We’ll cover the best practices businesses should apply when adding hybrid cloud backups, as well as common challenges and components to consider.

What is Hybrid Cloud Backup and How Does it Work?

Hybrid cloud architectures combine on-premises environments with one or more cloud resources, and hybrid cloud backups use this combination to create a more comprehensive strategy for data protection.

Hybrid cloud backups work by having data backed up to on-premises storage devices, such as servers and hard drives, and then saved as a copy to cloud storage. By having data stored in both locations, businesses improve their redundancy and have a backup they can use in the event of a disaster or outage. To ensure both copies are up-to-date, data is synchronized regularly, based on the level of tolerance a business has for lost files as part of their recovery point objective (RPO).

What Are the Benefits of Hybrid Cloud Backups?

Businesses that use hybrid cloud backups can enjoy benefits such as: 

• Improved redundancy: Saving a copy of your organization’s data in the cloud means that you have easy access to a backup that can be used during a disaster. This is one of several redundancy measures a business should implement when executing a disaster recovery plan.
• Better disaster recovery: Restoring data from the cloud can help businesses achieve their recovery point objectives (RPO) and recovery time objectives (RTO).
• Scalability: Storage capacity needs are not likely to be consistent from month to month. Having cloud storage as part of a hybrid backup solution means that businesses can easily scale based on their resource needs.
• Cost-Effectiveness: While it can cost more to store data in multiple locations, these expenses far outweigh the average cost of downtime businesses may experience during an outage, data breach, or other type of disaster. Hybrid storage can also be more flexible thanks to the flexibility and scalability of cloud storage, allowing businesses to only pay for what they need.

What Are the Challenges of Hybrid Cloud Backups?

Hybrid cloud backups can provide greater data protection and create more flexible storage options, but there are some challenges businesses may face when implementing a hybrid solution.

Because hybrid cloud is a mix of cloud and non-cloud environments, organizations need to manage complexity to leverage the environments effectively. There may be several different tools, security configurations, and processes to navigate to minimize vulnerabilities and keep backups effective. In fact, 32% of businesses list struggling with migrating workloads when moving to public cloud environments as one of their biggest challenges.

Data can also get fragmented when it spans across on-premises and cloud environments. It’s important that data is organized, classified, and synced properly to avoid issues associated with fragmentation.

Infrastructure security measures from cloud providers can make hybrid cloud backups more secure, but businesses also need to understand their role in keeping data protected in transit and at rest. Organizations should also understand which compliance measures they need to have in place to align with relevant data privacy regulations for their industry or type of business, which can get harder to unify when more environments are added.

Other challenges can include risk of vendor lock-in, lack of necessary in-house skills, and cost management associated with cloud storage and backups. Flexibility is a benefit, but vendor lock-in can make your future options feel rigid. Having someone available who can help you navigate backup options can help you manage costs and keep your options open.

Important Components of a Hybrid Cloud Backup Strategy

The essential components of any hybrid cloud backup strategy will consider the infrastructure used for backups, how data will be synchronized and replicated, where data will be managed, and the security measures necessary to protect data in any state. This can also be part of a larger hybrid cloud strategy.

On-Premises Backup Infrastructure and Cloud Backup Services

Initial backups and local data redundancy can be stored on physical storage devices such as hard disk drives (HDDs) or solid-state drives (SSDs). Long-term archival and offsite disaster recovery can be aided with the use of scalable cloud storage options.

Cloud services should be able to meet your goals for security, scalability, and compliance. If you think your needs may change in the next few years, analyze how easy it would be to migrate data from one provider to another.

Data Replication and Synchronization

For hybrid cloud backups to work effectively, data needs to move efficiently and quickly between on-premises and cloud environments. Replication tools can create copies of onsite data in the cloud for secondary off-site backup purposes. Synchronization keeps each copy current between environments, so if the backup needs to be used, little to no data is lost.

Centralized Backup Orchestration and Management

To make orchestration easier, backups should be managed by a centralized platform. The platform should allow your organization to schedule backups, generate reports, and monitor data replication efforts. This can help streamline the backup process and reduce errors that can make disaster recovery efforts more difficult.

Security Measures and Compliance Considerations

To safeguard critical data in hybrid cloud backups, data needs to be encrypted at rest and in transit. Other robust security measures businesses should implement include multi-factor authentication and access controls. Data backup policies should also comply with relevant policies such as HIPAA, GDPR, and PCI DSS depending on the level of data sensitivity, location of the business, and industry.

Six Best Practices When Implementing Hybrid Cloud Backups

Establishing a strong hybrid cloud backup strategy with the aforementioned components is the first step in implementation. From there, apply the following best practices to ensure your backups are achieving your business objectives.

1.) Establish RTOs and RPOs

An RPO identifies how much data a business can lose before it significantly impacts their processes or revenue. An RTO describes how much time a business can stand to use to restore critical business systems and processes.

Some organizations can afford to lose a day’s worth of data or more, whereas others would experience major disruptions in business processes if they lost more than a few minutes of data. The same goes for recovery time. Some businesses can go days before getting back to business as usual. Others need to be back up and running in minutes.

Your company’s RTO and RPO will depend on the sensitivity of your data and how much you rely on the workloads to conduct critical business processes. The RTO will dictate the backups’ recovery speed, while the RPO will also determine backup frequency to minimize data loss.

2.) Develop Backup and Recovery Policies

Creating a comprehensive policy around data backup and recovery can help reinforce your approach across your organization. A strong policy should include:

• Backup schedules: What’s the frequency that should be used for data backups?
• Retention periods: How long should data be saved?
• Disaster recovery procedures: Who is responsible for which steps, and what needs to happen in order to restore business processes?
• Testing and validation: How will you ensure your backups are working properly?

3.) Determine Your Data Security and Protection Requirements

Who needs access to which types of data? What other security protocols need to be enacted to protect data?

The sensitivity of your data and regulatory requirements will determine the security measures that need to be used to protect data. This can include encryption standards, access controls, and data transfer protocols.

4.) Evaluate Cloud Backup Providers

Before choosing a cloud backup provider, you should evaluate a few options.

You’ll want to evaluate based on the following questions:

• How well can the cloud provider accommodate future growth? How flexible and scalable is the infrastructure?
• Does the provider offer clear and detailed Service Level Agreements (SLAs) that guarantee data availability and recovery times?
• Which security features are available from the cloud provider, and which need to be implemented by the customer?
• What management and monitoring tools and capabilities are offered?
• What does the pricing model look like? Are there cost savings available for predictable workloads?
• How do people rate customer support? What is their reputation like?

5.) Assess Potential Integration Challenges

Depending on how old your on-premises infrastructure is, you may experience integration challenges with your chosen cloud backup solution. During and after the cloud provider selection process, you’ll need to think about how compatible the systems are, what data transfer requirements look like, and whether you’ll need additional software or other integrations to make syncing and transfer smooth.

6.) Outline Testing and Validation Schedule

Once everything is set up, it’s time to test. A regular testing schedule should confirm that hybrid cloud backups are ready during backup and data recovery scenarios.

Plan how often you want to simulate disasters and the types of scenarios you want to test. This will depend on where your data centers are located, how much redundancy you have, and the level of your data’s sensitivity that you’re trying to protect and restore.

By testing regularly, you can quickly identify deficiencies in your plan and implement additional safeguards before a real disaster.

Exploring Hybrid Cloud Backup Options

Choosing the right hybrid cloud backup solution will come down to how well you understand your specific priorities and needs. If you’re not sure where to start, TierPoint is here to serve as a partner to help you navigate your options. We have deep expertise in designing and implementing hybrid cloud and disaster recovery solutions that work with your existing infrastructure and meet your data storage and compliance needs.

TierPoint is also vendor-neutral and well-versed in integrations, allowing you to achieve greater flexibility when you ultimately select a cloud vendor. Learn more about our hybrid cloud consulting and schedule time to talk to a member of our team. In the meantime, check out this infographic to discover the 13 essential steps to creating an effective disaster recovery plan.

Whether those goals are best met with one cloud, a hybrid model, or a multicloud model will depend on your unique situation, dependencies, budget, and available resources. We’ll cover the difference between multicloud and hybrid cloud so you can make an informed next step.

Public Cloud vs Private Cloud?

Hybrid environments combine public and private clouds. And in the case of hybrid IT, it can also include non-cloud environments. Generally, the choice between public and private cloud will come down to how much control businesses want over resources compared to the amount of flexibility they need.

Public cloud providers, such as AWS and Azure, rent out resources to companies in predetermined amounts at a discount, or on a model where you pay for what you use. Businesses have the flexibility to scale up or down their resources on-demand. However, they must navigate and configure the security settings and tools provided by the public cloud provider to ensure optimal security.

Private cloud can run on-premises or offsite with a data center provider. Organizations have significantly more control over configurations and security settings in a private cloud environment. However, scaling resources can be more challenging, and the infrastructure is often more expensive compared to public cloud options. This control and security, combined with the challenges of scalability and cost, make hybrid cloud solutions an attractive option for many businesses.

What is the Difference Between Multicloud and Hybrid Cloud Computing?

In cloud computing, we often hear the terms “multicloud” and hybrid cloud. While both terms sound similar, there are a few key differences organizations tend to overlook. Understanding the differences between these two cloud approaches is essential for organizations that are striving to ensure cloud optimization and meet business needs.

Architecture

A hybrid cloud is the combination of cloud and on-premises infrastructure in a unified framework. It could include public cloud (Microsoft Azure, AWS, etc.) and private cloud infrastructure. Hybrid cloud adoption has increased over the past few years due to its many benefits, which we’ll be covering shortly.

Multicloud computing is the use of multiple public cloud platforms to support business functions. Multicloud deployments can be part of an overall hybrid cloud environment. A hybrid cloud strategy may include multiple clouds, but a multicloud strategy isn’t necessarily hybrid.

Intercloud Workloads

In a multicloud environment, workloads are deployed across different public clouds and often require additional processes and tools for interoperability. Similarly, hybrid cloud environments can include these workloads but also involve movement between cloud and on-premises infrastructures. This flexibility is often necessary for legacy systems with numerous dependencies that cannot be easily migrated to the cloud.

Vendor Lock-in

Vendor lock-in happens when a business feels overly reliant on one cloud provider and finds it difficult to switch to a new provider without significant investment and resources to do so. While both formats may introduce vendor lock-in, this may be more common in hybrid cloud environments where businesses are only using one public cloud provider. In a multicloud configuration, organizations may have more flexibility to move workloads to different public cloud environments.

Pricing

This flexibility in options within a multicloud environment can lead to more competitive pricing for businesses. Public cloud resources can be purchased in discounted packages for predictable workloads, while pay-as-you-go pricing is available for variable workloads.

Availability

With hybrid cloud, availability depends on both the public cloud provider and the on-premises infrastructure in use. In contrast, a multicloud environment can offer higher availability since data and workloads are distributed across multiple public clouds, reducing the risk of downtime.

Data Storage

Data storage has some similarities and differences between cloud environments. In hybrid cloud storage, on-premises storage (private cloud) is combined with public cloud resources. This provides greater control for sensitive data stored on the private cloud, but also requires tools to move data between environments that may be harder to set up compared to multicloud environments. Hybrid cloud can be ideal for businesses that have a mix of sensitive and non-sensitive data, and for those that want greater control over their core infrastructure.

With multicloud storage, data is stored across public cloud providers, which offers greater flexibility and scalability. Although multicloud storage can also be complex to manage, it reduces the risk of vendor lock-in by providing businesses the option to choose between different public cloud providers based on their specific needs and cost considerations. Multicloud is well-suited for businesses that want more scalability and flexibility, and don’t have as many data residency regulation concerns.

Security

In comparing multicloud and hybrid cloud environments, security plays a crucial role. Hybrid cloud setups allow organizations to implement tailored security measures across both public and on-premises infrastructures, providing greater control over sensitive data. In contrast, multicloud environments, which rely on multiple public cloud providers, often have less room for customization. While this can present challenges for specific compliance needs, many public cloud providers still meet essential standards such as GDPR and HIPAA. Ultimately, the choice between the two depends on an organization’s specific security requirements and regulatory obligations.

Flexibility

In terms of flexibility, hybrid cloud environments offer organizations the ability to seamlessly integrate on-premises and public cloud resources. This allows businesses to choose where to host specific workloads based on factors like cost, performance, and compliance. On the other hand, multicloud environments provide flexibility through the use of multiple public cloud providers, enabling organizations to select the best services from each provider.

While both approaches enhance adaptability, hybrid clouds excel in integrating legacy systems, whereas multicloud setups offer diverse options and avoid vendor lock-in, allowing businesses to respond more dynamically to changing needs.

How is Hybrid Cloud Similar to Multicloud?

Despite these differences, hybrid cloud and multicloud share many similarities. They can both be solid frameworks to store sensitive data when configured well, but they can come with common challenges, such as cloud complexity.

Infrastructure Security

Both hybrid and multicloud environments operate on a shared responsibility model, where the level of infrastructure security responsibility may vary. Cloud providers are responsible for securing the underlying infrastructure, while customers must secure their applications, data, and access controls within that infrastructure.

Key responsibilities for businesses include identity and access management (IAM), data encryption, and vulnerability management. Users should have access only to the resources necessary for their roles, whether in public or private clouds. Data must be protected both at rest and in transit, so organizations need to implement proper encryption measures. Regularly scanning for vulnerabilities and applying patches is essential to mitigate risks associated with security weaknesses, including zero-day attacks. By actively managing these responsibilities, organizations can enhance their overall security posture in any cloud environment.

Storing Sensitive Data

Even though public cloud providers offer fewer security customizations for businesses, both hybrid and multicloud environments can be suitable for storing sensitive data. Hybrid cloud gives organizations the power to place their most sensitive information on private infrastructure, whereas multicloud infrastructure allows for redundancy across multiple public cloud providers, mitigating risks from outages and data breaches.

Managing Data

In both multicloud and hybrid cloud, businesses must determine how to manage data across different platforms without compromising accessibility or performance. Hybrid clouds require tools and processes to facilitate data movement between public and private environments. While multicloud setups can simplify data management by leveraging multiple public clouds, they may still necessitate additional configuration to ensure effective data movement between those clouds.

Regulatory Compliance

Different businesses and industries are subject to different regulatory requirements, such as HIPAA, GDPR, CCPA, and PCI-DSS. Most public cloud providers are certified to meet common compliance standards, but if you have very specific needs, you may need to talk with the provider to confirm they can meet your compliance capabilities. Hybrid cloud offers more control over regulatory compliance, allowing businesses to store sensitive data on-premises or in an offsite private cloud.

Cloud Complexity

Cloud complexity is an issue for hybrid and multicloud environments, but what is being managed is where the difference resides. Hybrid cloud involves managing public and private cloud infrastructure. Multicloud involves managing different public cloud provider platforms, APIs, and security settings.

Can a Hybrid Cloud be a Multicloud?

A hybrid cloud can incorporate multicloud elements if it includes multiple cloud environments, such as a combination of public and private clouds. However, multicloud specifically refers to the use of multiple public cloud services from different providers, so it is not accurate to consider all multiclouds as hybrid clouds. While a hybrid cloud may include public clouds, it is distinguished by the integration of on-premises or private cloud resources.

Why Do Companies Use Multicloud?

Companies use multicloud to escape vendor lock-in and improve flexibility and performance across cloud environments. This isn’t a great fit for companies that have legacy frameworks they can’t easily move to the cloud. However, for businesses looking to innovate, multicloud can be a great option.

Why Do Companies Use Hybrid Cloud?

Companies tend to use hybrid cloud when they are either not completely ready to move all of their workloads to the cloud, or when moving some workloads would require more effort than it is worth, but they still want to leverage the benefits of the cloud. Hybrid cloud can serve as a happy medium or a long-term solution for digital transformation in a company, allowing for more innovation and flexibility compared to on-premises frameworks.

Find the Right Cloud Strategy For You with Cloud Experts

Choosing between hybrid cloud and multicloud hinges on your unique business needs. Data sensitivity, scalability, compliance requirements, and budgetary limitations will determine the optimal solution. Need guidance in figuring out what configuration will work best for you? TierPoint’s cloud experts can help you choose the right mix of cloud platforms that will help you reach and exceed your digital transformation goals while keeping your financial constraints and regulatory requirements in mind.

Part of adopting the cloud is convincing your leadership that it’s time to modernize your IT infrastructure. The drivers could be network performance, on-premises data center costs, and more. Read our complimentary eBook to learn how to have those conversations.

What is Cloud Storage Security?

Cloud storage security includes technologies and practices businesses use to protect their data in cloud storage solutions. This can consist of safeguards against theft, deletion, unauthorized access, or file corruption.

Why is it So Important?

Some security issues are the same between cloud storage and on-premises frameworks. However, moving to a new environment can pose new risks and compliance complexities. Organizations should understand their risks and responsibilities for keeping data safe in the cloud.

Understanding Cloud Storage Security Risks and Threats

While cloud storage offers ease of use and simple scalability, it can also come with new risks that can be more common in the cloud. Here are some of the top cloud-related security threats and risks to keep on your radar.

Malware and Ransomware

Organizations of all sizes need to be prepared against ransomware, which accounted for one-quarter of all data breaches in 2023. With ransomware, a user will click on a malicious link in a phishing email, download the wrong link, or neglect to update their software for known vulnerabilities, giving the attacker access to their systems. Once inside, a cybercriminal will encrypt files or lock the user out of their device, demanding a ransom for decryption or access.

Ransomware can often be used with malware, which is malicious code that can infiltrate cloud storage and infect files, steal data, and encrypt as part of the ransom.

Data Breaches, Corruption, and Unauthorized Access

Bad actors gain access to your confidential, sensitive, and valuable information through data breaches. While ransomware is one method cybercriminals may attack the software supply chain or enter through a business partner. Initial attack vectors can include zero-day vulnerabilities, cloud misconfigurations, system errors, or even malicious insiders. The most common starting attack vectors in 2023 were phishing and stolen or compromised credentials.

Insider Threats

Employees within a company can sometimes pose a data security threat and misuse, steal, tamper with, or leak valuable or sensitive data. Approximately 6% of data breaches start with malicious insiders, so while they are not as common as phishing or stolen credentials, inappropriate use and access from inside employees can be a material threat.

Accidental Data Deletion

Cloud storage data deletion can also be completely accidental. Team members may press the wrong button or think data should be deleted without realizing its importance. Without a backup in place, this can severely impact business performance or reduce trust in the company’s security.  Accidental data loss happens with about the same frequency as malicious insiders, costing businesses $4.46 million on average.

Poor Security Patching

A zero-day vulnerability is a previously unknown software security risk that attackers can use to exploit your systems. Patching software at regular intervals can substantially reduce this risk. However, users may ignore updates if they aren’t mandatory. IT teams also need to stay vigilant to prioritize critical patching. Known, unpatched vulnerabilities are responsible for about as many data breaches as malicious insiders and accidental data losses.

Shared Responsibility Model

Businesses that migrate data to cloud storage need to be aware of the shared responsibility model and the role they play in keeping data safe in a cloud environment. Cloud providers like AWS will implement infrastructural security measures, but businesses still need to secure their data within the platform through strong access controls, robust password policies, and encryption.

Compliance and Legal Requirements

Some industries and types of businesses will be legally mandated to implement certain data security protocols. Understanding the compliance obligations for cloud data storage can help businesses avoid fines and sanctions while keeping data safer.

How Do I Make My Cloud Storage Secure?

While organizations may take many approaches to protect data, here are seven best practices to follow to enhance cloud storage security.

Apply Access Controls, Multifactor Authentication, and Identity Management

Access controls determine who can access data and what actions they can take with the data – reading, writing, and deleting, for example. Multifactor or two-factor authentication determines and adds steps a user needs to take to log in, which can include an authentication key, a physical key, and using multiple devices. Identity management is a system businesses can use to set access permissions in cloud storage based on user identities.

Use Strong Encryption and Key Management

Data should be encrypted at rest and in transit, which means it should be scrambled when moving between points, as well as when it is in cloud storage so that it cannot be read without a decryption key.

Encryption keys used on the data should also be stored with a key management system to prevent unauthorized access.

Implement Data Backup and Disaster Recovery

Data that is only available in one place will always be more vulnerable than data that has a backup somewhere. Regularly backing up data to a separate location, especially one that is geographically distinct, can protect businesses from data breaches, natural disasters, accidental deletion, and more.

A disaster recovery plan should include a strategy for data backups, but should also outline how a business will restore data and applications after an outage or major security incident. This may include switching to another system automatically or manually and should detail the parties responsible for ensuring the backup works and testing it regularly.

Setup Monitoring and Logging

Unusual behavior can be a sign of malicious activity, such as logging in at odd times or users attempting to access parts of the system that they don’t normally use. A monitoring tool can identify unusual file modifications or unauthorized login attempts. Logging can track user activity for auditing purposes, which can help trace suspicious activity or analyze an incident after it’s been identified.

Create Patching Policies and a Patch Management System

Vulnerability management through a strong patching policy can reduce the threat of zero-day vulnerabilities without requiring much effort. Set a patching policy with a schedule for making updates – this might be once a month or once a week, depending on the criticality of the data available in your cloud storage. For example, Microsoft has Patch Tuesday on the second Tuesday of every month. Businesses may also implement a patch management system, which may include automated steps to ensure patching is done routinely.

Utilize a Segmented Network Architecture

Moving from an on-premises to an off-premises cloud storage solution may feel like you’re migrating data into one large pool. However, there are steps you can take to segment data. Network segmentation is where businesses divide their network into segments to isolate more sensitive data, keeping it separate from areas that are publicly accessible. This can reduce the harm caused by security breaches.

Leverage Storage Architecture with Advanced Security Features

To make your cloud storage more secure, you can use storage infrastructure with advanced security features such as:

• Immutability: Ensures data stored in the cloud cannot be modified or deleted, providing protection against ransomware and data breaches
• Secure multitenancy: Enables providing the security of a dedicated environment with the cost-efficiency of a shared storage environment
• Comprehensive security solutions: Including security and business continuity, managed networks, and guided by a team of experienced IT professionals

Perform Routine Security Assessments and Audits

On a high level, organizations should look at their systems periodically to identify new vulnerabilities that may call for additional IT security measures. Businesses may also want to bring in outside professionals to audit their cloud storage security if they lack in-house expertise or don’t have enough time to review their cloud security posture.

Building a Strong Cloud Storage Security Plan

Boosting your cloud storage security posture starts with a solid plan incorporating solutions with advanced security features, such as ransomware protection with immutability or Dedicated Storage as a Service powered by Pure Storage. Need help creating a plan? TierPoint’s IT security consulting services can help you create a strategy and execute it to protect your data both in the cloud and in transit. Contact us to learn more.

Although more companies have added cloud environments to their infrastructure, many have done so in a haphazard fashion by addressing needs as they’re realized rather than using a pre-planned strategy for cloud adoption. Those who take a piece-by-piece adoption approach are more prone to cloud sprawl, which can lead to:

• Unnecessary complexity
• Cloud budget waste
• Compliance issues
• Security gaps
• Reduced agility

To promote IT modernization and prevent future headaches associated with cloud sprawl, IT leaders should take time to develop and deploy a structured plan that will serve as a guide for implementing and governing the cloud and its resources across their organization. With that, let’s explore what exactly a cloud adoption strategy is, what challenges to keep in mind, and what to include throughout the planning process.

Why Cloud Adoption?

Because one of the biggest challenges businesses face in cloud migration is identifying app dependencies, it’s important to understand the current and future cloud environment before applying a cloud adoption framework. Businesses should be able to clearly define their objectives for cloud migration and evaluate the factors needed to find success with cloud adoption.

Organizations may choose cloud adoption to achieve the following:

• Improve scalability
• Provide better accessibility to data and applications
• Offer new opportunities for collaboration
• Save on capital expenditure costs
• Improve efficiency through automation and boosted performance
• Incorporate cloud-based services and innovate using newer technologies

And may need to consider the following factors:

• Migration complexity that may require a phased approach
• Skill gaps that may hinder smooth cloud adoption
• Existing IT infrastructure and data and what may need to change to improve the success of cloud migration
• How cloud migration will impact the business before, during, and after the project

What is a Cloud Adoption Strategy?

A cloud adoption strategy details the reason and approach an organization will take when moving to the cloud. This could include best practices, business goals, and the steps a business needs to take to achieve cloud adoption, defined by Amazon Web Services (AWS) as envision, align, launch, and scale in the AWS cloud adoption framework.

On a high level overview, an adoption strategy is the foundation for deploying and governing the use of the cloud across the entire organization, and should be created in conjunction with a cloud operating model.

Additionally, it should help the IT organization communicate the importance of cloud to the rest of the organization and explain how existing workloads and data can be moved to improve efficiency, modernize systems, boost automation and integration capabilities, and more.

Key Steps to a Successful Cloud Adoption Strategy

By assessing and planning a cloud adoption before deployment, and monitoring after migration is complete, businesses can ensure they have a more successful cloud adoption experience. Here’s what you should include in your strategy.

Assessment

Start by evaluating your existing IT infrastructure. This can include applications, data storage, and any app dependencies that need to be considered when moving to a new environment. Analyze the level of complexity and compliance needs associated with moving to the cloud, and understand any security settings that may need to change.

Planning

Your cloud adoption plan should include a definition of your objectives, identification of business factors, and creation of a cloud migration framework. Whether you’re looking to enhance data security, improve collaboration across teams, or improve business operations in some way, define your objectives early so you know how to measure success and prioritize phases.

Next, go beyond the technical considerations and evaluate the business factors relevant to cloud migration. What in-house skill sets can you draw on for cloud adoption, and where might you need to hire outside help? If your organization needs to meet certain compliance standards, one cloud provider may be more appropriate than another. You may also want to develop a data security plan to address concerns about ransomware and other cybersecurity risks. You may want to conduct a cloud adoption readiness assessment.

From there, develop a tailored cloud adoption framework that defines the migration approach you will take, the tools you will use, the timeline in which certain phases will take place, and the metrics you will use to measure success.

Deployment

After you’ve created a well-defined framework, it’s time to choose an appropriate deployment model. Each model – public cloud, private cloud, and hybrid cloud – offers unique benefits and considerations, so it’s essential to understand which one aligns best with your organization’s needs, security requirements, and budget.

• A private cloud offers dedicated resources and enhanced control, making it ideal for organizations with strict security and compliance requirements
• Public clouds, provided by third-party vendors, offer scalability and cost-effectiveness, making them suitable for businesses with fluctuating workloads
• The hybrid cloud model combines elements of both private and public clouds, allowing organizations to leverage the benefits of each. Hybrid cloud adoption enables businesses to keep sensitive data on-premises while taking advantage of the public cloud’s scalability for less critical workloads

Within the deployment model you choose, you’ll migrate relevant workloads to the cloud environment with the chosen approach, use identified tools, and adhere to established deadlines. Some applications and data may be migrated before other workloads based on dependencies and complexity. Organizations may also want to start with lower-risk applications to test the effectiveness of the approach before moving business-critical workloads.

Optimization

Because cloud optimization is an ongoing process, and not a one-time task, businesses should plan to continuously monitor their cloud environment to identify opportunities for better performance, stronger security, and improved cost efficiencies. New cloud services will also emerge in the months and years after a cloud migration. Businesses should have in-house or outside experts with a finger on the pulse of the latest technologies to continue to enhance cloud environments.

Cloud Adoption Strategy Challenges

Building a cloud adoption strategy can come with complications and challenges. Being aware of what your business might encounter, and planning for it along the way, will help your cloud adoption strategy go smoothly.

Security

Cloud computing comes with a lot of advantages, but the added ease of access and flexibility also means additional endpoints and vulnerabilities that can be used to infiltrate your business. To address these security concerns, it’s pertinent to understand the shared responsibility model in cloud security. While cloud platforms implement detailed security measures and adhere to strict regulations, the responsibility for data protection is shared between the provider and the customer. Cloud providers typically secure the infrastructure, while customers are responsible for securing their data, applications, and access management. This model emphasizes that organizations must actively participate in their cloud security strategy, implementing measures such as encryption, access controls, and regular security audits.

By understanding how cloud environments work and clearly defining security responsibilities, you can significantly improve your organization’s overall security posture and better protect assets in the cloud.

Vendors

Working with several vendors can help your organization get the exact cloud configuration you need, but it also opens the door to added complexity. Using more than one cloud provider can complicate billing, compliance, and application and workload management across all environments, not to mention potential security concerns. The better visibility you have across vendors, the less it will be a problem to operate between them.

Compliance

Compliance concerns vary by industry and region but can include data protection needs (GDPR and the like), specific procedures for sensitive financial or medical data, or complying with regulations set by an industry agency or governmental body. Best practices can be even harder to establish when compliance needs to be met in different ways on different cloud platforms.

ROI

Leadership can be slow to greenlight a project if proving the ROI is difficult. While cloud adoption can save money on capital expenditures, like hardware, physical data center rentals, utilities, and so on, the initial migration process can feel like extra spending to stakeholders who don’t see the bigger picture of a model that prioritizes automation and in-house resources. Creating a cloud adoption strategy that proposes migration in phases can help establish a lower entry point and make a case for further cloud adoption.

IT Skills Gaps

Without the right team members at the helm, it can be near impossible to execute a cloud adoption strategy or form one in the first place. Organizations are feeling the pinch from a shortage of IT skills in the market and over three-quarters of companies are looking for ways to address this discrepancy. Cybersecurity specialists alone represent a huge gap in the workforce, which currently stands at 3.4 million. Talent shortage and skills gaps in the U.S. are predicted to cause a loss of $8.5 trillion by 2030. For most businesses, looking outside the organization for providers who can be part of a cloud strategy team will be the only way to continue to modernize and stay competitive.

How to Plan a Cloud Adoption Strategy

Need help planning your cloud adoption strategy? Here are a few best practices to help you get started:

Consider the Business Value

When planning your cloud adoption strategy, you should be able to answer the following:

• How can a cloud investment help solve business problems, enable further innovation, and, overall, achieve your ideal long-time business goals?
• How will you prioritize the delivery of high-value cloud products and initiatives?
• How can you plan migration to achieve cloud success?
• How will you project and measure the impact of your cloud adoption strategy?
• Which cloud platforms will meet your governance and compliance needs?

Pick Your Platform

Thoroughly research your cloud options, and pinpoint which workloads will work best in which cloud environment – be it public, private, hybrid, or multicloud. With this information on hand, select your platform(s) and establish guidelines, principles, and guardrails for your architecture.

Keep in mind that it’s ideal to leverage platforms that have the capacity to meet your needs now and in the future so you can try to avoid a large migration if you outgrow your baseline infrastructure. With that, distributed cloud can be the happy compromise between private cloud and public cloud configurations. Multiple clouds can still be used to meet compliance, performance, or data security requirements, but with distributed cloud, they’re all managed centrally by a public cloud provider.

Define Operations and Management Guidelines

When developing your cloud adoption strategy, creating guidelines around operations and management is key. This area of your plan should include, but is not limited to, things like:

• Design principles to follow
• How to optimize operations to allow for scalability while delivering business outcomes
• Ways to improve the reliability of workloads
• Cloud environment monitoring
• How to ensure the availability and continuity of critical data and applications

Maintain Governance

Document how your cloud initiatives will maximize overall benefits for your organization while also minimizing any risks associated with cloud transformation. During this phase, set up policies, define how corporate policies will be enforced across platforms, and determine identity and access management to prevent the risk of future cloud sprawl. Additionally, consider how you can incorporate cost management and cloud cost optimization strategies to reduce unnecessary budget spend.

Establish Security, Disaster Recovery, and Resilience Practices

IT resilience can be make or break for business revenue, productivity, and reputation. Build holistic security and ongoing security management, for example a disaster recovery plan checklist and data resiliency plan. These plans include the following best practices within your security plan:

• Threat detection
• Vulnerability management
• Data protection
• Application security
• Incident response

Decrease the Talent Gap

The talent gap is one of the biggest challenges organizations have to contend with when working toward cloud adoption, and it’s a necessary obstacle to overcome. Part of your cloud adoption strategy should include promoting a culture of continuous growth and learning. Focus on providing internal learning opportunities and workshops that…

• Enhance cloud fluency
• Help transform the workplace to enable and modernize roles
• Evolve alignment with and accelerate new ways of working in the cloud

Choosing the Right Architectural Principles to Follow for Cloud Adoption

The architectural principles you follow to determine your cloud adoption should be based on your workloads, applications, what workloads/applications are most urgent to move, the characteristics and requirements of each workload/application, and any other dependencies you need to keep in mind. Try running an exercise using the 7 R’s of cloud migration (Retain, Rehost, Revise, Rearchitect, Rebuild, Replace, and Retire) to determine if you should focus your efforts on: 

• Cloud-native application adoption 
• Cloud-first adoption 
• Cloud-only adoption

Cloud-Native Application Adoption

Organizations focused on cloud-native adoption will prioritize technologies and services available via the cloud platform or provider being used, making the switch from original systems to cloud-native applications. This can look like taking advantage of tools provided by AWS and Microsoft Azure, for example.

Cloud-First Adoption

Cloud-first is when organizations always think about cloud-based solutions first before implementing a new IT system or replacing an existing one. In this scenario, you prefer to develop directly on cloud platforms from the start. There may be a reason to select an on-premises solution, whether it’s due to how it works with your other systems, the time it would take to switch things over, or necessary features not being available in cloud-based apps, but this strategy also doesn’t exclude non-cloud solutions.

Cloud-Only Adoption

With cloud-only adoption, organizations would look to cloud-based solutions to replace all of their current systems and fulfill all of their IT and organizational needs. Achieving a cloud-only adoption is manageable in theory, due to the many solutions available in the cloud. However, taking a cloud-only approach will largely depend on the in-house or

third-party resources employed to take this on, as well as how willing those who use the current systems are to change.

Accelerate Your Cloud Adoption Journey with the Help of TierPoint

Successful cloud adoption, deployment, and management all boils down to bringing in the right people who are qualified to handle your specific business requirements. Even with a robust internal team, organizations can benefit from bringing in an outside perspective. A managed services cloud provider can take your business goals, desired outcomes, and current IT environment, and help you identify the best roadmap to cloud adoption.

Need help building your cloud adoption strategy? TierPoint is here to help. We offer cloud readiness and cloud migration assessments to help build the best roadmap for your cloud adoption journey. Contact us to begin your assessment or download our Journey to the Cloud eBook to improve your cloud strategy.

We’ll talk about what should be part of modern data center architecture, as well as key considerations for businesses looking to move to a more effective data center.

Key Considerations for Data Center Design

When making decisions about a data center design, organizations should think about scalability, flexibility, power consumption, availability, redundancy, and security of their infrastructure.

Scalability and Flexibility

The design of a data center should include anticipation of future growth. Ensure there is enough space, power, and cooling capacity for additional servers and racks. Modular designs and adaptable layouts can improve flexibility and scalability, and high-density computing can make the most of your square footage.

Power and Cooling Efficiency

Powering equipment and keeping it cool can be a resource-intensive exercise. However, there are ways businesses can optimize and reduce their power consumption, making it more sustainable. By switching to energy-efficient equipment, leveraging renewable energy sources, and implementing strategies such as hot aisle containment to maintain a barrier around hot air exhaust, businesses can improve their power and cooling efficiency.

High Availability and Redundancy

When a data center has high availability and redundancy, the facility ensures continuous operation regardless of interruptions.

Backup generators, redundant power supplies, and copies of critical systems can mean that data centers are only down for a few minutes per year at the most.

Security and Physical Protection

Physical and digital security is vital in data centers. The facility should have access control systems to allow only necessary people into certain parts of the building or applications. Security cameras, fire suppression systems, and intrusion detection tools can help safeguard data and equipment.

What Should Be Included Within a Data Center Design?

When building a data center, the anatomy of the design should incorporate the aforementioned considerations and designed with geography, data sensitivity, performance, and availability in mind.

Building Structure

Every region is prone to certain natural disasters, such as hurricanes, floods, earthquakes, and tornados. A facility’s structure should be reinforced to withstand whatever mother nature brings, especially if it’s more expected in a certain region.

Access Controls and Physical Security

Physical access to data center resources should be restricted and tightly controlled. This can include protocols around access for sensitive areas of a building, use of two-factor authentication, biometric screening, and video surveillance that covers all doors and windows.

Virtual Security

When designing a data center, it’s crucial to include virtual security measures as part of a comprehensive cybersecurity plan. Effective cybersecurity measures are essential to protect data centers from threats and ensure data integrity, and can include:

• Firewalls
• Encryption
• Regular security audits
• Virtual private networks (VPNs)
• Intrusion detection and prevention systems (IDS/IPS)
• Security information and event management (SIEM)

Climate Control and Cooling

Heat, humidity, and static electricity can wreak havoc on data center equipment. Redundant environmental systems can enable continuous operations. Cooling methods also make a big difference in the performance of your equipment. Air cooling blows air on and around equipment, whereas liquid cooling circulates cool liquid to equipment and around the building to absorb heat. After that, the liquid is sent through radiators or cooling towers, providing an efficient way to cool key components.

Building Management Systems

Building management systems can give data center operators a high-level view of all factors of facility health, including HVAC, power loads, and voltage levels. Management systems can also monitor the status of emergency power systems such as uninterruptible power supplies (UPS) and generators.

Power

Diverse and redundant power sources can greatly reduce the chance of power outages affecting the availability of servers. Power distribution units (PDUs) do more than deliver power in a data center. They can also be used to track power consumption and identify voltage fluctuations that may indicate equipment issues.

Data centers can also include UPS as a first line of defense against short-term spikes or drops in power that can greatly hinder availability or damage equipment. Redundant UPS systems offer even higher availability.

Backup generators can be added to provide continuous power during utility power outage events. Facilities can also have additional fuel onsite to keep generators running longer.

Redundancy and Failover

Redundancy and failover add extra safeguards to a data center to boost availability. Duplicating critical components, such as hardware, network connections, and power, improves redundancy. Failover details the process where data centers switch automatically to a backup system when a primary system fails. This can be done by having both systems run simultaneously (active/active), or by having a backup system in place to start when the primary one fails (active/passive).

Environmental Monitoring

Data centers should be monitoring onsite operations as well as the environment. Onsite operations monitoring provides 24x7x365 visibility into possible security threats and elements critical to data center infrastructure performance. Environmental monitoring includes sensors for temperature, humidity, airflow, and power consumption. Detecting environmental issues early can reduce the likelihood of equipment failure.

Cabling, Connectivity, and Networking

Having one or two carriers to choose from can mean businesses may have to sacrifice availability or performance. When data centers are carrier-neutral and offer multiple connectivity options with different carriers, organizations enjoy higher availability, lower latency, greater choice, and improved disaster recovery.

Hybrid and Multi-Cloud Architectures

Is there a need to connect to on-premises infrastructure or form connections between multiple cloud environments? Data center design should consider the interconnectivity needed between different architectures and work to integrate as effectively as possible.

Business Continuity Workspace

Sometimes, a natural disaster or outage can lead to displacement, leaving employees looking for a safe place to work. Data centers can also include business continuity workspaces, allowing employees to set up shop during the recovery process. For example, TierPoint’s data centers have workspace sites that can accommodate up to 800 people.

Modern Data Center Design Strategies

To accommodate larger workloads and meet new demands, modern data centers are being designed with more scalability and agility built in.

Modular and Containerized Designs

Modular data center designs start with pre-fabricated modules that contain IT equipment, power, and cooling. Because the design is modular, it’s easy to add or remove pieces as needed, which makes scaling easy.

Similar to modular design, IT infrastructure can be kept within a containerized unit for rapid deployment. These are not as customizable as modular designs, but if time is of the essence, containerized designs can be the better choice.

High-Density Computing Solutions

High-density computing solutions can fit more computing power into smaller spaces using technology such as blade servers and GPU-accelerated systems. With blade servers, multiple server modules reside in one chassis, sharing power and cooling resources. The shared nature of the system reduces the physical blueprint without compromising on processing power.

Graphics processing units (GPUs) offer significantly higher processing power compared to central processing units (CPUs) and can be a better fit for machine learning and artificial intelligence tasks. High-density data centers are necessary to house GPUs effectively.

Choosing the Right Data Center for Your Needs

The data center design that is right for your business will depend on what data and applications you want in the data center, your tolerance for downtime, natural disasters common to your geographic area, and more. TierPoint’s 40 world-class data centers offer coast-to-coast connection, carrier-neutral connectivity, and hybrid flexibility to suit your business needs.

What is Cloud Storage?

Cloud storage allows organizations to store their data with a cloud storage provider, which provides easy access to data online from remote servers. Businesses could store photos, documents, applications, and videos using cloud storage, reducing need for on-premises infrastructure.

What is Local Storage?

Local storage is where users store data on the enterprise’s own hardware, such as corporate workstations and servers or on an on-premises data center run by the company. While there can be accessibility with local storage that extends beyond one device, there may also be limitations, such as not being able to access data when away from the office.

What is the Primary Difference Between Cloud Storage vs. Local Storage?

The primary difference between cloud storage and local storage is who owns the storage and how the data is being stored and accessed. Cloud providers handle data storage and access with infrastructure they manage, which can be scaled up and down based on business needs. Local storage is either on a particular device or on a server that manages all office devices.

Pros and Cons of Cloud Storage

Because of its flexible nature, cloud storage offers benefits that include scalability, accessibility, and cost-effectiveness. However, companies should also consider potential downsides, such as vendor lock-in, internet dependency, and security concerns. 

Pros of Cloud Storage

Compared to traditional local data storage methods, cloud storage is highly scalable. Businesses can increase or decrease capacity on demand without purchasing more physical hardware or worrying about underutilized resources. This can be ideal for organizations with fluctuating storage needs. Cloud storage is also normally more cost-effective. You only have to pay for what you use and reduce infrastructure costs.

One key benefit of cloud storage is its improved accessibility, which enables greater collaboration. Users can access their data from any device, whether they’re in the office or not, and can collaborate on files live more easily. This avoids issues that come with versioning or competing file names that may get saved to different devices or an on-premises server.

Cloud storage can be a key piece of business continuity planning as well. With cloud storage, organizations get built-in redundancy with data replicated across multiple servers, often in geographically distinct locations. This can protect data from natural disasters or hardware failures. Cloud storage servers also tend to automate data backups, reducing the risk of data loss from hardware failure or accidental deletion. While businesses are still responsible for specific aspects of data security, cloud storage providers may have infrastructural security measures in place as a first line of defense for stored data.

Cons of Cloud Storage

Despite cloud storage’s advantages, organizations should still be mindful of its limitations. While it’s more accessible, cloud storage relies on an internet connection for access, and particularly synchronization. Even if users have files or applications set for offline access, they can’t be updated in the cloud without a connection, so reliable internet is necessary.

Storage in the cloud is often more cost-effective than local storage; however, businesses should understand their options and weigh the benefits against vendor lock-in. Switching to a new cloud storage provider can be complex, especially for organizations storing a lot of data with one provider. Dependencies can pose an issue, and depending on the vendors you choose, easy export options may not be available. Pay-as-you-go models can be less expensive than local storage, but exceeding set storage tiers or storing large amounts of unnecessary data can run up a bill.

Cloud providers cover some security measures, while others are the customer’s responsibility. For example, data is encrypted in cloud storage, but organizations need to think about what happens when data is downloaded or accessed by various devices.

Pros vs. Cons of Local Storage

Cloud storage has become a big business, but that doesn’t mean it’s the right fit in every case. Local on-premises storage can offer more data control and sovereignty, as well as speed and performance, for businesses that need it. However, data capacity can be more limited when stored locally.

Pros of Local Storage

Unlike cloud storage, local storage affords an organization complete control over its data. Because the data resides on a physical device, such as a computer or on-premises server, the user has more direct control over data privacy and security.

Local storage also normally offers faster data access compared to cloud storage. Latency is reduced because data retrieval happens directly from a device. When applications need access to larger files, this speed can be essential to proper performance.

An internet connection is also less important, or not important at all, with local storage. In an environment with unreliable internet access, local storage may be your only option to retrieve and manage data.

There is also a potential for lower costs with local data in some instances. For businesses that have predictable storage needs that don’t vary much from month to month or year to year, they may be able to create a plan with on-premises storage options that are more affordable than a cloud storage subscription option.

Cons of Local Storage

Because of its limited capacity and lack of resources compared to cloud storage, many businesses may find that they’ve outgrown local storage options. Organizations that are growing may not want to shoulder the additional expenses associated with purchasing new hardware, maintaining, or troubleshooting storage challenges.

Local storage is also more prone to data loss due to the lack of automatic backups. If the server or device is damaged, data may not be able to be recovered after an outage, deletion, or ransomware attack.

Data can also become more isolated with local storage, creating data silos and conflicting versions of the same file. This can make collaboration, particularly remote collaboration, more challenging.

What to Consider When Choosing Between Cloud and Local Storage

Some businesses may find that local storage suits their needs. In many cases, cloud storage can be hugely beneficial, but it can also be a significant undertaking to migrate data to a new environment.

Before choosing cloud or local storage for your data, consider the following:

1. Scalability and Growth Projections

Cloud storage is much more scalable than local storage, making it ideal for businesses with fluctuating requirements. Local storage scalability is generally limited to the physical infrastructure your organization has purchased.

2. Performance and Latency Needs

Slow internet connections can increase latency and reduce performance in the cloud, which is especially noticeable for frequently accessed files. However, cloud providers offer tiered storage so businesses can prioritize performance where it matters most. With local storage, users have faster access to data with no internet latency. This may be appropriate for larger files.

3. Existing IT Infrastructure and Resources

Minimal IT infrastructure is required for cloud storage. The cloud providers are responsible for most of what is needed to maintain cloud storage. Local storage, on the other hand, requires more IT infrastructure, as well as additional resources for storage device maintenance and management.

4. Data Security and Compliance Requirements

Cloud providers encrypt data and typically have a few different options for encryption. However, users still have to think about data security on external servers. Local storage offers complete data control and sovereignty, but security is dependent on the encryption and backup strategies implemented by the business. Depending on the regulatory standards your business has to meet, compliance may be satisfied better by one storage approach over another.

5. Cost and Budget

Cloud storage operates on a pay-as-you-go model, which can change based on storage usage and features. Local storage is most expensive on the initial investment, with no recurring costs outside of energy and maintenance unless there is a need to upgrade and add more equipment.

6. Additional Considerations

You may also want to consider how much collaboration you need around data. Will teams be working on making real-time updates that are better suited for cloud storage? Disaster recovery is another consideration – cloud storage has built-in redundancy for data protection, which may be important for more sensitive information or operation-critical data. Internal resources may also play a role. Cloud storage requires less in-house technical expertise compared to local storage.

Cloud Storage vs. Local Storage – Which is Right for You?

Your organization’s needs will dictate whether cloud or local storage is optimal for you.  Cloud storage offers enhanced scalability, accessibility, and inherent redundancy compared to local storage solutions. Although the transition process demands thorough planning, TierPoint can help find the right storage solution for those seeking these advantages. Our IT advisory services can help you take the next step on the path to digital transformation, improving collaboration and fluctuating with your needs.

How Has Data Management Evolved with the Rise of AI?

As the amount of data we consume, create, and store has exploded, with global numbers estimated to reach 180 zettabytes by 2025, data management has become even more important, and artificial intelligence (AI) can help aid in its evolution in several ways:

• Automation: AI can automate tedious, manual tasks such as classification, data cleansing, and anomaly detection through machine learning algorithms. This can allow humans to focus on more strategic work.
• Data quality: Data coming in from different sources and in different formats can be streamlined and checked for accuracy by AI, ensuring higher data quality and reliability. This results in more accurate analyses and better decision-making.
• Security: Through anomaly detection, AI can help prevent security breaches and work to protect sensitive data.
• Integration: Instead of data existing in silos, AI can bridge the gap through automation and data quality measures, allowing for a more unified view of information that can be used for further data analysis.
• Analytics: AI can also do some heavy analytical lifting that can speed up the time it takes to reach important insights. Trends, forecasts, and patterns can be visualized and calculated more easily using artificial intelligence.

The Role and Benefits of AI in Data Management

AI can play an important role in effectively managing the growing volumes of information worldwide, both in the cloud and on-premises frameworks, providing a set of tools organizations can use to unlock value in their data.

With automation, businesses can enjoy streamlined processes and reduced time and effort on manual tasks. AI-powered data quality measures can help businesses make better-informed decisions. Real-time monitoring and threat identification can better safeguard data, and real-time insights can get organizations to their next product or service decision faster than ever. In many ways, artificial intelligence empowers companies by giving them a competitive edge and a head start toward pursuing innovative new projects.

6 Top Trends in AI-Powered Data Management

Instead of businesses reacting to new data challenges, AI can put them in a more proactive role. Emerging trends include organizations leveraging AI for data cataloging, advanced analytics, intelligent data preparation, keener predictions, and more.

1. Leveraging Automated Data Cataloging and Metadata Management

Data cataloging is when organizations create an inventory of all their data. Metadata can include information such as the location of the data, its type, a description of the data, where it came from (lineage), and the owner responsible for its maintenance.

Traditionally, data cataloging is a time-consuming and error-prone manual process. AI can automate this by tagging and classifying data assets, making it easier for users to find data, fix inconsistencies, and reduce errors.

2. Performing Advanced Data Analytics and Insights

Even with deep expertise and strong deductive powers, humans can miss subtle patterns in large datasets. Machine learning algorithms can be used to find hidden patterns or identify relationships more easily, especially in complex datasets. This can move businesses from simple to more sophisticated insights. AI can also create predictive models that allow for stronger trend forecasting.

3. Conducting Intelligent Data Preparation and Cleansing

Data preparation and cleansing are important in helping individuals accurately analyze and explore data. AI can automate tasks including finding and removing duplicate data, fixing inconsistencies in formatting, and filling in missing values. This creates better data that can be used to train AI models more accurately and reliably.

4. Applying Natural Language Processing for Data Exploration

Natural language processing (NLP) gives AI the ability to understand human language. When AI can understand natural language queries, it’s easier for humans to explore datasets in a more accessible and intuitive way. NLP can automate text summarization, find topics and themes in data, categorize named entities, and conduct sentiment analysis.

5. Using Predictive Analytics and Anomaly Detection

Sometimes we don’t see what’s coming down the road before it’s too late. AI can take historical data and use it to predict future trends or find anomalies in current data. This can assist businesses in anticipating issues before they become problematic, as well as make data-driven decisions to improve operational effectiveness.

6. Automating Data Governance and Compliance

Instead of reacting to breaches, AI-powered data governance and compliance measures can prevent issues before they occur. Data access control, audit logging, and lineage tracking can all be conducted with the help of AI tools. AI can also anonymize sensitive data, identify potential security risks from anomalous behavior, and automatically restrict access to data if suspicious activity is identified.

Unlocking the Power of AI in Data Management

Managing a vast amount of data can be challenging, but the right AI-enabled data management tools can simplify the complex. TierPoint’s AI advisory consulting services can help you better navigate and leverage your in-house data to unlock its true power and potential. Contact our advisory team today to start exploring how AI can transform your data management practices.

Learn how businesses like yours can use artificial intelligence and machine learning with our complimentary whitepaper. Download it today!

What Are AI Workloads?

AI workloads can be used to train, execute, and maintain artificial intelligence models. Different types of workloads are used to accomplish different tasks:

• Predictive analytics and forecasting: Customer behavior, maintenance needs, and sales trends can be predicted by training AI models on historical data.
• Natural Language Processing (NLP): Many users are now familiar with NLP – chatbots and virtual assistants use NLP to understand inputs and generate outputs that take after human language.
• Anomaly detection: By training AI on common patterns, this technology can identify unusual events in data sets. This can be used for fraud detection, catching possible cybercrime activity, or pinpointing equipment malfunctions.
• Image or video recognition: Similarly, AI can be used to identify objects, activities, and scenes in images and videos. This technology can be used by healthcare to analyze imaging, or by security systems to recognize faces.
• Recommendation algorithm: AI models can understand which products and services people may need by analyzing past browsing and purchase behaviors.

Even in uncertain economic times, it’s expected that AI workloads will continue to be important. About one-third of respondents on Flexera’s State of Tech Spend 2023 said they expect their AI budgets to increase significantly.

The Data, Compute, and Storage Requirements of AI Workloads

Because AI workloads are capable of so much, their computational requirements are much greater. They require complex computations, massive datasets, and a need to store and scale that greatly surpasses the needs of traditional workloads.

Training AI models requires massive datasets that have millions, or even billions, of data points. This calls for significant computational power. Central processing units (CPUs) typically handle one task at a time. AI workloads rely on parallel processing to break operations into chunks that can be handled simultaneously for faster computations. Graphical processing units (GPUs) excel at parallel processing and are necessary to accelerate AI workloads. The GPU market is on the rise and is expected to more than quadruple by 2029.

In the training phase, AI models need significant resources; however, these needs fluctuate depending on future applications. Storage needs can also ebb and flow. High-performance storage solutions, such as solid-state drives (SSDs), as well as cost-effective object storage, are important for short-term access and long-term archiving of immense amounts of data. 

5 Challenges of Managing AI Workloads

Because of these requirements and more, managing AI workloads in data centers can be difficult if the facility isn’t ready to meet the need. Networking, processing, and scalability features need to be in place for AI workloads to be functional.

Network Requirements

Because AI workloads tend to transfer large amounts of data between storage systems and compute resources, businesses need a solution that offers low latency and high bandwidth. Traditional data centers can be too sluggish to accommodate AI operations.

High Computational Power Needs

As previously mentioned, GPUs and specialized AI accelerators (TPUs) can aid in parallel processing and support AI workloads in a way that traditional data centers with CPUs cannot. More complexity also enters the picture when more diverse hardware resources are added into the mix.   

Real-Time Processing Demands

Real-time processing is already becoming essential for certain AI applications, including autonomous vehicles and fraud detection systems. When it comes to driving, even a split second of delay can lead to catastrophic results. Effective real-time processing requires powerful hardware, efficient data pipelines, and optimized software frameworks.

Massive Data Processing Requirements

Data centers need to be able to process the data used by AI models and meet storage, cleaning, and pre-processing requirements. What happens to the data throughout its lifecycle? Data centers need to manage the archival, deletion, and anonymizing of data as well. All touchpoints along the data’s lifecycle add layers of complexity to the process.

Scalability and Flexibility Constraints

Traditional data centers don’t tend to offer as much flexibility or scalability, making it more difficult for businesses to change resources to meet fluctuating needs. Training can require significant resources, while deployment may vary in its demands. Rigidity can slow down or stop the effectiveness of AI workloads.

Can High-Density Computing Support and Optimize AI Workloads? 

High-density computing (HDC) is a good fit for organizations looking to support and optimize AI workloads. As the name suggests, HDC can fit more processing power into a smaller footprint, leading to the following benefits.

Stronger Compute Density

A stronger compute density equals stronger processing power in a limited space, which can enable AI workloads to handle massive data sets and complex algorithms necessary for both training and execution.

Decreased Latency

When resources are packed more tightly together, travel distances are also decreased between components. In HDC environments, latency goes down due to the minimization of travel time. Latency is hugely important for real-time applications that require instantaneous responses.

Better Scalability

Because more resources can be packed into one rack, HDC is also great for scalability. New computing units can be added to existing racks and meet increased processing needs. Scaling down is just as easy.

Improved Resource Utilization

High-density computing offers a smaller space solution for businesses employing AI workloads, and the smaller footprint also promotes better resource utilization. Hardware is used more efficiently and organizations enjoy less wasted space. Data center power density can also be improved.

More Specialized Configurations

Different AI workloads have distinct needs. For example – latency may be more important in one workload, and scalability may be more important in another. HDC allows businesses to create highly customized configurations that meet the needs of specific AI workloads. This could look like high numbers of GPUs or more AI accelerators.

What Other Techniques Can Be Used to Better Support AI Workloads?

While high-density computing expands your ability to handle demanding AI workloads, some other approaches can be used to support and foster AI projects.

Integrate High-Performance Computing Solutions  

Processing power is vital for AI workloads, and good computing density is just the start. High-performance computing (HPC) solutions should also be incorporated. This could include high core count CPUs, GPUs, and AI accelerators called tensor processing units (TPUs). CPUs are good for raw processing, GPUs work best with parallel processing, and TPUs are perfect for machine learning tasks.

Optimize Data Storage and Management

AI models require huge datasets for training, so optimizing storage and management is important to keep operations efficient after deployment. Solid-state drives (SSDs) have fast read/write speeds, so their performance can be optimal for frequently accessed data. Object storage can archive less frequently accessed data.

Implement Efficient Networking

Technologies like Ethernet fabrics can offer higher bandwidth and lower latency than traditional data center networks. Moving between storage, compute resources, and even edge devices at high speeds is essential for AI workloads. Businesses may also consider adding network segmentation and traffic prioritization to direct data flow more efficiently and optimize networking.

Leverage Parallelization and Distributed Computing

Parallelization breaks AI tasks into subtasks and assigns them to multiple computing units. This can accelerate workloads by multiplying efforts. Containerization can also enhance this process further by packaging subtasks with their dependencies, simplifying deployment and enabling consistent execution.

Use Efficient Cooling Systems

Any computing generates heat, but high-performance computing and AI workloads generate significantly more heat than traditional workloads. Effective cooling systems can help you maintain optimal temperatures, reducing the likelihood of equipment breakdown or malfunction. Closed-loop liquid cooling can offer energy-efficient heat dissipation that keeps up with demanding computing.

Incorporate Cloud Solutions

Cloud computing adds the flexibility and scalability required for modern workloads. Businesses can access cloud GPUs on-demand from cloud providers for workloads that need greater-than-average processing power. This can be a more cost-effective alternative to maintaining your own GPU infrastructure in a data center.

Unlock the Full Potential of Your AI Workloads

Don’t let technological limitations handcuff your AI workload potential. By employing high-density computing, optimized data storage solutions, effective cooling systems, and more, your organization can take advantage of current AI capabilities and prepare for future developments.

If you feel limited by your current data center situation, TierPoint’s High-Density Colocation services could be your next move. These facilities are designed with AI in mind, ready to accommodate your high-performance workloads.

Learn more about our data center services and business applications of AI and machine learning.

What is Cloud Data Protection?

Cloud data protection includes measures businesses take to safeguard their information stored in the cloud. With 70% of organizations having half or more of their infrastructure in the cloud and 65% of organizations using multicloud environments, organizational reliance on the cloud means that data integrity and security are vital.

Different cloud data protection projects can involve cloud data security measures, data backup and recovery, data visibility, and governance and compliance measures around data protection and privacy.

Why Cloud Data Protection Matters

Due to the growth of cloud adoption across businesses, vast amounts of data are being stored and processed in the cloud, and threats associated with this data are also growing simultaneously. Even businesses that rely on cloud services need to be mindful of the shared responsibility model – managed public cloud providers are responsible for infrastructure-level security, but customers are responsible for the security of other parts of their systems, including applications, sensitive data, and operating systems.  

Key Challenges in Cloud Data Protection

Even when business owners are aware that cloud data protection should be a priority, the complexity and volume of work needed to improve the security of cloud data can feel challenging.

Data Backup and Recovery

Data backup and recovery ensures that data is recoverable when a disruption or outage occurs. When businesses don’t have backup and recovery measures in place, it can lead to costly consequences. The average cost of a data breach in 2023 was $4.45 million. 82% of these breaches happened with data stored in cloud environments. This is why understanding your part in the shared responsibility model is crucial.

Data Visibility and Control

You can’t control what you can’t see. Maintaining visibility on where data lives in your system, as well as how it’s being used and who has access to it, is an important first step in determining how best to protect the data. Organizations often struggle to gain full visibility over their cloud environments, or they don’t have the right tools and processes in place to monitor activity and manage access controls.

Compliance with Regulatory Standards

Certain industries have stringent regulatory requirements for data privacy and security. Oftentimes, cyber insurance policies require that companies meet specific data protection standards. Failing to stay compliant can mean businesses are subject to fines and other legal consequences.

Misconfiguration and Human Error

Even when organizations take on data protection projects, flaws in configuration or manual mistakes can create vulnerabilities that make it easier for cybercriminals to infiltrate. Without the right team in place and regular standards checks, businesses can feel secure but still be prone to cyberattacks.

Data Residency and Sovereignty

What you need to do to achieve compliance with data protection will depend largely on your data residency and sovereignty. Data residency is concerned with the physical location of data storage, whereas data sovereignty is more about the regulations and laws around the governance of your data based on that location. If you have data in multiple locations, this can make your compliance requirements more complex, quickly.

Changing Threat Landscape

Cybercriminals develop new attack tactics constantly. Artificial intelligence is making it easier for bad actors to fake voices, write more effective spearphishing emails, and develop more sophisticated social engineering attacks. Organizations need to be informed about the latest threats and what they need to do to keep their security measures relevant.

Cloud Data Protection Best Practices

Face your business challenges and improve your security posture by applying these nine best practices for cloud data protection and cloud data privacy.

Develop a Robust Disaster Recovery Plan

A well-defined disaster recovery plan will include any and all steps your organization needs to take to protect your data and applications in the event of disruptions. It should outline who is responsible for what, which teams and individuals need to be informed of the incident, what should be switched over automatically or manually, and what needs to be done to restore “business as usual” at the organization. To ensure the plan is effective, it’s important to test it annually, at a minimum.

Schedule Regular Backups

The schedule for regular backups should be determined based on how much data your business can lose in an outage or breach without causing a significant impact on your business processes. A recovery point objective (RPO) may be 5 minutes, 5 hours, or even 5 days. What your business can tolerate will depend on your industry and may vary based on the types of data you are looking to protect.

Implement IAM

Identity and Access Management (IAM) can help you define user roles and permissions in the cloud. It can also create a framework for multi-factor authentication. Developing IAM allows businesses to better control access to cloud resources based on user type.

Utilize Cloud Security Posture Management Tools

Your security posture isn’t fixed in time. It needs to be maintained through management solutions. Cloud security posture management (CSPM) can scan a cloud environment for security misconfigurations, empowering businesses to address vulnerabilities proactively.

Perform Continuous Monitoring

Monitoring can be made easier through artificial intelligence (AI)-powered tools, which can pick up on suspicious behavior based on pattern recognition. Anomalies that may fly under the radar can be more quickly spotted with AI, and continuous monitoring with AI tools offers a more cost-effective way to keep tabs on your cloud environment.

Use SIEM Solutions

Security Information and Event Management (SIEM) solutions take security data from different sources in a cloud environment and aggregate them into one view, making it simpler for security teams to see and respond to incoming threats.

Conduct Patch Management

When vendors find vulnerabilities, they create patches to address them. Businesses should regularly update their software and firmware in the cloud to mitigate issues from these known vulnerabilities, shortening or eliminating the possible window available to attackers.

Leverage Security Partners

Staying up-to-date on the latest cloud security trends is a full-time responsibility and can be difficult for small IT teams to accomplish effectively. By leveraging cloud security partners, IT leaders can add expertise to their team and gain access to advanced security solutions that may be out-of-reach for smaller organizations.

Execute Regular Security Assessments and Awareness Training

Just like monitoring and management should be constantly on your to-dos, regular security assessments and organizational training should never fall off your list. With scheduled security assessments, you can identify weaknesses and address them before they become bigger problems. Security awareness training can add a line of defense to your organization, arming your employees with more cybersecurity knowledge to stop potential threats.

Ready to Take Cloud Data Protection to the Next Level?

TierPoint’s IT Security Consulting services can help you bring your cloud data protection to new heights. We can augment your existing team with our experienced cloud security consulting experts. To learn more about boosting your security posture and developing defenses against top cloud security threats, read our whitepaper.

What is Data Center Sustainability?

Data center sustainability encompasses different practices and approaches facilities can take to reduce the impact of data centers. When considering and implementing sustainable business practices, data centers also need to keep security and reliability concerns in the mix.

Why is Data Center Sustainability Important?

Data center sustainability is important for several reasons. Data centers consume a lot of energy every year, and this number is on the rise due to the demands from AI services. Overall data center consumption in the U.S. is expected to reach 35 Gigawatts by 2030, more than doubling since 2022. Focusing on sustainability at data centers can help reduce their environmental impact, save money, conserve resources, and position a business as more environmentally conscious. In some cases, it may be important to focus on sustainability for regulatory reasons as well.

Key Aspects of a Strong Data Center Sustainability Approach

Data sustainability can best be achieved through a multi-pronged approach of innovative optimizations and energy-efficient techniques.

Innovative Cooling Techniques

Liquid cooling offers a more efficient way to cool your equipment compared to traditional air cooling. Liquids are better conductors of heat, so they can absorb heat more effectively, similar to water pipes compared to fans. Liquid cooling can also bring coolant directly to the source of the heat, which may be components like processors or graphics cards. The more precise the delivery, the more effective the cooling, and the less energy is wasted.

Energy Efficiency

While data centers can optimize energy use via liquid cooling, they can also implement energy-efficient servers, renewable energy sources, and smart power management strategies to save even more.

Resource Optimization and Waste Reduction

Other methods of resource optimization and waste reduction can include:

• Consolidation of underutilized servers via virtualization technologies
• Regulating power usage of servers based on current workloads
• Separating hot air exhaust and cold air intake with a hot aisle/cold aisle containment strategy
• Optimizing storage using tiers, prioritizing faster storage for the most frequently accessed data
• Use heat from the data center to heat the buildings or provide hot water for the facility
• Managing e-waste for decommissioned equipment responsibly

Monitoring and Measurement

It’s easier to improve your sustainability when you have ongoing monitoring in the data center of:

• Power consumption
• Water usage
• Humidity
• Other environmental factors

Knowing which resources are being wasted (i.e. water due to a leakage), impacting or using the most energy can help you chart a course for future sustainability initiatives.

Data Center Design

Hot aisle/cold aisle containment is one design decision you may choose to make to improve sustainability via data center design. Adding natural ventilation, using energy-efficient building materials, and optimizing airflow in server racks can all contribute to a more sustainable data center.

Internal Culture of Sustainability

One way to ensure a data center will continue to become more sustainable is through fostering a culture of sustainability throughout the organization. This can include employee training, brainstorming on sustainability initiatives, and reiterating the shared responsibility at the business to lessen environmental impact.

How Do You Measure Data Center Sustainability?

More than one metric is necessary to get a clear view of data center sustainability.

Power usage effectiveness (PUE) is measured by dividing total facility energy consumption by IT equipment energy consumption. Lower PUEs, closer to 1, means the data center is more efficient.

Similar to PUE, carbon usage effectiveness (CUE) evaluates data center energy efficiency by measuring carbon emissions that are generated from one unit of IT energy. Water usage effectiveness (WUE) measures the efficiency of water used for cooling purposes.

Other metrics data centers might use include renewable energy use, a percentage of energy consumption coming from renewable sources, and material use, such as the responsible management of electronic waste from decommissioned equipment. The metrics a data center chooses to track may depend on the efficiencies they’re hoping to make.

Can AI Be Used to Help Improve Data Center Sustainability?

Artificial intelligence (AI) can be used to improve data center sustainability. How? By employing the right AI tools, businesses can work to reduce their data center footprint.

Real-Time Monitoring and Analysis

AI can amplify manual efforts by continuously monitoring sensor data for temperature, power consumption, and other environmental changes. This can help spot inefficiencies and address issues quicker.

Predictive Cooling and Power Management

AI can predict cooling needs and adjust cooling systems proactively by learning from historical patterns and combining that with real-time usage and outside sources such as weather forecasts. AI can also predict future power demands and change consumption based on how workloads normally fluctuate.

Proactive Maintenance

Equipment that needs minor maintenance is much better than equipment that needs an overhaul. AI tools can take sensor data on equipment to predict potential equipment failures. By enabling preventative maintenance, data centers experience less downtime and less energy waste.

Server Provisioning and Virtualization

Automating provisioning and right-sizing servers with AI means that servers meet workload demands but don’t exceed them. When done effectively, energy consumption goes down and there’s less of a need for additional virtualization.

Workload and Data Placement Optimization

AI is much more effective at identifying the most efficient servers for certain workloads and consolidating lightly used servers on the fly. Proper workload distribution and data placement also minimize energy consumption.

Data-Driven Decision Making and Continuous Improvement

Because AI can analyze vast amounts of data in a fraction of the time it would take for a human to do the same thing, data-driven decision-making can be far more precise. Data centers are empowered with a richer view of their environment and can make continuous improvements toward more sustainable configurations.

Building a More Sustainable IT Strategy

Whether you are operating out of your own data center, or you’re looking to make your equipment in a facility you rent more energy-efficient, there are steps you can take to improve your sustainability today. If you need help building a more sustainable IT strategy, you can contact our team of experts today.