Veeam Software has unveiled its vision for the Hyper-Available Enterprise and its strategy to guide enterprise customers on their journey to Intelligent Data Management at massive scale.
At VeeamON 2018, Veeam demonstrated how customers around the world are leveraging the Veeam Hyper-Availability Platform for Intelligent Data Management to ensure business continuity, reduce risk and accelerate innovation in an era where technologies ranging from IoT, AI, machine learning and blockchain require a platform with massive scalability and ease of use for managing data.
The scale and complexity of managing the hyper-growth and hyper-sprawl of enterprise data today requires a new type of solution, one that moves from traditional policy-based data management to a more behavior-based system, so data can manage itself more autonomously and deliver critical business and operational insights at record speeds. Together with its ecosystem of more than 55 000 technology partners, the Veeam Hyper-Availability Platform is the most complete solution to help customers make this transition to Intelligent Data Management.
“Since Veeam’s founding in 2006, we have been the go-to provider of Availability solutions for apps and data in multi-cloud environments, firmly establishing ourselves as the leading vendor in the space,” says Peter McKay, co-CEO and president of Veeam. “However, as technologies like IoT, AI, machine learning and blockchain mature, and as customers grapple with mining massive amounts of data for better business insights, they need solutions that can do far more than ensure data Availability.
“We believe Hyper-Availability is the new expectation for data in today’s enterprise. The Veeam Hyper-Availability Platform, used by many of the world’s largest enterprises including Royal Caribbean, Mercedes-Benz, Telefonica and L’Oréal, is the most complete solution to help customers on their journey to Intelligent Data Management so that they deliver innovative digital services to market faster.”
Availability has been traditionally associated with business continuity and backup and recovery, to make sure organisations stay up and running. With increasing challenges in managing enterprise data, Hyper-Availability requires that data must evolve from basic backup and recovery solutions which mechanically copy data at prescribed intervals, to a much higher level of intelligence where data learns to respond instantly and appropriately to what actually happens anywhere across the enterprise data infrastructure. Data protection and data management must move from reactive insurance policies to a system that provides proactive business value.
“Veeam’s vision for Intelligent Data Management is based on a flexible set of integrated, plug-and-play solutions,” says Danny Allan, vice-president of product strategy at Veeam. “Veeam Hyper-Availability Platform provides the integration, visibility, orchestration, intelligence, and automation to evolve data management from policy-based to behavior-based, and from manual management to intelligent automation.
“This enables the provisioning and management of the massive, constant flows of data running across highly distributed, multi-cloud infrastructures to be securely automated, self-learning, and optimally orchestrated. Enterprises that run on Veeam Hyper-Availability Platform respond faster to any business need, gain multifold improvements in efficiencies, and have far greater agility to deliver new digital services and experiences that improve how people live and work.”
There are five stages on the journey to Intelligent Data Management for the Hyper-Available Enterprise:
Stage 1, Backup: Back up all workloads and ensure they are always recoverable in the event of outages, attack, loss, or theft.
Stage 2, Aggregation: Ensure protection and availability of data across multi-cloud environments to drive digital services and ensure the aggregated view of service level compliance.
Stage 3, Visibility: Improve management of data across multi-cloud environments with clear, unified visibility and control into usage, performance issues, and operations; data management begins to evolve from reactive to proactive, preventing any loss of data availability through advanced monitoring, resource optimization, capacity planning, and built-in intelligence.
Stage 4, Orchestration: Seamlessly move data to the best location across multi-cloud environments to ensure business continuity, compliance, security, and optimal use of resources for business operations. This requires an orchestration engine that enables enterprises to easily and non-disruptively execute, test, and document disaster recovery (DR) plans in a highly-automated fashion.
Stage 5, Automation: Data becomes self-managing by learning to back itself up, migrate to ideal locations based on business needs, secure itself during anomalous activity, and recover instantaneously. This stage brings new levels of automation to enterprise data management via a combination of data analysis, pattern recognition, and machine learning.