The GenAI winners of 2026 and beyond will be decided by actions taken now

Picture this: A surrealist oil painting in which an AI-powered sailboat whose sails are made of money is at the crest of an enormous wave. The boat is about to surf down the front of this wave, and in doing so will cross the starting line of a race that will finish in 2026.

That’s the prompt I typed into Dall-E 3, and the resulting image it generated after a few iterations. Why on earth did I ask a generative AI tool to conjure this image? Coming out of re:Invent you can’t help but think about AI in 2024, and this image sums up my high-level thoughts on the topic. Read on for my thoughts on the intersection of sailboat racing, Gartner’s Hype Cycle for Artificial Intelligence, and Dr. Werner Vogels’ AWS re:Invent keynote focus on cloud cost.

[AI-Generated] Behold the surreal depiction of an AI-driven sailboat, its sails adorned with currency motifs, ready to ride the wave towards the starting line of a transformative race set to culminate in 2026.

What the Gartner Hype Cycle says about generative AI: The crest of the wave

Anyone with an internet connection in 2023 has been hit with an onslaught of chatter about artificial intelligence, especially generative AI. So it’s fitting that Gartner placed genAI on their 2023 Hype Cycle at the very top of the “Peak of Inflated Expectations,” estimating it will reach the “Plateau of Productivity” in 5-10 years. What that means for the next year or two is a precipitous drop into the “Trough of Disillusionment.” (Isn’t that where Atreyu lost Artax in The Neverending Story?)

In plainer language, the market is currently as excited about generative AI as it’s likely to ever be. It’s literally all downhill from here, but that’s not entirely bad news. While companies focused on genAI will start experiencing greater skepticism, on the other end of the cycle will be true market acceptance. The companies that make it through the wild ride will reap the rewards. So how can companies developing generative AI products set themselves up for future success today?

Why it’s important to architect with scale and cost in mind: The sailboat

Dr. Werner Vogels’ AWS re:Invent keynote speech focused on the importance of building cost-conscious, scaleable architures, especially as companies evolve and markets mature. He drew parallels between cost and sustainability, and while little evidence was provided related to the implied environmental sustainability, cost optimization is an obvious element of business sustainability.

For companies developing generative AI applications, business sustainability is going to be an important focus on the downward slope into (and eventually back up and out of) disillusionment. The market has seen genAI’s potential, but is also starting to see the limitations of early iterations. The companies that make it through the upcoming era of skepticism will need to show their value in multiple ways.

Customers will need to see products that work as advertised, proving their worth with minimal hallucinations, maximal authenticity and real utility. Getting there will require better models and a constant stream of high volume, high quality data. At the same time, investors will need to see a sustainable business that includes sound financials with a clear path to profitability that includes controlled, predictable costs. This means architecting for scale and cost efficiency should be builders’ top priority.

Experts have suggested that over time, models will become somewhat commoditized, and the greatest competitive advantage will come from datasets. This expectation underscores the criticality of data and relatedly, maintaining its availability, security and resilience. But at the speed and scale required for generative AI, these datasets will be inundated with API calls, making resilience efforts that much more challenging.

Position early for long-term success: The starting line

The start of a sailing race is chaotic. Unlike other forms of racing in which you start from a standstill, sailboats cross the starting line already moving at full speed. The race really begins before the official start, with boats vying for an optimal starting position. They come within inches of one another, aiming to cross the starting line just as the gun is fired and in position to take maximum advantage of the wind. Cross the line at the right time, in the right position, with the right sails and you’re golden. Too early or late, with the wrong sails or in the wrong spot, and your race is pretty much over just as it’s begun.

Right now, generative AI builders are moving at full speed, about to cross that starting line, and not all of them will make it to the finish, the “Plateau of Productivity.” The race before the race has been chaotic (Bard getting a little too emo) and exciting (ChatGPT’s ubiquity). While some differentiation is already apparent, we’re far from declaring winners and losers. A lot can happen in the upcoming years.

Companies that have already built promising products while architecting for cost and scalability will get the best starts, but it’s still possible for others to make strategic moves that will be beneficial in the long run. Those changes would include setting up reliable pipelines of high-quality data, infrastructure that will scale in a cost-effective manner along with that data, and tools for data governance to ensure ongoing efficiency.

Protect your competitive advantage by protecting your data: Preparing for the race ahead

As companies position themselves across the starting line, there’s a third important aspect of business sustainability that is particularly important to generative AI companies; the protection and preservation of critical data.

AI relies on vast amounts of data for model building, training and inference, and that data is generally housed in a data lake, which is often stored in Amazon S3. The criticality of that data necessitates backing it up, a task that gets more challenging as data volume grows and API calls increase.

Backup strategies that were workable in early days can quickly become expensive and failure-prone as data scales beyond the solution’s capabilities. Worse yet, backup solutions that don’t adjust to optimize API pressure can bring the whole application down. The right sail can become the wrong sail as conditions change, and in the worst case can become an anchor.

Scalable, automated data resilience: The sail that’s always right

The easier way is to start the race with a sail that automatically adjusts to conditions. In data terms, one with automated, infinite scalability even in high-change environments. Clumio backs up data lakes as small as a few hundred objects and single terabytes, as large as 40 billion objects, hundreds of petabytes, and all sizes in between, maintaining low RPO point-in-time recovery at up to 20 million changes per hour. It helps customers keep cloud costs in control by finding orphan snapshots and other unnecessary data copies, and aligns with cost-conscious architecting by offering affordable, consumption-based pricing.

The race is on. Generative AI companies need to build better products while focusing on business sustainability through scalability and cost consciousness.

Start your race ahead of the competition:

Customer viewpoint #1: “We had no idea the risk we were incurring.”

The sooner you evaluate the risk created by having multiple cyber resilience solutions deployed to protect your data, the sooner you can reduce your potential data loss. Before making the move to Commvault Cloud, the study uncovered that most companies had more than 15 solutions deployed for data protection. These solutions were all replaced by Commvault Cloud, reducing unrecoverable data to less than 1%, with Nathan sharing that all interviewed customers reported zero instances of unrecoverable data, while also reducing their storage footprint by 31%.

Customer viewpoint #2: “Proof of recoverability + reporting = lower cyber insurance costs”

The ability to provide proof points of recoverability and audited reporting can lead to lower cyber insurance costs. Nathan shared that interviewed customers who deployed Commvault Cloud lowered their cyber insurance costs, offsetting the investment in Commvault Cloud. This is a result of having validated proof of recoverability and comprehensive, auditable reporting that satisfies auditors, boards of directors, and CISOs.

Customer viewpoint #3: “Commvault Cloud Security Scorecard is the best defense.”

Perhaps the most impactful story Nathan shared focused on the value customers gain from Commvault Cloud’s Security Scorecard, highlighting one customer’s comments: “We could hire 40 security experts to try and hack our systems and it still wouldn’t be as effective as what Commvault Cloud’s Security Scorecard does, continually monitoring and letting us know what more we can do to harden our security posture even more.”

The essential ingredient missing from most cyber resilience plans

The panel closed the session with advice on an essential ingredient missing from many cyber resilience plans: the ability to recover to a clean environment. Both Vidya and Jaimie provided insight into how Cleanroom Recovery, recently launched as a joint solution by Commvault and Microsoft, solves the challenge of having an immediately available, isolated, and “clean, infection-free” environment ready to restore your data. They shared that by adopting Cleanroom Recovery, organizations can confidently test their cyber-recovery plans, identify, and remediate vulnerabilities, and ensure business continuity in the face of cyberattacks.

Prepare to be more Cyber Resilient in 2024 with Commvault Cloud

Commvault Cloud brings to market capabilities that have never existed but that are quickly becoming imperatives. With features like Cleanroom Recovery, Cloud Burst Recovery, and Arlie (Commvault Cloud’s AI co-pilot) it defends against cyber threats, safeguarding your sensitive information, bringing your business back at the right place at the right time. When the next cyberattack hits, we’re ready to help. You can access the comprehensive results of the ESG study, “Analyzing the Economic Benefits of Cyber Resilience with Commvault Cloud” here.

More related posts

Understanding the AWS Shared Responsibility Model

The AWS Shared Responsibility Model is a framework that outlines how security and compliance responsibilities are shared between AWS and its customers. It is important for businesses to understand this model, as it determines which security controls they are responsible for implementing and which ones are managed by AWS.

Under this model, AWS is responsible for security of the cloud, while customers are responsible for security in the cloud. This means that AWS is responsible for the underlying infrastructure, such as data centers and networks, as well as managing access control to those resources. On the other hand, customers are responsible for securing their own applications and data within their AWS environment.

For example, consider a business that uses Amazon EC2 instances to host their web application. AWS is responsible for ensuring that the physical servers on which these instances run are secure, but the business is responsible for configuring firewalls and security groups to protect their own data.

It is important to note that responsibilities can be shared depending on the specific services used by each customer. The AWS Shared Responsibility Model provides guidelines on which responsibilities should be considered when deploying solutions within an AWS environment.

To further illustrate this point, consider a business that uses both Amazon S3 and Amazon EC2. While AWS manages the physical infrastructure for both services, the responsibility for securing data stored in S3 is mainly on the customer, whereas protecting data on EC2 instances falls under their responsibility.

Some critics argue that there is still confusion around what security risks are being shared. It is important for businesses to take ownership of their end of cloud security risk management so as not to rely solely on providers such as AWS. However, following best practices provided by vendors can go a long way in reducing risk factors in any partnership.

The AWS Shared Responsibility Model outlines how security and compliance responsibilities are shared between AWS and its customers, with AWS being responsible for the security of their physical infrastructure, and customers being responsible for securing their own applications and data within an AWS environment. It is important for businesses to understand this model to determine which security controls they should implement. However, businesses should also take ownership of their end of cloud security risk management and not solely rely on providers like AWS, while following best practices provided by vendors can lower risk factors.

Security of the Cloud vs. Security in the Cloud

One of the key concepts that cloud users must understand is the difference between security of the cloud and security in the cloud. As previously stated, AWS is responsible for managing and securing the underlying infrastructure of their cloud service. This is referred to as security of the cloud, as it involves securing the physical infrastructure.

Security in the cloud refers to data protection within a customer’s applications and servers hosted in the cloud. This responsibility falls on customers rather than AWS. It includes managing user access control, network settings and configurations, as well as encryption of sensitive data.

Think of security of the cloud as a hotel’s safe deposit boxes where physical things one keeps are stored. In contrast, security in the cloud is similar to passwords needed to protect one’s one belongings from intruders while inside their hotel room.

It is important to note that businesses should not ignore their responsibilities under security in the cloud just because AWS is responsible for security of the cloud. With this shared responsibility model, AWS provides best practices and guidelines on how customers can ensure their own security in addition to what AWS already provides.

For example, Amazon EC2 instances protected by a firewall provided by AWS have strict default settings with an option to customize. The customer must configure these firewalls on their end such that they will be able to control who can access their instance environments on top of what AWS has done.

Critics argue that relying solely on best practice documentation can result in inadequate protection against attacks. Cloud users need to be diligent about configuring their own systems according to current standards and proactive measures like automated patching systems that alert system managers on when patches become available.

Implementing the AWS Shared Responsibility Model

The AWS Shared Responsibility Model requires both the customer and AWS to take part in ensuring the security and compliance of their system. AWS manages and controls the physical infrastructure stack, while customers are responsible for securing their applications as well as handling identity access management (IAM). It is therefore crucial that customers implement the model effectively to mitigate any potential threats and maintain security.

One key aspect of implementing the model is identifying and evaluating your organization’s data processing needs. This includes understanding your data, classifying each data type and assigning responsibilities to ensure the secure processing and storage of all data. Any sensitive or regulated data must be stored in controlled environments, with strict access control measures in place.

Another important step is selecting a secure architecture design that incorporates access control, network segmentation, logging, monitoring, encryption services, and vulnerability management practices. Access should only be granted based on individual user roles and responsibilities through IAM best practices. At every stage of implementation, cybersecurity awareness training program must be instituted for all employees to ensure they understand their role in maintaining high levels of security.

For instance, let’s say you’re building an application on AWS using Amazon EC2 instances. As per the shared responsibility model of AWS, while AWS takes care of physical security and availability of hardware resources underlying Amazon EC2 instances as well as networks associated with them; it’s your responsibility to manage guest operating systems (including updates) and firewall configurations applied within these machines.

To further solidify this point about user access control, you can use AWS Identity and Access Management (IAM) tools to grant permissions based on what each user needs to do – for instance only allowing read permissions for logs or database queries. IAM also allows for integration with other services such as databases so that users don’t need remote connections – instead they can connect directly within your private network which minimizes exposure points.

An interesting debate that comes up is whether it’s better to be proactive or reactive when it comes to security. The former argues for planning ahead and anticipating potential threats, while the latter involves arriving at solutions after a security breach has already occurred. As with most debates, there are pros and cons to both approaches; however in terms of implementing the AWS Shared Responsibility Model, being proactive is definitely the way to go. This includes conducting periodic vulnerability scans and penetration tests, reviewing logs regularly to identify anomalous activity, and keeping an up-to-date disaster recovery plan ready in case of emergencies.

According to a 2020 IDC survey, 64% of IT professionals are leveraging security as a shared responsibility under cloud service providers like AWS to maintain a secure cloud environment.
In a 2019 McAfee report, it was found that organizations using AWS experienced more than 2,700 security threats in a month on average, emphasizing the importance of adhering to the shared responsibility model for enhanced protection.
A 2018 Gartner report estimates that by 2025, 99% of cloud security failures will be the customer’s fault, highlighting the importance of understanding and managing customer responsibilities within the shared responsibility model.

User Access Control and Data Management Practices

One area where customers have considerable responsibility under the shared model is that of user access control and data management practices. When dealing with critical data, customer permissions must be audited regularly as part of your IAM best practices. In doing so you can ensure that each user only has access to what they need and nothing more.

Data management best practices require you to enforce strict controls over how data is stored, processed, transmitted, accessed and deleted throughout its lifecycle. Data sensitive environments should be secured by role based access control mechanisms as well as encryption solutions like transport layer security (TLS) which safeguard against eavesdropping and man-in-the-middle attacks.

Suppose you have a team of developers working on critical applications in your infrastructure. By using AWS IAM policies in conjunction with Amazon CloudWatch Logs Insights, you can track user activity to find out who accessed what parts of your system and when. With this data, you can determine whether there are any unusual patterns or errors in their login attempts which could indicate a potential security breach.

Additionally by integrating various AWS services you can create a secure environment where users are prevented from leaking sensitive information outside your organization. An example would be using Amazon Macie along with AWS KMS to manage encryption keys so that valuable data stored on S3 is automatically encrypted when it’s written and decrypted when it’s read. This way, unauthorized access to sensitive information is prevented even if your buckets are accidentally exposed.

When it comes to managing user access controls there’s no one-size-fits-all approach; instead different organizations have different requirements and hence must implement a solution that works best for their use case. However, in order to efficiently implement the AWS Shared Responsibility Model genuine effort needs to be made by customers to maintain an environment which is secure and compliant with industry standards.

Advantages of the AWS Shared Responsibility Model

The AWS Shared Responsibility Model has numerous advantages for companies seeking to secure their IT infrastructure while maintaining flexibility in deployment. One clear advantage is that the model allows organizations to focus on their core competencies, rather than expending time and resources on IT security. By entrusting AWS with responsibility for “Security of the Cloud,” organizations can instead concentrate on managing their data, applications and other critical business functions.

Another advantage is that AWS manages all the physical and network infrastructure, reducing the risks of unauthorized access, data breaches or service disruptions. With its global network of data centers, AWS provides reliable, high-performance hosting services around the clock. This level of support enables businesses to scale up or down easily as required, without having to manage hardware upgrades or network implementations themselves.

Furthermore, both AWS and its customers share control over data management practices, meaning that customers can choose the best tools and technologies to manage their data in a way that aligns with their own compliance requirements. This also means that customers can leverage AWS’s industry-leading security controls and compliance certifications to demonstrate adherence to regulatory frameworks.

For example, a healthcare provider using an electronic health record system could use Amazon RDS to host its database while implementing encryption at rest to meet HIPAA compliance requirements. By leveraging AWS’s expertise in security and compliance controls, the company can avoid many of the challenges of managing its own IT infrastructure while still meeting key regulatory standards.

Another benefit is that companies can take advantage of the scalability and agility offered by cloud computing platforms like AWS. With the ability to provision resources on demand and scale up or down quickly as required, businesses can respond more readily to changing market conditions while avoiding unnecessary costs.

Overall, the shared responsibility model offers a flexible yet robust approach to IT security that is tailored to each organization’s unique needs. By leveraging AWS’s broad range of tools and technologies for security and compliance, companies can implement best practices for data management and application security while focusing on their core competencies.

Enhanced Security and Compliance Flexibility

Security and compliance are critical components of any IT infrastructure, especially for businesses that handle sensitive or regulated data. The AWS Shared Responsibility Model provides enhanced security and compliance flexibility by enabling organizations to utilize a range of tools and technologies to meet their unique requirements.

One key advantage is that AWS offers multiple layers of security controls that can be used in various combinations to meet specific needs. For instance, customers can use Amazon Inspector to assess the security vulnerabilities of their applications while leveraging features like AWS Identity and Access Management (IAM) to control user access.

Additionally, AWS provides enterprise-grade encryption capabilities that enable customers to secure their data both at rest and in transit. This includes support for Secure Sockets Layer (SSL)/Transport Layer Security (TLS) for web traffic, Key Management Service (KMS) for cryptographic key handling, and Hardware Security Modules (HSMs) for enhanced security. By making these technologies available, AWS enables customers to build highly secure architectures within its cloud environment.

Another way that the shared responsibility model supports enhanced security and compliance flexibility is by enabling organizations to maintain control over key aspects of their IT infrastructure. For example, using AWS services like Amazon EC2 Dedicated Hosts allows customers to host instances on hardware dedicated exclusively for their use, thus providing greater control over their computing environment and reducing the risks of unauthorized access or other security issues.

An organization handling classified information may require stricter controls than those provided by default shared tenancy architecture. In such cases, using a dedicated hosting solution through AWS would ensure a more secure computing environment without compromising flexibility or performance.

Finally, AWS offers a range of compliance certifications that can help organizations meet regulatory or industry-specific requirements. Compliance certifications applicable across different industries include ISO 27001, PCI DSS, SOC 1/2/3, and HIPAA, among others. By leveraging these certifications and other security tools in combination with the shared responsibility model, organizations can build secure and compliant IT infrastructures that meet their specific needs.

In the next section, we will explore some of the challenges that organizations may face when implementing the AWS Shared Responsibility Model.

Addressing Potential Challenges in the Shared Model

While the AWS Shared Responsibility Model provides a clear framework for dividing responsibilities between customers and service providers, some challenges can arise. These challenges can include understanding who has responsibility for particular elements of security, managing user access controls, and ensuring that compliance regulations are met. In this section, we’ll explore some common challenges faced by organizations when implementing the Shared Responsibility Model and offer suggestions for addressing them.

One common challenge that organizations face is determining what they are responsible for versus what AWS is responsible for in terms of compliance. Depending on the AWS services used and the IT environment integration, different areas of responsibility may fall on different parties. For example, an organization may be unclear about which regulations are applicable to its use of AWS services or how to configure them properly. A helpful approach here would be to consult AWS documentation or experts in the field to clarify any areas of uncertainty.

Another potential challenge is ensuring that users have appropriate access controls while still maintaining proper security posture. The Shared Responsibility Model requires that customers manage their own identities and access control policies within their own environment using IAM tools provided by AWS. This means that customers must ensure that users are authorized to access only what they need to perform their duties. Additionally, customers must ensure that roles and permissions are assigned appropriately based on job function, seniority level, etc., while also limiting access when not needed. Failing to adequately address these concerns can lead to severe consequences such as lost data or compromised systems.

To address these issues, some organizations choose to implement separate identity management solutions outside of AWS. While this can simplify administration and provide greater control over user access policies, it also introduces additional complexity into already complex environments. Moreover, many third-party vendors lack mature integrations with AWS services or may require custom development efforts.

One potential solution is for organizations to utilize AWS’ Identity and Access Management (IAM) service. IAM offers a range of tools and services that enable organizations to define, manage, and enforce policies for access control across their AWS environment. Additionally, customers can leverage IAM roles to provide temporary credentials to external users or use federated login options to support single sign-on (SSO) capabilities.

Another challenge that may arise within the Shared Responsibility Model is ensuring that sufficient levels of security are maintained at all times. While AWS manages the security of its infrastructure layer and abstracted platform services, customers are responsible for implementing secure guest operating systems, applications, and data configurations. One helpful analogy here is thinking about building a house: Just as contractors must ensure that the foundation is stable before adding additional construction layers, organizations must implement appropriate baseline security protocols before entrusting more data or workloads to AWS.

In conclusion, while the AWS Shared Responsibility Model provides an excellent framework for dividing up responsibilities between providers and customers, challenges can arise when implementing it in practice. These challenges commonly include issues around compliance regulations, user access controls, and implementation of appropriate security policies. By leveraging existing AWS tools like Identity and Access Management (IAM), carefully defining areas of responsibility, and following best practices around security configuration management, organizations can better address these challenges and realize the benefits of this model over time.

Common Questions

What are the customer’s responsibilities in the AWS shared responsibility model?

In the AWS shared responsibility model, customers are responsible for securing their own data and applications up to the operating system. This includes configuring security settings, managing access controls, and conducting regular security assessments.

According to research conducted by Gartner, “through 2025, 99% of cloud security failures will be the customer’s fault” (Gartner, 2018). This highlights the importance of understanding and fulfilling customer responsibilities in the shared responsibility model.

AWS provides a variety of tools and resources to help customers meet their responsibilities. These include security features such as Identity and Access Management (IAM) and Services like AWS Config which enables continuous monitoring and compliance checks.

Ultimately, it is crucial for customers to understand and take ownership of their responsibilities in order to safeguard their data and applications on the AWS platform.

What are the AWS provider’s responsibilities in the shared responsibility model?

In the AWS Shared Responsibility Model, the provider’s responsibilities include the security and management of the underlying infrastructure that supports the cloud. This includes physical security of data centers, network and firewall configuration, and operational security such as monitoring and incident response.

According to a report by Gartner in 2022, “AWS continues to be recognized as a leader in public cloud IaaS due to its comprehensive service offerings and expertise in running infrastructure at scale.” The report also highlights AWS’ strong position in security and compliance.

Additionally, AWS offers numerous security features for customers including identity and access management, encryption options, network security tools, and compliance certifications. These features are designed to help customers meet their own shared responsibility obligations.

However, it’s important to note that while AWS provides a secure infrastructure, customers are still responsible for securing their applications, data, and other assets within the cloud. This includes configuring access controls appropriately, patching operating systems and applications, and monitoring for potential threats or vulnerabilities.

Overall, understanding the shared responsibility model is crucial for any organization using cloud services. By working together with their provider (in this case AWS), customers can ensure their data and assets are properly secured in the cloud.

How does the AWS shared responsibility model differ from other cloud service provider models?

The AWS shared responsibility model sets itself apart from other cloud service providers by clearly defining the security responsibilities of both the customer and AWS. This means that customers have more control over their data and infrastructure while still benefiting from the security measures provided by AWS.

Unlike other cloud service providers, AWS takes responsibility for the physical security of their data centers, as well as the security of their cloud infrastructure. This includes the security of hardware, virtualization layer, storage location, and network infrastructure.

On the other hand, customers are responsible for securing their applications and data within the AWS platform. This includes configuring access controls, managing user identities and permissions, encrypting data in transit and at rest, and ensuring compliance with regulations.

According to a report published by Gartner in 2020, the AWS shared responsibility model played a significant role in helping customers improve their overall security posture. In fact, Gartner stated that “by 2023, 99% of cloud security failures will be the customer’s fault.”

In summary, by clearly outlining the security responsibilities of both parties involved, the AWS shared responsibility model provides customers with greater control over their own security while still benefiting from world-class cloud infrastructure security provided by AWS.

Are there any common misconceptions about the AWS shared responsibility model?

Yes, there are common misconceptions about the AWS shared responsibility model. One of the most widespread is that customers tend to believe that once they move to the cloud, all security responsibilities shift entirely to AWS. However, this is not true, and it is important for businesses to understand how the responsibility is shared when using AWS.

According to a survey conducted by LogicMonitor in 2019, 66% of IT professionals believed that cloud providers were solely responsible for securing their customer data. Furthermore, 70% of those surveyed thought they were less accountable for security in a cloud environment compared to traditional on-premise IT infrastructures. These statistics suggest that there is still a misunderstanding regarding security and responsibility in the cloud.

It’s essential to note that while AWS manages physical security and compliance of its infrastructure, customers are responsible for managing security controls within their own accounts. Customers must ensure proper configuration of their applications and infrastructure and implement safeguards such as firewalls, identity access management (IAM), data encryption, patch management, and more.

To quote a statement from AWS’ Shared Responsibility Model whitepaper:

“Customers retain control of what security they choose to implement to protect their content, platform, applications, systems, and networks, no differently than they would in an on-site data center.”

In conclusion, understanding the AWS shared responsibility model is crucial for businesses who use AWS or plan to migrate to the cloud. It’s essential to recognize that although AWS does provide excellent security measures, customers must take responsibility for security controls in their own infrastructures.

How does the shared responsibility model impact security and compliance in AWS?

The shared responsibility model is a key concept in AWS that dictates the different security responsibilities between the cloud service provider and its customers. This model enables users to have greater control over their data, while also allowing AWS to maintain the necessary security standards.

From a security standpoint, customers are responsible for securing their applications, data and credentials, as well as managing compliance requirements, while AWS is responsible for the security of its infrastructure. Amazon claims that its infrastructure is designed to be highly secure, and that it has implemented extensive controls to maintain this level of security—such as physical and environmental controls, network and perimeter controls, and access controls. Additionally, AWS provides built-in security measures such as encryption, monitoring tools and identity and access management services.

In terms of compliance, AWS adheres to various industry standards such as HIPAA for healthcare organizations and PCI DSS for payment card processing companies. However, customers are ultimately responsible for ensuring they comply with any relevant regulations for their industry or region.

According to a report by McAfee in 2020, misconfigured cloud storage services were the primary cause of 1.5 billion records being exposed during the first half of the year alone. This highlights the importance of understanding one’s responsibilities in an AWS environment. Following best practices such as using multi-factor authentication (MFA) for user access and keeping sensitive data encrypted can greatly reduce the risk of data breaches.

Ultimately, understanding the shared responsibility model is crucial for proper security and compliance in AWS. By leveraging AWS’ infrastructure capabilities while also implementing effective security practices on one’s own end, businesses can ensure a secure cloud environment.

AI-driven Attacks

Cybercriminals leverage AI in various ways and explore further enhancements to increase their attack capabilities. For example:

Advanced phishing and social engineering
Generative AI empowers bad actors to automate fraudulent activities, such as crafting of phishing mails, generating fake social media accounts, reviews, and comments, impersonating service and support agents, and carrying out scams. Massive datasets of stolen credentials and personal data can be analyzed in seconds to enhance phishing and social engineering campaigns.
Adaptive malware and botnet generation
AI-driven malware and botnets that shapeshift during attack stages expose exponential risk to IT and security teams by evolving in real-time to avoid security measures, identify vulnerabilities in target systems, and coordinate attacks more efficiently than human-generated threats. A growing concern in cybersecurity is related to AI-generated malware capable of bypass traditional signature-based defenses.
Zero-day exploits and supply chain attacks
Threat actors are creatively hiding malicious code and zero-day exploits from defenders to widen the attack distribution and extend the blast radius. For example, hiding malicious payload inside an AI model that is built to fulfill legitimate functions such as biometric authentication. In another scenario attackers can manipulate AI to learn algorithms of threat intrusion systems and evade their detection.
Credential stuffing and brute-force attacks
By automating the process of gaining unauthorized access to business accounts and systems through stolen credentials and common password combinations AI speeds up the attack itself. Additionally, machine learning algorithms are utilized to evade security detection systems and AI-driven tools accelerate password cracking by analyzing patterns in leaked password databases.
Deepfake attacks
Videos and audio generated by AI impersonate familiar voices and faces to manipulate individuals into performing actions that grant access to sensitive data, systems, and funds. The technology behind deepfakes creates convincing audio and images with minimal input gathered via social media or other public platforms.

AI has the power to amplify the impact and the complexity of cyberattacks increasing potential damage and risks to your data estates. Commvault helps you to address uncertainty by combining cutting edge data protection technology with strong cybersecurity measures in alignment with regulatory frameworks to invest in proper cyber resilience and detection mechanisms that keeps your data protected.

Spotting Threats Early

ThreatWise, our cyber deception service integrated in the Commvault Cloud that layer’s defenses along the path to your data, shielding it from AI-driven attacks, and surfacing threat actors that are targeting the most valuable assets in production – your data. This early warning layer enables your organization to adopt a cyber resilience strategy defending your data against tomorrows threat actors:

Limit the blast radius of an incident and divert the threat sooner – before it’s time to recover. ThreatWise alerts key business stakeholders upon first touch while simultaneously luring attackers in and away from actual critical assets, forcing them to waste resources.
Spot the attacker and gather insights about utilized tactics, techniques, and procedures across the complete kill chain. By revealing the original source of the AI-driven attack the symptoms and cause of it can be remediated to stop its aggravation.
Delay attacks by confusing and misleading attackers’ algorithms. ThreatWise feeds AI-driven threats fake tokens leading to deceptive data that is making it harder to automate and execute attacks while wasting threat actors’ time.
ThreatWise detection is highly accurate, because it’s not reliant on signatures to identify malicious activity, spotting zero-day attacks, shape shifting malware, and silent threats across workloads and data estates.
Maximize your response time by automating the alteration of key stakeholders across the business and ease coordination of your recovery to limit impact.

Keeping pace with evolving threats

For more information about how Commvault helps you unleash the power of AI without skyrocketing costs read this blog.

Learn more – see the joint solution in action

At Commvault, we’re excited to pursue data protection excellence with Microsoft. For organizations interested in seeing exactly how Microsoft 365 Backup Storage will function in a Commvault environment, click here for a walk-through demo. In the coming weeks, we will publish additional information regarding pricing, public preview, and general availability. For anyone interested in learning more about the integrated Commvault/Microsoft solution, email us at microsoft@commvault.com.

The Current Cyber Threat Landscape: When not If

According to a recent IDC study commissioned by Commvault, 61% of respondents believe that data loss within the next 12 months due to increasingly sophisticated access is “likely” to “very likely.” This alarming statistic highlights the urgent need for robust cyber resilience measures. Organizations must be prepared to detect, thwart, and recover from ransomware attacks swiftly. It’s a matter of when and how often.

This is why we have forged partnerships across the security tool chain, including security information and event management (SIEM), security orchestration, automation, and response (SOAR), network detection and response, vulnerability risk threat detection, and data governance and privacy.

Integrating with Leading Security and AI Partners

Commvault’s integration with a diverse range of security and AI partners through the Commvault Cloud platform offers customers a comprehensive approach to cyber resilience. Among them:

Avira: Provides advanced AI-driven threat protection, enabling customers to rapidly identify potential nefarious activity and enhance protection against emerging threats.
CyberArk: We live in a zero-trust world when it comes to cybersecurity. Commvault’s integration with CyberArk’s Identity Security Platform helps customers follow strong Zero Trust architecture practices, reducing the risk of credential theft and exploitation in the face of double and triple extortion attacks.
Darktrace: When “when” happens, quick response is key. Combining Darktrace’s innovative HEAL platform and Commvault’s AI-powered data insights, joint customers can proactively defend against potential cyber threats and swiftly respond to incidents.
Databricks: The more data you amass, the more difficult it can be to maintain governance. The integration between Databricks and Commvault enables customers to leverage AI-driven search capabilities, making it easier to identify sensitive data and improve data governance.
Entrust: Get advanced cyber resiliency to protect critical data from current and future threats with Entrust’s post-quantum cryptography and data encryption solutions, integrated with Commvault Cloud.
Netskope: Netskope’s global SASE cybersecurity platform, combined with Commvault Cloud, helps organizations apply zero trust principles to protect data, ensuring ultra-sensitive data awareness and threat protection.

These build on our already announced integrations with Microsoft Sentinel for intelligent SIEM and Palo Alto Networks’ Cortex XSOAR to accelerate response time.

Battling the threats of today and tomorrow

This is just the tip of the iceberg as there are more integrations with Commvault Cloud in the works to strengthen your cyber resilience against bad actors, malicious threats, and ransomware.

Together, Commvault and our partners help you navigate the evolving threat landscape and safeguard your data, applications, and production workloads across hybrid and multi-cloud environments. To learn more about how these integrations can help power the Commvault Cloud, visit www.commvault.com/platform/integrations.

Meet your new cyber resiliency partner, Arlie

There’s obviously a lot of hype around AI and how it’s changing the way we work and interact with software and systems. We’re putting AI to use help you act quickly and efficiently.

Users of Commvault Cloud will soon have access to Arlie—short for “Autonomous Resilience” and much easier to say—a new AI co-pilot that’s at the ready 24 hours a day, responding to inquiries in plain, simple language. We’re using Generative AI models to consolidate information and reports plus provide users with personalized actionable responses. You can use Arlie to verify or validate clean point of recovery for critical systems or generate requested code in mere seconds.

I’m excited about the possibilities this creates. It’s fueled by an integration with Azure OpenAI to enable amazing human-like interaction within Commvault Cloud to:

Give you real-time threat analysis and report summaries showing the latest information about their cyber resiliency health, removing the need to sift through filters and reports to prioritize the most pressing information. Imagine the time savings.
Offer a simplified way to build an integration or code an action: you simply type a description of what you want to do, and the code assistant will generate the code on the spot. No more missing semi-colon fouling up the works.
Provide context-sensitive, guided product walk-throughs that make it easy for you to set-up, customize, and tune Commvault Cloud to your specifications. Simply ask “how to” questions and get step-by-step documentation complete with annotated screenshots.
Constantly monitors the performance of Commvault Cloud using generative AI to find issues, provide fixes, and offer real-time recommendations on how to optimize cyber resilience.

That’s just the start. We’ll have more generative AI model integrations following fast.

Cloudburst™ Recovery

You know and love us for our ability to recover from ransomware or other critical situations quickly. We’re making it faster and more efficient.

The new Cloudburst™ Recovery capability can help you improve business continuity by using infrastructure-as-code and cloud-scaling to automate rapid and frictionless recovery of data to any location. This enables mass recovery from cloud storage at scale with the highest speed possible. You don’t have to run an expensive cluster in the cloud to be able to do this, saving you money and headache.

Cleanroom Recovery

We also have what we call Cleanroom Recovery, one of the standout features of Commvault Cloud. It’s a cutting-edge service that ensures rapid, frictionless, and reliable recoveries after a cyberattack.

When a cyberattack occurs, having a clean backup is crucial. But it’s equally important to have a clean location for recovery. That’s where Cleanroom Recovery comes in. With Commvault Cloud, you can recover your data to a secure, isolated environment in the cloud that is specifically designed for recovery purposes. This cleanroom environment is “at the ready,” meaning it’s always available to you and prepared to facilitate the recovery process.

Cleanroom Recovery offers several benefits, including:

Providing a secure and isolated space for recovery, ensuring that your data is protected from any lingering threats or vulnerabilities. This gives you peace of mind knowing that your recovered data is clean and free from any potential malware or malicious elements.

Enabling rapid recoveries. Time is of the essence when it comes to recovering from a cyberattack, and Cleanroom Recovery ensures that the process is as quick and efficient as possible. Using the power of the cloud, Commvault Cloud enables fast and seamless data recovery, minimizing downtime and allowing you to get back up and running in no time.

Cleanroom Recovery is not just for post-attack recovery; it’s also a valuable tool for conducting routine incident response testing. By regularly testing your recovery processes in the cleanroom environment, you can ensure that your systems are prepared and optimized to handle any potential cyber threats. This proactive approach to testing and validation helps to strengthen your overall cyber resilience.

AI-driven threat prediction

Attackers are using AI to make ransomware even quieter and harder to detect. One of the emerging attacks uses AI to change the shape of the malware. Security experts call these shapeshifting or poly-morphic attacks. Whatever you call it, they are extremely hard to see and go undetected by traditional anomaly detection techniques. In Commvault Cloud we’re using AI to fight AI. This helps you find AI-driven zero-day threats that have already impacted backup content so you can quarantine and recover data cleanly while avoiding reinfection during recovery.

Managing cyber resilience for you

As part of the Commvault Cloud release, we’re adding Platinum Resilience, a fully managed service that provides unmatched protection, engagement, and responsiveness to cybersecurity threats and disaster situations. This service, which is being introduced to select customers as part of an early access preview program with full availability planned in early 2024, provides the following:

Foundational backup and recovery, advanced AI driven automation, cyber deception, recovery testing and readiness checks, advanced reporting, security audits, custom telemetry, and more.
Powerful and comprehensive hybrid data protection and resilience, with the ease of use of the cloud using a dedicated, isolated control plane.
A ransomware readiness and response team dedicated to everything from setup to ongoing testing and validation to recovery upon a cyber event.

We’re confident that Platinum Resilience offers the best in end-to-end cyber resilience and we’re backing that up with a new Commvault Protection Warranty to give everyone from IT managers to board members peace of mind that recovery from an attack is guaranteed.

Commvault Cloud for Cyber Resilience

This is the boldest product launch in my 26-year history here at Commvault. I’m confident that your organization’s approach to cyber resilience will be revolutionized by Commvault Cloud, powered by Metallic AI. With its unified platform, advanced AI capabilities, and unique architecture, Commvault Cloud offers a comprehensive solution for data protection, security, intelligence, and recovery. By leveraging the power of AI, you can benefit from enhanced visibility, simplified processes, and optimized cyber resilience.

With Commvault Cloud, you can have peace of mind knowing that your data is safe, your operations are protected, and your business can continue to thrive in the face of evolving cyber threats. It’s the ultimate solution for achieving cyber resilience in your hybrid enterprise.

Commvault Cloud, a unified data resilience platform

A common misconception is that Commvault bought or acquired our award-winning Metallic SaaS technology. Well, we did neither… we built it from the ground up. Metallic was purposefully crafted to join Commvault’s existing portfolio of data protection offerings, as a light-touch, cloud-centric alternative.

Commvault Cloud, our newly introduced cyber resiliency and recovery platform, unifies our cloud, software, and appliance-based services into a single place. This not only provides our customers with a consistent and streamlined experience to consume our technologies, but also creates new synergies and capabilities that advance how our customers protect their data. Commvault Cloud stands as the industry’s first platform for true cloud data security. Simpler, smarter and more scalable than ever before for trusted cyber resilience to secure and recover data in today’s hybrid world.

Benefits for Metallic customers

By melding Metallic and Commvault technologies together into one platform, customers get even faster innovation, automation, and performance. While Metallic users will still enjoy the same SaaS-based backup they’ve come to know and love, the Commvault Cloud will pave the way for even more cloud-delivered advancements in disaster recovery, data security, artificial intelligence, and more. It means the best of all worlds: Simple SaaS protection, next generation cyber recovery innovations, and more flexibility of choice.

Advanced automation and intelligence with Metallic AI

While our SaaS-delivered backup and recovery offerings will be consolidated into our new Commvault Cloud platform, the spirit of Metallic lives on in our AI layer: Metallic AI. Metallic AI serves as our artificial intelligence layer that powers our new platform. From automation and machine learning to AI, Metallic AI brings greater performance and efficiency to every aspect of the Commvault Cloud. Metallic AI will also operate as a powerful integration layer for ecosystem partners, enabling developers to create robust, innovative new services that continuously optimize Commvault Cloud, and deliver greater value for those who use it.

We are excited for this next phase in our journey, how the Commvault Cloud is redefining cyber resiliency and recovery as we know it, and continuing to support our customers with award-winning SaaS-based data protection.

Want to learn more? Check out the following video or visit our FAQ in the Commvault Community for additional details.

SaaS Considerations

To achieve SaaS-delivered flexibility, there are five key factors to consider:

It’s important to choose a SaaS provider that offers a highly scalable and reliable cloud infrastructure. A significant advantage of SaaS is its inherent scalability. This ensures that the software can handle increased workloads and provide uninterrupted access to users.
Organizations should look for SaaS solutions that offer anytime, anywhere access. Gone are the days of being tied to a specific physical location to access critical business applications. As of last year, 41.4% of cloud leaders say they are increasing their use of cloud-based services due to the macroeconomic climate.² This means that employees can access the software and data from any location, as long as they have an internet connection. This flexibility empowers remote work, collaboration across geographies, and increases productivity.
Rapid deployment and updates are crucial for achieving SaaS-delivered flexibility. SaaS solutions can be deployed quickly, often within hours or days, allowing organizations to start using the software and reaping its benefits sooner, driving efficiency and productivity. Additionally, SaaS providers handle updates and maintenance, ensuring that businesses always have access to the latest features and security enhancements without any disruption or costly overhead of maintaining on-premises systems.
Customization without complexity is another important aspect to consider. Flexibility in software often goes hand in hand with customization, so organizations should look for SaaS solutions that offer the ability to tailor the software to their specific business requirements without the need for complex and costly customization. Again, we see a need for this level of customization as 72% of IT Pros are taking a hybrid approach by combining public and private clouds.³ With this model, businesses can configure the software to align with their unique processes and workflows, empowering them to work the way they want to, without compromising on functionality.
Integration and collaboration capabilities are essential for achieving SaaS-delivered flexibility. SaaS solutions should offer APIs and connectors that enable seamless integration and data exchange with other systems. This allows businesses to create a unified ecosystem of software tools, streamlining processes and enhancing productivity.

In conclusion, SaaS-delivered flexibility empowers organizations to adapt quickly to changing business needs. By choosing a SaaS solution that offers scalability, anytime access, rapid deployment and updates, customization options, and integration capabilities, businesses can achieve the flexibility they need to thrive in today’s dynamic business environment. Embracing SaaS is not just a technological shift; it is a strategic move towards future-proofing your business and unlocking its full potential.

For more information on SaaS delivered flexibility, please view our Solution Brief, and watch our recent October 3 webinar on demand.

References

1. Flexera State of the Cloud report, 2023 – 2. Google Cloud Brand Pulse Survey, 2022 – 3. Google Cloud Brand Pulse Survey, 2022

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