Sign In
Sign In

What is a CDN: Principles of Content Delivery Networks

What is a CDN: Principles of Content Delivery Networks
Hostman Team
Technical writer
Infrastructure

Latency, latency, latency! It has always been a problem of the Internet. It was, it is, and it probably will be. Delivering data from one geographic point to another takes time.

However, latency can be reduced. This can be achieved in several ways:

  • Reduce the number of intermediate nodes on the data path from the remote server to the user. The fewer the handlers, the faster the data reaches the destination. But this is hardly feasible. The global Internet continues to grow and become more complex, increasing the number of nodes. More nodes = more power. That’s the global trend. Evolution!

  • Instead of regularly sending data over long distances, we can create copies of it on nodes closer to the user. Fortunately, the number of network nodes keeps growing, and the topology spreads ever wider. Eureka!

The latter option seems like an absolute solution. With a large number of geographically distributed nodes, it's possible to create a kind of content delivery network. In addition to the main function—speeding up loading—such a network brings several other benefits: traffic optimization, load balancing, and increased fault tolerance.

Wait a second! That's exactly what a CDN is—Content Delivery Network. So, let’s let this article explain what a CDN is, how it works, and what problems it solves. 

What is a CDN?

A CDN (Content Delivery Network) is a distributed network of servers designed to accelerate multimedia content delivery (images, videos, HTML pages, JavaScript scripts, CSS styles) to nearby users.

Like a vast web, the CDN infrastructure sits between the server and the user, acting as an intermediary. Thus, content is not delivered directly from the server to the user but through the powerful "tentacles" of the CDN.

What Types of Content Exist?

Since the early days of the Internet, content has been divided into two types:

  • Static (requires memory, large in size). Stored on a server and delivered to users upon request. Requires sufficient HDD or SSD storage.

  • Dynamic (requires processing power, small in size). Generated on the server with each user request. Requires enough RAM and CPU power.

The volume of static content on the Internet far exceeds that of dynamic content. For instance, a website's layout weighs much less than the total size of the images embedded in it.

Storing static and dynamic content separately (on different servers) is considered good practice. While heavy multimedia requests are handled by one server, the core logic of the site runs on another.

CDN technology takes this practice to the next level. It stores copies of static content taken from the origin server on many other remote servers. Each of these servers serves data only to nearby users, reducing load times to a minimum.

What Does a CDN Consist Of?

CDN infrastructure consists of many geographically distributed computing machines, each with a specific role in the global data exchange:

  • User. The device from which the user sends requests to remote servers.
  • Origin Server. The main server of a website that processes user requests for dynamic content and stores the original static files used by the CDN as source copies.
  • Edge Node. A server node in the CDN infrastructure that delivers static content (copied from the origin server) to nearby users. Also called a Point of Presence (PoP).

A single CDN infrastructure simultaneously includes many active users, origin servers, and edge nodes.

What Happens Inside a CDN?

First, CDN nodes perform specific operations to manage the rotation of static content:

  • Caching. The process of loading copies of content from the origin server to a CDN server, followed by optimization and storage.
  • Purge (Cache Clearing). Cached content is cleared after a certain period or on demand to maintain freshness on edge nodes. For example, if a file is updated on the origin server, the update will take some time to propagate to the caching nodes.

Second, CDN nodes have several configurable parameters that ensure the stable operation of the entire infrastructure:

  • Time to Live (TTL). A timeout after which cached content is deleted from an edge node. For images and videos, TTL can range from 1 day to 1 year; for API responses (JSON or XML), from 30 seconds to 1 hour; HTML pages may not be cached at all. CDN nodes usually respect the HTTP Cache-Control header.
  • Caching Rule. A set of rules that determines how an edge node caches content. The primary parameter is how long the file remains in the cache (TTL).
  • Restriction. A set of rules on the edge node that moderates access to cached content for security purposes. For example, an edge node may serve requests only from nearby IP addresses or specific domains.

Thus, static content flows from the origin server through edge nodes to users, cached based on specific caching rules, and cleared once the TTL expires. Meanwhile, access restrictions are enforced on every edge node for security.

How Does a CDN Work?

Let's see how a CDN works from the user's perspective. We can divide the process into several stages:

  1. User Request Execution. When a user opens a website, the browser sends requests to CDN servers specified in HTML tags or within JavaScript code (such as Ajax requests). Without a CDN, requests would go directly to the origin server.
  2. Finding the Nearest Server. Upon receiving the request, the CDN system locates the server closest to the user.
  3. Content Caching. If the requested content is in the cache of the found CDN server, it is immediately delivered to the user. If not, the CDN server sends a request to the origin server and caches the content.
  4. Data Optimization. Content copies on CDN servers are optimized in various ways. For example, files can be compressed using Gzip or Brotli to reduce size.
  5. Content Delivery. The optimized and cached content is delivered to the user and displayed in their browser.

For instance, if a website’s origin server is in Lisbon and the user is in Warsaw, the CDN will automatically find the nearest server with cached static content—say, in Berlin.

If there is no nearby CDN server with cached content, the CDN will request the origin server. Subsequent requests will then be served through the CDN.

The straight-line distance from Warsaw to Lisbon is about 2800 km, while the distance from Warsaw to Berlin is only about 570 km.

Someone unfamiliar with networking might wonder: “How can a CDN speed up content delivery if data travels through cables at the speed of light—300,000 km/s?”

In reality, delays in data transmission are due to technical, not physical, limitations:

  • Routing. Data passes through many routers and nodes, each adding small delays from processing and forwarding packets.
  • Network Congestion. High traffic in some network segments can lead to delays and packet loss, requiring retransmissions.
  • Data Transmission Protocols. Protocols like TCP include features such as connection establishment, error checking, and flow control, all of which introduce delays.

Thus, the difference between 2800 km and 570 km is negligible in terms of signal propagation. But from a network infrastructure perspective, it makes a big difference.

Moreover, a CDN server in Berlin, finding no cached content, might request it not from the origin server but from a neighboring CDN node in Prague, if that node has the content cached.

Therefore, CDN infrastructure nodes can also exchange cached content among themselves.

What Types of CDN Exist?

There are several ways to classify CDNs. The most obvious is based on the ownership of the infrastructure:

  • Public. The CDN infrastructure is rented from a third-party provider. Suitable for small and medium-sized companies.
  • Private. The CDN infrastructure is deployed internally by the company itself. Suitable for large companies and IT giants.

Each type has its own pros and cons:

 

Public

Private

Connection speed

High

Low

Initial costs

Low

High

Maintenance complexity

Low

High

Cost of large-scale traffic

High

Low

Control capabilities

Low

High

Dependence on third parties

High

Low

Many CDN providers offer free access to their infrastructure resources to attract users. However, in such cases, there are limitations on:

  • Server capacity
  • Traffic volumes
  • Geographical coverage
  • Advanced configuration options

Paid CDN providers use various pricing models:

  • Pay-as-you-go. Costs depend on the volume of data transferred, measured in gigabytes or terabytes.
  • Flat-rate pricing. Costs depend on the chosen plan with a fixed amount of available traffic.
  • Request-based pricing. Costs depend on the number of user requests made.

Deploying your own CDN infrastructure is a serious step, usually justified by strong reasons:

  • Public CDN costs exceed the cost of running your own infrastructure. For example, high expenses due to massive multimedia traffic volumes.
  • The product hits technical limitations of public CDNs. For example, heavy network loads or a specific user geography.
  • The project demands higher reliability, security, and data privacy that public CDNs cannot provide. For example, a government institution or bank.

Here are a few examples of private CDN networks used by major tech companies:

  • Netflix Open Connect. Delivers Netflix’s streaming video to users worldwide.
  • Google Global Cache (GGC). Speeds up access to Google services.
  • Apple Private CDN. Delivers operating system updates and Apple services to its users.

What Problems Does a CDN Solve?

CDN technology has evolved to address several key tasks:

  • Faster load times. Files load more quickly (with less latency) because CDN servers with cached static content are located near the user.
  • Reduced server load. Numerous requests for static content go directly to the CDN infrastructure, bypassing the origin server.
  • Global availability. Users in remote regions can access content more quickly, regardless of the main server’s location.
  • Protection against attacks. Properly configured CDN servers can block malicious IP addresses or limit their requests, preventing large-scale attacks.
  • Traffic optimization. Static content is compressed before caching and delivery to reduce size, decreasing transmitted data volumes and easing network load.
  • Increased fault tolerance. If one CDN server fails or is overloaded, requests can be automatically rerouted to other servers.

The CDN, being a global infrastructure, takes over nearly all core responsibilities for handling user requests for static content.

What Are the Drawbacks of Using a CDN?

Despite solving many network issues, CDNs do have certain drawbacks:

  • Costs. In addition to paying for the origin server, you also need to pay for CDN services.
  • Privacy. CDN nodes gain access to static data from the origin server for caching purposes. Some of this data may not be public.
  • Availability. A site’s key traffic may come from regions where the chosen CDN provider has little or no presence. Worse, the provider might even be blocked by local laws.
  • Configuration. Caching requires proper setup. Otherwise, users may receive outdated data. Proper setup requires some technical knowledge.

Of course, we can minimize these drawbacks by carefully selecting the CDN provider and properly configuring the infrastructure they offer.

What Kind of Websites Use CDNs?

In today’s cloud-based reality, websites with multimedia content, high traffic, and a global audience are practically required to use CDN technology. Otherwise, they won’t be able to handle the load effectively.

Yes, websites can function without a CDN, but the question is, how? Slower than with a CDN.

Almost all major websites, online platforms, and services use CDNs for faster loading and increased resilience. These include:

  • Google
  • Amazon
  • Microsoft
  • Apple
  • Netflix
  • Twitch
  • Steam
  • Aliexpress

However, CDNs aren’t just for the big players — smaller websites can benefit too. Several criteria suggest that a website needs distributed caching:

  • International traffic. If users from different countries or continents visit the site. For example, a European media site with Chinese readers.
  • Lots of static content. If the site contains many multimedia files. For example, a designer’s portfolio full of photos and videos.
  • Traffic spikes. If the site experiences sharp increases in traffic. For example, an online store running frequent promotions or ads.

That said, there are cases where using a CDN makes little sense and only complicates the web project architecture:

  • Local reach. If the site is targeted only at users from a single city or region. For example, a website for a local organization.
  • Low traffic. If only a few dozen or hundreds of users visit the site per day.
  • Simple structure. If the site is a small blog or a minimalist business card site.

Still, the main indicator for needing a CDN is a large volume of multimedia content.

Where Are CDN Servers Located?

While each CDN’s infrastructure is globally distributed, there are priority locations where CDN servers are most concentrated:

  • Capitals and major cities. These areas have better-developed network infrastructure and are more evenly spaced worldwide.
  • Internet exchange points (IXPs). These are locations where internet providers exchange traffic directly. Examples include DE-CIX (Frankfurt), AMS-IX (Amsterdam), LINX (London).
  • Data centers of major providers. These are hubs of major internet backbones that enable fast and affordable data transmission across long distances.

The smallest CDN networks comprise 10 to 150 servers, while the largest can include 300 to 1,500 nodes.

Popular CDN Providers

Here are some of the most popular, large, and technologically advanced CDN providers. Many offer CDN infrastructure as an add-on to their cloud services:

  • Akamai
  • Cloudflare
  • Amazon CloudFront (AWS CDN)
  • Fastly
  • Google Cloud CDN
  • Microsoft Azure CDN

There are also more affordable options:

  • BunnyCDN
  • KeyCDN
  • StackPath

Some providers specialize in CDN infrastructure for specific content types, such as video, streams, music, or games:

  • CDN77
  • Medianova

Choosing the right CDN depends on the business goals, content type, and budget. To find the optimal option, you should consider a few key factors:

  • Goals and purpose. What type of project needs the CDN: blog, online store, streaming service, media outlet?
  • Geography. The provider's network should cover regions where your target audience is concentrated.
  • Content. The provider should support caching and storage for the type of content used in your project.
  • Pricing. Which billing model offers the best value for performance?

In practice, it’s best to test several suitable CDN providers to find the right one for long-term use.

In a way, choosing a CDN provider is like choosing a cloud provider. They all offer similar services, but the implementation always differs.

Conclusion

It’s important to understand that a CDN doesn’t fully store static data; it only distributes copies across its nodes to shorten the distance between the origin server and the user.

Therefore, the main role of a CDN is to speed up loading and optimize traffic. This is made possible through the caching mechanism for static data, which is distributed according to defined rules between the origin server and CDN nodes.

Infrastructure

Similar

Infrastructure

Microservices Architecture: What It Is, Who It’s For, and Tools to Use

Every developer strives to speed up product development while maintaining enough flexibility and confident control over the process. Microservices application architecture helps solve these tasks and, over the past 10 years, has begun actively competing with the traditional monolithic approach. To begin, let’s look at the difference between them. Microservices Architecture vs. Monolith The difference between these two software development approaches is easiest to illustrate with an example. Let’s imagine two online stores: one implemented as a monolith and the other as microservices. A monolithic online store is a single, indivisible structure that combines all components: databases (catalog, customer data), shopping cart, order and payment forms. All of these elements are tightly interconnected and located on the same server. In a microservices system, each component is an independent module that developers can work on separately. And naturally, nothing requires hosting these modules on a single server. Thus, microservices architecture is a kind of constructor that allows you to add new elements painlessly as you scale the application. A monolith, on the other hand, can be compared to a solid wall: scaling here is only possible by adding another identical monolith. It’s worth adding that microservices are sometimes mistakenly perceived as a set of very small services. This is not the case: for example, the database of a large online store may contain millions of records and occupy tens of gigabytes, yet still be just one of the modules within the microservices architecture of the whole application. Comparing Microservices and Monoliths by Key Criteria Now let’s look at the main characteristics of microservices technology in comparison with a monolith and see how both approaches solve the same developer tasks. Release Cycles Development speed and frequency of updates increase with microservices thanks to modularity: changes are made not to the entire codebase but to individual modules. With a monolith, however, the whole platform must be updated first, which increases testing and debugging time. As a result, development slows down and updates are released less frequently. Technology Stack The microservices model offers significantly greater flexibility because each service can be written in its own programming language and may use different libraries and data-storage technologies. With a monolith, the situation is different: changing the technology stack is nearly impossible. Developers are forced to stick to the initial tools. Developer Onboarding Each module in a microservices architecture is self-contained, making it possible to bring in programmers who are familiar with the functionality of a specific service. This substantially lowers the onboarding threshold. With a monolith, new developers must dive into the code of the entire application, understand the functions of every block, and only then begin productive work. Thus, maintaining a monolith is more dependent on specific team members. Optimization Characteristics The modularity of microservices architecture also positively affects optimization, since developers can optimize each service separately. Optimizing a monolithic structure is more difficult because the team must account for links between indivisible blocks, and updating any one of them inevitably affects the entire application. Application Scalability The distributed structure of microservices and their ability to run on separate servers make scaling fast and easy. In monoliths, scaling one component inevitably requires scaling the entire application as a whole. Fault Tolerance Because services are hosted on different servers and have a modular structure, microservices architecture achieves independence of each module. This significantly increases system resilience: a failure in one service does not cause the entire application to fail. With a monolith, the situation is different: all components are tightly interconnected, so the failure of one module can make the entire application inoperable. Do I Need to Switch to Microservices Right Now? As we’ve seen, microservices have advantages in many key areas. But does this mean you need to abandon monoliths as an outdated approach and immediately switch to microservices? The answer depends on the current state of your project. And let’s say right away: rushing to adopt microservices is not always the right choice. Distributed architecture also has its drawbacks. First, microservices require ensuring network connectivity between modules. If a network connection is unstable, this leads to delays and data inconsistencies, which create potential problems in application behavior. Second, each module of a microservices system requires separate testing and health monitoring. Additionally, you will need to allocate cloud resources for each module, which may increase costs. Third, with the microservices approach, teams responsible for different modules may encounter interaction issues. This means you may need a connecting link in the form of DevOps specialists who can streamline collaboration and speed up development. All the factors listed above allow us to conclude that the transition to microservices must be timely. Usually, during the early stages of a project, this is unnecessary, especially if developers have limited human or financial resources. Switching to a microservices architecture makes sense when there is a clear need for significant scaling, and scaling a monolith has already become difficult. Microservices may be right for you if: You have a large team. In this case, it makes sense to divide the team into separate, independent groups, each responsible for its own service; You have a complex, branched application. In this case, it’s far more convenient to update and maintain modules separately than to rebalance the entire system each time; Your application traffic is highly variable. For example, you see sharp spikes in load during certain periods. Microservices' distributed structure allows quick scaling during peak loads, after which you can easily return to normal capacity levels; Your application is frequently updated. Working with separate modules in this scenario is much simpler, and new releases will be significantly faster. If your project meets at least one of these criteria, this is a reason to consider breaking it into independent elements. However, if your application is relatively small and does not require frequent updates, it is reasonable not to rush away from monolithic architecture. Useful Tools for Organizing Microservices A modern development approach requires a containerization platform. In most cases, developers use Docker for these purposes. Docker tools allow them to isolate the application from the infrastructure, meaning they can work with it equally well locally or in the cloud, which is very convenient for development. Once containers become numerous, an orchestrator becomes essential for managing and organizing groups of containers. Kubernetes is most commonly used as an orchestrator due to its strong compatibility with Docker. Another necessary tool is a load balancer, which ensures even distribution of network traffic across all cloud resources. This significantly increases the application’s fault tolerance.
21 November 2025 · 6 min to read
Infrastructure

Serverless Architecture: Overview of Serverless Computing

Serverless is one of the popular directions in IT and continues to grow. Cloud providers are ready to provide all the necessary infrastructure and maintain it, and the user pays only for the execution time of a function—idle time is not billed. Serverless Ecosystem Serverless architecture is a way of building applications in which the developer writes the application logic, while the cloud provider is responsible for launching that logic, monitoring, scaling, maintaining the execution environment, and managing load planning. This is not always an external provider; such infrastructure can also be implemented inside a company using its own computing resources. The simplification of working with infrastructure traces back to the appearance of the first IaaS (Infrastructure as a Service), where the provider simply offered virtual infrastructure for rent, and then extended to widespread BaaS (Backend as a Service), where a developer’s microservice or a database is simply several containers running in the provider’s environment, and in the case of a database, with preconfigured replication. Another product is FaaS (Function as a Service), where the execution unit is a single function. In part, this resembles a microservices approach. Your function should not rely on state between calls (it must be stateless), because each call is launched by the provider as a separate instance in a container. There are also some limitations imposed by the cloud platform: not all programming languages can be used to write function code (although the list is usually wide), and there are limits on execution time and memory usage. The exact limits differ by platform and may depend on your pricing plan. Many providers offer trial periods from three months to a year with limits on the number of requests. The foundation of Serverless is FaaS and the provider’s ecosystem of products. Typically, there are Databases, Authorization Services, API Gateways, Message Brokers (such as Kafka), all provided as services (BaaS) that your function can integrate with. Architecture Each provider may offer a unique set of services, but applications built on FaaS generally have similar architectures. As an example of integration between provider products, you can consider a TODO application (the example is taken from the AWS website). The application logic is packaged in lambda functions, which interact with the DynamoDB database, provided by AWS as a separate service. In front of the functions is the API Gateway, which handles incoming requests and routes them appropriately. The architecture also includes the Amplify Console for managing the web interface of the application and the Amazon Cognito authentication service. Advantages and Disadvantages The main positive aspects of Serverless typically include: Flexible scalability Helps handle peak loads and rapid product growth. The provider will automatically scale the function, and when demand decreases, resource consumption will shrink. Pricing You pay only for the execution time of the function. For example, on AWS, the price includes the cost of function invocations and the amount of memory (GB/s) allocated during execution. Even with 24/7 availability (with some nuances), you do not pay for periods of inactivity. Automation CI/CD, integration with other services, monitoring, log management, and maintaining the execution environment—the provider handles all of this, allowing for faster product deployment. Compared to BaaS infrastructure or full server control (VPS), deploying an application into cloud functions has its downsides: Resource limits Cloud functions have memory and execution time limits, as well as restrictions on data sizes sent or received. Here are examples of such limits in AWS. Cold starts The provider will not keep a container with your function running at all times. If the function has been idle for some time, its next invocation will require time to start up. Startup time depends on the programming language, code size, and the provider’s internal processes, and can reach up to 10 seconds. Here’s a small article with examples on the topic, and a GitHub repo with code and research results. Best Practices Although FaaS-based systems and service ecosystems resemble microservice architecture and functional programming, they have their own best practices beyond monitoring, logging, request tracing, and mocking service responses. Warm Start If your application requires consistently fast responses, cold starts can be a major issue. The solution is to constantly “warm up” the function, for example, by periodically sending requests that create some load so the provider keeps the function active. The load itself does not matter; what matters is triggering the function. If necessary, the provider will scale by starting additional instances on the fly. Some providers offer built-in mechanisms for this (e.g., AWS), allowing you to keep a certain number of instances always running. Fan-Out Pattern A pattern that allows you to bypass memory, data size, and execution time limits by splitting a large task into smaller chunks. Downloading and processing data in chunks, sending emails in small batches—cloud functions will execute tasks in parallel across different function instances. The trade-off is more complex application code and paying for more function invocations. Event Driven Pattern Cloud FaaS functions can be triggered not only via API Gateway or direct invocation. A trigger can be an event from any integrated service, such as a message from Kafka. Event-driven code organization works extremely well for FaaS. Cost Optimization Unlike a fixed-price service (e.g., renting a VPS for a year), Serverless costs are composed of several different services, each with its own billing model. Continuous monitoring of costs and resource utilization, along with load planning, is key to reducing infrastructure expenses. Some providers have special offerings, such as AWS Lambda Reserved Concurrency, which allows reserving Lambda instances and keeping them active on a cheaper pricing tier. Tools for Working with Serverless Serverless Framework An open-source tool for simplifying the development, deployment, and management of serverless applications. It allows developers to focus on writing code without worrying about infrastructure and provider configuration. It supports AWS, Azure, Google Cloud, IBM Cloud, Oracle Cloud. It enables local function testing, integrates with CI/CD systems like Jenkins or Travis, has a large plugin ecosystem, and allows developers to create their own plugins. Terraform A HashiCorp tool representing the "infrastructure as code" approach. It allows defining infrastructure using configuration files in HCL (HashiCorp Configuration Language), which describe the desired infrastructure state rather than the steps to achieve it. Like Serverless Framework, Terraform supports many major cloud providers and allows defining modules, i.e., reusable sets of configuration files for creating and managing infrastructure components. AWS SAM The Serverless Application Model is an open framework created by AWS for developing, testing, and deploying serverless applications on AWS. SAM provides a simplified way to build serverless apps based on CloudFormation, AWS’s main tool for infrastructure as code. Kubeless Unlike the previous tools that focus on cloud providers, Kubeless is a serverless framework for Kubernetes. It allows creating and managing serverless functions directly inside your Kubernetes cluster. It works with standard Kubernetes objects like Deployments, Services, Ingress, etc. It provides scaling and fault tolerance for functions, has a CLI, and integrates with the Kubernetes ecosystem. OpenFaaS An open-source serverless framework. It allows creating functions in many programming languages, including Python, Node.js, Go, Ruby, Java, and others. It supports scaling and ensures fault tolerance. OpenFaaS integrates with Kubernetes and Docker Swarm. Areas of Application Today, Serverless applications cover a wide range of tasks, from notification and mailing services to analytics platforms, data stream processing, webhooks, game servers, file and multimedia processing, IoT applications, adapters for external services, monitoring and logging systems, business process automation, content rendering servers, customer support chatbots, and testing or deployment servers. Many examples exist within the Serverless Framework ecosystem. Major IT companies are migrating some processes to Serverless. For example: Netflix uses FaaS for encoding and transcoding video when preparing video streams for different devices. Airbnb uses Serverless in its StreamAlert system for real-time data analysis. Using Serverless is not only a way to reduce infrastructure costs, but also a tool for increasing development efficiency and flexibility. Serverless allows for rapid development and deployment of new functions and applications, as well as scaling them based on business needs. Additionally, Serverless technologies support creating more reliable and fault-tolerant applications because cloud providers ensure high availability and automatic scaling. This helps companies avoid downtime or service failures that could harm their reputation and customer experience. Development of Serverless Serverless architecture represents a significant step in the evolution of cloud computing, allowing companies to focus on application development without worrying about managing infrastructure. This approach brings flexibility, scalability, and efficiency to development processes while reducing maintenance and operational costs. In the future, we can expect development in several areas: Greater integration and compatibility between cloud providers, allowing users to choose the best solution without vendor lock-in. New services and tools tailored for Serverless architectures, such as advanced tools for monitoring, performance optimization, security, and expanded development and deployment capabilities. Growing adoption among companies, increasing the market’s growth and expanding opportunities for innovations and new business models. Serverless technologies are poised to continue reshaping the landscape of cloud computing, enabling companies to focus on building applications rather than managing infrastructure. With more integrations, new tools, and broader adoption, Serverless will increasingly become a key element in the modern developer’s toolkit.
20 November 2025 · 9 min to read
Infrastructure

How to Choose a Cloud Provider: Checklist

A cloud hosting provider is a company that offers users virtual resources for remote infrastructure management and application deployment. Unlike traditional web hosting, cloud-based service providers allow for flexible configuration of rented resources, helping clients save on hardware, software, and system administration costs. In this article, we’ll review the key factors to consider when choosing a cloud hosting provider, starting with the core services these companies offer. Provided Services There are three main service models that cloud hosting companies typically offer. Ideally, a reliable provider should support all three: IaaS (Infrastructure as a Service): Basic infrastructure resources such as virtual servers, networks, and storage. PaaS (Platform as a Service): Software platforms for various tasks: database management, big data analytics, containerized app development, machine learning systems, and more. SaaS (Software as a Service): Fully managed software solutions that run on the provider’s infrastructure, reducing the load on the client’s computer or mobile device. Key features offered by best cloud providers include: A firewall to protect against DDoS attacks and malware. Automated backups with redundant data storage across multiple locations for disaster recovery. Data encryption to ensure confidentiality; even provider staff cannot access your information. Pricing When evaluating pricing, focus not just on the base rate but on what’s included in the package. Some providers attract customers with low prices, but cheaper plans often come with limited resources or features. For instance: Low-cost plans may not suit clients who handle large data volumes due to disk space limits or slow storage performance. Some providers may offer a “cheap” cloud server but fail to mention that your virtual resources are shared with other clients, reducing performance. Keep in mind: a high-performance server cannot be truly cheap. Company Experience As a rule, the longer a provider has been in the cloud hosting  business, the more reliable it tends to be. However, reputation also matters: look for verified online reviews rather than marketing claims. If a provider has been operating for over 5 years and maintains a solid reputation, it’s usually a trustworthy choice. A broad range of services is also a good indicator of expertise. Certification and Standards A strong advantage is certification under ISO 27001, the international standard for information security management. While not legally required, it shows that the company has a well-structured approach to security: defined access levels, regular internal and external audits, and continuous process improvement. Free Trial Period A trial period can significantly influence a provider’s credibility. If a provider offers 5–10 days (not just a day or two) for testing, it’s a positive sign that they’re confident in the quality of their services. Hardware Pay attention to the performance of CPUs and disk subsystems. Ideally, a provider should offer configurations for different needs, from entry-level setups to high-performance solutions using modern server-grade processors and NVMe drives, which significantly outperform traditional SSDs in speed and reliability. Reliability and SLA A reliable provider must guarantee service uptime in its Service Level Agreement (SLA), typically expressed as a minimum annual availability percentage. The SLA should also guarantee that you receive the computing power and software specified in your plan and that you can modify configurations, add or remove resources, and perform other key management tasks. Data Center Location Providers often advertise the geographic location of their servers as an advantage, but the data center’s certification level is far more important. Look for certification under Tier III, which represents the optimal reliability level (Tier I being the lowest and Tier IV the highest and most expensive). Tier III data centers can perform maintenance without downtime thanks to redundant infrastructure components. Technical Support The quality of technical support is a key differentiator. Pay attention to: Response time. It should be clearly stated in your contract. Willingness to help with tasks like auditing or migrating infrastructure from other services. Professionalism and courtesy—hallmarks of a customer-oriented provider. Contract Termination Even with the best cloud hosting provider, circumstances may change. Before signing up, check: How and when you can retrieve your data. How the provider destroys virtual machines and ensures complete data deletion upon termination. Checklist: Choosing a Cloud Hosting Provider Before making your decision, verify that your provider offers: Support for IaaS, PaaS, and SaaS models with additional features. Flexible, well-priced service packages. 5+ years of experience in the market. (Optional) ISO 27001 certification. A 5–10 day trial period for testing. Multiple hardware configurations with scalable performance. SLA-backed uptime guarantees and resource reliability. A Tier III–certified data center. Qualified, responsive technical support. A secure and transparent contract termination process.
19 November 2025 · 5 min to read

Do you have questions,
comments, or concerns?

Our professionals are available to assist you at any moment,
whether you need help or are just unsure of where to start.
Email us
Hostman's Support