In a recent development, Cloudera announced the culmination of the enterprise data cloud with the premiere of Cloudera Data Platform Private Cloud (CDP Private Cloud). CDP Private Cloud is built for hybrid cloud, enabling enterprises to seamlessly connect their on-premise private clouds to public clouds with consistent, built-in security and governance.
While the enterprise data cloud delivers powerful, self-service analytics across hybrid and multi-cloud environments, CDP Private Cloud, supported by Red Hat OpenShift, completes the vision of an enterprise data cloud with a powerful hybrid architecture. It is powered by Kubernetes, that separates compute and storage for greater agility, ease of use, and more efficient use of private and public cloud infrastructure.
CDP was launched in 2019 and has since seen a strong adoption momentum in the Asia Pacific across numerous sectors, including telecommunications, public sector, financial services, and manufacturing, among others. CDP Private Cloud modernizes data platforms by leveraging decoupled storage and compute with containers and Kubernetes to accelerate time value by 10x. This ensures critical workloads meet their SLAs, realizing the vision of a consistent hybrid data cloud.
“The culmination of the vision for an enterprise data cloud allows the business to navigate complex data processes across multiple clouds, manage data governance, and enable multi-function analytics, regardless of where the data resides,” said Mark Micallef, vice president of the Asia Pacific and Japan, Cloudera.
Vinod Ganesan, country manager – India, Cloudera said that highly regulated industries in India like telecom, banking, and financial services, have security, governance and regulatory compliances that can sometimes restrict business flexibility. As businesses strive to swiftly respond to evolving market conditions, it may cause the rise of shadow IT.
“Our CDP private cloud helps organizations leverage the complete power of the cloud for agility while enhancing their security, governance, and compliance capabilities. It also serves as the crucial data foundation for AI-driven organizations by allowing data scientists to provision compute on demand without affecting regular mission-critical workloads,” he said.
It will have the following benefits:
- Easily deliver data analytics and machine learning services, up to 10x faster than traditional data management solutions and cloud services to react faster to changing business requirements and eliminate the risks of shadow IT.
- Meet the exponential demand for data analytics and machine learning services, with a Petabyte-scale hybrid data architecture that can flex to use private and public clouds, delivering faster time to value and supporting critical workloads at scale.
- Optimize and share compute infrastructure across the data lifecycle – streaming, engineering, warehousing and machine learning – increasing efficiency and lowering cost by reducing compute infrastructure requirements for data analytics and eliminating needless data replication.
- Ensure security and governance policies are easily and consistently enforced across hybrid and multi-cloud cloud deployments to reduce the risk of regulatory compliance issues and the resulting fines.
- Invest in a platform powered by open-source, ensuring continual, rapid innovation to address evolving business requirements today and tomorrow.
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Srishti currently works as Associate Editor at Analytics India Magazine. When not covering the analytics news, editing and writing articles, she could be found reading or capturing thoughts into pictures.