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10 Attractive and Innovative Services in the Public Cloud

May 15, 2024 Dionisio García

In an increasingly environmentally conscious world, it is crucial for companies to adopt practices that boost their growth and also contribute to the preservation of the planet. In this space, we will share the 10 most contracted or fastest growing services in Public Cloud, in the coming years, as well as their benefits, both in terms of optimizing operational efficiency, as well as in terms of cost reduction. 

The migration of workloads from an on-premise environment, either with reduced or oversized capacities, entails significant costs, including communications and electrical expenses. This leads us to increasingly consider Cloud migration, either of our entire landscape of systems, applications or for the use of pay-per-use services, with the intention of reducing both our CAPEX (capital expenditure) and OPEX (operating expenditure) costs.

As mentioned above, the services offered by the public cloud bring significant benefits in terms of optimizing operational efficiency and reducing costs, as well as offering innovative solutions to drive business growth. Below, we will present the services that will be most in demand in the coming years, which offer a wide range of benefits for businesses, from greater flexibility and scalability to enhanced security and regulatory compliance. Their adoption represents a fundamental step toward digital transformation and business success in the cloud era.




Top 10 Most Demanded Cloud Services in the Coming Years

  1. 🙌  On-Demand Instances: 

    Are you considering the implementation of a new database on your local server? Prepare your patience, because you are likely to encounter a considerable wait.

    However, if you are willing to explore the possibility of an on-premises virtual machine (VM) instead of a physical server, and your company uses VMware or similar technologies, your wait can be minimized. On the other hand, if you are considering creating a server instance in Public Cloud, it can be provisioned and running in about 15 minutes. Plus, you have the flexibility to tailor it to your needs and shut it down when not in use.

  2. ✨  Serverless Services: 

    The term "serverless" implies that a service or a piece of code will run on demand for a short period of time, usually in response to an event, without the need for a dedicated virtual machine for execution. When a service operates serverless, there is usually no need to worry about the underlying server; resources are allocated from a pool managed by the cloud provider.

    Serverless services, currently available in all major public clouds, typically include automatic scaling, built-in high availability and a pay-as-you-go billing model. If you are looking for a serverless application without being tied to a specific public cloud, you can opt for a vendor-independent serverless framework, such as Kubeless, which only requires a Kubernetes cluster that is available as a cloud service.

  3. 🔥  On-Demand Containers: 

    On-demand containers are an efficient and flexible way to package, distribute and run applications. In essence, a container is a lightweight software unit that encapsulates an application's code and all of its dependencies, allowing it to run uniformly in any environment, from a local development environment to a production environment in the cloud.

    Running containers on demand offers all the advantages associated with on-demand virtual machines, with the added bonus of requiring fewer resources and costing less. This feature makes them a highly favorable option for a variety of applications, combining efficiency and economy in their deployment.

  4. 📝  Pre-built Container Images: 

    Pre-built container images are pre-built templates that contain everything needed to run an application inside a container. These images are configured with the operating system, libraries and dependencies necessary for the application to run efficiently in any container environment.

    Pre-built container images are typically configured with security best practices. They are a powerful tool for simplifying and accelerating application development and deployment, while promoting consistency and reliability in container environments.

  5. 🌐  Kubernetes Container Orchestration:
    Kubernetes (K8s) is an open source system designed to automate the deployment, scaling and management of containerized applications. K8s is based on Google's in-house technology called "Borg", Kubernetes has emerged as a robust and reliable solution for orchestrating containerized environments.

    Kubernetes clusters are composed of a set of working machines, called nodes, that run containerized applications. These worker nodes host pods, which in turn contain the applications. Meanwhile, a control plane monitors and manages both the worker nodes and the pods, ensuring smooth and efficient operation of the system.  

    Kubernetes (K8s) is versatile and can scale without restrictions, which means it can run in any environment. All major cloud service providers offer Kubernetes solutions, and it is possible to run Kubernetes on your own development machine.

  6. 📊  Auto Scaling Servers:

    Auto Scaling Servers are a solution in Public Cloud that allows you to dynamically adjust the processing and storage capacity of a system according to real-time demand automatically, without the need for manual intervention. 

    Most public clouds allow you to automatically scale the size of virtual machines and services based on demand, either by increasing or decreasing the number of instances or by resizing them. This is done in response to real-time usage, enabling seamless scaling up or down as needed.

    The benefits of this technology include improved system responsiveness, resource optimization, reduced operating costs by avoiding over-provisioning of unnecessary resources, and increased service availability and reliability for end users.

  7. 🧑‍💻  Databases:

    Leading public cloud platforms, along with various database vendors, have implemented distributed database systems with redundant interconnections and distributed consensus algorithms. These advances allow them to operate efficiently and guarantee exceptional reliability, with uptime reaching up to five nines (99.999%).
    In the following list we present outstanding examples of cloud databases and vendors.

    Outstanding examples of cloud databases:

    • Google Cloud Spanner (relational)
    • Azure Cosmos DB (multi-model)
    • Amazon DynamoDB (key-value and document)
    • Amazon Aurora (relational)

    Examples of providers:

    • CockroachDB (relational)
    • PlanetScale (relational)
    • Fauna (relational/serverless)
    • Neo4j (graph), MongoDB Atlas (document)
    • DataStax stra (wide column)
    • Couchbase Cloud (document)

  8. ⛅️  Hybrid Services:

    Companies with large investments in data centers often want to extend their existing applications and services to the cloud rather than replace them with cloud services. All major cloud providers now offer ways to achieve this, both through the use of specific hybrid services, e.g. databases that can span data centers and clouds, and local servers and perimeter cloud resources that connect to the public cloud, often called hybrid cloud.

  9. 🚀  Business Continuity:

    Training deep learning models that require large data sets can extend for more than a week when running on CPU clusters. Using GPUs, TPUs and FPGAs can significantly reduce this time, and their availability in the cloud simplifies their use as needed.

  10. 🌎  Distributed Services and Perimeter Computing:

    Databases are not the only services that can benefit from distributed execution. The problem is latency. If computing resources are far away from the data or processes under management, it takes too long to send and receive instructions and information. If latency is too high in a feedback loop, the loop can easily get out of control. If the latency is too high between machine learning and data, the time it takes to perform training can explode. To solve this problem, cloud service providers offer connected devices that can extend their services to a customer's data centers (hybrid cloud) or near a customer's production plants (edge computing).

    The need to bring analytics and machine learning geographically closer to machinery and other real-world objects (the Internet of Things or IoT) has given rise to specialized devices, such as miniature computing devices with GPUs and sensors, and architectures that support them, such as perimeter servers, automation platforms, and content delivery networks. Ultimately, these all connect back to the cloud, but the ability to perform analytics at the perimeter can greatly decrease the volume of data sent to the cloud, as well as reduce latency.


👉 Move to the Cloud with Avvale

At Avvale, our mission is to help organizations in their digital transformation process through continuous innovation. We strongly believe in the power of technology as a catalyst to shape a future where businesses can actively choose to be both sustainable and profitable.

Through our Infrastructure as a Service (IaaS) services and our Business Technology Platform (BTP) and Rapid Application Development (Low Code) areas, we can provide you with 90% of the services mentioned in this article. We have the experience and expertise to help you achieve your goals and reduce the costs associated with infrastructure and operations, as well as optimize your operational processes.

Contact us for more information on how we can work together to drive your business to success.

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