Published at 24.01.2024
Cloud services are various resources and services provided over the internet by third-party providers. These services can encompass a wide range of functionalities, from basic storage and computing power to natural language processing and artificial intelligence. The key characteristic of cloud services is that they are delivered through the internet, and users can access them without having to manage physical servers or run software applications on their own computers.
When defining the cloud computing service models: IaaS, PaaS, SaaS, and Serverless Computing, a reasonable order can be derived from the level of abstraction each service provides, starting from the most infrastructure-focused to the most abstracted. This order not only follows a logical progression in the layers of cloud computing but also helps in understanding the evolution of these services:
Infrastructure as a Service (IaaS): This is the most foundational cloud service, providing virtualized computing resources over the internet. IaaS offers the basic building blocks for more complex cloud services and gives users the most control over the underlying infrastructure, such as servers, networks, and storage systems. Examples include AWS (Amazon Web Services), Microsoft Azure, and Google Cloud Platform.
Platform as a Service (PaaS): One level above IaaS lies PaaS. This cloud service provides a platform allowing customers to develop, run, and manage applications without the complexity of building and maintaining the infrastructure typically associated with developing and deploying applications. It includes tools and services to support the development process, like software development kits (SDKs), application programming interfaces (APIs), and code libraries. Examples are a9s PaaS, Google App Engine, and Heroku.
Software as a Service (SaaS): SaaS represents a further abstraction and is the most user-centric model. It delivers software applications over the internet, on a subscription basis, with the cloud provider managing the infrastructure and platforms that run the applications. Users simply access the software through a web browser without worrying about installation, maintenance, or infrastructure. Common examples include Microsoft Office 365, Salesforce, and Google Workspace.
Serverless Computing (Function as a Service - FaaS): Finally there is Serverless Computing, which abstracts the cloud services to the highest level. In serverless architectures, developers write and deploy code, and the cloud provider manages the execution of the code. It's called "serverless" because the servers are invisible to the developers, even though they exist. This model allows for building and running applications and services without thinking about servers. It automatically manages the allocation of machine resources, scaling up and down in response to the number of requests.
Each of these cloud service models builds upon and abstracts away from the complexity of the previous one. Each step up in abstraction provides greater ease and efficiency at the cost of control and customization, which is a key theme in understanding cloud services. Provided with this base information, let’s take a deeper dive into the particular cloud services at hand.
Infrastructure as a Service (IaaS) is a form of cloud computing that provides virtualized computing resources over the internet. In the IaaS model, a cloud provider hosts and manages the infrastructure, including servers, storage, and networking resources. Customers use this infrastructure to build and run their applications and services.
Compute Resources: This encompasses central processing units (CPUs), graphical processing units (GPUs), and internal memory (RAM), which are essential for performing tasks. Customers request these resources in the form of virtual machines or cloud instances.
Storage Resources: IaaS provides different types of data storage resources, such as block storage (like SSDs or hard drives), file storage (similar to Network Attached Storage), and object storage (storing data as objects).
Networking Resources: This includes resources like routers, switches, and load balancers, which are virtualized in the IaaS model. IaaS providers often offer additional services to support infrastructure management, such as system logs monitoring, implementation of security measures, and automated infrastructure tasks like backup and load balancing.
Initially, IaaS was pioneered by AWS, with other major players like Microsoft Azure, Google Cloud, and IBM quickly following suit. These services now offer a broad range of cloud solutions, including serverless functions, database access, big data compute environments, and more.
Platform as a Service (PaaS) is a cloud computing model that provides a platform allowing customers to develop, run, and manage applications without the complexity of building and maintaining the infrastructure typically associated with developing and launching an app. PaaS includes computing, memory, storage, database, and other app development services, and it often offers a suite of tools for application lifecycle management, from development to testing, managing, deploying, and updating applications.
As a responsible business partner we at anynines want to provide a broad and encompassing viewpoint, which includes things to keep in mind, when considering Platform as a Service (PaaS):
The use of cloud provider PaaS tools often raises the cost of running applications in the cloud. This is because each tool typically has an associated price, and costs can increase with usage, leading to potential unexpected cost overruns for enterprises.
To face this problem, anynines offers a flexible credit system which allows users to utilize a single license and included license credits to access a variety of data services known as the a9s Data Service Bundle. Users can mix and match these services across different projects, providing significant flexibility and convenience. This way users only obtain exactly what they need without additional costs and can at any time adjust their spending according to their requirements.
PaaS can lead to dependency on a specific provider's platform and tools, limiting flexibility and potentially making it difficult to switch providers or integrate with systems from other vendors. This loss of portability is a major concern for businesses wary of being too reliant on a single cloud provider.
To solve the risk of vendor lock-in for our customers, anynines offers a platform that is compatible with various infrastructures including cloud, on-premise, and hybrid models. The a9s Platform is a multi-cloud out-of-the-box solution, which utilizes the power of open source and is designed to be easily adaptable, allowing customers to use best practices or mix and match components to build a platform that meets their specific needs. Furthermore, as a member of Cloud Foundry Foundation and the Cloud Native Computing Foundation, anynines is involved in these communities’ standardization efforts.
While PaaS solutions often come with built-in security controls, there's an inherent risk in storing data and applications on a provider's servers. Businesses must trust the provider to secure their environment effectively. This situation can pose a security risk if the provider's security measures are not up to the company's standards or specific compliance requirements.
To maximize security, our a9s Data Service Bundle includes features like comprehensive logging and monitoring, robust security, and a dependable backup and restore strategy. We offer lifecycle management, operations support for Cloud Foundry and Kubernetes, as well as high availability, performance and availability monitoring, security audits compliant with organizational security policies, and the creation and maintenance of runbooks.
Apart from a9s Platform, some popular examples of PaaS offerings also include Microsoft Azure App Services, Elastic Beanstalk from AWS, Google App Engine, Red Hat OpenShift, and IBM Cloud.
Software as a Service (SaaS) is a cloud-based method of providing software to users. In this model, applications are hosted on the cloud, and users can access them over the Internet, typically via a web browser. This approach differs from traditional software installations where the software is bought once and installed on a user's device.
SaaS applications run on cloud servers, which might be located far from the user's location. Some common examples of SaaS applications include Gmail, Office 365, and Salesforce. These applications are accessible through a browser or an app, making them highly convenient and flexible.
Accessibility: Users can access SaaS applications from any device and any location, providing a great deal of flexibility.
Reduced Costs and Flexible Payments: SaaS products are usually available on a subscription basis, making them more affordable. This model eliminates the need for substantial upfront costs associated with traditional software purchases and maintenance.
Scalability: SaaS solutions can be scaled up or down based on the user's needs and company size.
Automatic Updates: SaaS applications are updated by the provider, ensuring users always have access to the latest features and security updates without needing to manually install them.
Customization: SaaS applications can often be customized to meet the specific needs of a business, and many offer integrations with other tools and services.
Issues Beyond Control: If the SaaS provider experiences service disruptions, users might be unable to access the platform during that time.
Security Concerns: While SaaS providers generally offer robust security, the nature of cloud computing means that data breaches are a potential risk.
Lack of Control Over Versioning: Users have little control over software updates and version changes, which can occasionally lead to disruption or the need for additional training.
Overall, the SaaS model is favored for its flexibility, cost-effectiveness, and ease of use, particularly for businesses that want to avoid the complexities and expenses of installing, maintaining, and updating on-premises software applications.
Serverless computing is a cloud computing model that enables developers to build and deploy applications without having to manage the underlying infrastructure. In this model, the cloud provider dynamically allocates machine resources as needed, taking care of servers on behalf of the customers. Despite the name "serverless," physical servers are still used but they are abstracted away from the developers, allowing them to focus on the code and business logic.
Backend Services on Demand: Serverless computing provides backend services as needed. It allows users to deploy code without managing the underlying infrastructure, making the development process more efficient and cost-effective.
Cost-Effective: With serverless computing, companies only pay for the computation they use. There is no need to reserve and pay for a fixed amount of bandwidth or number of servers. This auto-scaling feature ensures that resources are not wasted on unused server space or idle CPU time.
Simplified Scalability: Developers using serverless architecture do not need to implement policies to scale up their code; the serverless vendor handles all scaling requirements as demand changes.
Event-Driven Architecture: Serverless computing often uses an event-driven architecture. Functions are triggered by specific events, making it suitable for a range of applications, such as stateless application development, batch processing, real-time data analytics, and business process automation.
Backend and Frontend Division: In application development, the frontend is what users see and interact with, while the backend includes the server where the application's files and data are stored. Serverless computing primarily concerns the backend part of the application.
Reduced Operational Costs and Overhead: Serverless computing eliminates the need for server management and maintenance, reducing the overhead and costs associated with these tasks. This can be particularly beneficial for smaller businesses or startups that may not have the resources for extensive IT infrastructure.
Enhanced Developer Productivity: Developers can focus more on writing application code and less on managing and operating servers or runtimes. This can lead to faster deployment of features and applications, as well as quicker response to market changes.
Reduced Latency: Serverless functions can be deployed in multiple geographic regions, closer to the end users, reducing latency. Requests from users are routed to the nearest instance of the function, improving the performance of the application.
When it comes to the disadvantages of serverless computing, the following are a few points to consider:
Debugging and Monitoring Challenges: Debugging serverless applications can be more complex compared to traditional architectures. The ephemeral nature of serverless functions, which spin up and down in response to events, makes it difficult to track and replicate issues for debugging purposes.
Performance Issues: Serverless architecture can experience issues with latency, particularly during periods of cold starts — when the function is invoked after being idle. This startup time can impact the performance and responsiveness of applications.
Limitations in Functionality: Serverless computing may not be suitable for long-running processes, as it is primarily designed for short-lived, event-driven functions. This can limit its use in certain types of applications.
Complexity in Large-Scale Applications: Managing a serverless architecture can become complex and challenging as the application scales. The architecture's distributed nature can make it hard to track and manage multiple interdependent serverless functions.
All four mentioned cloud services can be deployed in private, public, and hybrid cloud environments. Each cloud model offers different advantages and is suitable for various use cases, depending on the organization's needs.
Public Cloud: In a public cloud, the cloud services are delivered over the internet and are shared across different organizations. This model is known for its high elasticity, scalability, and a low-cost subscription-based pricing model. It is suitable for predictable computing needs, such as IT and business operations, as well as software development and testing environments. Public clouds are often used for IaaS, PaaS, and SaaS due to their affordability and ease of scalability.
Private Cloud: A private cloud is dedicated solely to one organization, providing enhanced security and control. The infrastructure may be located on-premise or operated by a third-party vendor off-site. Private clouds are customizable to meet unique business and security needs and are typically used by organizations with strict compliance requirements. Private clouds can support IaaS, PaaS, and SaaS, offering greater control over the environment.
Hybrid Cloud: A hybrid cloud combines elements of both public and private cloud, allowing data and applications to move between the two environments. This model offers greater flexibility, deployment options, and the ability to scale up to the public cloud when needed. Hybrid clouds are beneficial for businesses that require a mix of high-level security and flexible performance. They are suitable for IaaS, PaaS, SaaS, and serverless computing, providing a balance of cost-effectiveness, control, and scalability.
The a9s Platform is a framework for building contemporary application development platforms with high operational efficiency. Alongside the a9s Platform, we also offer a robust set of data services for automation across the board, we refer to this as our a9s Data Service Bundle. The a9s Data Service Bundle consists of data services available for both Cloud Foundry and Kubernetes on-premise, public, or multi-cloud settings. Learn more about how our comprehensive platform can help your organization here, or trial our a9s PaaS environment with integrated a9s Data Services here.