Key Criteria for Evaluating Hybrid Cloud Data Protectionv 2.0

1. Summary

A strong data protection strategy remains at the core of every IT infrastructure, but cloud and edge computing have changed the way enterprises implement it. Machine-generated data is now outgrowing any other type of data and often underpins strategic big data analytics and artificial intelligence initiatives, forcing organizations to rethink data protection according to new rules that include hybrid and multi-cloud infrastructures.

More recently, the pandemic created a disruption in standard work and business processes with data that is created remotely but needs to be stored and protected with the same policies that were previously applied. In fact, enterprises accelerated the adoption of Software-as-a-Service (SaaS) applications and migrated more workloads to the public cloud as well.

Hybrid cloud is now considered a standard approach by organizations of all sizes, and many expect to move to multi-cloud later on. In this complex scenario, there are an increasing number of challenges, including:

• Exponential data growth: With machine-generated data taking the lion’s share now, backup and restore processes will have to change accordingly. For example, it is very unlikely it will be necessary to retrieve accidentally deleted single files.
• Disparate data types: Structured and unstructured data created by traditional applications are now joined by containers and SaaS data, metadata, and blobs. This new, complex type of data is usually self-consistent, capable of reproducing the entire application or recreating the state of a cloud service if necessary.
• Support for new technologies: It’s not only new cloud services; on-premises infrastructures are also evolving quickly. New types of databases, scale-out file systems, and Kubernetes are all technologies recently adopted by enterprises with additional data that has to be protected.
• Pressing SLAs: Digital transformation initiatives embraced by many organizations have transformed every process. It is becoming harder and harder to stop any part of the infrastructure or to have a long recovery time objective (RTO) or recovery point objective (RPO). Instant and continuous backups and fast recovery speeds are mandatory for an ever-growing number of applications.
• Data dispersion and consolidation: Data is now created, stored, and consumed on mobile devices, PCs, data centers, and many other places. In order to build the kind of effective data protection that is instrumental in implementing a data management strategy, it is necessary to consolidate backup repositories in a single physical or virtual domain.
• New security threats: Traditional risks and threats, such as natural disasters and human error, are now joined by cyberattacks like ransomware that are even more dangerous and harder to detect.
• Regulatory compliance: There are a growing number of demanding regulations (like GDPR or CCPA) that require strong data protection and tools able to search and find information quickly, or to remove/mask the information properly after retrieval, as in the case of the “right to be forgotten.”
• Data management and reusability: Backups can be transformed from a burden to an asset for an organization. By indexing data and making it searchable, the data’s real value is revealed, making it reusable by other users or applications across the entire organization.

For these reasons, data protection operations are very difficult and more critical than in the past.