Serverless computing is a cloud-computing execution model in which the cloud provider runs the server, and dynamically manages the allocation of machine resources. Serverless computing is a way to run applications or services without thinking about servers. And it’s not only for 12-factor apps or microservices anymore. You can now use serverless platforms to build full-stack applications, including traditional monolithic application architectures. In this post, we’ll give you an overview of what serverless computing is, its benefits and drawbacks, and some of the most popular serverless platforms available today.

Serverless Computing is a new computing model that enables building applications without having to worry about the underlying infrastructure. It allows developers to focus on application logic and not be concerned about the underlying cloud platform.

Serverless computing reduces costs associated with infrastructure management due to the lack of need for installation, setup, configuration, and maintenance. This allows organizations to reduce the Total Cost of Ownership and reallocate resources to accelerate innovation. Payment is based on throughput, meaning organizations will only pay for the features they use, and scalability is automatic, so they don’t have to worry about provisioning the underlying infrastructure. Additionally, since developers are using someone else’s computer to execute their serverless functions, there is no need to maintain infrastructure, further reducing costs.

Serverless computing helps with application deployment and scaling by providing a faster and simpler deployment process, as well as automatic scalability. This makes it easier for developers to release their applications without worrying about provisioning the underlying infrastructure or managing the servers or software. Additionally, it eliminates the need to manually configure autoscaling policies or manage infrastructure resources, while providing full scalability and fault tolerance. This allows applications to be deployed quickly and scale to meet demand in the event of sudden surges in traffic.

Easier application development comes with serverless computing due to its many benefits and advantages. Serverless computing allows developers to focus on building their applications and improving their products, without having to worry about the operational and administrative tasks associated with deploying and maintaining servers. This is achieved by using fully managed services, which provide automated scalability and high availability for the application. Furthermore, serverless computing provides cost-effectiveness, functions as a service, and simplifies auditing and reporting. By using serverless services, developers are able to quickly create applications using familiar approaches, while avoiding the challenges associated with monolithic systems. This enables teams to deliver more functionality in less time, increasing their agility and productivity.

Serverless computing improves scalability and availability by automatically scaling up or down to match the demands of any workload. This helps organizations reduce TCO and reallocate resources to accelerate the pace of innovation. Furthermore, it eliminates the need for administrative tasks, enabling developers to focus on core business logic. Companies such as Bustle have leveraged serverless computing to serve upwards of a billion requests to over 80 million people per month, resulting in high-performance, high-availability online services.

Serverless computing increases flexibility by allowing developers to focus solely on developing their products without having to worry about deploying and managing servers. This means that the development team can become more agile, delivering more features in a shorter amount of time. Additionally, serverless computing eliminates the need for a team of infrastructure and support engineers, allowing for smaller teams of developers to run code themselves. It also provides cost benefits, such as no need for licenses, installation, dependencies, and personnel costs for maintenance, support, or patching. Lastly, cloud providers are responsible for scaling the capacity to the demand, eliminating the need for developers and operators to create and tune autoscaling policies or systems. These benefits, combined with the ability to easily scale up and down with sudden changes in traffic on spiky workloads, make serverless computing a more agile and cost-effective solution for businesses when compared to renting or purchasing a fixed quantity of servers.

Serverless computing reduces complexity by eliminating the need for infrastructure setup, configuration, provisioning, and management. By taking a low-code/no-code approach to simplify the orchestration of combined tasks, developers can integrate different services (either cloud or on-premises) without coding those interactions, having to maintain glue code, or learning new APIs or specifications. Additionally, serverless computing allows for easier deployments and maintenance, cost-effectiveness, automated scalability, and function as a service, thereby helping organizations reduce TCO and reallocate resources to accelerate the pace of innovation.

Serverless computing increases security and privacy by providing an additional layer of protection around modern cloud-based applications. This layer helps to manage roles, users, and policies, allowing the root user to create, disable, or delete access keys and change the root password. Moreover, it gives companies full control over privacy mechanisms, just as with hosting in traditional server setups. Furthermore, serverless computing helps to reduce IT costs and increase productivity, as developers are able to focus their efforts on developing applications instead of managing and deploying servers. Additionally, serverless applications utilize a token service that generates temporary credentials for users, which can be used to invoke the function. Lastly, serverless security requires obtaining security intelligence from millions of events that are logged every day, which helps to increase transparency and monitoring.

Serverless computing helps improve resource utilization by enabling organizations to pay only for the resources they need and use, rather than for those that are left idle. This pay-as-you-go model means that teams can get exactly the right amount of compute they use and don’t pay for resources that are sitting idle. Furthermore, because serverless solutions scale up automatically and allocate resources based on the concurrent user volume and real-time data streams, they can efficiently accommodate sudden spikes in traffic. This allows companies to provide an optimal user experience without worrying about their systems crashing due to resource constraints.

Serverless computing increases efficiency and performance by eliminating the need for businesses to manage and maintain their own servers. By taking away the overhead of running and maintaining a server, organizations can save costs and reallocate resources to focus on innovation. Furthermore, serverless computing offers automated scalability and reduced operational costs, making it easier to deploy applications and build functionality faster. As a result, businesses can enjoy improved user experience, enhanced security profiles, simplified auditing and reporting, easier access, and increased productivity.

Serverless computing increases agility by allowing developers to focus their efforts on developing and not on deploying and managing servers. This results in increased agility of development teams to deliver more functionality in less time, as the operations dependencies are reduced on each development cycle. This also results in the ability to run or build any modern application, as well as the ability to automatically scale up and down with sudden changes in traffic on spiky workloads, with developers bringing their own containers to fully managed, Kubernetes-orchestrated clusters. Overall, this helps to reduce TCO and reallocate resources to accelerate the pace of innovation.

Serverless computing is a cloud architecture in which a cloud provider dynamically allocates resources to an application or program in order to execute a piece of code. The customer is only charged for the resources used and not a flat monthly fee. This makes it cost-effective and efficient for customers.

The vendor handles all the tasks related to the underlying infrastructure, such as provisioning, virtual machine and container management, and multithreading. It also handles regular tasks like system monitoring and capacity planning.

Customers upload code to the cloud service, triggering the serverless computing architecture to execute the code only when a request is made, making it event-driven. Customers are charged only for the time the code runs.

Serverless functions can be connected to create a processing pipeline, or they can be used as components of a larger application and interact with other code running in containers or on conventional servers. This makes it easy for developers to build and run applications and servers without having to manage the back-end infrastructure.

Function as a Service (FaaS) is a type of cloud-computing service that enables developers to write code as discrete functions that are executed in response to certain events, such as an image upload or HTTP request. The cloud provider will either execute the function on a running server, or create a new server to do so. This type of serverless architecture eliminates the need for end users to manually manage the infrastructure and can provide users with key capabilities such as running code without explicitly provisioning or managing infrastructure, scaling the runtime environment automatically, and offering additional capabilities for testing, development, and service assurance. It is an efficient way of paying for compute resources because users only need to pay for the times that their functions get called, rather than paying to have their applications always on and waiting for requests. Due to its convenience and efficiency, FaaS is becoming increasingly popular among serverless platforms.

Platform as a Service (PaaS) is a cloud computing model that provides users with a platform to develop, run, and manage their applications without having to manage the underlying infrastructure. It is popular for serverless applications as it eliminates the need for developers to manage server hardware and software, as well as software updates and storage. In addition, PaaS applications provide a scalable platform that can be deployed quickly and with minimal startup delays. By using PaaS, developers can focus on creating and running applications without having to worry about the underlying infrastructure. Furthermore, PaaS offers cost-effective solutions and allows users to pay only for the resources they use. Ultimately, the PaaS model is popular for serverless applications as it allows for a faster development process and more efficient utilization of resources.

Software as a Service (SaaS) is a type of cloud computing model in which cloud providers offer different types of software as services to users. It is one of the three main categories of cloud computing, the other two being Infrastructure as a Service (IaaS) and Platform as a Service (PaaS). In SaaS, the user does not have to worry about the development, deployment, and management of the services, as all of this is handled by the cloud provider. Examples of SaaS services include Gmail, Google Docs, and Google Forms.

Serverless architectures, on the other hand, add an additional abstraction layer to existing cloud computing paradigms, abstracting away server-side management from the developers. In serverless model, developers deploy their applications to the serverless cloud as functions. The cloud provider then takes responsibility for managing, scaling, and providing different resources to ensure the smooth running of these functions. In comparison to SaaS, serverless architectures are more event-driven and provide additional services such as storage, messaging, user management, etc.

Examples of cloud services as a serverless architecture include Amazon Lambda, Google Cloud Platform, and Microsoft Azure. Amazon Lambda is a platform for running serverless applications and functions. It is an event-driven platform that allows developers to deploy and execute applications and functions without needing to manage server-side resources. Google Cloud Platform is another cloud-based service that provides serverless services such as storage, networking, and cloud computing. It also offers a wide range of services for developers, such as machine learning and analytics tools. Microsoft Azure is a cloud computing platform that offers serverless services such as storage, networking, and computing resources. It provides a platform for running applications and functions with serverless architectures.

A Software-Defined Services (SDS) architecture is a way of improving the flexibility and scalability of cloud services by virtualizing the underlying infrastructure. It allows the cloud provider to manage the underlying infrastructure more efficiently and provides the customer with self-service access to resources. SDS is a type of Infrastructure as a Service (IaaS) model that enables customers to provision and configure resources on demand.

In contrast to serverless computing, SDS doesn’t eliminate the need for a server. Instead, it allows the customer to define and manage their own server infrastructure. With SDS, the customer is still responsible for managing the server, including for patching and updating. Serverless computing, on the other hand, does away with the customer’s need to manage servers, leaving all of that responsibility in the hands of the cloud provider. With serverless, the customer just pays for the resources they use, such as computing and storage, as they’re needed. This makes it more cost-effective than traditional server-based models.

The role of cloud-based application development in serverless architectures is to provide developers with a pay-as-you-go solution that can reduce their operations dependencies on each development cycle, increase their agility to deliver more functionality in less time, and enable them to focus on building the application rather than dealing with server maintenance. Serverless architectures enable developers to write a function in their chosen programming language and post it to a serverless platform, which then manages the infrastructure and the software, and maps the function to an API endpoint, automatically scaling function instances as needed. By utilizing cloud-based application development, organizations can save on resources, increase scalability, reduce latency, and improve the overall performance of their applications.

Cloud-based application management is a form of computing that allows organizations to outsource the management of their applications to a cloud provider. This essentially removes the responsibility of managing physical hardware, virtual machines, and web server software, allowing developers to focus on writing and maintaining their code. Serverless architectures take this one step further by allowing developers to deploy their code and have it run with high availability, removing any need to worry about resources or scaling. This allows developers to focus even more on the business logic rather than worrying about administrative tasks. Cloud-based application management provides organizations with cost savings, scalability, and increased agility, as well as the ability to easily scale or adjust resources as needed.

In a microservices architecture, the software is composed of multiple small and independent services that perform specific tasks and communicate through APIs. The overall application results from the combined output of these services. This architecture enables easier scaling and greater resilience to failure by breaking down the application into smaller, specialized services.

In contrast, serverless architectures adopt the principles of microservices but are hosted on a vendor’s cloud platform and do not require infrastructure management. These services are highly scalable and cost-effective, as one pays only for what one uses. Additionally, serverless functions allow developers to quickly add interactive elements to applications, without needing to configure an external server. Serverless technology is powered by containers and is perceived as a way to reap the benefits of containerized microservices without grappling with their complexity.

Serverless computing is a cloud architecture where a cloud provider dynamically allocates compute and storage resources for code execution and charges only for resources used. It eliminates the need for developers to set up and maintain infrastructure, enabling them to focus solely on coding. This approach is often mistaken for back-end-as-a-service, but the two are distinct. In back-end-as-a-service, the back-end server remains hosted in the cloud but still requires server management. In contrast, serverless computing fully removes server provisioning and maintenance, freeing developers to write and deploy code without server-related worries.

The benefits of using Serverless Computing are numerous, including lower costs, simplified scalability, simplified backend code, improved time to production, increased productivity, improved security, ease of management, automation, outsourcing and improved developer productivity. Serverless Computing also allows for pay for execution only and the ability to develop in any language. All of these benefits make Serverless Computing an attractive option for individual developers and enterprise development teams alike.

The main components of a Serverless Computing environment are serverless stacks, serverless frameworks, serverless databases, containers, serverless offline testing, hosted services for back-end and front-end hosting, automated and elastic infrastructure, and cloud service providers offering serverless services. Serverless stacks consist of programming language, application framework and triggers used to initiate code execution. Serverless frameworks include cross-platform models and open-source frameworks, such as Serverless Application Model (SAM) by Amazon Web Services (AWS), Apex and Serverless. Serverless databases interact with developers’ functions, taking away the complexity of backups, maintenance, replication, and scaling. Containers managed by vendors, such as orchestration platform Kubernetes, are responsible for powering serverless technology and enabling developers to reap the benefits of containerized microservices. Serverless offline testing allows developers to locally test their code on their own local hardware. Hosted services facilitate scalability, security, and compliance requirements. Finally, cloud service providers offer serverless services, enabling organizations to benefit from the advancements in cloud computing technologies.

Serverless computing differs from traditional cloud computing in several ways. Unlike the traditional cloud’s monolithic system that holds all business logic, serverless is broken into smaller, event-driven, and stateless triggers and actions leading to more efficient programming and reducing single points of failure. While traditional computing requires infrastructure configuration and management, serverless automates and elasticizes this, resulting in cost and operational efficiency. Serverless eliminates the need for system administrators, allowing developers to focus solely on code and app design. Finally, serverless offer higher security due to their distributed request-level authorization mechanism, compared to traditional computing which can be vulnerable to attacks with direct access to backend resources.

Serverless Computing is ideal for applications that demand scalability and efficiency, such as those relying on user interactions, trigger-based tasks, asynchronous processing, security checks, RESTful APIs, and CI/CD. It’s best suited for event-triggered computing, IoT data processing, serverless-first app building, mobile and PC uploads, and dynamic data updates.

The cost-effectiveness of serverless computing is one of its major advantages. Instead of paying for idle virtual machines, users and developers only pay for the time when code is running on the serverless compute platform. This can be described as “pay-as-you-go computing” or “bare-code” computing, as users only pay for the time and memory allocated to run their code. This can result in more cost savings than renting or purchasing a fixed quantity of servers, or even provisioning an autoscaling group.

Serverless computing can be more cost-efficient than traditional server options because it eliminates the costs associated with licenses, installation, dependencies, and personnel cost for maintenance, support, or patching. It also eliminates the need for purchasing or renting extra hardware or cloud instances that are mostly underutilized.

When comparing costs between serverless computing and traditional server options, it is important to consider the different costs associated with each. Traditional server costs include hardware and software upfront, such as licensing fees, server hardware, and setup costs. Additionally, traditional servers require ongoing costs for maintenance and support, as well as personnel costs for patching.

On the other hand, serverless computing costs are mainly related to the time and memory allocated to run the code. As the code is running on a serverless platform, users do not need to pay for idle virtual machines. Additionally, serverless computing eliminates the costs associated with licenses, installation, dependencies, and personnel cost for maintenance, support, or patching.

Overall, serverless computing can be more cost-effective than traditional server options, especially when compared over the long-term. By eliminating the need to pay for idle virtual machines, serverless computing can result in significant cost savings. Additionally, serverless computing eliminates the need to purchase or rent extra hardware or cloud instances, resulting in further cost savings.

Serverless Computing is a cloud computing model that provides organizations with on-demand access to the resources they need. It eliminates the need to develop and deploy the underlying infrastructure to run applications and programs. In this model, the cloud provider fully manages the server’s code execution, while customers only pay for the resources they use.

To use Serverless Computing, customers first purchase back-end services from a cloud vendor on a pay-as-you-go basis. The cloud vendor then takes care of all routine infrastructure management and maintenance, such as updating the OS, applying patches, managing security, system monitoring and planning capacity.

Developers can begin coding the application or program after purchasing the necessary services. They upload the code to the cloud provider that executes it. The code operates in an event-driven manner, triggering only upon receiving a request. The customer pays for the compute time used during the code’s execution.

Serverless computing simplifies the process for software developers to create code for cloud platforms and perform specific roles. It enables developers to avoid the hassle of handling servers, as the cloud provider fully manages the server code execution. Customers pay only for the resources they use, and resources are not assigned to an application when inactive.

Common serverless computing platforms include AWS Lambda, Google Cloud Functions, Azure Functions, IBM Cloud Functions, and Apache OpenWhisk. These platforms provide developers with cost-effective performance, supported programming languages and models, easy deployment, secure applications, and monitoring and debugging tools. Tools like Serverless and Apex empower developers to construct applications across multiple cloud providers and integrate languages unsupported by certain providers.

Security considerations of Serverless Computing include:

• 1. Authentication: Serverless applications must authenticate each request before sending a response, as there is no previous interaction history stored.
• 2. Monitoring: Serverless applications are distributed, meaning it can be difficult to monitor and gain security intelligence from the vast amount of events that are logged every day.
• 3. Token Services: Implementing a token service, where temporary credentials are generated for users, can help to secure the application.
• 4. Identity and Access Management: Integrating serverless-ready identity and access management services into the application, such as AWS Cognito, can help to authenticate user identity through SSO or social networks.
• 5. Securing the Functions: Organizations need to focus on securing the functions of applications, as they are event-driven and loosely coupled, rather than the applications themselves.
• 6. Visibility: Developers taking the lead can result in applications being pushed to production before they have been addressed by security teams, leaving them vulnerable to code-based threats.
• 7. Data Storage and Transportation: Data held in stateless and serverless functions remain cached rather than stored in memory, which runs the risk of leakage when moved to external locations.
• 8. Cloud Security: Cloud-based platforms also require additional Protection layers to be built around modern applications, as traditional security solutions are ineffective in this model.
• 9. Privacy Implications: Privacy considerations such as shared resources and access by external employees have to be taken into account when dealing with serverless technologies.

• Vendor lock-in. Switching cloud providers might be difficult since serverless services are delivered differently from one vendor to another.
• Inefficient for long-running apps. Using long-running tasks can cost more than running a workload on a VM or dedicated server.
• Latency. There’s a delay in the time it takes for a scalable serverless platform to handle a function for the first time, often known as a cold start.
• Debugging is more difficult. Because a serverless instance creates a new version of itself each time it spins up, it’s hard to amass the data needed to debug and fix a serverless function.
• Integration with in-house development and testing pipelines can be difficult.
• Limited scalability. Serverless functions are limited by their provider’s infrastructure and may not be able to scale quickly enough to meet demand.
• Sometimes, Serverless functions can be hard to test before deployment.
• Higher costs for large applications. Serverless computing may not be cost-effective when scaling up to millions of requests.

Serverless Computing is a cloud computing service that provides a variety of services, including FaaS, CaaS, and PaaS. These services are available from a variety of providers, including Amazon Web Services, Google Cloud Platform, and Microsoft Azure. Each provider offers a free trial so that you can explore the features and benefits of using Serverless Computing. Stay tuned for more information on Serverless Computing.

1. https://aws.amazon.com/serverless/
2. https://azure.microsoft.com/en-us/services/functions/
3. https://cloud.google.com/serverless/