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Autonomous Data Management: A Complete Guide

Digital transformation has made data a strategic asset for the organization, with hybrid, multi-cloud environments the preferred operational models. However, the advent of big data and the rush to store and back it up in the cloud has resulted in data scattered across multiple clouds, making it challenging to harvest its value or protect it.

The situation is worsened by the lack of optimized enterprise data management tools for hybrid and multi-cloud environments. As a result, organizations lack the operational agility to utilize their stored data fully.

Hence, modern digital enterprises need to adopt new data management approaches that operate efficiently within the cloud environment, provide intelligent automation, deliver operational agility and efficiency at scale, and deliver a consistent experience across clouds.

This guide explains autonomous data management and how Veritas is transforming the future of data management using autonomous, multi-cloud-optimized solutions like NetBackup 10 and Cloud Scale Technology. It also looks at the challenges that gave rise to the need for autonomous data management solutions and the technology’s essence for the modern enterprise.

The Road to Autonomous Data Management

The current data protection market, including disaster recoverybackup and recovery, replication, deduplication, and other technology, is evolving quickly. In addition, the market is shifting from manual operations and oversight to intelligent and autonomous data management.

The leap from data backup to autonomous data management did not happen overnight. It started with protected backups stored on on-premises databases and was reliant on human workloads and oversight. It then changed to cloud-enabled environments that natively leveraged public and private clouds. Later came data intelligence to sift through extensive data before graduating to autonomous data management that minimizes human intervention.

Before autonomous data management, the focus was on supporting IT production, with data and app backup and recovery being the core objectives. However, the adoption of cloud-based technologies to support and extend traditional on-premises environments changed everything.

Emerging technologies and solutions will seamlessly and natively leverage private and public cloud infrastructures to ensure backup and recovery. They will also protect workloads in the cloud environment and across on-premises and cloud infrastructure.

However, increasing digital transformation makes organizations’ requirements for data content and context a priority and a going concern. Therefore, they need to derive more intelligence from stored data, and the data management gaps are an obstacle they need to overcome as they race toward data intelligence and autonomy.

The ultimate goal for organizations is autonomous data management. Here, artificial intelligence (AI) and machine learning (ML) technologies allow the automation of data management processes and minimize human intervention and oversight. It results in operational efficiencies, increased uptime, enhanced security, and higher service levels.

Data intelligence and autonomy are relevant to Veritas and its introduction of the new Cloud Scale Technology to power autonomous data management.

The Challenges Facing the Cloud Environment

The need for organizations to manage and protect their data cost-effectively has never been more critical and challenging. But unfortunately, many of today’s data management technologies suffer from one or more of the challenges below:

  • Cloud-native vs. multi-cloud: The current data management solutions fall in one of two scenarios. They either provide multi-cloud support with a centralized control but consume many costly resources within each environment or are cloud-native. In the latter scenario, they are efficient within a single cloud environment but don’t scale across multiple clouds. The operational costs in both cases are higher than desired.
  • Functional silos with point solutions: The rush to implement cloud technology has created a proliferation of point solutions as cloud architects, app developers, and data scientists implement independent data management solutions, limiting centralized governance.
  • Manual operations: Enterprise data management solutions are programmable but retain a manual deployment and maintenance approach, slowing operational agility.
  • Passive cyber-resilience: Most of today’s data protection technologies take a passive approach to protecting data stored in the cloud. They back up data and restore it after an attack, resulting in unplanned downtime.

The need for multi-cloud strategies across the board has necessitated the development of a new autonomous approach to data management. The new Veritas technology supports multi-cloud operations, eliminates functional silos, automates all processes with minimal human intervention, and enhances cyber-resiliency using active ransomware detection and prevention methods.

What is Autonomous Data Management?

Autonomous data management allows enterprises to unlock full cloud benefits, including operational scale and agility. It refers to cloud technologies that operate autonomously and transparently with little to no human intervention. It also does not sacrifice human oversight.

Autonomous data management requires harnessing artificial intelligence, hyper-automation, and machine learning. It also combines this capability with an elastic, programmable, and multi-cloud-optimized technology.

Suppose you discover a new application deployed to the cloud that you require or use in your regular business operations. You would provide resources to immediately protect its data using the appropriate recovery point objective (RPO) and recovery time objective (RTO). However, you will rely on manual oversight since you don’t have the right intelligent technology to optimize your operations.

Unfortunately, humans are the weakest link because of their inherent limitations, especially in environments requiring swift and data-driven decision-making to achieve desired operational and business goals. In addition, human resources are prone to errors and are slower to execute than AI-powered solutions, especially when it comes to mundane, repetitive tasks.

Therefore, the best solution for managing data in a complex, hybrid, and multi-cloud environment is autonomous operation. It means minimizing the need and reliance on manual processes by combining hyper-automation with data-driven intelligence.

Achieving autonomous data management allows modern businesses to benefit from optimal data management that self-optimizes, self-heals, and self-provisions in multi-cloud environments. In this context:

  • Self-optimization means using AI and machine learning to adapt and adjust data protection and management policies and services.
  • Self-healing means the ability to predict, identify, and repair service errors or performance issues.
  • Self-provisioning means assigning appropriate protection and management policies and deploying the correct data management applications and services without requiring human involvement.

For example, before the advent of autonomous data management solutions, an app developer who wished to deploy a new application would have to rely on manual processes. Non-autonomous enterprise data management solutions require a lot of manual intervention and handoffs despite having some of the workflows automated. As a result, this makes the process inefficient, time-consuming, and prone to human errors.

Autonomous data management eliminates all the manual steps while protecting the application throughout the process without requiring any additional actions from the app developer, data protection team, or other IT personnel. Thus, it leads to an optimized, efficient, and secure environment.

Why is there a Need for Autonomous Data Management?

The 2021 State of DevOps report from Puppet reveals that manual operations increase an enterprise’s manual IT operations costs by 50-90%. Autonomous data management will significantly reduce these costs once fully implemented.

Data management is a crucial first step for organizations to analyze data at scale effectively. It leads to essential insights that add value to decision-making processes and customers and improve the bottom line. The following factors explain the need for effective autonomous data management:

  1. Visibility: Data management can increase an organization’s visibility of its data assets. It makes it easier to find the correct data for analysis. Additionally, data visibility allows organizations to become organized, productive, and confident in their decisions because employees and senior management can find the data they need.
  2. Reliability: Data management should be reliable and minimize potential errors. Therefore, organizations need to establish policies and processes for building trust and using their data to make decisions. Additionally, reliable and up-to-date data enables organizations to respond efficiently to customer needs and market changes.
  3. Security: Data management protects organizations and stakeholders from data theft, breaches, and losses.
  4. Scalability: Data management enables effective scaling and data usage with repeatable processes to keep it up-to-date. Easy-to-repeat functions allow an organization to avoid unnecessary duplication costs and occurrences, such as employees re-running costly queries unnecessarily or conducting the same research repeatedly.

How Veritas Aims to Transform Autonomous Data Management

The traditional data backup and protection market will morph into an intelligent and autonomous data management environment. Innovative new cloud architecture is powering the inevitable fundamental shift to provide secure and reliable cloud environments.

Veritas Technologies, a global leader in multi-cloud data management, has recognized this inevitable shift by introducing the Cloud Scale Technology. Now, NetBackup will use the technology to operate autonomously. It allows automatic provisioning, optimizing, healing, and configuring data management services with little to no human involvement.

Veritas’ NetBackup strategy provides the first AI-enabled autonomous data management solution delivered using Cloud Scale Technology – a flexible, multi-cloud-optimized platform.

In late February 2022, Veritas announced the launch of new technology to support autonomous data management. The new technology helps Veritas simplify how businesses manage their data and automate protection from cyber threats like ransomware.

Veritas’ NetBackup™ will harness artificial intelligence and hyper-automation to enable self-provisioning, self-optimizing, and self-healing in multi-cloud environments. In addition, the company unveiled Veritas Cloud Scale Technology as a new generation of industry-leading NetBackup architecture designed and modernized to operate at web-scale.

The state-of-the-art technology is available with the latest version of NetBackup software named NetBackup 10. Veritas believes in accelerating digital transformation and cloud adoption to deliver benefits to businesses worldwide.

Veritas has also laid out a strategy to solve new and developing cyberattacks in the wake of a joint advisory from the governments of the US, UK, and Australia security services highlighting the increased impact of ransomware attacks targeting cloud data and services. The company’s tools will help reduce cloud costs and footprint, keep data safe, and usher in autonomous data management.

Veritas Cloud Scale Technology

Veritas Cloud Scale Technology will power NetBackup, becoming the foundation that delivers autonomous data management. The technology delivers a programmable, containerized, and AI-powered microservices architecture to provide autonomous and unified data management services across clouds.

The new Cloud Scale Technology from Veritas uses leading-edge web-scale IT techniques and technologies to provide greater cloud efficiency and agility. It also enables elastic, auto-scaling cloud data management. In addition, it creates the foundation for the new NetBackup 10 features and the entire Veritas autonomous data management strategy to transform the enterprise data protection space.

The Veritas Cloud Scale Technology will enable autonomous provisioning, optimizing, and repairing of data management services. It will also empower end-users to enjoy self-service data recovery and protection and free up their IT staff to focus on other strategic and transformational activities.

Enterprise data management must meet the needs of emerging multi-cloud infrastructures because that’s where customers and companies have their critical data. Once achieved, it would lower ownership costs and improve returns on investment.

The full implementation of the Cloud Scale Technology and NetBackup 10 would translate into data self-service for other areas of the organization like cloud architects, data scientists, and application developers. It will also enhance operational agility, comprehensive protection, and cloud cost optimization.

Organizations can now enjoy AI-powered malware scanning, anomaly detection, and flexible data recovery options on-premises and cloud.

NetBackup™

NetBackup™, powered by Cloud Scale Technology, is the industry’s leading enterprise data management solution. It provides agile autonomous data management and security across multi-cloud environments at scale. It leverages automation, AI, and flexible architecture and has 100 exabytes of information under management.

NetBackup provides an integrated approach to delivering unmatched performance and cost savings, making it the preferred technology of choice for 87% of Fortune Global 500 firms. Cloud optimization, operations automation, and cyber resilience are its main selling points because they help simplify data management.

The launch of NetBackup 10 will enable companies to realize the benefits of Cloud Scale Technology. NetBackup 10 leverages Cloud Scale Technology to lower the total cost of ownership (TCO) for the cloud, increase operating efficiency, and improve security within multi-cloud environments.

The current space is characterized by organizations with a patchwork of piecemeal cloud data protection solutions and the deployment of individual workloads and applications managed in silos. However, while effective in the short-run, the costs add up over time and create a continually growing management and cost burden that becomes unsustainable at scale.

Therefore, organizations need a sustainable long-term solution to help reduce their cloud backup footprint and automate management.

NetBackup has earned a proven reputation for enabling scalable and unified enterprise data management. Therefore, by combining NetBackup 10 with the software-driven programmability, multi-cloud optimization, and dynamic resource provisioning capabilities of Cloud Scale Technology, it can operate autonomously with little to no human involvement.

The Benefits of NetBackup 10

NetBackup 10 is a cloud-optimized data management solution that provides the following benefits to organizations:

1.    Lower TCO through Cloud-Optimization

It features enhanced multi-cloud storage, backup, and orchestrated tiering capabilities. It also supports Amazon Web Services and Microsoft Azure, allowing companies to reduce their backup storage costs significantly.

Additionally, Veritas has upgraded its deduplication services to help minimize NetBackup’s cloud footprint. At the same time, elastic multi-cloud compute services can deliver the scale businesses need, which further reduces operating costs.

Finally, NetBackup 10 provides multi-cloud cross-platform recovery and supports all major Kubernetes distributions. This allows users to recover their data to any Kubernetes distribution.

2.    Simplified, Automation Processes Provide Increased Efficiency

NetBackup 10 now integrates with NetBackup SaaS Protection to provide customers with a central view of their entire data protection estate, enabling easier governance and compliance.

NetBackup 10 comes fully integrated with NetBackup IT Analytics, providing comprehensive AI-driven analytics. It also includes real-time reporting to mitigate risks and streamline data protection services.

Finally, NetBackup 10 features automated detection and protection capability to support platform-as-a-service workloads such as Apache Cassandra, Microsoft Azure Managed SQL, Azure SQL, and major Kubernetes distributions.

3.    Enhanced Security and Ransomware Resiliency

NetBackup 10 has integrated malware scanning capability. The automatic malware scanning occurs during backups and before restores for infection-free data recovery.

The technology comes equipped with a powerful, AI-driven anomaly detection system that automatically initiates malware scanning. When combined with the technology’s ransomware detection service, NetBackup 10 provides content-aware and granular flexibility with rapid clean data restoration.

The technology also expands immutable storage support, including Microsoft Azure Blob Storage.

Why is Autonomous Data Management Important?

The benefits of autonomous data management are numerous, including providing faster, easier, and better self-service insight. Other benefits are:

  1. Security: Autonomous data management technologies encrypt data, monitor workloads and data in transit, and keep track of who accesses information to ensure enhanced cyber security and compliance.
  2. Speed: Automation eliminates manual data installation and analysis, providing decision-makers with essential insights faster.
  3. Efficiency: Autonomous data management leverages AI and ML to ensure it always runs efficiently.
  4. Scalability: Autonomous data management is scalable across multi-clouds with minimal human intervention without giving up human insight.

Veritas Cloud Scale Technologies and NetBackup are paving the way for AI-powered autonomous data management solutions that solve the challenges the industry faces today. The new Cloud Scale Technology has redefined enterprise data management for multi-cloud and hybrid cloud environments by powering NetBackup 10 to enable autonomous operations.

As the new generation of the NetBackup architecture, Cloud Scale Technology employs similar technologies found in web-scale services leading to elastic, portable, and programmable services. Additionally, by containerizing services like backups, deduplication, and snapshots, NetBackup services can grow and shrink depending on load, thanks to Cloud Scale Technology.

Containers also enable portability and reliability because they work within multiple clouds and provide greater resiliency. Additionally, Cloud Scale Technology enables NetBackup 10 to operate efficiently due to automation, subscription-based services, and multi-tenancy.

Efficient operation in multi-cloud environments controls costs, improves ROI, and delivers cyber-resilience to mitigate and reduce the impact of cyberattacks. NetBackup combines event-driven malware detection and AI-powered anomaly detection to identify potential threats proactively. Additionally, once an attack occurs, it offers flexible recovery options for data restoration to alternate clouds as needed to reduce the recovery time.

The Bottom Line

Enterprises are pursuing digital transformation by accelerating their multi-cloud strategies. However, many of the existing enterprise data management solutions are not equipped to meet the challenges of managing and protecting data in multi-cloud environments effectively. Hence, the need for autonomous data management solutions.

Veritas NetBackup and Cloud Scale Technology deliver the first autonomous data management solution powered by AI. The result is a cyber-resilient, autonomously-operated, and multi-cloud-optimized platform that allows worldwide data storage, protection, and recovery, no matter the threat. It also will enable organizations to operate cost-efficiently across any cloud and enable autonomous data management without sacrificing human insight.

Veritas customers include 98% of the Fortune 100, and NetBackup™ is the #1 choice for enterprises looking to back up large amounts of data.

Learn how Veritas keeps your data fully protected across virtual, physical, cloud and legacy workloads with Data Protection Services for Enterprise Businesses.