Infrastructure via Drag & Drop
| Author / Editor: Henrik Hasenkamp / Florian Karlstetter
"Infrastructure as a Service" (IaaS) allows companies to set up their server landscapes in an uncomplicated and cost-effective way. It is important to reduce IT costs by making operation as simple as possible.
Servers, storage, load balancers, firewalls, IP addresses, SSH keys, API tokens, RDBMS, in-memory storage - setting up an optimal IT infrastructure for companies is time-consuming and complicated. But that's only half of the truth. Because what can take considerable know-how and many admin hours in a data center is a matter of a few minutes with an infrastructure service in the cloud.
IaaS allows users to quickly build their server landscape and use it immediately. The technological basis of IaaS is the data center technology working in the background as well as its abstraction in a software layer, which allows an extensive automation of all operations necessary for IT infrastructures.
This basis results in fast provisioning and rapid scaling of resources - servers, but also processor cores or storage space can be adapted immediately and even automatically. This provides customers with much greater convenience than traditional hosting services. Once the infrastructure is in place, they can focus on their own projects and core business. If something needs to be adapted to the infrastructure, there are no annoying waiting times.
Understanding the user interface quickly
Above this is the user interface. It is the central element for a positive user experience. This user experience is summarized in technical jargon with the abbreviation "UX" (for User Experience) and is an increasingly important part of software engineering.
Behind this lies the realization that UI/UX is more than just a few appealing design elements and icons on the screen. Because the workflows possible with the user interface in the narrower sense as well as its design in the context of current system states determine the user experience. Especially for non-technical users it is important that they understand the user interface quickly, can use it intuitively and reach their goal easily.
The design of the user interface must therefore be clear and graphically clean. In the context of IaaS, for example, the server and storage objects are merged with the mouse using drag & drop to form infrastructures. In addition, the user should only see those functions that he currently needs. The user interface of gridscale looks accordingly: It is clearly structured and offers only those functions that are important in the respective context. In addition, there is an expert mode that supports experienced users with high requirements.
Easy-to-use infrastructure services of this quality are only possible if new approaches are implemented in data center operations and if the focus is on maximum efficiency - through automation and machine learning. gridscale does this in two ways: by collecting data in the data center and by monitoring actual user behavior.
Machine Learning automates data center operations
The determination of typical operational data in a data center can be used for dynamic capacity management. It ensures that, from the customer's point of view, availability is 100 percent. This is achieved by a concept that has rarely been used in cloud services so far: Predictive maintenance using self-learning algorithms. The concept is known from industry 4.0 and is implemented very similarly in data centers: sensors record important operating data and software for machine learning examines them for unusual patterns.
In a data center, these could be temperatures inside and outside the housings, voltage levels or latency times. Deviations from normal values often announce disturbances and failures. After some time of training, the algorithm can distinguish between normal and abnormal states. Problems of all kinds can be detected before they actually occur. This makes it possible to reduce "downtime" to zero from the user's point of view.
But there is more that can be done with data and machine learning, such as developing automation functions for the customer. The actions of users in their dashboards continuously generate data. These can help to better understand the customer and customize the user interface and experience of the platform to best address the user's problem.
For example, many users take regular snapshots, some perhaps daily, others weekly. Developers can now try to make this behavior easier by simplifying the user interface, for example by adding an automation feature. The practical result is a planning function that regularly saves snapshots as backups.
Optimization of the user experience
The statistical evaluation of real-time user data also serves to adapt the user interface to the respective active customer. For example, each user sees different selection and detail options according to their technical experience. In addition, the algorithms of the user interface make a kind of assessment of the user actions. They make different suggestions, depending on what the user is likely to want to achieve. In this way, users only receive the options that are relevant to them. This allows data analysis to be used to optimize the user experience (UX) and dynamic provisioning with customized visual interfaces becomes possible. As a result, customers from SMEs or agencies can easily set up their own virtual data center.
The cloud variants IaaS and Platform as a Service (PaaS) are thus opening up a new market driven by the digital transformation of the economy. One important consequence: IT-supported products, services and business models are now shaping every industry. For this reason, the possibilities offered by information technology are no longer only used by experts. This requires suitable offerings on the market that are as easy to use as possible. The provision of IT infrastructure should be uncomplicated: one mouse click and the new IT resource should be available.
The original article in german can be found here.