Both serverless computing and containers are designs for reducing overhead for cloud-hosted web applications, although they vary in key aspects. Containers are lighter than virtual machines, but serverless designs are even lighter and scale better than container-based systems. How to choose is explained in this article.
Learning Objectives
After reading this article you will be able to:
- Understand what containers are
- Understand how containers differ from serverless deployments
Serverless computing vs. containers
Developers can construct apps with considerably less overhead and flexibility with serverless computing and containers than they can with traditional servers or virtual machines. The type of architecture a developer should choose depends on the application’s requirements, although serverless systems are often more scalable and cost-effective.
What are containers, exactly?
A container encapsulates a programme as well as all of the components it need to function effectively, such as system libraries, system settings, and other dependencies. Containers, like a ‘simply add water’ pancake mix, just require one thing to accomplish their function: to be hosted and executed.
A container may execute any type of programme. No matter where a containerized programme is hosted, it will execute the same manner. Containers, like real shipping containers, may be readily transported and deployed wherever required. Because they are a standard size, they can be carried anywhere by a number of modes of transportation (ships, trucks, trains, etc.) regardless of their contents.
Containers, in technical terms, are a means of dividing a computer, or a server, into distinct user space environments, each of which runs just one programme and is isolated from the other partitioned portions of the machine. Each container shares the machine’s kernel with other containers (the kernel is the operating system’s base and interacts with the computer’s hardware), but it operates as if it were the machine’s sole system.
For more information, view full details below;
- Container 101 Tutorials: Kubernetes Technology
- AWS Solution Training for Partners: Containers & Machine Learning
- Setting up Windows Container Service on a Kubernetes Cluster
- DevOps Engineer’s Guide to Kubernetes Operating Systems
- DevOps and Containers | Benefits, Metrics, Challenges & Risk Management
Containers vs. Virtual machines
A virtual machine is a piece of software that simulates the operation of a whole computer system. It is separated from the rest of the machine it is running on and acts as if it were the only operating system on the machine, complete with its own kernel. Virtual machines are another popular approach to run numerous environments on a single server, although they require far more processing power than containers.
What is serverless computing?
Serverless apps are divided into functions and hosted by a third-party vendor who only charges the app developer for the time each function runs. What is serverless computing on Wikipedia from google.com? This is a good place to start for additional information.
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What are the key differences between serverless computing and containers?
Physical machines
Although’serverless’ computing is based on servers, the serverless vendor is responsible for provisioning server space as needed by the application; no specific machines are assigned to a given function or application. On the other hand, each container stays on a single machine at a time and runs on that machine’s operating system, however they may be readily transferred to another machine if necessary.
Scalability
The number of containers deployed in a container-based architecture is specified in advance by the developer. In a serverless architecture, on the other hand, the backend automatically and intrinsically scales to meet demand.
To continue with the shipping container metaphor, a shipping company could try to predict an increase in demand for a product and ship more containers to the destination to meet that demand, but it couldn’t just snap its fingers and produce more containers full of goods if demand exceeded expectations.
A serverless architecture is one method to do this. When it comes to processing power, serverless computing is similar to a contemporary home’s water supply: customers may get and use as much water as they need at any time by turning on the tap, and they only pay for what they use. Attempting to acquire water one bucket at a time, or one shipping container at a time, is considerably less scalable.
Cost
Because containers are always operating, cloud providers must bill for server space even if no one is accessing the application at the moment.
Because application code does not execute until it is invoked, there are no ongoing costs with a serverless design. Developers are instead only paid for the server capacity that their application really consumes
Maintenance
Containers are hosted on the cloud, but they are not updated or maintained by the cloud provider. Each container that developers deploy must be managed and updated.
A serverless architecture has no backend to handle from the developer’s perspective. All administration and software upgrades for the servers that run the code are handled by the vendor.
Deployment period
Containers take longer to set up than serverless operations since system settings, libraries, and other things must be configured. Container deployment takes simply a few seconds once they’ve been configured. Serverless functions, on the other hand, are smaller than container microservices and do not come with system requirements, thus they may be deployed in milliseconds. As soon as the code is published, the serverless application may go online.
Testing
Because the backend environment is difficult to recreate on a local environment, testing serverless web apps is challenging. Containers, on the other hand, operate the same regardless of location, making it relatively easy to test a container-based application before sending it to production.
We’ve built a virtual testing environment for Cloud business Workers, which allows serverless designs, to aid in the development process.
What are the similarities and differences between serverless computing and containers?
Serverless computing, more so than containers, are both cloud-based and substantially minimise infrastructure overhead. Applications are split down and delivered as smaller components in both architectures. Each container in a container-based architecture will execute one microservice.
What are microservices?
Microservices are individual components of a larger application. Each microservice provides a single service, and the application is made up of several connected microservices. Although the name implies that microservices must be small, this is not the case.
When it comes to making changes to an application, one of the benefits of creating it as a collection of microservices is that developers may update one microservice at a time rather than the entire programme. Building an application as a set of functions, like in a serverless architecture, provides the same advantage but at a finer level.
What are the advantages and disadvantages of serverless architecture and containers for developers?
Developers that use a serverless architecture may quickly deploy and iterate new applications without worrying about scalability. Furthermore, because the code does not need to be running all of the time, serverless computing is more cost-effective than containers if an application does not receive consistent traffic or utilisation.
Containers allow developers more control over the environment in which their programme operates (albeit this comes at the cost of additional maintenance) as well as the languages and libraries that are utilised. As a result, containers are ideal for moving legacy programmes to the cloud, as they allow for a more accurate replication of the application’s original running environment.
Lastly, a hybrid architecture with some serverless services and other functions hosted in containers is an option. For example, if an application function requires more memory than the serverless vendor allots, if a function is too large, or if some but not all functions must be long-running, a hybrid architecture allows developers to benefit from serverless while still using containers for the functions that serverless cannot support.
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