Every building needs an underlying architecture that defines how it will be designed, shaped and ultimately constructed. The architect incorporates many components into his planning and supervises the entire construction process. The Industrial Internet of Things (IIoT) is also based on such architecture – most commonly this is the so-called cloud architecture. Cloud architecture refers to the underlying infrastructure and the components that support the cloud. For the construction, the cloud architect must consider the use of databases, the software function, as well as the applications that the cloud provides. To begin with, the question is which cloud computing deployment model and which service model is right for your organization to get started with IIoT. For this purpose, we would like to provide you with an overview that can support you in your decision.
Cloud computing deployment models
Cloud condition and architecture depend primarily on what the cloud is needed for. You may have heard of the two most popular models – the public cloud and the private cloud. However, in addition to these two, there are a variety of other models, each with its own structure, requirements and associated advantages and disadvantages. These include:
- Public Cloud: The public cloud is suitable for a wide audience. The resources that comprise the cloud environment do not belong to the end users and can be redistributed to multiple clients. For example, “Gmail” is a public cloud because it is available to many users, but the cloud environment does not belong to the users.
- Private cloud: In contrast to the public cloud, the private cloud is available to a smaller number of users (only the end users). The private cloud can also be hosted and managed by a company’s own data center, for example. The code for the “Google Mail” application is made available in a private cloud for instance.
- Hybrid cloud: The hybrid cloud represents a mixture of private cloud and public cloud. Accordingly, it combines the advantages of both models and is very versatile. Thus, on the one hand, the data protection requirements of the private cloud and, on the other hand, the high flexibility of the public cloud are achieved. However, the parallel use of the two types of cloud also increases the complexity of the IT infrastructure. An example of the hybrid cloud would be the use of “Google Mail” in conjunction with a separate Outlook account.
- Community cloud: The community cloud is a special case that arises rather rarely. Here, IT infrastructures are used and provided by several companies via the cloud. However, they are not publicly available, but are restricted to a selected group of users. This model is suitable for universities or for different companies that want to work together. They can then work jointly on a document in the Google Cloud, for example.
- Multi Cloud: The Multi Cloud represents a further development of the Hybrid Cloud. Several cloud models are integrated and thus enable users to use the services, applications and infrastructures on the cloud structures of different providers simultaneously. The individual services can therefore be obtained from the most suitable provider in each case, depending on requirements, performance and price. For example, it is conceivable to use the storage space from Dropbox, the web services from Amazon and the computing capacities in the Google Cloud.
Different service models in the cloud
IT services are provided as services via the Internet. They can relate to five different components. Choosing the right model also raises the question of what the cloud will ultimately be used for. The most important service models are:
- Infrastructure as a Service (IaaS): IaaS provides a scalable IT infrastructure, such as computing power or data storage. Companies can use their own applications and platforms in the infrastructure offered by the service provider. An example of an IaaS is the “Compute Engine” of the Google Cloud Platform (GCP).
- Container as a Service (CaaS): With this model, customers can use services related to container-based virtualization. The resources for virtualization – such as computing power, storage space and container engine – are provided by the service provider. The “Google Kubernetes Engine” is such a tool.
- Platform as a Service (PaaS): With PaaS, an entire platform is provided in addition to the infrastructure, on which application components can be developed, managed and deployed. This platform (in the GCP the “App Engine“) is equipped with everything needed for the development of new software.
- Function as a Service (FaaS): FaaS is a serverless cloud computing model. While the provider makes individual functions available to the user (in the GCP the “Google Cloud Function“), the actual infrastructure of the provider remains hidden from the user. The user gets results back from the functions and can use them to develop, operate or manage applications.
- Software as a Service (SaaS): In this model, application software is operated and supported by an external service provider and made available to the customer via the Internet. One example is the “Google Mail” application software. This allows users to store and analyze data without having to worry about managing the software.
The scitis.io solution can be classified as Platform as a Service and Software as a Service, as it provides a platform for users on the one hand, and also offers software components on the other.
Components of a cloud architecture
A building always consists of certain basic elements such as the floor, the roof and the walls – in interaction, they enable a safe and reliable stand. In the same way, cloud architecture is also based on certain components that are meaningfully connected with each other.
For the end user, the frontend represents the visualized user interface. More precisely, the user accesses the backend via the Internet, but can see the frontend provided for him. The backend includes the areas: security, management, service, storage and application. It takes care of all background calculations – this includes checking whether a user is allowed to log in, the user’s access permissions, but also transferring data from the end device to the corresponding storage.
The scitis.io Cloud Architecture
- IoT Core: IoT Core is a communication service that is especially important for device management and authentication. IoT Core guarantees secure device connectivity and management for data from millions of devices around the world.
- Big Query: The Big Query is responsible for the persistent storage of data and makes it possible to evaluate, analyze and forecast data in real time.
- Cloud storage: The Cloud storage is a particularly important component of data storage. All important information and metadata are stored in the cloud storage. For each entry there is a so-called entity that contains various information. Entities can be edge devices or machines, for example, for which the corresponding information is then obtained.
- App Engine: Various framework services are provided within the App Engine:
- The default version of the App Engine is responsible for the frontend application. All stylesheets that are displayed to the end user are stored here.
- The Cloudplug (or Device) backend provides a service for processing data from edge devices.
- The user backend is used to manage users, roles and permissions.
To see how companies have used and benefited from the scitis.io architecture, feel free to take a look at some of our case studies. Perhaps one or the other use case can also be transferred to your company?
The question of which cloud computing deployment model and which service model is right for you and your business can only be assessed on an individual basis. But one thing is certain: the cloud offers you endless possibilities. In fact, the services used by scitis.io on the Google Cloud Platform represent only a fraction of what exists in the Google Cloud cosmos. Take your time when deciding on your cloud architecture – just as you would take your time when building a house. Because the architecture represents the foundation for further decisions and a secure future in the Industrial Internet of Things.
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