Transforming Data Management Through Cloud-Native Computing
As we move deeper into the digital age, the demand for faster and more agile data management and storage solutions increases. Consumers today create, access, and consume massive amounts of data on a daily basis.
To adapt to this increased consumer demand for data, we must leverage cloud-native technologies to transform data storage deployment and access.
The Shift to Cloud-Native Models
Among the major transformations in the industry today is the shift of enterprise IT apps and infrastructure to cloud-native models. In fact, IDC FutureScape predicts that by 2023, cloud-native approaches will be used to develop and deploy over 500 million digital apps and services.
This accelerated shift to cloud-native will also transform data storage deployment.
Container Deployment and Microservices
Deployment in cloud-native computing environments relies on containers that offer the benefits of portability, agility, and scalability. Enterprises shifting to microservices architectures can leverage containers in implementing their applications. As Monolithic architecture can be a burden In implementing new features and sending them out to Consumers as it will require code changes from all members on the cloud, require intensive upfront integration & functionality testing & development teams are restricted to use one or two languages max
Containers are designed to run reliably as they are transferred from one environment to another, whether private or public clouds. They are also lightweight and can be run simultaneously on a single server. Moreover, they have impressive modularity, enabling apps to be split among several containers for faster deployment. They can also package several apps together with libraries while providing isolated environments to run services.
Database server containers are also fast gaining popularity due to their compatibility with automation tools. They offer reliable speed and efficiency in data environments. Because they are extremely efficient, they are effective with CI/CD approaches. Containers also provide a cost-efficient solution to data management and storage since it is possible to run several containers on the same infrastructure.
They are also easy to integrate with third-party solutions. Lastly, database containerization enables enterprises to seamlessly scale their operations on multiple cloud platforms.
Cross-Cloud Workload Management
The Flexera 2020 State of the Cloud Report shows that 93% of enterprise respondents have a multi-cloud strategy with 87% of them utilizing hybrid cloud. With workloads managed across different clouds, enterprises switch from one cloud to another to store and access data. Kubernetes and cloud-native tools make this switch simpler and faster. Their portability and extensibility enable enterprises to manage cross-cloud workloads with ease.
As the cloud-native market matures, we’ll likely see a marked decrease in architectural dependence on cloud providers.
Evolution of Data Management
As our need for data grows, data management will continue to evolve. There will be a constant need to look for new solutions to meet changing demands from both consumers and business enterprises.
There will be a greater need for speed, accuracy, and scalability.
Today, cloud-native computing delivers these. To remain competitive in an increasingly fast-paced and dynamic landscape, you must optimize the use of cloud technologies through agile cloud-native architecture.
- Bajaj, D., Bharti, U., Goel, A., & Gupta, S. C. (2020, May). Partial Migration for Re-architecting a Cloud Native Monolithic Application into Microservices and FaaS. In International Conference on Information, Communication and Computing Technology(pp. 111-124). Springer, Singapore.