Since the COVID-19 virus outbreak in December 2019, the disease has spread to almost 100 countries around the globe with the World Health Organization declaring it a public health emergency. The global impacts of the coronavirus disease 2019 (COVID-19) are already starting to be felt, and will significantly affect the Cloud Computing Platform as a Service (PaaS) market in 2020.
COVID-19 can affect the global economy in three main ways: by directly affecting production and demand, by creating supply chain and market disruption, and by its financial impact on firms and financial markets.

The outbreak of COVID-19 has brought effects on many aspects, like flight cancellations; travel bans and quarantines; restaurants closed; all indoor events restricted; over forty countries state of emergency declared; massive slowing of the supply chain; stock market volatility; falling business confidence, growing panic among the population, and uncertainty about future.
This report also analyses the impact of Coronavirus COVID-19 on the Cloud Computing Platform as a Service (PaaS) industry.
Based on our recent survey, we have several different scenarios about the Cloud Computing Platform as a Service (PaaS) YoY growth rate for 2020. The probable scenario is expected to grow by a xx% in 2020 and the revenue will be xx in 2020 from US$ xx million in 2019. The market size of Cloud Computing Platform as a Service (PaaS) will reach xx in 2026, with a CAGR of xx% from 2020 to 2026.
With industry-standard accuracy in analysis and high data integrity, the report makes a brilliant attempt to unveil key opportunities available in the global Cloud Computing Platform as a Service (PaaS) market to help players in achieving a strong market position. Buyers of the report can access verified and reliable market forecasts, including those for the overall size of the global Cloud Computing Platform as a Service (PaaS) market in terms of revenue.
Players, stakeholders, and other participants in the global Cloud Computing Platform as a Service (PaaS) market will be able to gain the upper hand as they use the report as a powerful resource. For this version of the report, the segmental analysis focuses on revenue and forecast by each application segment in terms of revenue and forecast by each type segment in terms of revenue for the period 2015-2026.
Regional and Country-level Analysis
The report offers an exhaustive geographical analysis of the global Cloud Computing Platform as a Service (PaaS) market, covering important regions, viz, North America, Europe, China, Japan, Southeast Asia, India and Central & South America. It also covers key countries (regions), viz, U.S., Canada, Germany, France, U.K., Italy, Russia, China, Japan, South Korea, India, Australia, Taiwan, Indonesia, Thailand, Malaysia, Philippines, Vietnam, Mexico, Brazil, Turkey, Saudi Arabia, U.A.E, etc.
The report includes country-wise and region-wise market size for the period 2015-2026. It also includes market size and forecast by each application segment in terms of revenue for the period 2015-2026.
Competition Analysis
In the competitive analysis section of the report, leading as well as prominent players of the global Cloud Computing Platform as a Service (PaaS) market are broadly studied on the basis of key factors. The report offers comprehensive analysis and accurate statistics on revenue by the player for the period 2015-2020. It also offers detailed analysis supported by reliable statistics on price and revenue (global level) by player for the period 2015-2020.
On the whole, the report proves to be an effective tool that players can use to gain a competitive edge over their competitors and ensure lasting success in the global Cloud Computing Platform as a Service (PaaS) market. All of the findings, data, and information provided in the report are validated and revalidated with the help of trustworthy sources. The analysts who have authored the report took a unique and industry-best research and analysis approach for an in-depth study of the global Cloud Computing Platform as a Service (PaaS) market.

The following players are covered in this report:
Cloudflare
IBM Cloud
Oracle
Salesforce
Google
ServiceNow
Apache Stratos
Windows Azure
AWS
OpenShift
Plesk
Zoho Creator
Red Hat
VMware
SAP
Cloud Computing Platform as a Service (PaaS) Breakdown Data by Type
Video Communication Paas
Cloud Telephony Paas
Web and Mobile Optimization
Others
Cloud Computing Platform as a Service (PaaS) Breakdown Data by Application
Large Enterprises
SMEs

With the rapid growth of the “as a service” business model in today’s business domain, we are slowly moving towards a world where developers may not need to rely on physical infrastructure to run codes. After the surge of cloud-based platforms, IT companies are switching to a serverless computing paradigm, which promises to be a cost-effective way of building and operating applications in the cloud. IBM outlines serverless as an approach to computing that offloads responsibility for common infrastructure management tasks (e.g., scaling, scheduling, patching, provisioning, etc.) to cloud providers and tools. This allows the engineers to focus their time and effort on the business logic specific to their applications or process. It also allows developers to create and deploy apps without having to worry about server infrastructure.

Basically, serverless computing is the abstraction of servers, infrastructure, and operating systems. This means that, while this technology eliminates the need for infrastructure provisioning and management, it certainly does not eliminate the need for servers. Serverless lets developers shift their focus from the server level to the task level. A developer only has to specify how much RAM and CPU to allocate for the function, what trigger or event should cause the code to execute, and then finally upload the function source code. The users of this technology are only billed for when their code is running, down to the nearest 100 milliseconds. Often times, cloud providers call their serverless services as, Function-as-a-service (FaaS). E.g., AWS Lambda. In reality, FaaS is actually a subset of serverless. Here, applications are written by developers but run in stateless compute containers that are event-triggered and fully managed by a third party.

Serverless is primarily used for transient data exchanges by web and business applications in the cloud. Also as the name suggests, serverless computing services reduce the overhead and cost of managing either physical or virtual infrastructure. This approach further, helps teams increase their productivity and launch products to market faster, and allows better optimization of organizational resources. Applications of serverless computing include: continuous integration pipeline, processing big data, i.e. structured data (JSON, XML, etc.) or unstructured data (images, audio, etc.), including transcoding, moving, combining or manipulating. It also helps integrate language assistants and chatbots, implement micro-services, run scheduled tasks and much more.

Some of the popular serverless computing services are Google Cloud Functions, Microsoft’s Azure Functions, IBM OpenWhisk, Cloudflare Workers and more. Though Google Cloud Functions supports Node.js JavaScript, Python, and Go, it allows for unlimited execution time for functions. Meanwhile, Microsoft’s Azure Functions, supports a wider range of languages including Bash, Batch, C#, F#, Java, JavaScript (Node.js), PHP, PowerShell, Python, and TypeScript.

fPaaS
One of the most prominent manifestations of serverless computing is function platform as a service, or fPaaS. According to analyst firm Gartner, half of the global enterprises will have deployed fPaaS by 2026, up from only 20% today. Gartner also believes that the next-generation technology of serverless computing will enable agility, elasticity and cost-effectiveness when applied to appropriate use cases.

Serverless vs. Containers
Containers are a lightweight virtualization technology that wraps source code together with application dependencies, allowing easy portability and consistency. There are a few fundamental differences between serverless computing and containers. Although both use virtualization technology, containers virtualize the operating system (OS) whereas serverless virtualizes the runtime and scales via functions. Unlike the latter, containers require hardware to run. This means, the hardware must be updated, patched and maintained by the concerned team too.

Further, scaling a container requires manual intervention by increasing the number of containers. On the other hand, scaling a function in serverless is taken care of by the vendor based on load. Besides, container scaling is by the application team and for serverless scaling, it is done by the vendor.

Advantages
There are multiple benefits of leveraging serverless computing. It offers dynamically scalability within seconds to match the demands of any workload. It also minimizes the operations dependencies on each development cycle, increasing development teams’ agility to deliver more functionality in less time. Users don’t have to worry about the cost of procuring, maintain, and upgrading a server either. Since there is no need for a backend configuration, it also facilitates quick deployments and updates. It also has high error tolerance thanks to flexible hardware infrastructure in the provider’s computer center. Further, it grants service assurance purposes, like monitoring, logging, tracing and debugging. Moreover, serverless vendors, ask end-users to pay only for resources being used, never paying for idle capacity.