real-time monitoring and analytics capabilities.
Now people realize that data should be close to where its absorbed from or consumed, said David Linthicum, chief cloud strategy officer at Deloitte, the consulting and advisory services firm. If youre flying an airplane, you dont want to send data down to a cloud server to see if the engines are on fire.
Still, cloud resources are essential, for cost-effectively analyzing large data volumes over time that can feed models for implementation on devices operating at the edgewhether in a plane, controlling autonomous vehicles, re-calibrating factory machines, or deployed throughout a so-called smart city.
The problem everybody is trying to solve is how to balance data between edge-based devices and cloud systems, Linthicum said.
New York-based Oden Technologies developed an industrial automation and analytics platform that used a cloud-to-edge architecture to provide manufacturers with an AI-powered production recommendation system to optimize production and hit peak factory performance. An edge gateway server connects to the companys Oden Cloud to enable complex data processing and real-time machine learning in edge applications.
Our Golden Run platform uses a machine learning model that is periodically updated. Whenever there is enough new data, we run it to see if there might be a new optimization to implement, said Oden co-founder and CEO Willem Sunblad. We might do that a week at a time so it doesnt have to run at the edge, but predictive quality should run in real time and for that you want latency to be low and dont want the dependency of the internet.
How to Navigate Cloud-to-Edge Models?
The Linux Foundation-supported State of the Edge 2020 report noted that infrastructure to support edge computing is nascent and enterprises may have to implement their own until the technology matures. Until there are public edge clouds and ubiquitous high-speed networks (e.g., 5G connectivity), custom edge installations may be the only way to reliably implement an edge application, the report asserted. However, as the demand for edge applications grow[s], the cloud will drift to the edge. Edge computing will become part of the standard internet topology.
Cloud the next destination of geospatial – Geospatial World
Image Courtesy: Forbes
Think of a time, when you have used a map to find a caf for your family dinner. Or perhaps, you used it to look for a newly opened fashion store in your neighborhood. Working with location technology day in and out, I am fascinated by the journey of maps- from paper to a tap on the phone. I have never been more energized by the growth of these location technologies having an impact on our daily lives, the way we work and interact. The beauty of maps, however, is that they can be used in a variety of forms, beyond just navigating roads and finding landmark buildings. Location mapping and technologies, as companies are now finding out, is helping businesses small and large across the world, to combine geography with business intelligence, thus enabling them to make faster and efficient business decisions.
One of the most important examples of how businesses are benefitting from spatial technologies and platforms can be found in the transport and logistics sector. While battling with challenges around high infrastructure maintenance costs, energy consumption, environmental challenges, safety regulations, etc., companies continue to navigate through a complex network of multiple carriers, service providers, physical locations and unexpected inefficiencies in the supply chain and high costs.
By deploying location data and analytics, businesses are now devising innovative solutions and, in some cases, creating new business opportunities. For example, in 2016, the automobile giant, Mahindra and Mahindra launched an agricultural rental equipment service. Using its app called Trinngo, farmers can now rent tractors and equipment on a pay-per-use basis. These orders are then passed on to the nearest franchisee using location-based mapping.
Alternatively, retail companies are using data from location check-ins and customer detecting in-store Wi-Fi antennas that can detect nearby smartphones and triangulate their location, to create geo-behavioral consumer profiles that help them devise personalized and targeted marketing communications. For instance, OLX India used hyper-location targeting to reach second hand mobile and automobile markets using pin-codes. Competitive-minded businesses have been leveraging, location analytics, in the context of big data and micro-level data models, to identify new markets and make other decisions such as where to open a new store.
Despite the tremendous advances made by location mapping and technology industry, there are significant challenges to its widespread adoption and its potential, thus remains untapped. This can be traced back to reasons such as lack of awareness around geospatial and predictive analytics, data privacy concerns, capital intensive network and data storage infrastructure and lack of proper data collection methodologies.
In addition to the scale and cost challenges, new and emerging technologies pose another challenge to businesses today. Being an early adopter of these technologies has lots of advantages but often necessitates careful planning, forcing companies to consider how they operate and conduct business. Fortunately, the emergence of cloud computing aims to provide a potential solution for all these challenges. Cloud computing on its own has become an integral part for many companies today, helping them with greater convenience, lower costs and enhanced efficiencies. Having grown as a disruptive technology itself, today cloud computing serves as an equalizer for the accessibility and affordability of big data and other innovative solutions, including geospatial technologies.
Let us look at the benefits of integrating these two technologies together and how location as a service could be a key ingredient for any business strategy:
As is in the most cases around emerging technologies, regulatory and security concerns around data privacy in cloud remain. Businesses are worried about data leaks, vulnerability attacks and lack of control around off-premise infrastructure. However, the benefits of convergence of cloud computing with spatial sciences are likely to exceed and rather offers compelling ready- to- use, affordable and scalable alternative to companies, especially the small and medium enterprises, who unlike their larger counterparts lack the money and human resource muscle. To put things in perspective, users can increasingly leverage a cost-effective, flexible, on-demand computing platform to integrate- observation systems, clustering, analytical visualizations, statistical trend analysis, parameter extracting algorithms, simulation models, map-based storytelling, etc., all essential components for geospatial technologies.
At the most basic level, convergence of these two technologies means the ability to store and process higher volumes of data at an unprecedented scale. However, location as a service can deliver actionable location insights that are real-time and that can be cross leveraged across a spectrum of web and mobile applications. Cloud based location solutions can enable anyone with an internet connectivity and a Web browser using any device such as desktop, a laptop, a tablet or a smartphone to access maps including high definition imagery, topography, street based maps and functionalities like geo-coding on the cloud on the move, thus reducing on premise spends on developing and maintaining an IT infrastructure.
Last, but not the least, it can also make data sharing and collaboration between multiple parties easier, faster and secure. Businesses can take advantage of crowd sourcing as individuals turn both into consumer of the geospatial services as well as data sensors.
Our location intelligence platform, called the- HERE Platform, allows businesses to enrich their data through an advanced development workspace that offers standardized developer tools, analytics, scaled out processing and data management. Customers and partners can also monetize and license their maps with third-party data to create new, innovative offerings in a neutral, secure and open marketplace. The platform also makes it easier to analyze and archive the data, process events, visualize information and create dynamic datasets on the factors that include their businesses- whether it is determining business locations for retail stores, determining least cost path navigation for fleet management or creating new insurance incentives on road by profiling driver habits. With an equal emphasis on security, the HERE Platform complies with all applicable privacy and security regulations across geographies.
As we continue our journey in a digital world, connected with new and autonomous technologies, businesses will have to focus on building capabilities that help them stay ahead of the competition and remain profitable. Thus, at the convergence of cloud computing and spatial intelligence, lies the next big opportunity to make location intelligence accessible and strategic business advantages.
Note: This is a guest blog by Damandeep Kochhar, Global VP and MD India, HERE Technologies
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Cloud the next destination of geospatial - Geospatial World
FERC Opens Inquiry into Virtualization and Cloud Computing Services – Lexology
On February 20, 2020, FERC issued a notice of inquiry (NOI) to learn more about the potential benefits and risks of virtualization and cloud computing services in the bulk electric system operations. The NOI also seeks information about the barriers that exist in FERC-approved Critical Infrastructure Protection (CIP) Reliability Standards that impede the voluntary adoption of virtualization or cloud computing services.
As explained in the NOI, virtualization is the process of creating virtual versions of computer hardware to minimize the amount of physical computer hardware resources needed to perform various functions. Cloud computing is defined as a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources.
FERC issued the NOI in response to comments made during FERCs June 27, 2019 Reliability Technical Conference and the Department of Energys and FERCs March 28, 2019 Security Investments for Energy Infrastructure Technical Conference.
Specifically, FERC seeks comments on four general topics, each of which are accompanied by various question prompts in the NOI: (A) scope of potential use of virtualization and cloud computing services (e.g. which BES reliability operating services referenced above could be implemented in a virtualized environment?); (B) potential benefits and risks associated with virtualization and cloud computing services (e.g. what are the potential benefits associated with adopting virtualization for the BES reliability operating services?); (C) potential impediments to adopting virtualization and cloud computing services (e.g. how the CIP Reliability Standards could be augmented to address these challenges?); and (D) potential use of new and emerging technologies in the current CIP standards framework (e.g. whether the CIP Reliability Standards limit the ability to take full advantage of new and emerging technologies for BES reliability operating services.).
FERC intends to use the record in this proceeding to determine if it should, pursuant to section 215(d)(5) of the Federal Power Act, direct NERC to develop modifications to the CIP Reliability Standards for the voluntary adoption of virtualization and cloud computing services by registered entities.
Initial comments are due 60 days after the date of publication in the Federal Register. Reply comments are due 90 days after publication in the Federal Register.
Click here to read the full NOI and the procedures for commenting.
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FERC Opens Inquiry into Virtualization and Cloud Computing Services - Lexology
Fog and edge computing: revolutionary new technologies operating at the edge of the law – Business MattersBusiness Matters
But cloud computing is not without its risks. What if hackers attack your cloud provider or its service is unavailable? As a data controller, you will be primarily liable under data protection law.
Cloud providers may also operate business models based on standard non-negotiable terms which can pass the risk onto the user. Ensuring compliance with data protection law (GDPR) can be a headache when appointing a cloud provider.
Also, its worth considering how easy it will be to get your data back or port it elsewhere if required,
There is also the risk of losing control of your data unexpectedly; Google has just announced the transfer of UK user data to the USA, for example.
Although many cloud providers will offer to localise data for you, this may cost you more than their basic service.
Regulators too have had cloud computing in their sights.
The use of the cloud in the financial services sector in particular has been the subject of regulatory scrutiny.
Financial services companies cant outsource their regulatory responsibilities here they remain firmly on the hook.
Currently, the legal risks of cloud computing are generally well-understood, even if legal advice is required to navigate those risks. However, the future of the cloud, while exciting, presents new threats to businesses.
These risks are due to the growth of the Internet of Things (IoT), which means connected devices at home, in the street or at work.
Smart devices for personal and home use including autonomous vehicles and drones as well as industrial applications such as factory robots are all data intensive. They collect massive amounts of data, which needs processing exceptionally quickly in the case of a robot, a drone or an autonomous vehicle where an individuals life or property might be at stake.
Data-intensive artificial intelligence (AI) is also increasingly used for image recognition as well as the operation of the devices themselves.
All this data requires processing at the edge of a network close to the devices generating the data. Here the classic cloud computing model breaks down.
Its too slow to pass all this data to a centralised cloud server at a large data centre for processing. The device needs the ability to process the data very quickly and minimise latency the time taken for data to travel over a network.
This can be achieved by using edge computing putting processing power at the edge of a network, close to where sensors collect the data. Advances in computing make this possible. Already mini data centres are springing up putting computing power close to where its needed.
Edge computers, when connected over a network, form what is called a fog a network of distributed computing resources which process data very quickly as needed and also connect with the cloud for overall communication and control.
The growth of 5G networks will only encourage this as they allow fast high-capacity local data flows but also require local data processing resource too so more mini data centres.
This interconnected environment is set to expand rapidly but raises a lot of new legal issues. Who owns all the data sensors collect and which is then processed?
If the data is personal data, how is compliance with data protection law ensured? How do users exercise the rights data protection law gives them?
Also, what about the risk of security breaches? The general view is that a distributed network with lots of remote devices connected to it is likely to be inherently less secure than a large data centre or cloud server ring-fenced with security, which are easier to monitor for breaches.
There are ways around this for example encrypting data both when in transit and at rest (when stored on a device) but encryption is power intensive and can also slow things down.
A problem with regulation is that it can quickly become out of date as technology advances. The GDPR was an attempt to reboot data protection law for the age of Facebook and Google. But when it comes to the IoT and AI, the GDPR already risks being left behind.
Complying with the GDPR in this new world requires several steps including:
These steps may become unworkable as 5G and AI take off, and the IoT expands to every facet of our lives at work, when we travel and at home.
We are literally at the edge of an IoT, AI and 5G revolution how the law responds to this challenge and protects both our privacy yet facilitates innovation will be an increasingly pressing topic as the new decade advances.
Cloud Computing Market by Type and Distribution Channel: Global Opportunity Analysis and Industry Forecast 2020-2025 – News Times
The global Cloud Computing market size is expected to gain market growth in the forecast period of 2020 to 2025, with a CAGR of 27.9% in the forecast period of 2020 to 2025 and will expected to reach USD 172960 million by 2025, from USD 64540 million in 2019.
The report also tracks the latest market dynamics, such as driving factors, restraining factors, and industry news like mergers, acquisitions, and investments. It provides market size (value and volume), market share, growth rate by types, applications, and combines both qualitative and quantitative methods to make micro and macro forecasts in different regions or countries.
This Report Provides an overview of Cloud Computing market, containing global revenue, global production, sales, and CAGR. Also describe Cloud Computing product scope, market overview, market opportunities, market driving force and market risks. The forecast and analysis of Cloud Computing market by type, application, and region are also presented. Next part of report provides a full-scale analysis of Cloud Computing competitive situation, sales, revenue and global market share of major players in Cloud Computing industry. The basic information, as well as the profiles, applications and specifications of products market performance along with Business Overview are offered.
Get Complete Overview of the report (Including Full TOC, List of Tables & Figures, Chart):
This section gives a worldwide view of Cloud Computing market. It includes production, market share revenue, price, and the growth rate by type. Next Section of the report focuses on the application of Cloud Computing, by analyzing the consumption and its growth rate of each application. The regional consumption and value analysis by types, applications, and countries are included in the report. Furthermore, it also introduces the major competitive players in these regions.
Major Players involved in the Global Cloud Computing Industry:
Amazon Web Services, SAP, Aliyun, Microsoft Azure, Rackspace, IBM, Vmware, Salesforce, Google Cloud Platform, Oracle, DELL, EMC,
The report can help to understand the market and strategize for business expansion accordingly. In the strategy analysis, it gives insights from marketing channel and market positioning to potential growth strategies, providing in-depth analysis for new entrants or exists competitors in the Biofortification industry.
Global Cloud Computing Market Segmentation by Product:
By TypeCloud Computing market has been segmented into Infrastructure as a service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), etc.
Global Cloud Computing Market Segmentation by Application:
By Application Cloud Computing has been segmented into Government, Small and Medium sized enterprises, Large enterprises, etc.
Top Region Covered In This Research:
South America (Brazil, Argentina)
The Middle East & Africa (South Africa, Saudi Arabia)
Europe (Spain, U.K., Italy, Germany, Russia, France)
North America (U.S., Mexico, Canada)
Asia-Pacific (China, Japan, India, Southeast Asia)
Cloud Computing Introduction and Market Overview
1.3 Cloud Computing Market Scope and Market Size Estimation
Cloud Computing Market Segment Analysis By Type
Global Cloud Computing Market by Type
Global Cloud Computing Production and Market Share by Type (2015-2019)
Global Cloud Computing Revenue and Market Share by Type (2015-2019)
Global Cloud Computing Average Price by Type (2015-2019)
Cloud Computing Market Segment Analysis By Application
Global Cloud Computing Market by Application
Global Cloud Computing Production and Market Share by Application (2015-2019)
Leading Consumers of Cloud Computing by Application in 2018
Cloud Computing Market Segment Analysis by Sales Channel
Global Cloud Computing Market by Sales Channel
Global Cloud Computing Production and Market Share by Sales Channel (2015-2019)
Cloud Computing Market Segment Analysis By Region
North America Cloud Computing Value and Growth Rate (2015-2020)
Europe Cloud Computing Value and Growth Rate (2015-2020)
China Cloud Computing Value and Growth Rate (2015-2020)
Japan Cloud Computing Value and Growth Rate (2015-2020)
Middle East & Africa Cloud Computing Value and Growth Rate (2015-2020)
India Cloud Computing Value and Growth Rate (2015-2020)
South America Cloud Computing Value and Growth Rate (2015-2020)
Market Dynamics
Drivers
Emerging Countries of Cloud Computing
Growing Market of Cloud Computing
Limitations
Opportunities
Cloud Computing Industry Chain Analysis
Major Players of Cloud Computing
Major Players Business Distribution Regions and Market Share of Cloud Computing in 2019
Cloud Computing Business Cost Structure Analysis
Business Cost Structure of Cloud Computing
Major Downstream Customers of Cloud Computing Analysis
Competitive Landscape
Competitive analysis
Global Cloud Computing Market Analysis and Forecast by Type and Application
Global Cloud Computing Market Value Forecast, by Type (2020-2025)
Global Cloud Computing Market Value Forecast, by Application (2020-2025)
Cloud ComputingMarket Analysis and Forecast by Region
North America Market Value Forecast (2020-2025)
Europe Market Value Forecast (2020-2025)
China Market Value Forecast (2020-2025)
Japan Market Value Forecast (2020-2025)
Middle East & Africa Market Value Forecast (2020-2025)
India Market Value Forecast (2020-2025)
South America Market Value Forecast (2020-2025)
Industry Barriers and New Entrants SWOT Analysis
Research Finding and Conclusion
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Cloud Computing Market by Type and Distribution Channel: Global Opportunity Analysis and Industry Forecast 2020-2025 - News Times
Compare serverless tools and services in the public cloud – TechTarget
Infrastructure management and server maintenance can bog down IT teams and pull their focus away from more critical and complex tasks. Serverless computing removes those hurdles by shifting infrastructure management responsibilities to the cloud provider.
Serverless computing -- also referred to as function as a service (FaaS) -- is an event-driven model in which functions are units of code that execute in response to predefined or on-demand triggers. Serverless functions can be used to run code, build mobile and web applications, manage containers and handle other cloud computing tasks.
Public cloud providers offer a range of serverless tools and services that relieve cloud users of infrastructure management tasks. Evaluate the main serverless compute offerings from AWS, Google and Microsoft and decide which tool best fits your needs.
AWS Lambda: Developers can use this event-driven cloud computing service to run functions in the AWS cloud without having to manage or provision resources, such as servers and storage. With AWS Lambda, AWS manages the infrastructure and developers write the code. This service supports Node.js, Python, Java and C#, among other languages.
AWS Lambda executes via Lambda functions, which carry out specific, programmatic tasks in response to events from other Amazon cloud services -- such as Amazon S3, Amazon Simple Notification Service and CloudWatch. Lambda can also be orchestrated into workflows with AWS Step Functions.
Users can update and monitor Lambda functions via the AWS Lambda dashboard, command-line interface or software development kit. AWS Lambda can be used to process data, build web applications and various other capabilities in the AWS cloud. Lambda functions are priced on a pay-per-use basis.
AWS Lambda@Edge:Developers use AWS Lambda@Edge to run Lambda functions at the edge of AWS' global content delivery network. This serverless compute feature runs code geographically closer to end users to reduce latency. With Lambda@Edge, IT teams do not need to manage and provision infrastructure in multiple locations. Amazon CloudFront generates events that trigger Lambda@Edge to run and deliver location-specific code.
AWS Fargate:AWS Fargate is a serverless compute engine for containers in the AWS cloud. This service works with Amazon Elastic Container Service and Amazon Elastic Kubernetes Service. AWS users can build and run Kubernetes applications in AWS without provisioning and managing pods.
With Fargate, developers control the parameters and access policies of their containerized applications while Amazon manages the underlying infrastructure. Fargate automatically scales to run containers in highly available environments. This service can launch thousands of containers simultaneously. Users can opt for Fargate Spot, a discounted version of the service built for interruption-tolerant applications.
Google Cloud Functions:Google Cloud Functions is the platform's serverless, event-driven computing service. Similar to AWS Lambda, Google Cloud Functions abstracts away the underlying infrastructure management and enables developers to focus on writing code and other tasks. With Google Cloud Functions, small programmatic code segments execute functions into a cloud environment in response to specific events.
This service can be trigged by resources within or outside of Google Cloud Platform (GCP). Google Cloud Functions connect with other GCP services along with other third-party services. GCP's serverless compute tool can trigger log analysis and data backups and carry out redundant tasks on data sets, among other tasks. Users pay for the number of functions they use.
Google App Engine:App Engine is a serverless PaaS product from Google where developers can build mobile and web applications. App Engine scales resources of any size with automatic infrastructure management and server maintenance. This tool provides built-in services, such as load balancing, application logging and health checks. The serverless compute platform also offers data storage and configuration capabilities.
App Engine users can access the Google Cloud Security Scanner to detect application security issues. App Engine is available in standard or flexible environments. In the standard App Engine environment, instances run in a sandbox environment and support a specific set of programming languages. The standard environment is suitable for applications that deal with rapid scaling.
The flexible environment for App Engine instances runs in containers on Google Compute Engine virtual machines. The flexible environment option works with applications that receive consistent traffic or experience fluctuations in traffic, and applications that scale gradually. The type of environment has fewer restrictions and supports more source code languages than the standard environment, including Python, Java, Node.js, Go, Ruby, PHP or .NET.
Google Cloud Run:Google Cloud Run is a serverless container management tool that runs stateless containers in managed environments. Google Cloud Run is built on Knative, an open source set of tools for building serverless apps on Kubernetes. It enables workload portability and supports all programming languages and open source libraries.
HTTPS requests trigger Cloud Run services. Cloud Run is used to build portable, container-based mobile and web applications with automatic scalability. This service works with other container management tools and technologies, such as CodeBuild, Container Registry and Docker.
Cloud users can deploy the managed, pay-per-use version of Google Cloud Run, which deploys stateless containers on Google Cloud. Or, users can opt for Cloud Run for Anthos, which runs containers on Google Cloud, on premises or on VMware environments. Cloud Run for Anthos supports custom machine types and provides additional network capabilities.
Azure Functions:Azure Functions is Microsoft's serverless compute service with comparable features to AWS Lambda and Google Cloud Functions. This event-driven serverless compute platform simplifies application development for IT teams by managing the infrastructure. Functions are executed via event triggers from Azure services or third-party sources, such as the Azure Event Hub, HTTPS requests, GitHub and message traffic from services such as Azure Storage.
Azure Functions handles development tasks such as data processing, file maintenance and data collection from IoT devices, among other capabilities. This service also integrates with other Azure offerings, including Azure Cosmos DB, Azure Mobile Apps and Azure Service Bus. Users pay for Azure Functions based on the amount of time a function runs in a billing cycle.
Azure App Service:Azure App Service is another serverless offering from Microsoft. Developers use this service to run mobile, web and Azure API applications in a managed environment. Azure App Service supports .NET, .NET Core, Java, Node.js, Python, PHP and Ruby. Azure App deploys applications in containers or as code and can run on Windows or Linux operating systems.
This serverless compute service provides features such as on-demand code, load balancing and autoscaling, as well as continuous integration and deployment with Azure DevOps, GitHub, BitBucket, Docker Hub or Azure Container Registry. Users can customize their Azure App Service model by choosing from one of several pricing plans that range from Free to Premium.
Azure Kubernetes Service:Microsoft Azure offers serverless container management with Azure Kubernetes Service (AKS). This serverless tool provides Kubernetes-orchestrated clusters that automatically scale depending on traffic spikes.
With AKS, Microsoft handles overhead management, configuration and integration with services such as Azure Active Directory. AKS also integrates with the Azure Container Registry for Docker image storage and Azure Disks. Azure cloud users can access the service with the AKS management portal, AKS command-line interface or Azure Resource Manager templates. Cloud users are not charged for Kubernetes clusters managed with AKS. Pricing is based on the cloud resources used in containers.
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Compare serverless tools and services in the public cloud - TechTarget
Cloud Database and DBaaS Market Worth $24.8 Billion by 2025 – Exclusive Report by MarketsandMarkets – Benzinga
CHICAGO, Feb. 27, 2020 /PRNewswire/ -- According to a new market research report "Cloud Database and DBaaS Market by Database Type (SQL and NoSQL), Component, Service, Deployment Model, Organization Size, Vertical (BFSI, Telecom and IT, Manufacturing, Healthcare and Life Sciences), and Region - Global Forecast to 2025", published by MarketsandMarkets, the global Cloud Database and DBaaS Market size is expected to grow from USD 12.0 billion in 2020 to USD 24.8 billion by 2025, at a Compound Annual Growth Rate (CAGR) of 15.7% during the forecast period.
The growing demand to process low-latency queries is one of the major factors driving the growth of the market.
Browsein-depth TOC on"Cloud Database and DBaaS Market"105 Tables 35 Figures160 Pages
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The Banking, Financial Services and Insurance vertical segment to account for the highest market share during the forecast period
The Banking, Financial Services and Insurance (BFSI) vertical is one of the most data-centric verticals where large volumes of databases are generated at an exponential rate. Various factors are expected to contribute to the growth of the database in the financial sector. Some of these factors include electronic transactions, Automated Teller Machines (ATMs), credit cards, call centers, and mobile-based sources. The database generated from these sources is scattered across various branches and departments across various financial institutions and needs to be interlinked together. The linking of this database is important to derive meaningful insights and sustain in the competitive market. The BFSI vertical demands an additional secured environment to secure its online transactions 24*7, which can be achieved by cloud database and DBaaS. Hence, the adoption of cloud database and DBaaS solution helps BFSI companies to store, manage, access, and modify data for further processes. Cloud database and DBaaS ensure the seamless execution of transactions. These solutions further improve the accuracy and efficiency of various processes and assist in the regulatory and compliance reporting by collating data from multiple sources. Most banks are increasingly deploying cloud database and DBaaS solutions to enhance performance and improve cost-savings.
The Not only Structured Query Language segment to grow at a higher CAGR during the forecast period
The growing amount of digital data in unstructured data format generates the need for dynamic scalable database. Structured Query Language (SQL) offers databases only in the tabular format, but Not only Structured Query Language (NoSQL) offers database and queries in various formats: column, graphical, document, and others. Thus, the need is fulfilled by the non-relational database with its highly scalable and easy to program model. NoSQL is also known as non-relational database. It offers great features to the clients; scalability is apparently the most important one. In addition to this, NoSQL allows users to store and retrieve unstructured data. Today, most of the cloud database and DBaaS vendors provide NoSQL compatible cloud database services. Owing to this, dealing with huge data processing on the web has been made cost-effective.
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North America to lead the Cloud Database and DBaaS Market during the forecast period
North America is expected to account for the highest share of the Cloud Database and DBaaS Market in 2020. The region comprises developed countries, such as the US and Canada, and is considered the most advanced region in terms of adoption of advanced technologies. The North American region exhibits a wide presence of key industry players offering cloud database and DBaaS solutions and services, and its financial position enables the region to invest majorly in leading tools and technologies for effective business operations.
Key and emerging Cloud Database and DBaaS Market players include Google (US), Microsoft (US), AWS (US), IBM (US), Oracle (US), Alibaba Cloud (China), SAP (Germany), MongoDB (US), EnterpriseDB (US), Redis Labs (US), Tencent (China), Rackspace (US), Teradata (US), CenturyLink (US), Neo4j (US), DataStax (US), TigerGraph (US), MariaDB (US), RDX (US), and MemSQL (US) are some of the leading companies operating in this market.
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Cloud Database and DBaaS Market Worth $24.8 Billion by 2025 - Exclusive Report by MarketsandMarkets - Benzinga
Tech Disruptors from the Anaheim Show: Life After the Mars 2020 Rover – DesignNews
The morning keynote panel at the Pacific Design and Manufacturing show earlier this month, revealed a wide range of bleeding edge technology. Tech Disruptors Transforming the Robotics Revolution included Hari Nayar, principal technologist and supervisor of Robotic Surface Mobility Group at Nasa Jet Propulsion Lab; David Noonan, director of systems and robotics at Auris Health; and Brian Schmitz, director of surgical robotics at Stryker. The moderator was Lori Jordan, former director of business development for AI and ML at Microsoft.
Engineers at the Jet Propulsion Lab install the legs and wheels of the Mars 2020 Rover. (Image source: NASA/JPL-Caltech)
Hari Nayar offered a look into advances in robotics at Nasa Jet Propulsion Lab. He specifically revealed some of the new projects in development at the Labs Robotic Surface Mobility Group.
Nayar explained some of the technology that is reaching beyond this years robot star, the Mars 2020 Rover. Were working on follow-up missions for the Mars 2020 Rover. One of the missions is to pick them up items on Mars and bring them back to earth, said Nayar. Were also working on robotics research for bodies further out in the solar system. We work on cutting-edge technology that includes machine learning and AI. Were looking at areas of Mars we havent explored before, rugged areas. Were also working on a Mars helicopter so we can fly on Mars.
Nayars team uses cloud technology for the Mars project, since a wide range of engineers are involved in the development and operation of the Mars 2020 Rover. Were using cloud computing. When were operating the spacecraft, hundreds of people on the ground are involved, said Nayar. In order to do things quickly, we need a lot of people on earth. When you get the data back, you need to analyze it. It is greatly facilitated by cloud computing so we can share it. The cloud enabled us to share it.
Getting the Technology into the Marketplace
Nayar noted that one of NASAs goals is to commercialize some of its technology. With our own technology, after weve used it a few times, we believe it should be commercialized. So, a lot of our work ends up in commercial operations. Our sea cameras have ended up in smart phones.
Much of the NASA technology that gets commercialized goes through the University system. Were a NASA center, but were operated by Caltech, so a lot of the technology we develop is licensed by the university, said Nayar. We develop useful things that can be further developed commercially. We are also adopting technology that is originally developed commercially, like robotic driving. Some of the commercial development is way ahead of us.
Another way NASA works in the commercial technology marketplace is to make sure NASA suppliers flourish. In some cases, we actually help companies grow, said Nayar. We need to acquire specialized applications, so NASA invests in companies that develop the technology we need. We try to help the companies grow and provide the products that we will be customers for.
We Get Small Business Involved
In working with commercial companies, NASA has a program devoted specifically to small business. There are government programs supporting small companies. NASA is a supporter of that. We do support small businesses, said Nayar. We also work with small companies to contract some of the work we do. We are not allowed to work on technologies that commercial companies can provide. Some of that work applies to non-NASA entities, and some of those entities are small commercial companies.
As NASAs technology spills out into the commercial world, Naysar is surprised to see it show up in familiar places. I watch TV with my kids, and I end up seeing stuff weve been working on, said Nayar. The public is excited about the work we do, so we actively disseminate that information.
Additional articles from this panel look at the advanced work on robotics by Auris Health and Stryker.
Rob Spiegel has covered automation and control for 19 years, 17 of them for Design News. Other topics he has covered include supply chain technology, alternative energy, and cyber security. For 10 years, he was owner and publisher of the food magazine Chile Pepper.
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Tech Disruptors from the Anaheim Show: Life After the Mars 2020 Rover - DesignNews
Global Cloud Computing Data Center IT Asset Disposition (ITAD) Market 2025 by Orbis Market Reports | Expected to Grow as Demand from End-Users- AMI,…
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Report covers following manufacturers:AMIIron MountainCloudBlueApto SolutionsArrowTes-AmmSims RecyclingITRenew
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Breakdown Data by TypeIT EquipmentSupport Infrastructure
Breakdown Data by Application:Data SanitizationRecoveryRecycling
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Some TOC Points:1 Study Coverage2 Executive Summary3 Market Size by ManufacturersContinued
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Global Cloud Computing Data Center IT Asset Disposition (ITAD) Market 2025 by Orbis Market Reports | Expected to Grow as Demand from End-Users- AMI,...