Kubernetes has been effectively dominating the DevOps universe for the last few years. It is surely winning because of the virtues it has to offer for a fast-paced development environment. Kubernetes is the de facto platform for orchestrating containers and belongs at the core of cloud-native applications. Due to a broader ecosystem, we must provide better security support to the Kubernetes environment. The rising use of Kubernetes, containers, and microservices on a broad scale is giving birth to complex security problems. So, we need to devise cutting-edge solutions for these problems. Going further, we will why it is so complicated and how Artificial Intelligence can help.
of backend developers globally use Kubernetes.
of IT shops prefer DevSecOps as the best way to ensure strong Kubernetes security.
of hiring managers in the IT industry demand cloud and container technologies including Kubernetes.
of IT professionals integrating Kubernetes environment into their infrastructure expect it to reduce their annual costs by 20% or more.
Artificial Intelligence is a set of intelligent machines and smart algorithms that have the potential to perform complex tasks instead of human intelligence. AI machines have the ability to learn from experience, adjust to new inputs, and perform tasks as humans do.
Kubernetes, as the most popular container orchestration platform, is used by the top cloud service providers including Google Cloud, Amazon Web Services, and Microsoft Azure. A large user base and an increasing number of users are making it more prone to cyber threats. The security threats in Kubernetes and container environments are not just as straightforward as they are in conventional aspects of the IT infrastructure.
It might seem like a smooth ride when you start off. But as you progress, things start to get tricky. If anything is broken, you need an expert to handle and resolve the complex problems coming your way.
With all these complex issues, when you need to address a security incident, it becomes a tough challenge. AI can prove to be a great ally for your security teams in the battle against continuously evolving cyber threats. It can help your Kubernetes environment stand against vicious attack vectors that are usually sophisticated and hard to detect and mitigate.
The community developing and using Kubernetes takes security very seriously. Kubernetes comes with several security protocols by default. For instance, the control plane is locked down and there are no privileged containers. There is high-end encryption between APIs and Kubernetes also has the ability to limit communication between services. Moreover, it is declarative in nature. So, you can add more security parameters to it. It also allows you to deploy the “shift left” approach for ensuring top-notch security levels. This helps the operation teams to avoid security issues at the time of deployment and after it as well.
However, there are more than enough chances of making a mistake. And even one such mistake can bring down the whole infrastructure. If you make lapses in carrying out any process, it might leave a bolt loose making the whole Kubernetes environment insecure. These lapses might include directly editing a deployment instead of the manifest. Sometimes users turn off the default security controls to make their tasks easier for a short time. This short-lived convenience might result in catastrophic incidents later.
As you can see in the above paragraph, all the security lapses are originating from human error. AI replaces human intelligence with advanced algorithms. Along with it, it eliminates the scope of human error in Kubernetes security.
Nowadays, we see a huge influx of data in the Kubernetes environment. AI can help in streamlining the flow of data. Furthermore, it has the potential to troubleshoot efficiently if any roadblocks come in the way of this influx.