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What Is Data Resiliency?

Maintaining data resiliency is now crucial for any company as cyberattacks become more sophisticated and the amount of data surges. With their increasing reliance on data for day-to-day operations, organizations must ensure that their data remains secure, available, and intact. In this article, we’ll explore the concept of data resiliency, its importance, benefits, and strategies to implement it effectively.


Learn how storage reliability is the key to navigating evolving requirements in the era of digital transformation. 


What Is Data Resiliency?

Data resiliency refers to the ability of an organization to protect, recover, and maintain its data in the face of unexpected events or disruptions. These events can include hardware failures, software glitches, cyberattacks, natural disasters, or human errors. A resilient data infrastructure is designed to prevent data loss, minimize downtime, and quickly recover from any adverse situations.

What Is Data Resiliency in the Cloud?

In the cloud computing era, data resiliency takes on a new dimension. Cloud-based data resiliency involves leveraging the scalability, redundancy, and distributed nature of cloud infrastructure to ensure data availability and durability. By storing data across multiple data centers and employing advanced backup and recovery mechanisms, organizations can achieve high levels of data resiliency in the cloud.

Why Is Data Resiliency Important?

Data is the lifeblood of modern businesses. The loss or unavailability of critical data can have severe consequences, including financial loss, reputational damage, and even legal liabilities. Data resiliency ensures business stability by minimizing disruptions, enabling continuity, and safeguarding critical information. It allows organizations to recover quickly from data loss incidents, ensuring that operations can resume without significant impact.

Benefits and Downsides of Data Resiliency

Data resiliency offers several benefits. It provides protection against data loss, reduces downtime, and increases reliability. By implementing effective data resiliency measures, organizations can enhance their disaster recovery capabilities and improve business continuity planning. However, data resiliency also comes with costs and complexity. It requires investments in infrastructure, technologies, and personnel. Balancing the benefits and costs is crucial in designing an efficient data resiliency strategy.

Business Continuity and Compliance

Data resiliency plays a crucial role in business continuity planning. By ensuring data availability and timely recovery, organizations can minimize the impact of disruptions and maintain uninterrupted operations. Additionally, data resiliency is closely linked to regulatory compliance. Many industry regulations and data protection laws require organizations to have robust data backup, recovery, and security measures in place.

Data Integrity and Reliability

Data integrity and reliability are fundamental aspects of data resiliency. Organizations must ensure that their data remains accurate, consistent, and free from corruption. Data resiliency strategies often include mechanisms such as data replication, checksums, and error detection codes to validate and maintain data integrity. By minimizing the risk of data corruption or tampering, organizations can rely on their data for decision-making and operational processes.

Costs, Complexity, and Overhead

Implementing data resiliency measures can be complex and resource-intensive. It requires investments in infrastructure, software, and skilled personnel. Organizations must assess the costs and overhead associated with data resiliency and strike a balance between the level of resiliency needed and the available resources. Automation, cloud-based solutions, and efficient planning can help manage the complexity and reduce costs.

What Makes a Good Data Resiliency Strategy?

Data Resiliency vs. Data Backup and Recovery

While data resiliency and data backup and recovery are related concepts, they are not interchangeable. Data backup and recovery focus on creating copies of data and restoring it in case of loss. Data resiliency, on the other hand, encompasses a broader range of measures to ensure data availability, durability, and recoverability. A robust data resiliency strategy combines data backup and recovery with additional layers of protection, redundancy, and proactive measures to prevent and mitigate potential disruptions.

Replication and Redundancy in Data Resiliency

Replication and redundancy are essential components of a data resiliency strategy. By replicating data across multiple locations or systems, organizations can ensure that there are redundant copies available in case of failures or disasters. Redundancy can be achieved through technologies like redundant arrays of independent disks (RAID) or by utilizing distributed storage systems. This approach not only enhances data availability but also improves performance and minimizes the risk of data loss.

Disaster Recovery Strategies

Disaster recovery is a key aspect of data resiliency. It involves developing comprehensive plans and procedures to recover data and resume critical business operations after a catastrophic event. This may include having off-site backup storage, establishing alternate data centers, and implementing failover mechanisms. Disaster recovery strategies should consider factors such as recovery time objectives (RTOs) and recovery point objectives (RPOs) to determine the acceptable downtime and data loss tolerances.

Data Encryption and Security

Data resiliency is closely tied to data security. Encryption plays a vital role in protecting data from unauthorized access, ensuring confidentiality and integrity. By encrypting data both at rest and in transit, organizations can mitigate the risks of data breaches and ensure that even if data is compromised, it remains unreadable to unauthorized parties. Robust access controls, authentication mechanisms, and security audits are also crucial elements of a comprehensive data resiliency strategy.

Data Resiliency through Archiving, Integrity Checks, and Validation

Archiving older or less frequently accessed data can contribute to data resiliency. By moving infrequently used data to secondary storage or archival systems, organizations can free up resources and improve performance for critical data operations. Additionally, regular integrity checks and validation processes can help identify and correct any data inconsistencies or corruption, ensuring the ongoing reliability and resiliency of stored data.

How to Design a Data Resiliency Strategy

Your data resiliency strategy will depend on your organization’s size, type, and mission, but there are some general best practices for creating a good data resiliency strategy. 

These are the high-level steps we recommend:

1. Assess Risks and Vulnerabilities

The first step in designing a data resiliency strategy is to assess the risks and vulnerabilities that your organization may face. This includes evaluating potential threats, such as hardware failures, cyberattacks, natural disasters, or human errors. Conducting a thorough risk assessment helps identify critical data assets, potential points of failure, and the impact of data loss or unavailability on business operations.

2. Develop a Data Resiliency Plan

Based on the risk assessment, organizations can develop a data resiliency plan that outlines the necessary measures and procedures to mitigate identified risks. The plan should include data backup and recovery processes, disaster recovery strategies, data replication mechanisms, encryption policies, and incident response protocols. It should also define roles and responsibilities, establish communication channels, and outline testing and maintenance procedures.

3. Choose a Data Resiliency Solution and Technology

Selecting the right data resiliency solutions and technology is crucial to the success of the data resiliency strategy. Organizations should evaluate available options based on their specific requirements, budget constraints, and scalability needs. This may include investing in backup and recovery software, cloud-based storage solutions, data replication technologies, encryption tools, and monitoring systems. It’s important to consider factors such as ease of use, compatibility with existing infrastructure, and vendor reputation when making these decisions.

Data Resiliency Tools and Vendors

Numerous tools and vendors offer data resiliency solutions. Some popular options include:

Amazon Web Services (AWS): AWS provides a range of services and features to ensure data resiliency in the cloud, such as S3 storage with built-in redundancy, Glacier for long-term archival, and Elastic Block Store (EBS) with data replication options.

Veeam Data Protection and Resiliency: Veeam offers comprehensive data protection and resiliency solutions, including backup and recovery, replication, and monitoring tools. Veeam’s solutions are designed to work across various environments, including on-premises, virtualized, and cloud-based systems.

Commvault: Commvault offers a complete suite of data management solutions, including backup and recovery, disaster recovery, and data archiving. The platform provides comprehensive data protection and resiliency capabilities for organizations of all sizes. When choosing a vendor, organizations should consider factors such as the vendor's reputation, customer reviews, support services, scalability, and integration capabilities with existing infrastructure.

What Makes AWS Resilient?

AWS is renowned for its robust data resiliency capabilities. Some key features that contribute to AWS's resilience include:

  • Multiple Availability Zones (AZs): AWS infrastructure is designed with multiple physically separated availability zones, each with its power, cooling, and networking capabilities. This architecture ensures high availability and durability for data.
  • Data Replication and Redundancy: AWS offers data replication options, such as Amazon S3 replication, which allows for automatic replication of data across different AZs or regions. This redundancy ensures that data remains accessible even in the event of failures or disasters.
  • Elasticity and Scalability: AWS allows organizations to scale their infrastructure based on demand. This elasticity enables organizations to handle sudden increases in workload and maintain data resiliency without disruptions.
  • Managed Services: AWS provides managed services for data resiliency, such as AWS Backup and AWS Disaster Recovery. These services simplify the backup and recovery processes and provide automated tools for disaster recovery planning.

Veeam Data Protection and Resiliency

Veeam is a well-established provider of data protection and resiliency solutions. Some key features of Veeam's offerings include:

  • Comprehensive Backup and Recovery: Veeam provides a comprehensive backup and recovery solution that supports various platforms, including virtualized environments, physical servers, and cloud-based systems. The solution offers features such as incremental backups, data deduplication, and fast recovery options.
  • Replication and High Availability: Veeam enables organizations to replicate their critical data and applications to alternate sites or cloud-based environments. This replication ensures that data remains available and recoverable even in the event of primary system failures.
  • Monitoring and Reporting: Veeam offers monitoring and reporting tools that provide visibility into the data protection and resiliency environment. Organizations can track backup performance, identify vulnerabilities, and proactively address any issues that may impact data resiliency.
  • Integration with Cloud Providers: Veeam integrates with major cloud providers, including AWS and Microsoft Azure, allowing organizations to leverage cloud-based storage and backup services for enhanced data resiliency.

Data Resiliency from Commvault

Commvault provides a comprehensive data management platform that includes data resiliency capabilities. Some highlights of Commvault's offerings include:

  • Unified Data Management: Commvault's platform offers a unified approach to data management, including backup and recovery, disaster recovery, and data archiving. This holistic approach simplifies data resiliency planning and operations.
  • Intelligent Data Protection: Commvault utilizes intelligent data protection features, such as deduplication, compression, and incremental backups, to optimize storage utilization and reduce backup windows. These features enhance data resiliency by minimizing the impact on network and storage resources.
  • Flexible Deployment Options: Commvault's solutions can be deployed on premises, in the cloud, or in hybrid environments. This flexibility allows organizations to design data resiliency strategies that align with their specific infrastructure and business requirements.
  • Compliance and Governance: Commvault provides features to ensure compliance with data regulations and governance policies. This includes capabilities for data retention, e-discovery, and data classification, which are crucial aspects of maintaining data resiliency in regulated industries.

Conclusion

Data resiliency is of paramount importance for modern businesses. It ensures the availability, durability, and recoverability of critical data, even in the face of unexpected events or disruptions. Implementing a robust data resiliency strategy involves a combination of data backup and recovery, replication and redundancy, disaster recovery planning, data encryption, and security measures. It also requires assessing risks, developing a comprehensive plan, choosing suitable technology and solutions, and regularly testing and maintaining the resiliency measures.

Cloud providers like AWS offer resilient infrastructure and services, while companies like Veeam and Commvault provide comprehensive data protection and resiliency solutions. By investing in data resiliency and implementing best practices, organizations can minimize the risk of data loss, maintain business continuity, comply with regulatory requirements, and safeguard their reputation in an increasingly data-driven world.

A Key for Data Resiliency: Ransomware SLAs

A service level agreement (SLA) for ransomware recovery is a guarantee from a service provider that specifically pertains to ransomware attacks. Similar to all SLAs, which outline agreed-upon minimum performance and capacity to a customer (depending on their service tier), a ransomware recovery SLA specifically outlines the time to shipment of clean recovery array(s) in the event of a ransomware attack. This will allow you to restore services while the contaminated arrays are set aside for forensic investigation. The SLA also guarantees a recovery plan and data transfer rate and includes an onsite professional services engineer to install the clean arrays. Ransomware recovery SLAs are an important step in helping organizations be more resilient in the face of rising, costly, and disruptive ransomware attacks.

Learn more about SLAs: SLA vs. SLO vs. SLI

What Does the Pure Storage® Evergreen//One™ Ransomware Recovery SLA Promise?

The Pure Storage Evergreen//One ransomware recovery SLA guarantees:

  • Next business day shipping of clean recovery array(s)*
  • 48 hours to finalize a recovery plan
  • 8 TiB/hour data transfer rate
  • Bundled services, including technical services engineering to finalize the recovery plan and an onsite professional services engineer from time of array arrival through replacement of infected array(s)

*If shipping to North America, Europe, or the UK. For Asia-Pacific, it will be 48 hours.

This critical capability bolsters what Pure Storage can offer customers during the response and recovery phases of an attack.

With this new, first-of-its-kind SLA, Evergreen//One now gives customers of all sizes peace of mind around their data and full knowledge that their data resiliency is as good as it can be.

Learn more about Evergreen//One.

 

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