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Automation|Business|Design|Efficiency|Environment|Risk Management|Service|Storage|System|Technology|Solutions|Infrastructure|Operations
Automation|Business|Design|Efficiency|Environment|Risk Management|Service|Storage|System|Technology|Solutions|Infrastructure|Operations
automation|business|design|efficiency|environment|risk-management|service|storage|system|technology|solutions|infrastructure|operations

Leveraging AIOPs at the storage layer to improve IT focus on business, not technology

10th November 2022

     

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This article has been supplied as a media statement and is not written by Creamer Media. It may be available only for a limited time on this website.

By Eric Herzog, Chief Marketing Officer at Infinidat

The current environment is exceptionally challenging for businesses from an Information Technology (IT) perspective. Some of the issues organisations must contend with include lack of time, the need for talent with critical skills, and budgets that are always tight and must be optimised. There is also risk, including risk inherent in the design, integration, and deployment of new solutions, as well as universal risks such as cyberthreats and compliance requirements. Alongside this is the added complexity of environments with multiple architectures and technology stacks with siloed applications. The storage layer lies at the heart of addressing many of these challenges. With an intelligent solution, organisations can exploit infrastructure intelligence, ensure service level delivery, improve IT efficiency, and focus on business aspects and not worry about how the technology operates. 

Leveraging AIOps at the storage layer

Artificial Intelligence (AI) can be utilised at the storage layer to optimise performance by optimising the cache, creating a better understanding of workloads and behaviours, and delivering memory-speed access to data. Deep learning capabilities deliver enhanced cache utilisation, with the ability to accurately predict which workloads will be required so that they can be brought into the cache. 

These algorithms learn to pre-fetch the data that will likely be required, to have it ready on request in memory. This improves the speed of both read and write, sequentialising inputs and outputs (IOs) based on behaviour and understanding block sizes in relation to each other and to applications. The result is not only higher performance, but also greater consolidation of applications based on data utilisation, with multiple nodes that also deliver enhanced redundancy. This ability continuously improves the more the algorithm is used.  

AI outside of the storage system

AI can also be used outside of the storage layer through cloud-based applications to deliver a multi-system, detailed and granular view of and across workloads, platforms and data centres. This provides a singular, consolidated dashboard across the entire storage architecture, for early issue detection and prevention, alerting and management. 

Open, cloud-based architecture ensures that these solutions can be extensible to fit various workflows, while predictive analytics can deliver trend analysis and reporting, anomaly detection and enhanced resource planning. This enables automated, actionable insights on areas such as performance and capacity, that can ultimately lead to better business decisions, such as ServiceNow, VMware vCenter Ops and other pan-data centre/cloud AIOps packages. 

Integrate storage insights into DevOps capabilities

An intelligent storage solution can deliver not only high performance, improved storage utilisation and actionable insight, but also integrated development operations capabilities, while ensuring the storage stays in tune with the needs of the storage administrators as well. This gives direct access to broad and deep capabilities through proven solutions, including cyber resilience, in-family seamless migration, automatic file system extension, infrastructure as code, and Storage as a Service (STaaS) automation. This in turn expedites solution deployment while eliminating solution development risk, as well as integration capability with other third-party functionality, such as Ansible and other pan-data centre/cloud DevOps packages. 

Intelligence is everything

Utilising an intelligent storage architecture can assist organisations to deal with many of the challenges they experience today. By integrating AIOps, less time is required for infrastructure because it is self-managed and self-optimised, with 100% uptime. In addition, direct access to DevOps allows for functionality to be extended with simplified solution implementation, expedited solution delivery, and reduced solution risk. This also reduces budgetary requirements, as there is no additional cost for AIOps or DevOps capabilities. 

With a ‘set-it-and-forget-it’ enterprise storage management approach thanks to AI capabilities, and standardised processes across applications and service levels, complexity is dramatically reduced, requiring less time and fewer people to manage storage architecture. A single architecture that breaks down siloes and supports diverse workloads also maximises consolidation and return on assets, while minimising operational expenses (OPEX), significantly assisting with budget optimisation. 

Improved risk management is delivered through proactive, continuous, and automatic optimisation, reduced solution deployment risk, integrated cyber resilience, 100% guaranteed uptime and assured service level delivery. Bringing this all together through intelligent storage allows organisations to shift their focus away from the underlying technology and focus on business aspects that add greater business value.

Edited by Creamer Media Reporter

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