What is data storage?

Every piece of information you gather in your business is potentially important. Whether it’s a database of customer accounts and their purchase histories, human resources records for every employee, financial information such as payroll or accounts receivable, or intellectual property such as specifications for your products, that information needs to be stored somewhere so you can access it as needed to operate your business.

Forms of data storage

File storage Also referred to as file-level or file-based storage, this type is presented as files that are stored in folders and subfolders in a directory. If you’ve used a PC and saved a document to the hard drive, for instance, you have experienced file storage. Files are accessible through a path that users must know. File storage is the most common type of storage on computer hard drives and network-attached storage (NAS) devices. Block storage Rather than storing data in a complete file, block storage breaks apart data and stores it in blocks that can hold 256 KB up to 4 MB. The blocks are then placed randomly on the storage device – which doesn’t hinder access speeds because each block is tagged with a unique identifier. When a user or application needs a file, the computer queries the block storage system, which rapidly identifies and collects all the needed blocks and reassembles them into a complete file. Block storage is ultra-efficient because it doesn’t use metadata, which takes up room on the storage device. Because it’s so fast, businesses tend to use block storage when they want to scale up quickly and when read/write performance is a critical priority. Object storage This type of data storage separates information into distinct objects with unique identifiers and metadata. It doesn’t form a hierarchy like file storage and is considered “flat.” Metadata is a critical component of object storage and each object can have quite a bit of metadata, such as information about the creator of the data and keywords, as well as policies for security, privacy, and access. Object storage works well with APIs so it’s simple to use with existing software and systems. It also scales very well. It could be spread across hundreds or thousands of devices and locations and still be super speedy because all the data is stored in one namespace. It’s the storage type of choice for public cloud providers, such as AWS, and organizations that deal with a lot of unstructured data such as video files, emails, IoT sensor data, social media content, and more.

Types of data storage solutions

Direct-attached storage (DAS)Network-based storage: NAS and SAN

The importance of data storage

Long-lasting preservation of data – Digital data storage makes it easy to pool large volumes of information for long periods of time. Easier accessibility – Everyone can get the information they need, right from their desktop computers instead of having to physically go to a room full of file cabinets.More efficient data recovery – Stored data is easily backed up by making copies, so recovery is faster and simpler if a file gets lost or corrupted. Smaller physical footprint and easier scalability – There’s no need for physical file cabinets, which take up lots of room over time, and adding more digital capacity is simple.Potentially increased security – For very sensitive data, there are many more ways to secure and protect that information digitally using today’s advanced security tools and features.Easier collaboration across teams – Centrally stored data is accessible to every authorized user and can be accessed and shared among teams as they work together. More efficient document management – It’s easier to categorize and organize data digitally, and it can be done from a computer desktop or other connected device. Enhanced productivity and workflows – Saving data digitally takes less time than printing out physical pages and creating files, which must be stored in file cabinets.

How does data storage work?

When you store data on a computer, the digital information is saved to a device, where it remains until deleted. Storage differs from computer memory in a major way: While you can access information quickly from your computer’s RAM, that data is only available in RAM until your computer is turned off. Data storage, however, retains data whether the computer is powered on or off. That’s how it can store data long-term.Saving data on a computer storage device lets you access that information when you need it. For example, the accounting department can retrieve stored data about employee work hours and use it to carry out bimonthly payroll tasks. A sales rep can pull up information about a customer before a sales call to see recent orders and go over the last visit to remind them of the issues they discussed.

Types of data storage devices

Cloud storageHybrid cloud storageSSD and flash storageBackup storage

What is the best for storing data?

DAS can be a good choice for:Small businesses, branch offices, and home offices that want a cost-efficient solution and don’t need networkingHosting just one application and its dataSecuring and isolating data for compliance purposesSAN can be a good choice for: Large data centers or business-critical applications that need centralized storage resourcesLarge numbers of employees and an IT staff with skills to manage and maintain the solutionApplications that require very high performance, such as transactional databases Hosting large relational databases that need high performanceLarge enterprises that need a high degree of storage scalabilityA fault-tolerant environment for critical applicationsNAS can be a good choice for:Reliable, cost-effective storage for many users that doesn’t compromise performanceLarge volumes of unstructured data that need to be shared among usersApplications that aren’t performance-sensitiveArchiving or backing up dataServers hosting virtual desktop infrastructure (VDI) and virtual machines (VMs)Cloud storage can be a good choice for: Archiving or backing up data for disaster recoveryData lakes and data analytics platformsApplication development and testing Storing workloads during a data migrationStorage for cloud-native applications and their dataStorage for industry and regulatory complianceIoT and machine learning data

What is the safest form of data storage?

DAS can be considered secure in the sense that a hacker cannot infiltrate a network and carry out an attack. Many removable storage devices such as SSDs, USBs, and so on are considered “air gapped” if they aren’t on a networked system. However, if the device is damaged or lost, the data could be irretrievable. NAS is a fairly common target for hackers. The storage system is only as secure as your network and router, so it’s important for NAS users to take proven security measures such as regular updates, two-factor authentication, single sign-on processes, encryption, and so on. SAN is inherently more secure than NAS because its data protection algorithms stay consistent and because if your LAN is attacked, having your data stored on a separate network keeps it protected. Cloud storage is typically considered the most secure type of data storage because major cloud service providers, such as AWS, Google, and Microsoft have put billions of dollars into making it secure. It’s also secure because providers make multiple copies of your data to create a high degree of redundancy – so if a cloud server goes down, you can still access your data because it’s stored in various servers and locations.

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Latest Report Shows Difficulties in Scaling DevOps to Hybrid Cloud

August 31, 2023 | min

Modern organizations strive to increase agility so they can respond quicker and more effectively to fluctuations in market and customer demands. A DevOps approach can be beneficial because DevOps teams create platforms that enable them to automate continuous integration and continuous delivery (CI/CD). These platforms can help speed up time to market, reduce costs, and make processes more efficient.

The answer isn’t always that simple, however. The latest Gartner® report, Leverage Platform Engineering to Scale DevOps Platforms into Hybrid Cloud, states that “Organizations often struggle to scale DevOps toolchains into hybrid cloud environments.” Further stating/mentioning that, “Organizations are looking to adopt/extend DevOps platform that provide flexibility and improve speed, consistency, reduce costs, enhance performance and efficiency in deployment across complex hybrid cloud environments.”

Hybrid Cloud is Essential but Also Creates DevOps Challenges

Hybrid cloud is quickly becoming the standard for today’s organizations that want to stay competitive and ready to pivot when situations change. The cloud is essential to their success and it’s critical that companies can migrate workloads into the cloud (or multiple clouds) and choose the right cloud platforms and services for their unique applications and needs.

As much as organizations need hybrid cloud, it also presents a number of challenges when it comes to scaling DevOps. It can be daunting to create hybrid cloud DevOps pipelines and manage, secure, and maintain compliance around multiple disparate and often siloed ecosystems. It’s difficult to keep processes consistent across environments that include on-premises datacenters, multiple clouds, and (increasingly) the edge. Making updates to pipelines to support cloud-native applications or containers, for instance, can require different processes depending on the cloud platform. And automating the deployment of workloads to the right platforms at the right time can get quite complicated.

As Gartner analysts look at the tension and potential friction between DevOps and Infrastructure and Operations (I&O) teams, they offer several recommendations to help organizations resolve their hybrid cloud challenges.

Three Steps to DevOps Success in the Hybrid Cloud

The report includes three key recommendations for organizations that want to get the most out of DevOps in a hybrid cloud environment. I&O leaders should work closely with DevOps and other relevant stakeholders to take the following steps:

Build and evolve the DevOps toolchain by establishing a platform engineering team to manage the requirements across the different environments and identify needs shared across development teams.
Assess if on-premises tools meet the needs of hybrid cloud deployment by working with software engineering and security teams to define future platform landscape of cloud workloads’ continuous delivery needs and application architectures.
Establish scalable and consistent ways to implement and manage the DevOps tasks by optimizing and simplifying standardized pipelines for the needs of platform users across environments.

Let’s take a closer look at each step.

Create a platform engineering team

Platform engineering is all about making the DevOps platform more efficient, agile, consistent, and cost-effective across the various environments in the organization. It entails working with platform users to determine their needs and challenges in terms of self-service, templates, platform consolidation, and consistent tools. Gartner recommends:

Platform Engineering Teams Must Have Platform Owners
Define the Goal and Engage Key Stakeholders
Adopt Agile Practices to Evolve the Product Via Changing Requirements

In the report, Gartner analysts state that “by 2027, 80% of large organizations must embrace platform engineering to successfully scale DevOps initiatives in hybrid cloud environments, up from less than 30% in 2023.”

Define the hybrid cloud architecture that needs DevOps support

The platform owner should continue to work with stakeholders and platform users to evaluate needs. According to Gartner, “To do so, the platform owner — in collaboration with consumers of the platforms — should adopt the following evaluation methods to identify the target solution and architecture for a future DevOps platform in hybrid cloud:

Collaborate with software engineering leaders or business product owners to identify the existing tools in use in accordance with the critical capability of DevOps toolchains (see Note 1 and How to Build and Evolve Your DevOps Toolchains). Identify the pain points and constraints of SWE teams existing toolchains.
Identify the application architectures and future use cases of technology stacks of cloud workloads, including CI/CD pipelines and data of applications to do gap analysis to identify future tools needed (i.e., tools to support cloud native architecture or serverless).
Align future toolchain platform architecture planning with the organization’s cloud strategy. If cloud strategy is focused on private cloud for most cloud workloads while public cloud or multi-clouds are used to enable technology innovation due to regulatory compliance and security requirements, then the master instance of the DevOps platform should be deployed on-premises. Agents can be deployed to the public clouds as cloud workloads require (e.g., a Jenkins agent to support the CI/CD task to deploy the workload to public cloud or multi-cloud as one scenario (see Comparing DevOps Architecture to Automate Infrastructure and Operations for Software Development).
The platform engineering team may lack the skills to develop an entire, comprehensive DevOps platform, or the existing technology stacks and tools of the DevOps toolchain may not meet the needs of product or development teams. If cases like this, evaluate the third party or cloud-native DevOps platform solution or product together with platform customers based on the organization’s functional needs, non-functional needs (i.e., compliance and security requirements, customer support, service and delivery experiences) and total cost of ownership (TCO).
When planning the security functionality for the platform, prioritize security as part of a continuous-improvement process spanning development and operations.”

Simplify standardized pipelines

In DevOps, different activities—such as compiling software source code or deploying a code package to a container—often require different tools. Because it’s important to optimize and streamline workflows and tools where possible to reduce complexity, Gartner recommends:

Keep the thinnest viable platform (TVP) concept in mind. The platform should provide as thin and simple an abstraction as possible so that it does not cost too much to build/maintain, and so that it does not become deeply proprietary to the organization.
User-centered design. The platform product design should base on the needs of platform users rather than seeking to change the user's behavior around how a platform product works.
Self-service paved road. Platform should provide an easy, self-service paved road and reusable tools or services for users.
Demand-driven. Based on product team or development team needs, improves, and simplifies the pipeline by integrating automation tools and workflows to build, compile, test and release the application.

How Nutanix Can Help

One of the primary goals at Nutanix is to make hybrid multicloud easy. We do that by providing a simple, seamless, consistent platform that allows you to manage, operate, and maintain all of your applications and workloads from a single pane of glass—whether they’re on-premises, in multiple clouds, or on the edge.

DevOps platforms can be scaled and extended to include multiple cloud deployments quickly and without hassle. With the Nutanix Cloud Platform™, you can:

Automate operations and accelerate service and application delivery according to DevOps best practices.
Increase productivity by giving developers the flexibility and platform performance they need to iterate faster.
Speed time to market by moving code from development to production more efficiently.
Lower costs with the ability to securely run dev/test workloads with your other workloads on the same infrastructure.

Visit our website to learn more about how Nutanix can help you achieve a seamless, consistent hybrid multicloud.

Gartner, Leverage Platform Engineering to Scale DevOps Platforms into Hybrid Cloud, Carolin Zhou, Daniel Betts, George Spafford, 14 March 2023. GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.

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