The Latest Cloud Computing market research report focuses on a comprehensive understanding of the global market segment, as well as the economic trends of the leading producers and industry statistics. The study also includes expert advice to assist clients in developing their implementation policies and making responsible decisions. This research report examines historical data and key trends discovered to determine the major factors influencing the global Cloud Computing industry’s development.

The report provides details about this industry in terms of a specified evaluation and in- depth assessment of this business. The Cloud Computing market is appropriately bifurcated into segments, according to the report. An overview of the industry with regards to the market size in terms of renumeration and volume aspects, alongside the current Cloud Computing market scenario is inculcated in the report.

Most of the businesses are facing a growing litany of business-critical concerns related to the coronavirus outbreak, including supply chain disruptions, a risk of a recession, and a potential drop in consumer spending. All these scenarios will play out differently across various regions and industries, making accurate and timely market research more essential than ever.

The study presents a brief related to the topographical spectrum of this vertical along with the firms that have earned a significant position across the marketplace.

An overview of the Cloud Computing market scope:

An overview of the competitive landscape
A thorough analysis of the regional expanse
An outline of the market segmentation
Synopsis of the competitive landscape:

The Cloud Computing market report consists of brief analysis of the competitive terrain of this industry.
The report specifies an analysis of the competitive scope of the terrain. According to the report, the competitive reach of the Cloud Computing market spans the companies such as Amazon Web Services , Vmware , Microsoft Azure , Aliyun , Google Cloud Platform , IBM , SAP , Salesforce , Oracle , Rackspace , DELL and EMC.
Data related to the industry participant’s current share in the market, production sites, area served, and more is inculcated in the report.
Information about profiles of the companies alongside the data relate to their profit margins and models.
Information about the regional expanse:

The report divides the regional spectrum of this industry extensively. According to the report, the Cloud Computing market has formed its stance spanning the regions of United States, China, Europe, Japan, Southeast Asia & India.
Details regarding the industry share of these regions is mentioned in the report. Additionally, information about the growth opportunities for the players with their base in these regions have been specified.
The predicted growth rate to be registered by every geography over the predicted time period is specified in the report.
A brief of the market segmentation:

The Cloud Computing market report presents the segmentation of this vertical with the right precision.
The product expanse of the Cloud Computing market is split into Infrastructure as a service (IaaS) , Platform as a Service (PaaS) and Software as a Service (SaaS whereas the application landscape of the Cloud Computing market is segmented into Government , Small and Medium sized enterprises and Large enterprises.
Information regarding industry share accrued by every product segment, along with the market value in the industry is provided in the report.
Details with regards to the production growth are also inculcated in the report.
Details regarding market share with regards to application spectrum acquired by every application division is defined in the report.
Data related to the product consumption of every application as well as the growth rate of each application segment is likely to be registered over the predicted timeframe.

Cloud Computing Market 2021-2026: Key Highlights:

Examination of the global Cloud Computing market size by value and size.
To accurately calculate the market segments, consumption, and other dynamic factors of the various units of the market.
Determination of the key dynamics of the market.
To highpoint key trends in the market in terms of manufacturing, revenue and sales.
To summarize the top players of Global Cloud Computing industry and show how they compete in the industry.
Study of industry procedures and costs, product pricing and various developments associated with them.
To showcase the performance of different regions and countries in the Global Cloud Computing market.
Key Answers in the Report

Possible users of this report in the global Cloud Computing market.
Effective strategy formulation by end-users.
Product and services leaving a lasting influence on the global Cloud Computing market.
Growth factors are likely to attract the attention of market players.
Challenges to the expansion of the market.
Product or service offering the most revenue.
Recent developments influencing the global Cloud Computing market.
Innovations are likely to positively impact the market.
Enlisting micro and macro factors according to geography.
Disruptions caused by Covid-19 to the supply chain.

The Cloud Computing in K-12 market report is intended to provide a 360-degree view of the market in terms of advanced technology, key developments, drivers, restraints, and future trends and analyze the impact of these trends on the market in the short, medium term. and long term in the forecast period. Additionally, the report covers profiling the key players with detailed SWOT analysis, financial facts, and key product/service developments over forecast period.

The Cloud Computing in K-12 market report is a comprehensive documentation of the prevalent industry trends and aims to educate the readers about competitive scenario and regional business dynamics. It leverages the expert verbatim to warn about challenges dormant in the industry, while providing insights about the profitable opportunities across various market segments. Moreover, the study entails numerous scenarios, including COVID-19 impact, hence enabling companies to formulate contingency plans and stakeholders to take informed decisions.

Takeaways from COVID-19 impact scrutiny:

An overview on the influence of coronavirus on global economy
Variations in demand and supply trends in the industry
Immediate and far-sighted consequences of COVID-19 pandemic on the business dynamics

Summary of regional landscape:

The report fragments the Cloud Computing in K-12 market into regions, namely, North America, Europe, Asia-Pacific, South America and Middle East and Africa.
Information pertaining to the growth patterns followed by various geographies over the forecast period is elucidated.
Data about sales amassed, profits garnered, and revenue contribution in the recent past, alongside prediction about valuation is presented in the report.
Other highlights from Cloud Computing in K-12 market report:

Industry moguls profiled in the Cloud Computing in K-12 market report are Adobe Systems,Ellucian,SAP,Microsoft,Instructure,Dell EMC,Oracle,Salesforce,Cisco,Blackboard andNetApp.
Details about the business profile of each company, along with their product portfolio, production quantity, as well as pricing pattern followed by them are elucidated.
Insights about the industry share held by different business contenders, and overall profits generated by them are given.
Moving on to product spectrum, the report bifurcates the Cloud Computing in K-12 marketplace into SaaS,IaaS andPaaS.
It goes on to study the sales volume and revenue share of each product segment, to predict its contribution towards market remuneration over the forecast period.
Speaking of application spectrum, the Cloud Computing in K-12 market products are used across Training & Consulting,Integration & Migration,Support & Maintenance, ,Geographically, the detailed analysis of production, trade of the following countries is covered in Chapter 4.2, 5: ,United States ,Europe ,China ,Japan andIndia.
The report expounds on the portion of industry stake held by each application and their growth graph in the ensuing years.
The business intelligence contains thorough dissection of the supply chain to review and infer the competitive hierarchy of the market.
It further includes Porter’s Five Force model and SWOT analysis to identify the potential of new projects.
Points Covered in The Report

The report encompasses an exhaustive discussion of the major players operating in this vertical, inclusive of the prominent companies, raw material & equipment suppliers, traders, distributors, and end-users.
In-depth profiles of companies is hosted in the document, covering all important aspects like capacity, production, pricing, revenue, gross margins, sales volume, growth rate, import, export, supply, future strategies, and technological development.
A comprehensive analysis of five years of historical data as well as market forecast is provided.
Data and information with respect to market player, region, type, application, etc., along with customized research as per specific requirements is offered.
SWOT analysis of the market is included.
Top Reasons to Buy The Report

To gain valuable insights on the market and have a deeper understanding of the overall industry size and its commercial environment.
Evaluate the product processes, major challenges, and risk-averting methodologies.
To comprehend the major driving and restraining factors and their effect on the global market.
Learn about the key strategies being employed by leading companies.
To know the future outlook and prospects of the industry.
Apart from standard structure reports, one can also obtain custom research as per the specific requirement.

The new record on the global Microservices market gives snippets of data concerning the techniques for information assortment from different areas and information collecting units nearby social gathering information on different applications and conversing with different industry prepared experts and others who hold express degree and incorporation with the field and offer true information to the examination associations over the new occasions.

It gives data on pieces of a few boss models and perspectives that on a huge level effect the business share. Further, the record shows the total of the key affiliations that are working in the business space nearby their valuation, market share, encounters about the social affair units and present day workplaces of the relationship to the degree their zones and production worth and volume.

Leading Key Players of Microservices Industry. Analyzed Globally:

IBM
Microsoft
Salesforce
Infosys
NGINX
Oracle
Pivotal Software
Syntel
SmartBear Software
Marlabs
RapidValue Solutions
Kontena
Macaw Software
Unifyed
RoboMQ
Idexcel

Further, the record supports misleads and tips to the affiliations that are truly arising in the business space and helps the financial accomplices in settling on solid choices.

Market Segmentation by Type Consists:

On-Premise
Cloud Based

Market Segmentation by Applications Consists:

Retail and Ecommerce
Healthcare
Media and Entertainment
Banking, Financial Services, and Insurance
IT and ITes
Government
Transportation and Logistics
Manufacturing
Telecommunication
Others

The report on global Microservices market contains clear course of action of the verbalized data as pie diagrams, follows, line follows and various updates which pulls out the authentic data into sensibly clear longings to give vigorous improvement of the nuances to the customer without eating up a monster store of their time. Besides, the report on global Microservices market contains assessment of affiliation portfolio and products that the clients are referencing for nearby the upgrades in the products. It gives information about the presence of mind of the pushing toward tries and degree of the advantage event enlargements by the affiliations. It intends to give high ground to the arising huge parts in this industry space.

Moreover, the data on the global Microservices market is contained with thorough analysis of the production patterns, latest mergers, acquisitions, buyers, vendors, partnerships that have taken place in the market and hold a major impact on the industry share of the segments such as applications, products, competitors, and regional overview of the industry space. Further, it contains data on several CEOs and industry experts that have a major say in the events happening in the industry.

Orbis Research (orbisresearch.com) is a single point aid for all your Market research requirements. We have vast database of reports from the leading publishers and authors across the globe. We specialize in delivering customized reports as per the requirements of our clients. We have complete information about our publishers and hence are sure about the accuracy of the industries and verticals of their specialization. This helps our clients to map their needs and we produce the perfect required Market research study for our clients.

Snowflake has appointed a new president for the Asia Pacific & Japan (APJ) region.

Jon Robertson will join the data cloud company in early March. He will be responsible for driving the adoption and expansion of Snowflake’s Data Cloud in the local market, with a specific focus on empowering local enterprises to mobilise their data for valuable business insights.

Robertson is an experienced executive who, prior to joining Snowflake, served VMware in the APAC region for the last 14 years.

Most recently, he served as president of VMware Japan K.K., responsible for all aspects of the virtualisation, digital workplace and cloud business in Japan.

Prior to this, he was general manager at VMware ASEAN from 2012 to 2015, and served as area vice president at VMware Japan K.K. beginning in 2007.

Throughout his tenure at VMware, Robertson was involved in strategic planning, business development, and client engagement, playing a key role in growing the business to its current status in the cloud market.

Throughout his career, Robertson also held senior positions in sales and field management at EMC, SAP and M3i in Japan and APJ markets.

He is fluent in Japanese, French, and English and holds a Bachelor of Arts degree in Political Science from McGill University in Montreal, Canada.

Snowflake chief revenue officer Chris Degnan says, “Jon brings extensive knowledge of the local market and a strong track record of success in the cloud computing industry to both the Snowflake team and our customers in the APJ region.

“Jon’s leadership and expertise will expand Snowflakes footprint and empower local enterprises to mobilise their data for business value.”

On his appointment, Robertson says, “Data is at the core of the most successful businesses today, and local enterprises can realise deep benefits from the power of Snowflake Data Cloud.

“I’m proud to join the Snowflake team and work with clients across the region to show what’s possible for their businesses with Snowflake’s platform. I will continue the Snowflake commitment of putting customers first, within our local APJ organisations.”

Snowflake delivers the Data Cloud a global network to help organisations mobilise data with scalability, concurrency, and performance.

Inside the Data Cloud, organisations are able to unite siloed data, discover and securely share governed data, and execute diverse analytic workloads, the company states.

The Snowflake platform powers and provides access to the Data Cloud, enabling data warehousing, data lakes, data engineering, data science, data application development, and data sharing.

In 2020, the company launched its first global partner program. The Snowflake Partner Network includes resale and managed service provider programs, as well as a program designed to help technology partners expand their offerings.

Announced at the SAP Tech-Ed conference, the free tier comes at a time when SAP is encouraging developers to use its applications as a foundation for digital business process transformation initiatives.

As part of that effort, SAP is also extending the capabilities of the low-code tools it makes available to customize SAP Cloud Platform Workflow Management and SAP Intelligent Robotic Process Automation (RPA) 2.0 to make it easier to integrate these offerings with other applications. SAP beginning in January is also promised to include a limited edition of SAP Intelligent RPA in every SAP S/4HANA Cloud subscription.

Finally, SAP is beta testing SAP Ruum, a set of no-code tools it plans to make available alongside the low-code tools it already includes in its portfolio of tools for building custom applications that extend the packaged applications it provides on-premises and in the cloud.

At the heart of the SAP digital business transformation strategy is SAP Business Technology Platform, which makes it possible to share data across SAP applications via a common data and object model. SAP makes available SAP Cloud Platform to provide a distinct platform-as-a-service (PaaS) environment through which developers can build extensions to its applications.

Most recently, SAP has made SAP Graph tools in beta offering as a complement to a revamped SAP API Business Hub that will be available in beta this month.

Thomas Grassl, vice president and global head of developer relations and community for SAP, said the company is also embracing continuous integration/continuous delivery (CI/CD) platforms as it continues to encourage developers to move away from waterfall-based approaches to building and deploying applications.

The free tier of resources SAP is providing developers will encourage organizations to experiment more at a time when many organizations are now quite certain what digital process may ultimately gain traction with their end customers and suppliers. SAP is also focusing on no-code and low-code tools to enable organizations to accelerate the development of those applications. SAP already has an existing partnership in place with Mendix, a unit of Siemens, to make available low-code tools.

SAP’s biggest concern, of course, is that digital business transformation initiatives will revolve more around application platforms from Oracle, Salesforce, ServiceNow and Workday. Every major provider of enterprise applications offers low-code and no-code tools to customize their applications. Many enterprise IT organizations are employing these tools more widely to accelerate digital business initiatives as an alternative to building entire applications from the ground up.

The challenge these organizations will soon encounter is that as the backlog of applications that need to be deployed starts to build, they will have to modernize their approaches to deploying applications to keep pace.

As a dominant provider of enterprise applications, SAP is in a position to drive digital business transformation in a way that extends the reach and scope of its enterprise resource planning (ERP) portfolio. The issue is finding a way to accomplish that goal when organizations thanks to the COVID-19 pandemic have a pressing need to transform much sooner than later.

SAP and Microsoft announced today an expanded partnership to enable customers to design and operate intelligent digital supply chain and Industry 4.0 solutions in the cloud and at the edge.

The partnership, which includes a collaborative approach to standards, consortia, and open source, will shape the future of supply chain and manufacturing.

SAP Digital Supply Chain and Industry 4.0 Solutions Run on Microsoft Azure
As a result of this partnership, organizations will be able to use a comprehensive set of SAP Digital Supply Chain solutions on Microsoft Azure, including SAP solutions for digital manufacturing, SAP Intelligent Asset Management solutions, SAP Integrated Business Planning, and SAP Logistics Business Network.

SAP will use Microsoft Azure to run these solutions in a software-as-a-service (SaaS) model that can help reduce the customer’s need to manage the software and underlying infrastructure while accelerating time to value of supply chain applications. Customers will be able to scale globally by leveraging Azure which offers enterprise-grade compute, storage, and network services to support mission-critical performance and business continuity to run SAP Digital Supply Chain solutions.

SAP Manufacturing Suite, SAP Intelligent Asset Management, supply chain networks solutions from SAP, and the SAP Internet of Things (SAP IoT) solution are already available on Microsoft Azure in Europe and the United States today.

SAP and Microsoft Collaborating to Bring Business Processes to the Edge
Historically, enterprises have been reluctant to migrate mission-critical factory applications to the public cloud, primarily due to security, regulatory requirements, and availability concerns.

In addition, when managing a global, distributed supply chain and manufacturing environment, companies face challenges with constrained bandwidth, latency, and massive volumes of data that can adversely affect execution and quality scenarios. Here, the solution lies in edge computing.

Think of edge computing as a form of distributed computing where data, applications, and business processes are run near the source of generated data. The ability to extend and run business processes at the edge enables organizations with factories, plants, warehouses or remote operations, to fully automate and run their operations independently – enabling faster processing and support for data residency requirements. Customers have the choice to only send data to the cloud that is relevant for additional analysis or an aggregated view across many edges to save costs.

SAP and Microsoft are also collaborating to make SAP solutions available on Microsoft Azure Stack Edge, starting with SAP Digital Manufacturing Cloud. This helps manufacturers process data locally across machines and control systems to address latency or connectivity restraints.

Customers are empowered to choose what business process to run in the cloud or at the edge based on business need; they can deploy specific business processes and relevant business data to specific edge nodes using SAP Edge Services. According to IDC research, ‘70% of IoT deployments by 2023 will include edge-based decision-making to support organizations’ operational and strategic agendas.’ The report also states that by ‘2023, 70% of enterprises will run varying levels of data processing at the IoT edge. In tandem, organizations will spend over $16 billion on IoT edge infrastructure in that time.’

Customers have a choice to use either Microsoft Azure IoT or SAP IoT to bring their time series data to the cloud. Time series data collected from machines or devices at the edge and sent to the cloud is of little value on its own. Companies need to put time series data into business context by augmenting it with information stored in business applications for materials, products, customers, inventory, assets, and more. Combining business semantics and time series data using the SAP IoT solution creates business relevance, leading organizations to improved business outcomes and better decision-making.

‘The expansion of the partnership between SAP and Microsoft provides our mutual customers with the ability to leverage SAP Digital Supply Chain and manufacturing solutions in the cloud to gain better business insights and accelerate the time-to-value as they roll out their applications on a global scale. By extending SAP Digital Supply Chain solutions and the Azure cloud capabilities to the edge with Azure Stack Edge, businesses will also be able to manage SAP solutions locally across their factories and warehouses to drive immediate decision-making and actions where they are needed,’ said Ulrich Homann, corporate vice president of Cloud + AI at Microsoft.

Companies Will Provide Reference Architecture as Guidance to Their Customers
The partnership in supply chain and manufacturing will be further enhanced with reference architectures to provide customers guidance on deploying SAP Digital Supply Chain on Azure and the integration of SAP and Microsoft products and services, building on previously developed architecture blueprints.

For example, customers have a choice to use either Microsoft Azure IoT or SAP IoT to bring their time series data to the cloud. Time series data collected from machines or devices at the edge, and sent to the cloud, may be of little value on its own. Companies need to put time series data into business context by augmenting it with information stored in business applications for materials, products, customers, inventory, assets, and more. Combining business semantics and time series data using the SAP IoT solution creates business relevance, leading organizations to improved business outcomes and better decision-making.

SAP and Microsoft Shape the Future of Industry 4.0 with Open Standards
With software development and standards, the benefits of aligned reference architectures and common semantics are obvious. Adopting industrial standards and creating shared asset models in industrial IT are as significant to digital supply chain as a dictionary is to literacy. Business partners who wish to succeed in this space need to endorse open standards, open consortia, and open source.

As part of this partnership, SAP and Microsoft will work together to drive compatibility and interoperability across industrial machines, software, and services as members of consortia like the Open Manufacturing Platform and the Open Industry 4.0 Alliance – to aid in the accelerated path to value of supply chain and Industry 4.0-related solutions based on open standards.

What Is the Cloud Computing Stack?

The cloud computing stack refers to the layered set of services that together form a complete cloud offering. Each layer builds on the one below it, abstracting away progressively more infrastructure complexity. The three canonical layers are:

• Infrastructure as a Service (IaaS) – Raw compute, networking, and storage resources delivered over the internet. Teams retain full control over the operating system and above.
• Platform as a Service (PaaS) – A managed environment for developing, testing, and deploying applications without managing the underlying infrastructure. The provider handles the OS, runtime, middleware, and scaling.
• Software as a Service (SaaS) – Fully managed applications delivered via a browser or API. The provider is responsible for everything from infrastructure to the application layer itself.

These three layers are often visualized as a stack because each higher tier consumes services from the tier below it. A SaaS product, for example, typically runs on PaaS or IaaS underpinnings provided by a hyperscaler.

Layer 1: Infrastructure as a Service (IaaS)

IaaS gives engineers the most control over their environment. Typical IaaS resources include virtual machines, block and object storage, virtual networking, load balancers, and bare-metal servers. The consumer manages everything from the guest operating system upward—patching, runtime configuration, security hardening, and application deployment all remain the team’s responsibility.

Common use cases:

• Lift-and-shift migration of legacy applications
• High-performance computing and batch workloads
• Custom network topologies and security configurations
• Disaster recovery and backup infrastructure

Key IaaS providers: Amazon Web Services (EC2, S3, VPC), Microsoft Azure (Virtual Machines, Blob Storage, VNet), Google Cloud Platform (Compute Engine, Cloud Storage), IBM Cloud, Rackspace, and OVHcloud.

Layer 2: Platform as a Service (PaaS)

PaaS removes the burden of OS and middleware management, letting development teams focus on writing and deploying code. The platform handles auto-scaling, load balancing, and often integrates CI/CD pipelines, managed databases, and monitoring out of the box.

Common use cases:

• Web and mobile application development and hosting
• Microservices deployment on managed Kubernetes clusters
• Serverless function execution
• Managed database and messaging services

Key PaaS providers: AWS Elastic Beanstalk and Lambda, Azure App Service and Azure Functions, Google App Engine and Cloud Run, Heroku (Salesforce), IBM Cloud Foundry, and SAP Business Technology Platform.

Layer 3: Software as a Service (SaaS)

SaaS is the most abstracted layer. End users interact with a fully managed application—there is no infrastructure or runtime to configure. From a DevOps perspective, SaaS is relevant both as a consumer (using tools like GitHub, Datadog, or PagerDuty) and as a target delivery model when building products for customers.

Common use cases:

• CRM and ERP systems
• Collaboration and productivity tools
• Monitoring, observability, and ITSM platforms
• Developer tooling (source control, CI/CD, issue tracking)

Key SaaS providers: Salesforce (CRM), Microsoft 365, Google Workspace, SAP, Oracle Cloud Applications, and Avaya cloud communications.

Major Cloud Vendors Across the Stack

Most hyperscalers operate across all three layers simultaneously. Below is a concise overview of the leading vendors and their primary strengths:

Choosing the Right Layer for Your Workload

Selecting the appropriate cloud layer is a trade-off between control and operational overhead:

• Choose IaaS when you need maximum control over the OS, network configuration, or custom hardware (e.g., GPU instances, specific compliance requirements).
• Choose PaaS when developer velocity matters more than infrastructure control—managed runtimes, auto-scaling, and built-in CI/CD integrations reduce toil significantly.
• Choose SaaS when the capability is not a core differentiator for your business and a third-party product meets your requirements—let the vendor handle operations entirely.

Many production architectures combine all three layers. A typical e-commerce platform might run compute on IaaS virtual machines or containers (IaaS/PaaS), use a managed database service (PaaS), and integrate a SaaS CRM for customer data—all within the same cloud account.

Market Context and Growth Drivers

Adoption of cloud services has accelerated across every industry vertical, driven by several converging factors:

• Operational agility: Cloud provisioning reduces the time from idea to running infrastructure from weeks to minutes.
• Cost model shift: Moving from capital expenditure (CapEx) to operational expenditure (OpEx) improves financial flexibility.
• Global reach: Hyperscaler regions and edge locations allow teams to deploy closer to end users worldwide.
• Managed services breadth: Vendors continually expand their PaaS and SaaS catalogues, reducing the engineering effort required for common capabilities such as databases, message queues, and ML inference.
• Regulatory and compliance tooling: Cloud providers now offer certified environments for regulated industries (HIPAA, FedRAMP, ISO 27001, PCI DSS), lowering the barrier for enterprise adoption.

Key Takeaways for DevOps Teams

• Understand which layer each service in your architecture sits on—it directly determines your shared responsibility boundary with the vendor.
• Evaluate managed PaaS options before defaulting to IaaS; reduced operational overhead often outweighs the loss of low-level control.
• Multi-cloud strategies can avoid vendor lock-in but introduce their own complexity—ensure your team has the tooling (Terraform, Kubernetes, etc.) to manage it consistently.
• Security and compliance ownership shifts depending on the layer: IaaS gives you the most responsibility; SaaS gives you the least. Map this explicitly in your threat model.

Guardicore, HubSpot, Zscaler, Domo, SAP, Slack, CloudBolt Software, OpsRamp, Fortinet, Zoho, Skykick, and New Relic are the most likely to be recommended by their employees to friends looking for a cloud computing company to work for in 2020.
Cloud software companies dominate the highest-rated cloud businesses when indexed by the percent of employees who would recommend their company to a friend.
Taken together, the 12 CEOs leading the top-rated cloud computing companies are approved by 96% of employees as of February 20, 2020, on Glassdoor. CEOs in this group include Brian Halligan of HubSpot, Josh James of Domo, Jay Chaudhry of Zscaler, Stewart Butterfield of Slack, Sridhar Vembu of Zoho and Jennifer Morgan and Christian Klein of SAP.
These and many other insights are from an analysis completed today comparing Computer Reseller News’ 100 Coolest Cloud Computing Vendors of 2020 by their respective Glassdoor scores. The Computer Reseller News annual list of the 100 coolest cloud computing vendors is an impartial, 3rd party benchmark of the fastest-growing and most likely to hire cloud businesses expanding today. By far, the most common request from Forbes readers is which cloud computing companies are the best to work for. The goal of this analysis is to provide readers with insights into which cloud computing companies best fit their skills and at the same time, have a strong reputation based on feedback from existing employees.

Indexing the most interesting and fastest-growing cloud computing companies by their Glassdoor scores and reputations is a great way to begin defining a long-term career growth strategy. One factor not quantified is how well of a fit an applicant is to company culture. Take every opportunity for in-person interviews, read Glassdoor ratings often and observe as much as possible about daily life in companies of interest to see if they are a good fit for your skills and strengths.

Using the 2020 CRN list as a baseline to compare the Glassdoor scores of the (%) of employees who would recommend this company to a friend and (%) of employees who approve of the CEO, the table below is provided. You can find the original dataset here. There are 16 companies on the CRN list that don’t have that many or any entries on Glassdoor, and they are excluded from the rankings shown below. You can find their mention in the original dataset. If the image below is not visible in your browser, you can view the rankings here.

Major Cloud Vendors Serving Retail Banking

The competitive landscape in cloud services for retail banking is broad. Hyperscalers and specialised enterprise software vendors both compete for bank workloads. Prominent players include:

• Amazon Web Services (AWS) – Offers dedicated financial-services competency programmes, compliance frameworks (PCI-DSS, SOC 2), and managed database and AI/ML services widely used by banks.
• Microsoft Azure – Provides strong integration with enterprise productivity tools and Azure Government/Sovereign Cloud options for regulated data residency requirements.
• IBM – Long-standing banking partner with hybrid cloud offerings built on Red Hat OpenShift, plus managed services for mainframe workload migration.
• Google Cloud – Increasingly targeting banking analytics and AI workloads, with dedicated financial-services industry solutions.
• Alibaba Cloud, Tencent Cloud, Huawei Cloud, Baidu AI Cloud, China Telecom, China Unicom, Kingsoft Cloud, and UCloud – Dominant cloud providers serving Asia-Pacific retail banks, particularly in China where domestic regulations shape cloud procurement.
• Infosys, TCS, and Wipro – Systems integrators and managed-service providers that deliver cloud migration, DevOps tooling, and banking-platform modernisation on top of hyperscaler infrastructure.
• Oracle, SAP, Salesforce, Workday, and Intuit – SaaS and PaaS vendors supplying core banking, CRM, ERP, and financial-management capabilities as cloud-native or cloud-hosted services.
• Medidata, Veeva Systems, and Ellie Mae – Vertical SaaS providers whose platforms intersect with banking and financial-services data management use cases.
• BBVA and Bankinter – Notable examples of retail banks that have invested heavily in internal cloud platforms and open-banking APIs, making them both consumers and, in some cases, providers of cloud-based financial technology.

Market Segmentation

By Service Type

• Infrastructure as a Service (IaaS) – Compute, storage, and networking resources consumed on demand; commonly used for disaster-recovery, batch processing, and dev/test environments.
• Platform as a Service (PaaS) – Managed runtime environments, databases, messaging queues, and integration layers that reduce operational overhead for development teams.
• Software as a Service (SaaS) – Fully managed applications such as core-banking systems, CRM, fraud-detection engines, and regulatory-reporting tools.

By Deployment Model

• Public Cloud – Shared infrastructure managed by a hyperscaler; cost-efficient for non-sensitive workloads.
• Private Cloud – Dedicated infrastructure operated on-premises or in a co-location facility; preferred for sensitive customer and payment data.
• Hybrid Cloud – Combination of public and private environments connected by orchestration tooling; increasingly the dominant model in banking because it allows regulatory data-residency controls alongside cloud-native scalability.

By Application

• Core banking system modernisation
• Customer relationship management (CRM) and personalisation
• Fraud detection and anti-money-laundering (AML) analytics
• Regulatory compliance and reporting
• Mobile and digital banking platforms
• Risk management and stress testing
• Data warehousing and business intelligence

Regional Landscape

Cloud adoption patterns in retail banking vary significantly by region, driven by local regulation, infrastructure maturity, and competitive pressure from fintech entrants.

North America (United States, Canada, Mexico)

North America represents one of the most mature markets. Large US banks have invested heavily in multi-cloud strategies, and regulators such as the OCC and FFIEC have issued guidance on cloud risk management rather than outright restrictions. Canada’s OSFI and Mexico’s CNBV each impose their own data-residency and third-party risk requirements.

Europe (Germany, France, UK, Russia, Italy)

GDPR, EBA outsourcing guidelines, and the EU Digital Operational Resilience Act (DORA) heavily influence cloud procurement decisions. Many European banks favour hybrid or sovereign-cloud arrangements to maintain data control. The UK’s post-Brexit regulatory environment, managed by the PRA and FCA, adds additional complexity for cross-border deployments.

Asia-Pacific (China, Japan, South Korea, India, Southeast Asia)

Asia-Pacific is one of the fastest-growing regions for cloud adoption in banking. China’s domestic cloud providers (Alibaba, Tencent, Huawei, Baidu, China Telecom, China Unicom) dominate the local market due to data-localisation requirements. India’s RBI has issued cloud-adoption frameworks encouraging managed migration. Southeast Asian markets show rapid growth driven by digital-only bank licensing regimes.

South America (Brazil, Argentina, Colombia)

Brazil’s LGPD privacy law and the Central Bank of Brazil’s open-finance initiatives are accelerating cloud investment. Hyperscalers have expanded local infrastructure to meet data-residency requirements.

Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria, South Africa)

Cloud adoption is growing from a lower baseline. The UAE and Saudi Arabia have established clear cloud-first government policies that indirectly influence banking. Nigeria and South Africa represent the leading African markets, with central banks developing cloud-risk guidance.

Key Growth Drivers

• Legacy system debt – Decades-old mainframe and on-premises applications are expensive to maintain and difficult to integrate with modern APIs, creating a strong business case for cloud migration.
• Fintech competition – Digital-native challengers operate at lower cost bases using cloud-native architectures, pressuring incumbent banks to modernise.
• Customer experience demands – Real-time payments, personalised offers, and always-on mobile services require the elastic scalability that cloud platforms provide.
• Regulatory reporting volume – Increasing regulatory complexity demands analytics platforms capable of processing large, rapidly changing datasets—a strength of cloud data warehousing.
• AI and machine learning adoption – Fraud detection, credit scoring, and customer segmentation models require compute resources that are cost-prohibitive to provision on-premises at scale.
• Operational resilience requirements – Regulators increasingly demand active-active disaster-recovery capabilities that public cloud regions and availability zones can deliver more economically than traditional data-centre pairs.

Key Restraints and Challenges

• Data sovereignty and residency rules – Regulations in many jurisdictions restrict where customer financial data can be stored or processed, limiting hyperscaler flexibility.
• Concentration risk – Regulators worry that widespread dependence on a small number of hyperscalers creates systemic risk for the financial sector.
• Security and compliance complexity – Banks must maintain PCI-DSS, SOC 2, ISO 27001, and local regulatory certifications across cloud environments, increasing operational overhead.
• Skills gaps – Cloud-native development, DevSecOps, and FinOps expertise remain scarce in many banking organisations.
• Migration risk – Moving mission-critical core-banking systems carries significant operational risk and requires extensive testing and rollback planning.

Technology and Innovation Trends

• API-led open banking – Cloud platforms provide the managed API gateways and event-streaming infrastructure (e.g., Kafka-as-a-service) that open-banking mandates require.
• Containerisation and Kubernetes – Banks are increasingly packaging workloads in containers to gain portability across cloud providers and reduce vendor lock-in.
• Serverless and event-driven architectures – Reducing idle compute costs for transaction-processing pipelines with variable load profiles.
• Confidential computing – Hardware-based trusted execution environments (TEEs) allow sensitive banking data to be processed in the cloud without exposing plaintext to the cloud provider.
• Generative AI integration – Banks are piloting large-language models for customer service automation, document processing, and code generation, typically through managed cloud AI services.

Conclusion

Cloud computing is no longer an emerging concept in retail banking—it is an operational reality for institutions of all sizes. The combination of legacy modernisation pressure, fintech competition, and demand for real-time, data-driven services means that cloud adoption will continue to accelerate across all regions. For DevOps and platform engineering teams working in financial services, understanding the regulatory context, vendor landscape, and architectural patterns specific to banking is essential for designing resilient, compliant, and cost-effective cloud environments.

Overview of the Global Public Cloud Service Market

The global public cloud service market entered 2019 as one of the fastest-growing segments of the technology industry. Enterprises across virtually every vertical were accelerating their migration from on-premises infrastructure to cloud-based platforms, driven by cost flexibility, scalability, and the broadening maturity of cloud-native tooling.

A market research report titled Public Cloud Service Market Research Report 2018–2026, published by Innovate Insights, examined the competitive dynamics, regional distribution, and service-type segmentation of this market. The following sections summarise the report’s key structural findings for practitioners who want a concise reference without marketing filler.

Key Players in the Public Cloud Service Market

The report identified the following companies as the primary competitors in the global public cloud service landscape:

• Amazon Web Services (AWS) – the longest-established hyperscale cloud provider, dominant in IaaS and PaaS revenue share.
• Microsoft Azure – strong enterprise penetration, particularly in hybrid cloud and Windows-integrated workloads.
• Google Cloud Platform (GCP) – competitive in data analytics, machine learning, and Kubernetes-native workloads.
• IBM Cloud – focused on regulated industries and hybrid deployments, reinforced by the Red Hat acquisition.
• Oracle Cloud – targeting database-heavy workloads and ERP migrations.
• Salesforce – dominant in SaaS CRM; a significant force in the broader public cloud ecosystem.
• SAP – enterprise application SaaS and platform services, particularly in ERP and supply chain.
• VMware – hybrid cloud infrastructure and virtualisation-layer services.
• Rackspace – managed cloud services across multiple provider platforms.
• Red Hat – open-source PaaS and container platform services (OpenShift).
• Adobe – creative and marketing SaaS on its own cloud infrastructure.
• Verizon Cloud – telecom-adjacent cloud and managed hosting services.
• Navisite – managed cloud for mid-market enterprises.
• Dropbox – cloud storage and collaboration SaaS.
• Egnyte – enterprise content collaboration and governance.

The report examined each player’s market share, production and service delivery locations, pricing models, gross margins, and product portfolio breadth.

Market Segmentation by Service Type

The public cloud service market is broadly segmented by the type of service delivered. The report categorised offerings into the following segments:

Infrastructure as a Service (IaaS)

IaaS provides virtualised compute, storage, and networking resources on demand. AWS EC2, Azure Virtual Machines, and Google Compute Engine are canonical examples. Organisations consume IaaS to replace or augment physical data centres without long-term capital commitments.

Platform as a Service (PaaS)

PaaS layers a managed runtime, middleware, and developer toolchain on top of IaaS. It removes the need for teams to patch or scale the underlying OS and runtime. Examples include AWS Elastic Beanstalk, Azure App Service, and Google App Engine.

Software as a Service (SaaS)

SaaS delivers fully managed applications over the internet under a subscription model. Salesforce, Office 365, Google Workspace, Dropbox, and Adobe Creative Cloud are among the largest SaaS products by revenue.

Cloud Bursting

Cloud bursting is a hybrid architecture pattern in which a workload running on private infrastructure automatically expands into a public cloud when local capacity is exhausted. It is particularly relevant for batch processing and seasonal traffic spikes.

Multi-Tenant Computing

Multi-tenancy is a core architectural principle of public cloud, allowing a single provider infrastructure to serve many customers with logical isolation between them. It is foundational to the economies of scale that make public cloud pricing competitive.

Resource Pooling

Resource pooling refers to the provider’s ability to aggregate physical resources and dynamically allocate them across customers, a core characteristic in NIST’s definition of cloud computing.

Market Segmentation by Vertical / Application

Demand for public cloud services was analysed across the following industry verticals in the report:

• Government – sovereign cloud requirements, compliance mandates, and digital transformation of citizen services.
• Private Organisations – broad enterprise adoption across manufacturing, retail, media, and professional services.
• Academics and Education – remote learning platforms, research computing, and student information systems.
• Banking, Financial Services, and Insurance (BFSI) – high-compliance workloads, real-time payments infrastructure, and risk analytics.
• Healthcare – electronic health records, medical imaging, and AI-assisted diagnostics, subject to HIPAA and regional equivalents.
• Supply Chain Management – real-time inventory tracking, demand forecasting, and logistics optimisation.

Geographical Scope

The report’s regional analysis covered the following geographies, with attention to market share, projected growth rates, and emerging opportunities in each:

• United States – the largest single market, home to the three dominant hyperscalers.
• China – a distinct competitive environment dominated by Alibaba Cloud, Tencent Cloud, and Huawei Cloud, with significant regulatory separation from Western providers.
• Europe – growth driven by GDPR compliance requirements and increasing data residency demands, with rising sovereign cloud initiatives.
• Japan – mature enterprise IT market undergoing cloud-first policy adoption.
• Southeast Asia – high-growth emerging market with rapid mobile-first cloud adoption.
• India – rapidly expanding developer ecosystem, significant public-sector cloud initiatives, and growing startup demand.

Key Market Dynamics

Drivers

• Shift from capital expenditure to operational expenditure models.
• Growing demand for elastic compute for AI, ML, and big data workloads.
• Proliferation of DevOps and CI/CD practices requiring on-demand provisioning.
• Remote work and distributed team enablement.

Challenges

• Data sovereignty and cross-border data transfer restrictions.
• Vendor lock-in risk with proprietary managed services.
• Security and shared-responsibility model complexity.
• Unpredictable egress and inter-region data transfer costs.

Opportunities

• Edge computing extending cloud capabilities closer to end users and IoT devices.
• Multi-cloud strategies reducing dependence on any single provider.
• Expansion of cloud marketplace ecosystems enabling ISV distribution.
• Managed Kubernetes and serverless platforms lowering the barrier to cloud-native development.

Report Structure at a Glance

For practitioners assessing whether the full Innovate Insights report suits their needs, the table of contents covers the following major areas:

• Global market size (volume and value) and forecast through 2026.
• Regional market share breakdown and growth rate projections.
• Competitive landscape with company profiles, pricing models, and gross margins.
• Service-type segmentation with revenue and growth data per segment.
• Vertical application segmentation with demand and growth data.
• Marketing channel analysis (direct vs. indirect).
• Market dynamics: drivers, challenges, and influence factors.
• Research methodology and data triangulation approach.

Takeaways for DevOps and Cloud Engineering Teams

Market reports of this type are most useful when cross-referenced with your own procurement and architecture decisions. A few practical considerations:

• Provider selection – AWS, Azure, and GCP continue to dominate IaaS/PaaS revenue. Niche providers (Rackspace, Navisite) remain competitive for managed service overlays rather than raw infrastructure.
• Service model clarity – Clearly distinguishing IaaS, PaaS, and SaaS responsibilities is essential for security posture and cost attribution. Each model shifts a different portion of the shared-responsibility stack to the provider.
• Vertical compliance – BFSI and healthcare workloads require explicit verification of provider certifications (SOC 2, ISO 27001, HIPAA BAA, PCI DSS) before migration planning.
• Multi-cloud strategy – The breadth of named competitors in this space underscores why multi-cloud governance tooling (cost management, policy enforcement, identity federation) has become a primary concern for platform engineering teams.

Source: themarketsegment.com / Innovate Insights – Public Cloud Service Market Research Report 2018–2026 (referenced September 2019).

Basis Technologies Brings SAP DevOps Automation to Major Fall 2019 Conferences

In September 2019, Basis Technologies announced it would showcase its automated DevOps and testing platform for SAP at three major industry events: SAP TechEd 2019 Las Vegas (September 24–26), DSAG-Jahreskongress 2019 in Nuremberg, Germany (September 17–19), and SAP TechEd 2019 Barcelona (October 8–10). The announcement highlighted both new technology demonstrations and customer case studies from organizations that had already adopted DevOps practices for SAP environments.

Proof of Concept: abapGit + Jenkins + ActiveControl

The centerpiece of the SAP TechEd Las Vegas appearance was a proof-of-concept demonstration of an end-to-end DevOps workflow for SAP, combining three tools:

• abapGit – An open-source Git client for ABAP, enabling distributed and independent development of ABAP-based SAP applications. By bringing Git-based version control to the ABAP layer, abapGit opens the door to branching strategies and collaboration models common in non-SAP software development.
• Jenkins – A widely used open-source CI/CD automation server, used here to orchestrate the pipeline.
• ActiveControl – Basis Technologies’ proprietary DevOps solution for SAP, providing automated change analysis, deployment orchestration, and audit trail capabilities.

The combination aims to give SAP development teams a more flexible, automated path from code commit to production deployment—while preserving the safety and compliance controls that SAP environments typically require. According to Basis Technologies CTO James Roberts:

“The combination of abapGit and ActiveControl is a great example of one way they may be able to increase speed and competitiveness without compromising on the safety, transparency and efficiency of their SAP systems.”

James Roberts, CTO, Basis Technologies

Why This Matters for SAP DevOps Practitioners

SAP landscapes have historically been challenging to integrate into modern DevOps pipelines. Traditional SAP transport management is sequential and manual, making continuous delivery difficult. Tooling like abapGit represents an effort to bridge SAP-specific development with mainstream DevOps practices by introducing source-code-level version control for ABAP objects.

Pairing abapGit with an enterprise-grade change automation layer like ActiveControl addresses a key concern for SAP operations teams: how to move faster without introducing regression risk into business-critical ERP systems. The proof-of-concept shown at SAP TechEd Las Vegas 2019 was positioned as an early-stage demonstration rather than a production-ready solution.

Customer Perspectives: Real-World SAP Automation Results

A notable aspect of the conference appearances was the presence of Basis Technologies customers sharing their own DevOps journeys. Speakers from the following organizations were scheduled to present:

• Interpublic Group (IPG)
• thyssenkrupp Steel Europe
• BJ’s Wholesale Club
• Newell Brands
• Booking.com

Orhan Ozalp, Executive Director of Global SAP Solutions at IPG, described the practical impact of their DevOps adoption:

“We decided to embark on a DevOps project and began building our strategy in 2018. We have observed significant productivity gains and now we can deploy our solutions quickly to our production environment without worrying about business disruption. We were doing a major release and a minor release every year … now we’re just continuously delivering.”

Orhan Ozalp, Executive Director, Global SAP Solutions, Interpublic Group

This shift from release-based to continuous delivery is a common goal in enterprise DevOps transformations, and IPG’s account illustrates how it can be achieved even in complex SAP environments.

The Basis Technologies Platform: ActiveControl and Testimony

Basis Technologies’ automation platform for SAP consists of two certified products:

ActiveControl

ActiveControl is a change and release automation solution built specifically for SAP. It handles automated analysis of transport requests, controlled deployment sequencing across SAP system landscapes, and provides a full audit trail of changes. The goal is to give teams the ability to deliver frequent, high-quality changes to production without risking system stability or business continuity.

Testimony

Testimony is described by Basis Technologies as the first Robotic Test Automation (RTA) solution designed for SAP regression testing. Unlike traditional SAP test automation approaches, Testimony does not require scripted test cases or ongoing test script maintenance. Instead, it captures real business transactions from production and replays them against updated systems to detect regressions automatically.

Both products are certified for SAP NetWeaver and SAP S/4HANA. Together, they are positioned to support a “shift left” testing approach, enabling teams to perform full regression testing for every release rather than only at major milestones.

Event Booth Details (Fall 2019)

Key Takeaways for SAP DevOps Teams

• The integration of abapGit with enterprise change automation tools like ActiveControl represents a meaningful step toward Git-native workflows for ABAP development.
• Continuous delivery is achievable in SAP environments, as demonstrated by IPG’s shift from annual releases to continuous deployment.
• Robotic Test Automation (RTA) approaches like Testimony offer an alternative to high-maintenance script-based SAP testing.
• Both ActiveControl and Testimony are certified for SAP S/4HANA, making them relevant to organizations planning or executing S/4HANA migrations.

This article is based on a press release issued by Basis Technologies in September 2019. Product capabilities and certifications should be verified directly with Basis Technologies for current accuracy.

The four practices below address the most common decision points teams encounter when standing up DevOps for SAP Cloud Platform: toolchain selection, developer freedom, landscape structuring, and proprietary service adoption.

1. Break Out to a Shared Enterprise DevOps Toolchain Where Possible

SAP Cloud Platform ships with built-in support for source control, basic CI/CD pipelines, and monitoring. These built-in tools lower the barrier to entry, but they come with trade-offs that compound over time.

If your organisation already operates enterprise-grade tooling, use it. A mature Git repository platform — whether GitHub Enterprise, GitLab, Bitbucket, or Azure DevOps — provides significantly richer branch protection rules, pull-request workflows, code review features, and external integrations than SAP Cloud Platform’s native Git infrastructure. Similarly, established CI/CD engines such as Jenkins or Drone, Agile tracking tools such as Jira or Azure Boards, and your existing observability stack will all integrate more cleanly with the rest of your engineering organisation.

Relying solely on SAP-bundled tooling creates two specific risks:

• Vendor lock-in: Teams build muscle memory and automation scripts around tools that are difficult to replace or migrate away from if your SAP deployment changes.
• Feature ceiling: Native SAP Cloud Platform Git infrastructure, for example, lacks many of the collaboration and governance features available in dedicated SCM platforms and can be cumbersome to access from outside the SAP environment.

Adopting a shared toolchain also benefits teams new to DevOps: they can learn industry-standard tooling with broad community support rather than SAP-specific variations of the same concepts.

2. Be Agnostic About Developer Tooling

Shared infrastructure such as version control, ticketing systems, and build pipelines must be standardised — that is non-negotiable. However, the local development environment a developer uses to interact with those systems should not be mandated from the top down.

SAP Web IDE (and its successor, SAP Business Application Studio) are reasonable defaults, and many developers will prefer them for SAP-specific tasks. But forcing every developer to use a single IDE carries real costs in ramp-up time, reduced productivity for those comfortable with other editors, and friction in hiring experienced engineers who have established workflows.

A better approach is to invest in infrastructure that exposes standard interfaces — standard Git remotes, open API contracts, documented local development setups — so developers can connect with their preferred tools. If you have already adopted shared toolchain practices from the first best practice, much of this groundwork is already in place. The goal is to give developers professional autonomy while maintaining consistency in the artefacts they produce.

3. Use Subaccounts for Tiered Landscapes

One of the most common architecture questions for SAP Cloud Platform DevOps is how to separate development, QA, and production environments. Should they be different applications, different SAP HANA spaces, or different subaccounts?

The recommended approach is to use separate subaccounts for each environment tier. Subaccounts provide the strongest isolation boundary — separate security configurations, service entitlements, and administrative scopes — which reduces the blast radius of misconfigurations and simplifies access control.

The downside is resource duplication. If you are running SAP HANA as your database layer, a three-tier landscape (development, QA, production) may require three separate HANA instances, which has cost implications.

Before accepting that duplication as inevitable, examine whether your DevOps process can eliminate a tier entirely. For example, teams using the SAP Cloud Application Programming Model (CAP) can often do meaningful local development against a local SQLite database and CAP’s Node.js modules, pushing integration testing to a shared QA subaccount rather than maintaining a dedicated per-developer cloud environment. Removing a tier from the cloud infrastructure can offset the subaccount duplication costs significantly.

4. Use SAP’s Proprietary Tools Where They Add Genuine Value

Recommending shared, agnostic tooling does not mean ignoring SAP’s own services. SAP Cloud Platform includes a catalogue of proprietary services — SAP Mobile Services for offline mobile applications, the ABAP environment for teams with existing ABAP expertise, Cloud ALM for application lifecycle management, and various machine learning services under the SAP Business Technology Platform umbrella — that can provide genuine capabilities not easily replicated with generic tooling.

The key is intentional adoption rather than default adoption. Ask three questions for each proprietary service you consider:

1. Does it solve a problem that shared tooling handles poorly? If yes, it may be worth the integration overhead.
2. Can it be integrated into your shared DevOps toolchain and processes? A service that cannot be invoked from your CI/CD pipeline or tested locally will create a gap in your automation.
3. What is the abstraction cost? Some services require wrapping in abstraction layers to enable local development and testing. That work is often worthwhile, but it should be planned and budgeted.

In the best cases, a proprietary SAP service is well-designed for integration and slots into your existing pipeline with minimal extra work. In other cases, you will need to build small extensions or adapters. Either outcome is acceptable as long as the decision is made deliberately, with eyes open to the integration effort involved.

Bringing It All Together

Each of these four practices — preferring shared toolchains, giving developers tool freedom, using subaccounts for landscape isolation, and selectively adopting proprietary SAP services — addresses a specific failure mode in SAP Cloud Platform DevOps implementations. They are not mutually exclusive; in fact, they reinforce each other. A shared toolchain makes developer agnosticism easier. Subaccount isolation makes pipeline promotion cleaner. Thoughtful proprietary service adoption avoids the gaps that toolchain agnosticism might otherwise create.

As with any DevOps implementation, the details matter — but so does stepping back periodically to ensure that the individual decisions you are making add up to a coherent, strategic approach that delivers long-term value for your organisation rather than short-term convenience that becomes tomorrow’s technical debt.

SAP Targets Manufacturing with Cloud and IoT Products

SAP announced a new suite of cloud-based products aimed at helping manufacturers monitor operations, integrate business systems with the shop floor, and collaborate across the supply chain. The offerings combine cloud computing with Industrial Internet of Things (IIoT) capabilities, signaling SAP’s push to move manufacturing customers away from on-premises-only deployments.

SAP Digital Manufacturing Cloud: Key Components

The umbrella product family, SAP Digital Manufacturing Cloud, is split into distinct modules addressing different operational needs:

• SAP Digital Manufacturing Cloud for Execution – Integrates ERP and other business systems with shop-floor operations. It provides component- and material-level visibility across both single-site and global multi-site installations, aiming to reduce the gap between enterprise planning and physical production.
• SAP Digital Manufacturing Cloud for Insights – Focuses on data-driven performance management. By aggregating operational data, it enables manufacturers to track key production metrics and identify trends that affect output and efficiency.
• Predictive Quality – Applies predictive algorithms to production data to anticipate defects, deficiencies, or process variations before they result in scrap or rework. The module is designed to recommend corrective actions automatically, reducing reactive quality management.

SAP Manufacturing Network: Collaboration Across the Supply Chain

Alongside the Digital Manufacturing Cloud, SAP unveiled a manufacturing network — a cloud-based collaborative platform integrated with SAP Ariba. The network is designed to connect manufacturers with service providers such as suppliers of 3D printing and CNC machining services, as well as raw material providers.

Within the platform, manufacturers can:

• Collaborate on part and product design in real time
• Highlight design changes and suggest alternative approaches
• Link design discussions and associated data directly to requests for quotation (RFQs)
• Solicit pricing from single or multiple suppliers and initiate purchasing workflows

The intent is to cover the full manufacturing lifecycle — from initial design through part production — within a single connected environment rather than relying on disconnected email threads or siloed procurement tools.

Connected Worker Safety: IoT Wearables in the Factory

SAP also introduced its Connected Worker Safety service, which aggregates data from wearables and environmental sensors to monitor worker health and workplace conditions in real time. The service collects data points including:

• Worker biometrics: heart rate and body temperature
• Environmental conditions: air quality, ambient temperature, light levels, and noise

When sensor readings cross defined thresholds, the application triggers alarms for incidents such as falls, injuries, dehydration, or fatigue. All data from connected wearables and other IoT devices is surfaced through a single dashboard built on a generic platform, reducing the integration complexity that typically arises when multiple device vendors are involved. At the time of announcement, the service was slated for release to customers within the same quarter.

SAP’s Strategic Position in Industrial IoT

Bernd Leukert, SAP’s executive board member for products and innovation, framed the launch around the broader IIoT opportunity:

“Our manufacturing cloud solutions help customers take advantage of the Industrial Internet of Things by connecting equipment, people and operations across the extended digital supply chain and tightly integrating manufacturing with business operations.”

Bernd Leukert, SAP Executive Board Member for Products & Innovation

The announcements reflect a broader industry trend in which ERP vendors are extending their platforms into operational technology (OT) domains — blending IT systems like ERP and procurement with factory-floor data streams and IoT device networks. For DevOps and platform engineering teams supporting manufacturing environments, this kind of convergence raises important questions around data pipeline architecture, device management, security boundaries between IT and OT networks, and integration patterns between cloud platforms and on-premises industrial systems.

Takeaways for Engineering and Operations Teams

• Integration complexity is the core challenge. Connecting shop-floor systems to cloud ERP requires robust, low-latency data pipelines and careful attention to protocol translation between industrial and IT standards.
• Predictive quality requires clean data. Algorithmic recommendations are only as good as the underlying sensor and production data; data quality and labeling strategies matter as much as the ML models themselves.
• Worker safety applications carry high reliability requirements. Any system raising alarms for health emergencies must have well-defined uptime SLAs, alerting fallback mechanisms, and clear incident response procedures.
• Supply-chain collaboration platforms introduce new security considerations. Opening design and procurement data to external suppliers expands the attack surface and requires careful identity and access management.

The SAP Regression Testing Problem

SAP environments must continuously evolve to keep pace with business requirements. But every update — whether a configuration change, a patch, or a major cloud migration — carries risk. Regression testing exists precisely to catch the unintended consequences of those changes before they reach production. The problem is that traditional regression testing in SAP is slow, expensive, and often delivers incomplete coverage.

Manual regression testing demands significant human effort: end-user recording sessions, business process discovery workshops, and the ongoing maintenance of test scripts. Automated testing tools have historically offered only partial relief, typically focusing on user interface (UI) interactions and still requiring considerable setup time. The result is that many organisations face an uncomfortable trade-off between test coverage and delivery speed — a trade-off that becomes acute during high-stakes projects like S/4HANA migrations or cloud re-platforming.

According to research cited by Basis Technologies at the time of this announcement, 66% of organisations using SAP software expected their regression testing burden to increase in the short term, and were actively seeking a cost-efficient solution.

Introducing Testimony and Robotic Test Automation (RTA)

Basis Technologies responded to this challenge with Testimony, a product built around a concept the company calls Robotic Test Automation (RTA). Rather than requiring manual test script creation or end-user recording sessions, Testimony automatically learns what needs to be tested and how — by observing real system usage.

The core RTA workflow works as follows:

• Automatic learning: Testimony monitors live SAP usage to understand actual business processes and execution paths, without requiring manual input from testers or end users.
• Automatic configuration: Based on what it has learned, the tool builds and configures a test suite that reflects real-world system behaviour.
• Automatic execution: Tests are run without manual intervention, validating new releases against the captured baseline.
• Automatic updates: As the system evolves, the test suite updates itself, reducing the maintenance burden that plagues traditional automated testing tools.

The practical outcome is that system-wide regression testing can reportedly be initiated within days rather than weeks or months, with no manual scripting phase required upfront.

Going Beyond the UI Layer

One of the most significant technical differentiators Basis Technologies highlighted is that Testimony does not limit its monitoring to the user interface. Many SAP regression test tools operate solely at the UI layer — an “outside-in” approach that misses what happens inside the system when a transaction is executed.

Testimony monitors SAP at both the UI layer and at the code-and-system level, capturing a broader range of execution paths and technical interactions, including:

• Remote Function Calls (RFCs)
• BAPIs (Business Application Programming Interfaces)
• Other internal technical interactions that UI-only tools would not observe

This deeper instrumentation means the resulting test plan covers significantly more of the system’s actual behaviour, reducing the risk of regressions that slip through a UI-only safety net.

Service Virtualisation for Integration Testing

Modern SAP landscapes rarely exist in isolation. They integrate with external systems — other SAP instances, third-party applications, and cloud services. Testing business processes that span these integrations has traditionally been difficult: either you require all connected systems to be available in the test environment (expensive and logistically complex), or you rely on incomplete stubs and estimated data (inaccurate and risky).

Testimony incorporates service virtualisation to address this challenge. It automatically isolates the SAP system under test from its external dependencies, capturing representative inputs and outputs from real interactions. During regression testing, these virtualised services stand in for the real external systems, allowing full end-to-end business process testing without requiring every connected system to be available or replicated in the test environment.

Enabling Shift-Left Testing and DevOps for SAP

A recurring theme in modern software delivery is shift-left testing — moving testing activities earlier in the development pipeline so that defects are caught closer to their point of introduction, where they are cheaper and faster to fix. For SAP environments, this has historically been difficult because of the overhead associated with test preparation.

By dramatically reducing the time and manual effort required to set up and maintain a regression test suite, Testimony is positioned to make shift-left testing practical for SAP. This aligns directly with DevOps principles: faster feedback loops, more frequent releases, and greater confidence in the quality of each deployment.

Early Adopter Perspective

Gavin Thornton, IT Senior Application SME – SAP at CBH Group, was among the first users of Testimony. He offered the following perspective at the time of the announcement:

“Testimony really is revolutionary. We were one of the first to use the product and the output immediately challenged what we thought we knew about the impact of change in our systems. It has already fundamentally altered the way we think about testing SAP software. We’ve evaluated automated testing tools before but until now none of them have successfully addressed our basic challenges. Testimony is different. It gives us a way to massively increase the speed and effectiveness of testing, so that we can deliver the changes that the business needs with much greater confidence.”

— Gavin Thornton, IT Senior Application SME – SAP, CBH Group

Key Capabilities at a Glance

About Basis Technologies

Basis Technologies is a software and services company specialising in DevOps tooling for SAP environments. Testimony was announced as an expansion of their DevOps Toolset in 2017. For current product information, capabilities, and availability, visit the Basis Technologies website directly, as product features and positioning may have evolved since this announcement.