10 Workloads That Should Be Moved to Cloud Right Now

Cloud technology continues to improve and expand its range of service offerings to businesses. The recent shift to remote work at the start of the 2020s saw higher demand for cloud-based services in the market. The many benefits of cloud platforms allowed for a great transition in the workplace.

Most cloud service solutions are available to organizations with a "pay-for-use" model, allowing companies to eliminate the costs required for expanding their use of these services. Shifting data and other IT assets to off-site platforms offer organizations many advantages, especially regarding systems security.

A distributed cloud model reduces organizational dependence on the geographic proximity of data and applications. The shift to remote work seems sustainable some two years after 2020, with up to 75% of organizations retaining this model for employees.

As a result, we can expect the mass adoption of cloud solutions to continue. Cloud adoption continues to accelerate as organizations shift key workloads to support remote workers and maintain their operations at data centers.

Not all workloads benefit from cloud solutions, with some application categories required to remain on-site. Still, companies are looking to shift as much responsibility to the cloud as possible, including most workloads.

So, what is a cloud workload, and how can companies benefit from instituting this practice? The cloud offers several advantages to organizations, including access to secure or sensitive data where there are severe privacy concerns.

In addition, cloud users must be careful when migrating any performance-critical or mission-critical applications off-site. Some data and applications are subject to legal restrictions or compliance regulations and require extensive analysis before migrating to the cloud.

This scenario is especially important for disaster recovery and business continuance. Many companies saw line-of-business leaders execute cloud adoption decisions without first consulting on the issue of central IT governance. As a result, these decisions created several inefficiencies and several cloud vendors to manage.

We can expect management to be unaware of these decisions' impact on cloud adoption. As a result, they may overspend on their solutions by as much as 50% moving toward 2024. Several workloads are suitable for moving to the cloud to save on business expenses. This post examines ten of these workloads.

We'll look at how IT decision-makers must understand these organizational cloud trends and why these apps are suitable candidates for a cloud transformation.

#1 Mobile apps

Mobile apps include several remote work application workloads, excluding remote and virtual desktops, that we'll cover later. These apps also have users taking advantage of using mobile devices on-site or in remote work applications.

The cloud offers an optimal landing place for app maintenance due to the highly variable hardware resource demands in scenarios with moderate to low data usage. These applications benefit from implementing cloud workloads while the bulk of the data remains on-site.

#2 Advanced analytics and databases

Data analytics and data center workloads are not always consistent, but they are very demanding on resources. These high-compute, high-volume applications require cloud elasticity, with research showing data analytics and databases widely supported in the public cloud.

Conventional analytics are not typically a cloud-native application, and organizations took time to understand the need for this to change within their processes and systems while undergoing digital transformations.

One of the biggest trends for analytics and data in 2022 is the increased need for cloud-based AI data processing. Experts admit that by 2025, AI models and context-driven analytics will replace some 60% of models constructed on conventional data.

Organizations must build out improved data pipelines to prepare for this change, leveraging AI cloud services. That task requires the prioritization of D&A workloads through cloud migration strategies.

High-demand, high-compute analytics workloads previously equated to significant computing power and hardware investments. However, in the modern environment, these conventional architectures are not sufficient in a manner that's cost-effective and scalable for organizations.

Shifting these workloads to the cloud offers organizations less latency and more real-time opportunities. Both points are crucial to engineering data-driven decision intelligence.

#3 Content management and collaboration

Regarding content management and collaboration environments, collaboration entails human relationships in technology usage and design. These functions include multi-author document creation, agile team-based software design, and the use of collaboration-based apps like Office 365.

Content management workloads in the cloud are not always more cost-effective, but they allow for the successful expansion of remote work experiences and improved collaboration between teams. Governance concerns are the only exception to this application category.

Issues such as legal requirements and regulatory compliance requiring regular reporting or privacy filters can result in less cost-effective applications in the cloud, as forced outages may be necessary for organizational compliance.

#5 Dev and test workflows

DevOps teams have high standards and significant demands on resources and need to make fast decisions in real-time. Moving these tasks to cloud workloads creates scalable, self-service, collaborative environments for QA and DevOps to achieve their objectives.

More organizations decide to leverage "as-a-service" systems, and moving DevOps workflows to the cloud lets these teams flourish. DevOps requirements are an issue of quality, quantity, and autonomy, and shifting these workloads to the cloud achieves these objectives.

Before the introduction of cloud solutions, IT admins found themselves forced to provide on-site resources. This strategy resulted in underutilized server capacity or hardware and limitations on resources. Shifting the Dev/test workloads to the cloud gave development teams the flexibility to spin-up environments where necessary.

The strategy assists teams with achieving optimal productivity and agility, along with the ability to work in parallel and run iterative dev/test cycles. As dev environments grow with contained apps, DevOps can scale to spin-up end-to-end testing environments for these projects.

We've already seen how better tech solutions ease friction between database admins and DevOps. Unified storage and the cloud implement the same for DevOps and IT teams. These Dev/test environments underpin flash storage, removing complexity while enabling devs self-service access to data sets and the ability to roll-back backups where required.

#6 Virtual and remote desktops

The panic of 2020 saw many employees undergoing the shift to remote work. This change significantly impacted the use of remote and virtual desktop workstations. As a result, on-site data center costs become increasingly expensive as the workforce disperses.

Another core issue is software and hardware support and maintenance. IT support normally coordinates hardware rollouts, upgrades, and on-site employees' software updates. However, shifting to remote work requires implementing effective remote and virtual desktop solutions to control various operating systems and hardware platform choices.

Cloud implementation simplifies and centralizes virtual desktop support, outsourcing this task to external service providers to reduce expenses.

#7 Scaled applications

As workloads increase, they test limits on resources. These workloads start to demand additional resources like CPU power, memory, network bandwidth, and storage capacity. Scale-out applications have a distributed architecture like multi-cloud implementations.

Some cloud solutions providers offer features that increase the availability of resources as required. A good example is AWS Auto Scaling. Some data-intensive, high-performance workloads don't benefit from the move to cloud migration.

These workloads usually perform better with the co-location of the data. Big data applications and enterprise data warehousing are good examples, especially when integrated with transactional apps.

For example, operational systems handling services or product purchases may require the execution of big data queries when attempting to uncover financial fraud. Moving these big data applications to the cloud won't save time, resources, or money since they're typically small, and the big data applications have configuration using a scaled-up architecture.

#8 Back-office applications

Implementing these core business application workloads in cloud solutions, such as those used by HR, accounting, finance, and logistics, outgrow legacy infrastructure. Back-office apps are least likely to be operating in the cloud, but they begin to follow customer-facing apps to cloud solutions.

The backbone of enterprises was previously heavily customized, legacy back-office apps defining these processes. In the modern era, these systems are entwined with bound-together apps and a complex web of integration, making them challenging to work with and inconducive to data sharing and agility.

Back-office modernization offers a solution to integrate that data, enriching the organization over time while revealing the value levers. As organizations outgrow the legacy systems they invested heavily in decades prior, the migration of these apps to the cloud will increase substantially.

The crucial component is ensuring customization to on-site software isn't lost during the transition to the cloud. This move leaves the question of how to replace or rebuild these applications in the cloud. Other critical factors involve the data security offered where it's used or moved.

Reports show experts think plans to migrate these workloads to the cloud will continue well into 2024. This strategy includes the structure of hybrid environments. There are significant challenges when moving workloads into mixed environments.

The key to success is having a unified, single view of all workloads, regardless of the location. You get an AI-driven data-services platform and more with the right IT partner.

#9 Disaster recovery planning

Disaster recovery planning is another crucial workload cloud systems can integrate into organizational planning. DRPs are essential for any business, from local businesses to the largest corporates. Experts predict more than 50% of companies will increase budgets for cloud-based DRP solutions by the end of 2022. A pay-per-use environment offers a sought-after, cost-effective solution for supporting cloud-based DR solutions. This shift indicates an IT disaster recovery plan must be cloud-based. Since disaster recovery plans typically contain several degrees and levels of disaster, they must account for issues like network failures, single hardware unit failures, site failures, and electric power failures.

IT decision-makers must distinguish between locating DR backups and migrating DR processes to the cloud. Some local disaster scenarios, like single-unit hardware failures, might not see any benefit from allocating DR processes and data in cloud solutions.

However, site failures may benefit from cloud-based disaster recovery solutions, including off-site secondary solutions. Stakeholders will also have to address compliance and regulatory issues in these cases. Some service providers may require regular testing of standardized DR plans.

For example, credit card merchants must comply with the Payment Card Industry (PCI) Security Council standards.

#10 Business continuity strategies

Shifting backup, data archives, and DRPs to the cloud is essential to effective business continuance strategies. In the modern era, conventional legacy recovery solutions have become increasingly inadequate for organizational data protection requirements.

Additionally, backups don't just store data for the disaster. They are flexible, available, and fast solutions to a disaster. Cloud-based backup and DR solutions are common and critical to maintaining business continuance in a disaster.

Modern backup and data recovery strategies require a more accessible and agile approach than legacy solutions like tape can provide. The cloud offers cost-efficient methods of keeping business-critical data sets available and safe at the click of a mouse.

Availability is a key requirement for data backups. Legacy solutions don't offer organizations the agility required to get these backups out of a neutral state.

Shifting recovery and backup workloads to cloud-based solutions give organizations better resilience in an environment of ever-increasing threats from bad actors.

Organizations that replace antiquated disk-to-disk-to-tape with flash-to-flash-to-cloud solutions and cloud-native data storage environments address regional data security laws. The migration and duplication of their stack and multi-cloud management strategies replace these legacy systems.

In closing – Work with the right IT partner

Moving these ten workloads to the cloud enables organizations to save on the data-related costs associated with cloud use and remote work environments. However, companies must understand how to structure their cloud usage.

Compliance and financial expenses are huge considerations to the sustainability of these solutions moving forward. Choosing the right IT services in Atlanta is essential for managing the transition to the cloud and its operations.

Don't delay your digital transformation or place your organization at risk by choosing the wrong IT partner. It would help if you had a team that fits your organizational directives, sizes, and goals. Choosing the right team significantly affects the success and efficacy of moving these workflows to the cloud.