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In the technological scenario, the search for innovation shapes the way companies manage their resources and data. In this context, two technologies have emerged as protagonists of major transformations: migration to the cloud and the impressive advancement of artificial intelligence (AI) .
Together, these two technologies not only revolutionize the way organizations operate, but also lay the foundation for a future full of possibilities.
Cloud computing, by providing flexible, on-demand access to resources, has become a backbone for businesses of all sizes. However, truly revolutionary potential is unlocked when the cloud seamlessly intertwines with artificial intelligence .
Thus, the evolution of AI is not just about more advanced algorithms or more sophisticated machine learning; it is about the ability to generate, understand and interact, in an increasingly closer way, with human beings.
Therefore, in this article, we will explore the relationship between cloud migration and generative AI, showing how these two forces converge to drive the future of companies – and technology.
Stay with us!
What is cloud migration?
Cloud migration is the process in which an organization moves its digital assets (such as data, applications and workloads) from an on-premise to a public cloud environment.
Thus, the cloud enables the remote use, via the internet, of various computing resources. A company's programs and applications can be accessed at any time and from anywhere by authorized people.
In practice, this reduces the company's spending on physical equipment such as computers, servers and air conditioning. According to data from Gartner , cloud computing is 40 times more economical compared to companies' internal IT structures.
Proper planning is essential for a successful migration. Companies must consider what data and applications will be transferred and the order in which it occurs.
In short, migrating to the cloud is not just a technical change, but a strategic transformation that can leverage the operational capabilities of the business as a whole.
What is generative AI?
Generative AI (or Generative Artificial Intelligence) represents a fascinating advancement in the machine learning and data arena.
This technology employs deep learning models – also known as neural networks – that are trained with vast data sets to create original content .
In this way, the content generated can be in numerous formats, from texts and images to music and videos, highlighting the adaptive and innovative capacity of this technology.
generative models are distinguished from discriminative , whose main objective is to classify existing data. Instead, generative AI uses complex patterns and learnings from its data analysis to create new data, which can be used in a variety of applications, such as:
- Development of virtual assistants (e.g. chatbots in general);
- Creation and modification of images and art (Ex.: Midjourney);
- Automatic generation of narrative and informative texts
The use of generative AI is a reflection of artificial intelligence's ability to not only understand and process information, but also to be a source of creation , generating new ideas and solutions.
Given this scenario, fueled by a growing volume of data and the continuous improvement of algorithms, it is becoming an increasingly powerful instrument in various market and research sectors.
What is the relationship between cloud and generative AI?
The relationship between the cloud and generative AI lies in providing robust infrastructure and the large-scale data processing capacity cloud environments offer.
Thus, the cloud enables AI systems, including those focused on machine learning , to access and store massive data with greater efficiency and flexibility.
Therefore, before investing in artificial intelligence , it is essential that your business invests in efficient cloud computing solutions .
Check below in which aspects the cloud enhances generative AI:
Scalability
AI systems, especially generative AI, demand a large amount of computing resources . Cloud environments allow scalability to deal with these needs efficiently, adjusting resources according to demand.
Agility in development
Using the cloud accelerates the development of generative AI applications, as it offers access to ready-to-use services and infrastructures, in addition to reducing the need for maintenance of local systems.
Data access
For generative AI, the quality and quantity of data are fundamental. The cloud makes it easier to access, store, and analyze large data sets, which are essential for accurately training AI models.
Cooperation and innovation
The cloud fosters a collaborative environment where developers and companies can share AI tools and systems . In this way, this stimulates innovation and the development of new generative AI applications.
Finally, we can say that the combination of cloud and generative AI is powerful and amplifies data processing and analysis capabilities, creating a cycle of innovation and continuous improvement in various technological applications. A perfect alliance for business growth!
Why migrate to the cloud?
The possibility of working with generative AI is just one of the countless benefits that migrating to the cloud offers businesses.
It represents a significant transformation by providing access to advanced technologies and optimizing resources. Thus, the process brings strategic advantages regarding costs, safety and operational efficiency. Check out:
AI closer to your business
As we have seen, AI becomes more accessible to businesses with migration to the cloud. Cloud-based AI services can be integrated into business processes, improving decision-making and creating competitive advantages.
Improved data analysis
The cloud environment offers advanced tools that provide insights from large volumes of data . With the scalability that the cloud provides, data processing and analysis become more efficient, enhancing data-driven strategies .
Greater agility
Migration makes it easier to quickly adapt to market changes, as cloud services allow you to deploy and scale resources more quickly than in a traditional IT environment.
Modernized data
In the cloud, data can be stored in a modernized , favoring governance and collaboration. Thus, migration paves the way for more effective and up-to-date data management.
Security
Cloud security is always reinforced by advanced mechanisms and constant updates. Cloud providers invest in robust security protocols that can surpass those of many data centers .
See also: How the cloud transforms companies by offering greater scalability
What are the types of cloud migration?
Currently, there are different approaches when it comes to migrating workloads and applications to cloud environments. Therefore, it can occur in different ways, depending on the needs and strategies of an organization. Check out the main three below:
1. Rehost
It involves moving applications and data from the on-premises directly to the public cloud without making significant changes . It is often the fastest route, although not always the most efficient in terms of cost and performance.
2. Rearchitect
It involves restructuring and optimizing applications to better leverage cloud-native services. This technique may be more costly and time-consuming initially, but tends to offer greater scalability and operational efficiency.
3. Replatform
In this modality, the application undergoes some changes to adapt to the new environment, but without a major redesign of the application core. For example, it may include the use of managed services for databases.
How to choose the best migration service?
When considering cloud migration for your business, it is critical to carefully evaluate the services and providers available.
It is critical that companies align their migration strategies with the specific needs of their workloads, data and applications. Therefore, we have listed some tips to help you and your business when making this choice. Check out!
First steps:
- Clearly define business objectives
- Create a detailed migration plan
Evaluation factors:
- Service compatibility: check whether the provider offers the necessary tools and services;
- Performance and scalability: choose cloud solutions that can adapt to the company’s growth;
- Compliance and security: confirm that they comply with industry regulations.
Market-leading providers offering robust solutions :
- Azure: offers easy integration with Microsoft products and robustness in hybrid solutions;
- AWS: stands out for its wide range of services and is recognized for its capacity for innovation;
- Google Cloud: is valued for advanced data analysis and machine learning .
Final items for consideration:
- Evaluate the support and service level (SLA) offered;
- Compare costs to ensure a good investment;
- Look for success case to understand how the provider met the needs of other companies.
How to migrate to the cloud in times of generative AI?
In times of the rise of generative AI, migration to the cloud requires a strategic and methodological . Companies should start with a workload analysis to identify which data and applications will benefit most from the cloud environment.
Therefore, detailed planning is essential. The transition must include listing all data and applications to be migrated, as well as defining AI tools and resources that will help with the ongoing management of the cloud environment.
Additionally, the migration process must operations downtime This is why it is so important to carry out the migration in phases, carrying out parallel tests to verify performance and security.
When moving to the cloud , AI systems can assist with process automation and predictive analytics for continuous optimization. Successful migration does not end with transferring data and applications ; it extends to adapting to new tools and exploring the potential offered by generative AI in the new environment.
The future of generative AI in the cloud
As it advances, generative AI is expected to transform cloud infrastructure, offering scalability and flexibility for different types of businesses and applications.
In cloud environments, integrating generative AI with existing technologies has the potential for exponential growth. Aspects such as self-learning and self-sufficiency are beginning to be integrated, enabling more intelligent and autonomous systems.
Check out 3 statistics below that confirm this promising future:
- According to data from Gartner , by 2026, more than 80% of companies will have used APIs and generative AI models;
- Adoption and opportunities surrounding cloud computing will continue to expand, leading to a market worth more than $1 trillion by 2027, according to IDC ;
- Data from Forrester shows that 12% of companies with a solid AI strategy now have a chief AI officer, or CAIO c-suite role on the rise.
Your migration to the cloud with Skyone
Now that you know that to explore generative AI in your business it is essential to adopt a cloud computing solution , you need to know that we, at Skyone, are the ideal partners to carry out your migration efficiently and safely!
cloud computing module features Skyone Autosky , which has everything you need to migrate, manage and orchestrate your cloud assets safely – and without headaches!
Want to know more about our platform? Request a demo!
Conclusion
As we have seen so far, with the continued evolution of cloud infrastructure and innovations in AI, experts are optimistic about the role of generative AI in driving digital transformation in organizations.
However, taking care of all aspects of your migration to the cloud is the key to guaranteeing the world of possibilities that this technology brings. Take advantage and understand in depth how the migration processes work – as this is a very important factor in the success of the its operation. Check out our complete guide!
