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Five Strategies for Achieving Application High Availability

Solutions Review

In this feature, SIOS Technology ‘s Todd Doane offers five strategies for achieving application high availability. Business-critical applications, such as SAP, S/4 HANA, SQL Server, and MaxDB, serve as the backbone of many organizations. The company relied on securities trading applications based on Oracle Database.

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Our Latest eBook – Backup & Disaster Recovery Strategies for the New World of Work

OffsiteDataSync

In it, IT pros will find a wealth of information that enables them to successfully implement data protection at a time when a lot of corporate data and applications no longer live within the confines of the network perimeter. . Chapter One looks at how the pandemic has changed work and created new issues. Changes and Challenges.

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Business Continuity vs Disaster Recovery: What’s the Difference?

NexusTek

Unexpected downtime can be caused by a variety of issues, such as power outages, weather emergencies, cyberattacks, software and equipment failures, pandemics, civil unrest, and human error. Included in the plan is a list of all disaster recovery technology to be deployed and the owners of each deployment when applicable.

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25 Data Protection Predictions from 14 Experts for 2022

Solutions Review

Despite the added complexity of running different workloads in different clouds, a multicloud model will enable companies to choose cloud offerings that are best suited to their individual application environments, availability needs, and business requirements. ” Companies Will Reconsider On-Prem Data Centers in Favor of Cloud.

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BCP vs. DR Plans: What Are the Key Differences?

Zerto

These events could be man-made (industrial sabotage, cyber-attacks, workplace violence) or natural disasters (pandemics, hurricanes, floods), etc. References to Runbooks detailing all applicable procedures step-by-step, with checklists and flow diagrams. Business Continuity Plan vs. Disaster Recovery Plan.

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45 World Backup Day Quotes from 32 Experts for 2023

Solutions Review

As generative AI applications like chatbots become more pervasive, companies will train them on their troves of internal data, unlocking even more value from previously untapped information. The result is that large sections of corporate datasets are now created by SaaS applications.

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