Multi-Cloud: Strategic Flexibility or Hidden Risks?

Cloud computing refers to computations performed not on the user's local machine, but within a cluster of remote servers, i.e., "in the cloud".  Large clouds can be geographically distributed, meaning groups of servers are located in different data centers connected to each other.  This is the essence of cloud computing—computation is based on the collective (as a unified whole) use of resources from separate physical machines.  As a result, the payment model is based on actual usage of resources in real-world tasks. You pay as much as you use—almost a linear dependency. The standard set of cloud services includes: computing power, data storage, administration and development tools (optional), additional services and applications (optional). Cloud capabilities and terms of use depend on the specific provider that owns the physical servers. Cloud in the Network Infrastructure Context When the internet was just beginning, the concept of the cloud did not exist. In the 2000s, the average company could have its own small servers (a mini data center), maintained by a couple of specialists. This was a common approach.  However, as global network infrastructure became more complex, centralized hubs emerged—companies owning a large number of physical servers in one location and renting them out.  This network’s “evolution” into such an architecture is essentially the result of the division of labor, especially in the context of globalization. Everyone focuses on their own expertise: some manage networks and servers, others develop services and applications. From an infrastructure standpoint, however, the cloud is more than just server rental. It’s a broader concept.  A cloud is more flexible. All physical servers of a provider are combined into a single entity, fragments of which are provided to clients. Hence, higher flexibility and scalability, instantaneously on demand. Cloud Computing Models The cloud clearly separates physical and software levels. This high level of abstraction is the hallmark of cloud computing. The entire range of clouds, cloud services, and applications built on them can be divided into several software layers: IaaS (Infrastructure as a Service): This layer provides only computing resources. This is pure cloud. Examples include Amazon Web Services and Elastic Compute Cloud. However, since the 2010s, IaaS has lost popularity compared to PaaS and SaaS models. PaaS (Platform as a Service): This layer offers not just the cloud, but a full platform with preinstalled development and administration tools. It provides a complete stack for specific application tasks. This can include operating systems, databases, containers, libraries, frameworks, microservices, etc. Examples include Google Cloud Platform and Red Hat OpenShift, the latter offering containerization tools like Docker and Kubernetes. SaaS (Software as a Service): This layer includes client-facing cloud services with ready-to-use functionality that is accessible "out of the box." Users typically pay a monthly or annual subscription fee, although free versions with limitations are often available. SaaS is by far the most widespread model. Examples: Google Drive, Salesforce, Dropbox. From the user’s perspective, cloud computing thus represents serverless computing—a model where infrastructure management is shifted to the provider, allowing developers to focus on business logic. This approach enables automatic scaling based on request volume, with application logic executed only when needed—users pay for actual computations, not idle capacity. This fourth model, in addition to the three above, is called FaaS (Function as a Service). FaaS allows developers to execute code (functions) in response to specific events—triggers. Charges apply only when the code runs. Cloud Types The cloud model is not the same as the cloud type. The model relates to how the infrastructure is organized and how the provider interacts with clients (technically and economically). The type describes how the cloud integrates into the broader internet infrastructure, i.e., how strongly or weakly the provider's physical servers are differentiated within the global network. Here are the main types of cloud: Public Cloud The most common type. Most clouds—especially SaaS—are public, open to everyone and not isolated from the internet. Any user can access remote servers via an interface, typically a browser or client app; for example, Google Drive via a web page, Dropbox via a desktop app. These clouds often follow a subscription model offering extended features. If intended for personal users, a limited free version is usually available. For enterprise clients, everything must be prepaid.  Public clouds typically serve many clients, often individuals. Services like AWS, Google Cloud, IBM Cloud, Microsoft Azure, and Oracle Cloud have millions of users. The provider is responsible for the data centers. Users expect strong security, achieved through internal corporate controls and encryption. Still, data breaches occur. With public clouds, there’s no absolute guarantee of security. Hence, corporate clients often prefer other cloud types. Private Cloud A cloud environment where computing resources are entirely allocated (isolated) for a single client: individual or corporate. It is as flexible and scalable as a public cloud but without the drawback of public access. It's harder to hack and is controlled directly by the client. It may be hosted locally or by a provider, but server capacities may be segregated per client. The main reason for using a private cloud is the protection of confidential documents, intellectual property, financial, and personal data. However, private clouds require expertise—specialists for deployment and management. For young projects, this may be costly. Hybrid Cloud A hybrid cloud combines public and private resources to achieve greater flexibility and security. Such clouds orchestrate workloads depending on the task: sensitive data remains in the private segment (more expensive to maintain), and business logic is in the public segment (where high control is not needed). This approach allows organizations to meet goals more efficiently than relying on a single type. With a custom private cloud architecture, a company can move workloads to the public cloud when needed, optimizing resources. Multicloud A multicloud is an abstraction over multiple clouds from different providers. These are different clouds, united in one ecosystem to perform shared tasks. It can combine SaaS, PaaS, and IaaS models. For example, email services may come from one provider, a code repository from another, and media storage from a third. Multiclouds can also be hybrid, combining public and private environments. Companies benefit from multiclouds by avoiding dependence on a single vendor, like diversification. They can switch to more innovative providers when needed. On the flip side, managing many tools complicates the environment. It's important to strike a balance—too many dependencies can backfire. Advantages of Cloud Computing Compared to on-premise server infrastructure or renting dedicated resources, cloud computing offers clear advantages: Cost Reduction Clouds maintained by global network participants relieve developers (users) from most expenses. No need to buy, install, configure, or manage servers. No need for deep server management expertise. Development companies use ready-made clouds, keeping only essential specialists focused on the product and business logic. This significantly reduces both financial and time costs. Flexibility and Speed  Provider-supplied clouds typically include server applications and services that assist in development and administration. Access is instant. Options are immediately available—no waiting on traditional IT teams or vendors. Some providers even allow developers to customize their cloud segments. Efficient Scalability  Clouds can be resized depending on business logic needs. Instead of overprovisioning, the application scales up or down based on load, in real time, within the user request pipeline. Cloud Computing Challenges Security and Confidentiality  Most cloud issues relate to privacy. Public cloud providers can access stored data: code, media, databases. Large providers focus on security and usually have no interest in user data. However, smaller, less-known providers may sell or misuse data. Some disclose this in privacy policies that users agree to. Some contracts omit data ownership rights entirely—legal action may be ineffective. Thus, reputation and brand size matter. Be cautious with unknown vendors. Insecure Interfaces  The client-provider connection is a critical security point. Proper credential control and encryption protocols are essential. Providers must build safe, user-friendly API architectures. Many users lack understanding of risks when connecting to remote servers. Security literacy is vital, especially as cloud computing becomes routine. What's the point of encrypting everything if you store passwords in a plain .txt file? Outages and Data Loss  Providers can experience issues beyond the client’s control. To clients, servers are a "black box." Failures can cause anything from data loss to complete computation halts. Dependency and Support Guarantees Except for private clouds, users don’t own the infrastructure—the provider does. Outsourced infrastructure creates dependency. Small or mid-size providers may not guarantee longevity. Major providers (Google, Amazon) are more reliable, but users must comply with their policies and limitations. In this sense, physical control over equipment (as with private clouds) is preferable, albeit costlier and more demanding. Conclusion The key feature of cloud computing—the separation of physical and logical layers—has become a driving force in the evolution of modern network infrastructure.  The global network is moving toward a state where devices around the world connect to localized hubs: data centers or clouds.  This pervasive network is now known as the Internet of Things (IoT), a concept where every object is connected to millions of others through a global shared network. It's a world where even your vacuum and coffee machine have digital reflections (avatars) on the internet. The physical world is mirrored in virtual reality. In the end, the global internet is turning into a distributed network of localized clouds, connected and communicating with one another.  Yes, the internet has always been decentralized. But the cloud era brings greater flexibility, adaptability, and bandwidth. Such a network is far more responsive to change than traditional architecture. And this global cloud trend is only gaining momentum.

Cloud hosting services are essential for businesses of all sizes, providing scalable resources and reliable performance for web applications and data storage. In 2024, the cloud hosting market is more competitive than ever, with various providers offering cutting-edge solutions to meet different needs. This article will cover the best cloud hosting providers in the US, focusing on their strengths, pricing, and key features. Evaluation Criteria When choosing a cloud hosting provider, it's crucial to evaluate a few critical factors: Performance: Speed, reliability, and uptime are crucial for any hosting service. Scalability: The ability to grow with your business, supporting increased traffic and resource demand. Security: Security measures such as encryption, firewalls, and backup solutions are vital to protect your data. Customer Support: 24/7 support can be a lifesaver during technical issues. Pricing: The cost of cloud hosting should align with the services and resources provided. Ease of Use: A user-friendly interface and comprehensive documentation can help manage your services more efficiently. Top Cloud Hosting Providers in the US Here are the leading cloud hosting providers for 2024, with your company listed first, alongside an overview of their features, benefits, and a comparison with competitors. 1. Hostman Key Features: Simplified cloud hosting with a user-friendly interface High scalability and flexibility – users can easily adjust configurations when they need more power, ensuring seamless scaling for growing businesses Free 24/7 customer support with a response time of less than 15 minutes Integrated CI/CD pipelines for smooth and efficient development workflows Fully automated deployment, eliminating the need for manual configuration Perfect for startups and small to medium-sized businesses due to its simplicity and ease of use Budget-friendly pricing with a pay-as-you-go mode Hostman is designed to simplify cloud hosting for businesses of all sizes, with a particular focus on automating complex tasks such as deployment and scaling. Compared to other providers, Hostman offers a more developer-friendly experience, particularly for those seeking seamless CI/CD integrations without the need for extensive configuration. Moreover, Hostman provides VPS USA hosting solutions for any project.   Comparison with Competitors:   Hostman AWS Azure Google Cloud DigitalOcean Automated Deployments Yes Requires setup Requires setup Requires setup Manual setup Integrated CI/CD Yes, built-in Separate services Separate services Separate services Third-party tools 24/7 Support Free Paid service Paid service Paid service Paid service Ease of Use Very simple Complex Complex Moderate Simple Pricing Transparency Transparent Complex Complex Moderate Transparent Hostman’s ease of use and automation make it a standout choice for developers and small businesses who prioritize simplicity and scalability. Unlike larger providers, which often require manual setup for CI/CD. Hostman’s integrated approach saves time and reduces the need for specialized DevOps knowledge. 2. Amazon Web Services (AWS) Key Features: High scalability and flexibility Pay-as-you-go pricing model Comprehensive service portfolio (including EC2, S3, RDS, and more) Industry-leading security features Extensive global infrastructure AWS is the most well-known cloud hosting provider, offering a wide range of cloud-based hosting services. It caters to businesses of all sizes, providing a high level of customization, scalability, and reliability. However, AWS can be complex to set up and manage for smaller businesses or developers without significant cloud expertise. 3. Microsoft Azure Key Features: Excellent hybrid cloud capabilities Tight integration with Microsoft products Advanced AI and machine learning tools High performance and uptime guarantees Azure is a strong competitor to AWS, offering similar cloud hosting services. It stands out due to its seamless integration with Microsoft software such as Windows Server, Active Directory, and Office 365. While robust, Azure may be more complex and costly for smaller businesses that do not require deep integration with Microsoft products. 4. Google Cloud Platform (GCP) Key Features: Robust data analytics and machine learning services Competitive pricing Fast global network with high uptime Kubernetes support for containerized applications Google Cloud is a popular choice for businesses focused on big data, machine learning, and containerized workloads. Their Cloud SQL, BigQuery, and Kubernetes Engine services are top-notch for developers and data scientists alike. However, for those who do not need advanced data tools, GCP may offer more than what’s necessary, and its pricing can be difficult to predict. 5. DigitalOcean Key Features: Simple and intuitive control panel Affordable pricing with predictable monthly billing Strong developer community Global data center presence DigitalOcean is ideal for small to medium-sized businesses and developers looking for affordable, easy-to-use cloud hosting services. Their droplets provide a simple VPS solution, and their documentation is well-regarded for its clarity. DigitalOcean’s simplicity comes with fewer advanced features than AWS, GCP, or Azure, but it remains a favorite among developers for small to medium-sized projects. 6. Vultr Key Features: High-performance cloud servers with SSD storage Competitive pricing with hourly or monthly billing Over 25 global data centers User-friendly control panel with one-click app deployment Vultr is a cloud hosting provider that offers a variety of services, including cloud compute instances, block storage, and bare metal servers. It's a solid choice for startups and smaller businesses needing reliable cloud hosting. However, Vultr lacks some of the more advanced features that larger providers like AWS or Google Cloud offer. 7. IBM Cloud Key Features: Strong support for hybrid and multi-cloud environments Integration with AI and machine learning tools Advanced security options, including data encryption and disaster recovery Flexible pricing options, including pay-as-you-go and reserved instances IBM Cloud is well-suited for businesses that need hybrid cloud solutions and advanced data security. It also excels in AI, making it a good option for enterprises looking to integrate machine learning into their workflows. However, IBM Cloud can be more expensive and complex to manage than smaller providers. 8. Linode Key Features: Affordable cloud computing solutions 24/7 customer support with a focus on smaller businesses One-click apps and easy setup for developers Reliable performance with SSD storage and fast CPUs Linode is known for its simplicity and affordability, offering cloud hosting tailored to developers and small businesses. It provides a straightforward interface and strong customer support for those needing basic cloud services without the complexity. Linode may not offer as many advanced features as AWS or Azure, but it is a reliable and cost-effective solution for smaller workloads. Summary of the Top Cloud Hosting Providers Hostman stands out as an ideal choice for small to medium-sized businesses seeking a simple, user-friendly cloud hosting solution. Its fully automated deployment process and integrated CI/CD pipelines allow startups and growing companies to focus on development without the complexities often associated with cloud hosting. Amazon Web Services (AWS) remains a top choice for large-scale, enterprise-level hosting due to its vast service offerings and global reach. Microsoft Azure stands out for businesses already using Microsoft products or those seeking robust hybrid cloud capabilities. Google Cloud Platform (GCP) offers strong performance in data analytics and machine learning, making it a top contender for businesses in these fields. DigitalOcean and Vultr provide affordable, easy-to-use solutions for developers and small to medium-sized businesses, with a focus on VPS services. IBM Cloud is ideal for enterprises requiring hybrid cloud solutions and advanced security, while Linode caters to developers and small businesses with affordable, reliable services. Tips for Choosing the Right Cloud Hosting Provider Assess Your Needs: Identify the specific needs of your business. Do you need high-performance computing, storage, or advanced analytics? Consider Scalability: Choose a provider that can scale with your business, offering the flexibility to add resources as needed. Compare Pricing Models: Cloud hosting providers offer various pricing models, such as pay-as-you-go or reserved instances. Choose a model that fits your budget and usage patterns. Check Uptime and Reliability: Review each provider's uptime guarantees and ensure they have a strong track record of reliability. Look for Support: Choose a provider that offers the level of customer support you need, whether it's 24/7 availability or comprehensive self-help resources.

Containerization greatly simplifies the software development process, and the biggest advantage of using containers is their portability. However, running a container on the cloud can lead to some complications. Of course, you can deploy containers on cloud provider servers using an IaaS (infrastructure as a service) model, but you will have to administer these servers. To avoid this, cloud providers came up with the CaaS (Containers as a Service) model. How to run a Docker container in the cloud without configuring the infrastructure Containers as a service, or CaaS, is a modern model that allows developers to run their Docker containers directly in the cloud without having to deploy infrastructure, including orchestration tools (Docker Swarm, Kubernetes, OpenStack, etc.) and software cluster management software. The main benefits of using CaaS are as follows: Reduced costs. There is no need to maintain the infrastructure to run your Docker container, which means running CaaS is faster and cheaper. Flexibility. In most cases, you can easily move from cloud to cloud or even back to on-premises infrastructure, freeing you from being tied to a specific provider. Speed. Because the underlying infrastructure is already provisioned, you don't have to worry about managing and maintaining the hardware your Docker containers will run on, meaning you can deploy them faster. Security. CaaS not only makes it easier to run applications, but also improves security as most CaaS solutions include vulnerability scanning. There are some important factors to consider when choosing the right CaaS solution. For example, the ability to work with multi-container applications, supported storage functions and file formats, and the technologies used to ensure data safety. Each solution has specific features and limitations, which we will now examine in detail. Amazon Elastic Container Service (ECS) Amazon ECS is a scalable container orchestration platform for running and managing containers in a clustered environment. You can choose the containers to run, how many containers to run, how they communicate, and the resources your containers use. There are two ways to use ECS: through EC2 instances or with Fargate. In the first case, containers will be deployed on EC2 instances (virtual machines) created for the cluster. This gives you full control over the type of EC2 instance you use. For example, if your container is used for machine learning and is GPU-centric, you can run a virtual machine optimized for that task. The only downside to this solution is that you will be responsible for patching, managing network security, and scaling. With the AWS Fargate model, you don't have to worry about managing EC2 instances. Fargate directly manages the underlying servers needed to run Docker containers by pre-configuring a cluster. Thus, you will relieve yourself of the need to manage infrastructure. However, only one network mode (awsvpc) is still supported, which may limit your ability to implement a number of tasks. AWS Lambda This is a serverless service from AWS where you submit code in various languages (Java, Go, C#, Python, Powershell, Node.js, Ruby), and Amazon runs it in the corresponding Lambda interface. Lambda functions are primarily called by connecting them to AWS API Gateway, which exposes the functions as REST API calls. Initially, AWS Lambda did not support containerization applications, but since December 2020, this service from Amazon can create a Docker image and run containers up to 10 GB in size. Using Lambda to run a Docker container in the cloud will give you, first of all, good scalability: Lambda can create up to 500 new instances every minute automatically. However, since Lambda is AWS's own serverless technology, you may have to face challenges when moving to another cloud provider. Among other restrictions, we note that Lambda functions can be executed for no more than 15 minutes, which means you can forget about long-running tasks. AWS App Runner Launched in May 2021, AWS App Runner allows you to move your web application to the cloud without worrying about scaling or the infrastructure associated with the application. Essentially, it just launches ECS with Fargate to run your container, but you don't need to configure anything related to Fargate to get started. AWS App Runner can run in build mode, pulling code from your GitHub repository and building the application on any commits you push to master/main. It can also run in container mode, where you connect your container registry (though only AWS ECR is currently supported) and specify your image. The main advantage of AWS App Runner is that it is easy to set up and provides an easy way to run a web application in the cloud. Among the disadvantages, we note that the build mode only supports the Python and Node.js runtimes. Build mode also doesn't have integration with AWS CodeCommit or other version control systems, meaning you'll only have to use GitHub. Finally, the application cannot communicate with private VPCs. Azure Container Instances (ACI) This solution from Microsoft offers: persistent storage by connecting an Azure file share to a container; managing groups of containers that share a host, local network, or storage; full control over the instance on which your Docker container runs; increasing the computing power of the GPU to the required values. Let's also add that since the container is located in your virtual network, it can communicate with other resources in it. The only drawback of ACI is that calling Docker containers is only supported from the registry. Google Cloud Run Google's CaaS solution is built on the Knative platform based on Kubernetes. As with AWS App Runner, you can specify a container registry or repository containing your application code. Google Cloud Run's advantages include Google Secret Manager support and code support in many programming languages, including Go, Python, Java, Node.js, and Ruby. Among the shortcomings, we note only a limited number of regions compared, for example, with Azure and AWS services. Conclusion While there are some differences in the solutions from Amazon, Microsoft, and Google, they share a common goal of making it easier for developers to run Docker containers in a cloud orchestration environment while maintaining the flexibility needed to support a wide range of workloads. Moreover, each solution has its own limitations that must be taken into account when choosing a solution for your tasks.