IaaS (Infrastructure-as-a-Service), PaaS (Platform as a Service), SaaS (Software-as-a-Service), serverless Computing
Cloud computing refers to the provisioning of computing resources (e.g. servers, storage, network components, databases, development tools, software, such as analysis software from the fields of IoT, artificial intelligence or big data) via the Internet, i.e. the cloud. Cloud computing offers companies faster innovation, flexible resources and economies of scale. As a rule, payment is only made for cloud services that are actually used. Cloud computing helps companies reduce operating costs, make their infrastructure more efficient and scale on demand.
One of the main advantages of cloud computing services is the possibility of elastic scaling. With cloud computing, companies can provision exactly the amount of resources that is needed. These resources can be scaled up or scaled down very flexibly if business requirements suddenly change.
Accelerate innovation with easy access to a variety of technologies. Resources scale to meet needs. This applies to infrastructure services such as data processing, storage and databases as well as to big data analytics, machine learning, Internet of Things (IoT), data lakes, etc.
Cloud computing services offer a number of advantages over an on-premises data center, such as lower network latencies for applications and greater cost savings. The reason: Cloud services run in a global network of secure data centers that are regularly updated to the latest generation of faster, more efficient computing hardware.
Since cloud computing services are on-demand and often self-service offerings, even very large amounts of computing resources can be deployed in minutes. This deployment can usually be realized with just a few mouse clicks. The pressure associated with capacity utilization planning is thus a thing of the past, so that companies benefit directly from this flexibility.
Cloud computing simplifies data backup, disaster recovery, and business continuity by allowing data to be mirrored across multiple redundant locations on the cloud provider’s network. The major cloud providers also provide numerous policies, technologies, and controls to protect customers’ data, apps, and infrastructure from potential threats.
The cloud eliminates large capital investments for hardware (such as data centers and servers). Instead, companies only pay for the resources they actually use. In addition, the variable costs are also significantly reduced by the mentioned elasticity and faster development compared to the self-supervised provision
There are many different varieties in cloud computing. Companies should carefully check which one is suitable for their own regulations and requirements. areto supports you in identifying cloud models, cloud types and cloud services in order to find an ideal solution for the company.
As a first step, determine the type of cloud deployment – the cloud computing architecture on which your cloud services are to be implemented. There are three ways to deploy cloud services: public cloud, private cloud, and hybrid cloud. Let’s take a closer look at the alternatives:
In the public cloud, hardware, software, and other supporting infrastructure components are owned by the cloud provider. They are managed by the latter and shared with the users (so called cloud tenants). These cloud mandates can access all cloud services via a web browser. areto customers use a public cloud, for example to provide storage as well as development or test environments.
In a private cloud, services and infrastructure always remain in a private network, and hardware and software are used exclusively by the organization. A private cloud can be physically located in the organization’s on-premises data center or hosted by a third-party cloud service provider. Private cloud is often used by government agencies, financial institutions, and organizations that must follow strict data retention regulations.
With the hybrid cloud, the on-premises infrastructure or private cloud is combined with a public cloud, so that it is possible to move data as well as apps between the two environments.
As a result, companies are able to meet regulatory requirements or data sovereignty requirement and are better able to exploit investments in local technologies or solve problems with low latency.
Most cloud computing services fall into four basic categories: IaaS (Infrastructure-as-a-Service), PaaS (Platform as a Service), SaaS (Software-as-a-Service), and Serverless Computing.
IaaS includes the basic building blocks for cloud IT. It typically provides access to networking features, computers (virtual or dedicated hardware), as well as data storage. IaaS gives the maximum flexibility and management control over IT resources. It is very similar to existing IT resources that many IT departments and developers are already familiar with.
PaaS (Platform-as-a-Service) is a complete development & deployment environment in the cloud – from simple cloud-based apps to mature cloud-enabled enterprise applications. PaaS includes Iaa’s infrastructure components, but also offers middleware, development tools, business intelligence services, database management services and much more. With PaaS, web applications are quickly built, tested, deployed, and managed.
SaaS (Software-as-a-Service) is a software solution that is purchased from a cloud service provider based on a pay-as-you-go payment model. Users can connect to and use cloud-based apps over the Internet. All underlying infrastructure, middleware, app software, and all app data are managed by the vendor. This also ensures the availability and security of the app and the data.
Serverless computing focuses on building app capabilities. Developers save the time to manage the servers and infrastructure required for this. Setup, capacity planning, and server management are handled by the cloud provider. Serverless architectures are highly scalable and event-driven.
The ability to gain new insights from the analysis of one’s own data has become an immediate competitive advantage. In the future, it will shape the value creation of companies. However, transforming data into valuable business value is a complex issue that can easily lead to the use of dozens of technologies, tools, environments. areto has a wealth of experience in the conception and implementation of cloud analytics projects. We look forward to helping build your enterprise-wide cloud analytics solution.
Amazon Web Services (AWS) is the world’s most comprehensive cloud platform, with more than 200 services delivered in globally distributed data centers. Our customers rely on AWS to become more agile, reduce costs, and innovate faster.
The Azure cloud platform consists of more than 200 products and cloud services and is designed to help you develop new solutions. So you can address current challenges and pave the way for the future. You can develop, run and manage applications – in multiple clouds, on-premises or at the edge. You can use the tools and frameworks of your choice.
Increasing data volumes, new data types, more complex processes as well as increasing requirements of the business areas lead to new challenges for DWHs and analytics. At the same time, cloud solutions are changing the way data is stored, structured and retrieved.
Cloud data warehouses make it possible to react adequately to changing requirements. With cloud data warehousing, organizations can now scale out to meet either compute or storage needs as needed. This can significantly reduce the costs of over-provisioning servers at traditional DWHs.
Another advantage of the Cloud Data Warehouse is its flexibility. In the past, IT teams had to estimate how much storage capacity was needed for their business units. Due to the problem-free scalability of cloud data warehouses, the risk of long-term undeniable miscalculations is almost completely eliminated.
Matillion Data Loader impresses with a simple, intuitive user interface, simple configuration using a wizard and the SaaS-based platform. This allows developers to quickly set up data pipelines without having to worry about coding or infrastructure.
Scaling data warehouses in the cloud is much easier compared to on-premise warehouses
Cloud-based warehouses are cheaper to set up because there is no hardware or upfront licensing costs
It’s quick and easy to get a cloud data warehouse up and running. Deploying an on-premises data warehouse takes much longer
Cloud data warehouses are optimized for analysis. High performance for complex queries through massively parallel processing (MPP)
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