Home Artificial Intelligence Artificial Intelligence Media Enabling Digital Transformation with Hybrid Cloud Data Management – Gigaom

Enabling Digital Transformation with Hybrid Cloud Data Management – Gigaom

  1. Summary
  2. Object Stores, The Digital Transformation Data Foundation
  3. Build for Hybrid While Preparing for Multi-Cloud
  4. Scality RING8 and Zenko
  5. Key Takeaways
  6. About Enrico Signoretti

Analysis

Object storage is becoming more mainstream than ever, with organizations of all sizes adopting it for an ever-growing number of workloads. Traditional use cases such as second tier storage, backup, and long-term archive, are now joined by next-generation, cloud-native workloads that require data to remain always and quickly accessible. With billions of devices creating and consuming content like never before (smart data lakes, media rendering and management, edge and IoT, machine learning, and artificial intelligence projects) digital transformation processes are being embraced by organizations globally.

Digital transformation also means that every industry is experiencing tremendous data growth thanks to new tools like mobile phones, wearable technology, high-resolution cameras, sensors, and applications that can take advantage of them. Regardless if it is a B2C or a B2B application, examples are everywhere. Banking applications allow consumers to deposit checks simply by taking pictures of them. Manufacturing processes are continuously improved thanks to data analysis from billions of sensors. Image recognition is becoming a standard feature in social media, retail stores, healthcare analysis, and so on. These applications create petabytes of data which have to be stored, analyzed, and often preserved for a long time. Therefore, application workloads and data are beginning to span across on-premises and cloud infrastructures.

Even the most conservative enterprises are now confidently building hybrid cloud infrastructures for multiple use cases. Here are some examples:

  • Cloud bursting: leveraging the vast amounts of available computing power in the cloud for highly-demanding workloads and fast analysis, while keeping full control over data and paying only for the time required.
  • Cloud tiering: offloading cold data to the cloud to take advantage of the low $/GB while maintaining flexibility.
  • Business continuity (BC) and disaster recovery (DR): eliminating the expense of a secondary DR site without sacrificing data protection or infrastructure resiliency.
  • Advanced data management and governance: complying with increasingly demanding regional regulations while serving global customers.
  • The proliferation of edge services: supporting users, applications, and data generators that are pushing and pulling data to and from core and cloud infrastructures.

All of these use cases have challenges and without the right technology, the digital transformation benefits could be limited by trade-offs and added complexity. These challenges must be addressed early to avoid cloud silos, which increase complexity and costs, limit data mobility and access, and compromise overall operational efficiency. In fact, cloud silos are even worse than the enterprise data center silos of the past because the data may be distributed on several clouds and accessed through multiple modern or legacy file interfaces.

If an organization’s current infrastructure is only on-premises and there is a hybrid or multi-cloud strategy planned, choosing the right technology today is key for infrastructure sustainability. Creating a data foundation layer is necessary to empower digital transformation processes for all business units in the organization.

Fig. 1: Data and Application Silos, Cloud and On-premises

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