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// PREDICTIVE INTELLIGENCE // of the time , they meant they were going to virtualise their environment .
With Kubernetes , however , regional enterprises now have skilled teams in place ( skillsets are quite unique in this space ) and because it is controlled by developers and not infrastructure teams , there is a much better and deeper understanding which ultimately leads to high quality deployments .
In Saudi Arabia , which is one of the biggest IT markets in the region , government agencies are the leading adopters of Kubernetes technologies , followed by banks and financial institutions . Typically , these organisations have a large number of users of digital services . The reasons for high adoption rates are clear .
Government entities providing public services are unable to predict the number of users that will be accessing their services . If they decide to go with a traditional IT model of physical infrastructure and virtualisation and estimate that a maximum of 50,000 users would access their systems , then they would need to pay upfront for an infrastructure that can accommodate all these users , involving an undesirably high CAPEX .
With Kubernetes , as explained earlier , because services and applications are decoupled from the data and the operating system , those services can scale up and down easily and the customer doesn ' t need to make a huge upfront investment to have dedicated physical servers for each application or service or each operating system . The self-healing aspect of a Kubernetes environment is another big advantage . Any microservice or replica of a microservice that is not running properly can be restarted easily without affecting the overall service . Self-healing translates to better uptime in terms of the availability of the service to customers and end users .
The competitive nature of the banking and financial industry is a big driver for Kubernetes adoption . Banks are constantly trying to be the first-to-market when it comes to innovative applications and services . Kubernetes short circuits the laborious app provisioning cycle , making it quick and easy to spin-up apps .
Protecting Kubernetes environments
There is no doubt that the attack surface is growing as more companies adopt containers and do their orchestration using Kubernetes . The complexity that early adopters are finding is the lack of data management and data integrity when it comes to protecting Kubernetes and container workloads .
Kubernetes and containers are often compared to virtual machines , but it is a very different approach . It is very much focused on a different persona . The person that looks after the life cycle of containers in a Kubernetes environment is not your traditional operations infrastructure admin . They are focused on the application and have more of a DevOps function , but also understand the platform where the application lives . Bringing the infrastructure or platform closer to the application carries its own benefits anyway . But this same approach means that data integrity has to be looked at differently than how we approach virtual machine backup .
Kubernetes environments require an application-centric approach over an infrastructure focus . This is why regional enterprises need to look at modern data protection technologies that work against a wide range of Kubernetes application stacks and deployment methods . �
Mohamad Rizk , Regional Director , Middle East & CIS at Veeam Software
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