Industrial Use Cases of Kubernetes : Nokia
Content of this blog
- About Kubernetes
- Case Study : Nokia : Challenges
- Case Study : Nokia : Solution
About Kubernetes
Kubernetes is an open-source container orchestration tool that could automatically scale, distribute and manage fault tolerance.
It was first released in 2014, originally created by Google and then it was donated to Cloud Native Computing Foundation. It is widely used in production environments, to handle container tools in a fault-tolerant manner.
Due to its open-source nature, it is available on various platforms and systems like Google Cloud, Microsoft Azure and Amazon AWS. It provides a new way to deploy applications using containers by creating an abstraction layer which could be manipulated with declarative rather than imperative programming which makes it much simpler to deploy and upgrade services over time
Case Study : Nokia- Enabling 5G and DevOps at a Telecom Company with Kubernetes
About Nokia
Nokia Corporation is a Finnish multinational telecommunications, information technology and consumer electronics company. It was founded in 1865 and it’s headquarters are in Espoo, Finland.
Challenges
- Core business of Nokia involves building telecom networks end-to-end and its main product are related to the infrastructure, such as antennas, switching equipment and routing equipment.
- Also, to deliver their software to several telecom operators , they need to put the software in their infrastructure , and each of the operators have a bit different infrastructure.
- There are operators that also runs on bare metal , virtual machines or on VMware Cloud or OpenStack Cloud.
- Thereby, they needed a solution that would help them in running same product on all of these infrastructures without making the changes in the product itself.
Solution
- The solution included moving to cloud native technologies that allowed the teams to have infrastructure-agnostic behavior in their products. The simplicity of label-based scheduling acted as indicator of the possibility of the scalability of the architecture.
- They reduced their dependencies on the system by separating the infrastructure and the application layer , which made the implementation of features in the application layer easier.
- The teams started testing the exact binary artifacts independent of target execution environment , thereby allowing them to detect errors in the early phases of the testing. It also eliminated the need to run the same test on different target environments .
