The Cloud & Resilience In Companies: 4 Stages Of Implementation

Resilience is an issue that concerns more and more companies. Rapid digitization and the associated use of the cloud are critical drivers of this relatively new requirement for IT.

To bring resilience in companies in connection with the cloud, a basic definition is worthwhile in the first step: Resilience describes the permanent and resilient functional reliability of all IT-technical areas that are important for a company’s business – regardless of whether the systems are in an in-house data center or the cloud.

The Principle Of Resilience In Companies: 4 Pillars

  1. Resilience in companies ensures that IT systems recover from a failure – as independently as possible.
  2. Resilience in companies can absorb incidents.
  3. Resilience in companies describes the ability to function even on the edge of system boundaries.
  4. Resilience in companies includes the sustainable adaptability of systems, for example, with the help of artificial intelligence (AI).

Resilience is not new and has been practiced for many years, for example, in critical infrastructures such as power supply. The same applies to the operation of satellites or hospitals. Today, due to digitalization, many companies are in a situation where even minor failures could cause damage or even trigger a cascade of damage. That is why resilience is now needed on a larger scale.

Resilience In Companies – The Cloud Is Resilient

Implementing resilience in the in-house data center is a challenge, especially since it is not a rigid system but is subject to iterative, i.e., continuous adaptation and change. As soon as components in the system are changed, the resilience also needs an adjustment. However, those who rely on the cloud have an advantage. Because the cloud already brings a large part of resilience inherent to the system. To make this clear, it is worth making an analogy between the cloud and vehicle leasing. The parallelism and importance quickly become apparent if you look at both the cloud and leasing as a service concept.

Cloud And Resilience Level 1

In the case of a leased vehicle, the manufacturer takes care of the operation. In the event of a defect, the manufacturer ensures it is rectified without the vehicle owner doing anything himself—quite the same with cloud services. You book a virtual system that is part of a more extensive network. The cloud provider ensures reliability, failure safety, and, above all, independent recovery. The cloud is redundant, and thus the first level of resilience is fulfilled without the user having to do anything.

Cloud And Resilience Level 2

If there is a significant problem with a leased vehicle, the owner is protected from all eventualities. He gets a replacement vehicle or even an exchange. Stage two, i.e., the absorption of disruptions, is also fulfilled in the cloud. The cloud provider ensures that the services continue to run for the user without any interruption. This level does not exist in the cloud, as there is theoretically no limit to the resources.

Cloud And Resilience Level 3

If the lessee has decided on a small city runabout and the situation arises that he has a lot to transport over the long term, he swaps his vehicle for a larger one. Operation at the edge of the system limits is the domain of the cloud. The resources are consistently well above the level required by the individual user. With appropriate contracts and SLAs (Service Level Agreements), even peak loads can be variably covered. This means that the cloud can make resources available even at the edge of the system’s boundaries.

Cloud And Resilience Level 4

The further development of vehicle technology is the responsibility of the manufacturer. The lessee only uses the vehicle and knows that he is constantly updated with updates or regular changes. According to the principle of resilience, systems must adapt sustainably and independently. Therefore, a certain level of intelligence is required, which some specialized cloud providers also offer using artificial intelligence (AI).

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