Managed.IT - issue 65

16 01732 759725 BUSINESS CONTINUITY zero RTO and RPO objectives and compliance by providing real-time cloud replication of actively used GenAI data. This method reduces costs and ensures continuous data accuracy should recovery be necessary, enabling development and analytics teams to continue working with the most up-to-date material. n No Downtime is a Must. Any data movement can hamper business continuity if it requires application downtime. Data migration solutions that can facilitate large-scale data changes and migration to the cloud will help minimise disruption. n Automation is the Answer. In the event of a system failure, IT teams can use active-active replication over multi-cloud environments, as necessary, to ensure automatic failover and recovery, minimising data loss and downtime. Practise Secure GenAI Use Before the end of this decade GenAI and unstructured data will become a larger and more powerful element in production, data science and day-to-day business operations. Now is the time to review business continuity practices to ensure business teams can effectively manage and secure the LLMs and data sets they are using. Updating security practices will help avoid costs associated with a data breach, as well as loss of customer trust and loyalty. It is too easy unwittingly to introduce confidential data into training LLMs and security and functional teams will need to work together to set limits on unstructured data that could pose a threat to data protection, privacy and continuity of operations. IT teams must also avoid the fragmentation of policy controls, update recovery practices and use replication technology to ensure business continuity. As businesses assemble large data sets using GenAI-powered processes and transfer this data into applications, there is an immediate need to ensure LLMs are subject to the same security and data protection practices as any other application or data asset. To ensure recovery and business continuity, there are several immediate considerations: n Visibility is a Priority. The principle that you can’t manage assets you don’t know about holds true for unstructured data. Functional teams, or lines of businesses, must have visibility into the unstructured data in their environment to avoid cyber attacks, data privacy breaches and budget impact. By having visibility, teams can make a judgment as to which GenAI data and/or models are critical and need to be categorised as such to support continuity. n The Cloud is King. LLMs are built on data that needs to live in the cloud as the expense and lack of hardware support for datasets needed to train LLMs makes on premises storage highly prohibitive. Best practice is required to store this data securely and execute recovery as needed. If a business has adopted a multicloud strategy, it needs to consider a solution that can support large data set migration across multiple cloud providers. n Recovery is the Point. GenAI has changed the amount of data flowing through an organisation and to the cloud. In refining a business continuity strategy to integrate GenAI, functional teams need to review their recovery time objectives (RTO) and recovery point objectives (RPO) and ensure they have backup and recovery processes for critical GenAI large data sets or applications. n Replication is Imperative. Organisations can support nearDisaster recovery and business continuity already function in a highly risk-laden environment and this is now being made even more complex with the rise of generative AI (GenAI) and the large data sets created to feed data science and analytics. The need to manage data analytics fed by large language models (LLMs) while providing the replication safety net that supports business continuity is forcing CIOs to refine their business continuity strategies to address the magnitude of unstructured data within their environments. In its Global Industry Vision report, Huawei predicts that the volume of global data will reach 180 zettabytes by 2025, 80% of which will be unstructured. It forecasts that by 2030, 25% of unstructured data will be used for production and decisionmaking, eventually rising to 80%. GenAI is driving this growth by aggregating text, voice, documents, videos, emails and messaging platforms. At the same time, its rapid development, use of large data sets, potential for misapplication and lack of robust security controls make it a rich target for cyber criminals. Contributing to the security challenge is the fact that different functional teams are using and generating unstructured data in their own fashion, with varying degrees of security. In a study sponsored by Box (Untapped Value: What Every Executive Needs to Know About Unstructured Data), IDC warns that application sprawl and fragmentation of unstructured data, ‘often with diverse sets of identity and authentication models and different administrative features’, are expanding the attack surface and potentially doubling the annual cost of security breaches to $4.5 million. GenAI & business continuity Paul Scott-Murphy, CTO of Cirata, explains how to manage recovery and business continuity in an unstructured data environment fuelled by AI Paul Scott- Murphy