Three of the most common cloud service execution models are Infrastructure-as-a-Service (IaaS), Containers-as-a-Service (CaaS) and Platform-as-a-Service (PaaS). These execution models differ in terms of which elements of the technology stack are managed by the service provider and which remain under the purview of the customer. In the IaaS model, the vendor provides hardware and virtualization services. In the CaaS model, the vendor provides hardware, virtualization services, an operating system, and a container system. In the PaaS model, vendors supply hardware, virtualization, O/S, containers and runtime, leaving the customer responsible for just the application.
Serverless computing is an execution model for cloud computing services that is very similar to the PaaS model. As all applications require computer hardware to run, there is no such thing as a truly "serverless" application. The defining feature of serverless computing as a cloud service execution model is that the servers are not accessible to the developers running the code. Instead, a third-party cloud service provider hosts and manages the infrastructure that runs the code, controlling aspects like hardware provisioning, load balancing, scaling, and security.
In a serverless application, all the business logic is implemented as functions and events. Developers of serverless applications must architecture their applications as a series of independent code scripts known as "functions". Each of the functions that comprise the application runs on a server and is triggered by a specified event. Once a developer uploads the function code and attaches an event source to it, the cloud service provider handles all of the back-end requirements of securing and delivering the function.
For organizations developing software for the cloud, there was a time when purchasing and maintaining your own physical servers was the only option. Development teams that build their own physical infrastructure for hosting an application take on a series of cumbersome responsibilities. They must pay to maintain the server even when it is not fulfilling any requests, manage its availability and maintenance status, and secure it by regularly applying patches and updates. If the organization wants to scale up its operations, that means more servers and more administrative overhead.
For software developers who drive value creation by building and administering an application, building and maintaining application infrastructure and support services is a distraction that can hurt productivity and negatively impact service levels and time-to-market.
With serverless computing, software development teams can outsource all of their application infrastructure and support requirements to a third-party cloud service provider. This helps developers eliminate the administrative overhead associated with managing a physical IT infrastructure and enables increased productivity while driving down costs and reducing time-to-market.
Serverless architecture makes it possible for software developers to fully outsource application infrastructure and support services to a cloud service provider. Serverless computing capabilities provide a range of benefits for the developers that leverage them.
Serverless Architecture is Cost Efficient
One of the major problems associated with establishing physical IT infrastructure is the cost. Renting or purchasing a fixed quantity of servers to support an application can be expensive, and servers may be underutilized or experience idle time that makes it difficult to realize their value. The pay-as-you-go service model that characterizes cloud services helps make serverless cost-efficient, as customers only pay for the exact amount of service they use.
Serverless Architecture Promotes Efficient Scaling
One of the key benefits of serverless architecture is that your application will automatically scale as the load increases. Whether you have one hundred visitors per day or one hundred thousand, you'll always have precisely the amount of resources that you need to serve your customers - and that's all that you'll pay for. With most services, you'll be charged based on the total computing resources consumed by the code at run time. This makes the cost of serverless computing highly predictable relative to your total usage.
Serverless Architecture Reduces Administrative Overhead
Maintaining a physical application infrastructure requires a lot of manual administrative tasks. With serverless computing, these requirements are outsourced to a third-party. As a result, your development team can focus on building and maintaining their application and there's no need to develop IT infrastructure management capabilities in-house. Low management overhead is consistent with agile principles that promote shorter development cycles and faster time-to-market.
Serverless Architecture Increases Availability and Fault Tolerance
Serverless computing provides have access to an extensive IT infrastructure with mechanisms for guaranteeing service availability and sophisticated fault tolerance configurations. Cloud service providers can easily supply a back-up server with their existing infrastructure and capabilities, whereas developing those same capabilities in-house would be extremely costly for your organization.
Despite the time and cost-saving benefits of serverless architecture, there are certain drawbacks that software developers should be aware of before outsourcing their entire application infrastructure to a cloud service provider.
The unique architecture of serverless applications makes it difficult to test them outside of the serverless environment. This can lead to situations where the running basic unit or functional tests can cost money, especially as your battery of test cases increases in size.
The prospect of vendor lock-in is a risk that many IT organizations would prefer to avoid. If you partner with a specific cloud service provider and develop your entire application for compatibility with their serverless architecture, you may face compatibility and functionality issues if you want to switch vendors.
If your application depends on low latency, cold starts might be an issue for you. A cold start is a time lag that occurs when a serverless function is called for the first time. The time lag happens because it takes some time for the server to partition some computing power for the function or to assign a container. Containers are destroyed a short time after executing their function, so cold starts may happen on a regular basis for some functions.
Sumo Logic makes it easy to monitor serverless application deployments. We have purpose-built applications to help you collect continuous intelligence from the most widely used serverless computing providers - Amazon Web Services (AWS) Lambda and Google Cloud Functions.
These Sumo Logic applications let you monitor the performance of your serverless functions in real-time, track and analyze key security and performance metrics and proactively resolve latency and compliance issues to drive customer satisfaction.
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