Server-less architecture is event-driven stateless compute containers that are heavily relied on third party services. These third-party services are known as Backend as a Service (BaaS) or Mobile Backend as a Service (MBasS) or custom code that's run in ephemeral containers (Function as a Service or "FaaS"). For example, you developed a mobile app whose backend and database system is not designed by you but you used a ready to be deployed backend system like parse or firebase.
The term serverless may be confusing. The application has a server hardware and server process which running somewhere else and managed by third-party vendors. Serverless in this scenario that the organization is not looking for hardware and the server-side code itself.
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Let's see an example of an eCommerce app.
In serverless architecture instead of writing our own authentication logic and managing the data, we use a third-party service like Facebook or Google authentication.
Use a third-party database as a service product in cloud-like firebase or amazon dynamo DB or azure cosmos DB to create our product database.
Use a cloud search functionality inside your application to allow users to search and discover products.
An event-driven purchase function that writes successful purchase to a purchase database.
Server-less computing supports multiple languages and abstracts the underlying infrastructure from the developer so that they can focus on building the business logic and rich user experience. Resources are charged for the time they are being used. In serverless applications are broken into small specific core components.
Serverless computing came after the penetration of cloud computing into development. Serverless computing eliminates the hassle of setting up a server, database, and server-side code writing. Instead, we have APIs we use for interacting with the database and servers.
In the cloud and with a third party BaaS provider we can have a lot of connectors and predefined functions so the developer needs not write their own code to connect with services. Instead, they write functions that trigger in response to an event.
These functions are evolved as Function as a Service (FaaS). AWS Lambda and Azure Functions are two top Server-less architecture.
Azure Functions is a serverless architecture inside the Microsoft Azure cloud computing platform. It allows writing a small piece of code (function) in any supported programming language like PHP, JavaScript, bash, C#, etc and runs them inside a container.
Azure functions app can connect into azure cosmos DB storage and external applications like sendgrid, dropbox, etc. through connectors.
In server-less stack, functions are bound to specific events and triggered when necessary. Example events are
Server-less computing abstracts the underlying infrastructure from the developer so the developer can focus on building the business logic. The performance of server-less computing depends on the configuration and client-side logic and performance of third-party connectors.
Azure service plans and data center regions also affect the scalability of function apps.
Pay for what you use: in server-less computing you only pay for the runtime usage and resource consumption of your function. You do not need to pay for idle resources.
Scalability: In server-less computing the backend service provider will scale the infrastructure according to load. Developers are no need to write code for scalability or make any provision for resource allocation.
Rapid Development and Iteration: In server-less computing each functions are single threaded. single threaded functions make debugging easy and deployment easier. The development team are no longer dependent on IT team and deployment happens directly from codebase. CI and CD makes rapid development fast.
Less System Administration: In server-less computing servers are managed by the third party service provides. Developers need not manage and provision servers and infrastructures. No patching and server updates.
Developer Productivity: As the underlying infrastructure is abstracted from developer, they can focus on writing the efficient business logic.
Server-less computing decreases the complexity of the application thus making deployment easier.
Azure Functions is a serverless architecture inside the Microsoft Azure cloud computing platform. It allows writing a small piece of code (function) in any supported programming language like PHP, JavaScript, bash, C#, etc and run them inside a container.
Azure functions app can connect into azure cosmos DB storage and external applications like sendgrid, dropbox, etc. through connectors.
Azure functions are event-driven and can perform multiple tasks like
Related Article: Azure Stack - Cloud Services
Logic apps are managed services that let developers create business apps without writing code. Logic apps provide a building block based on IFTTT (If this then that). Logic apps provide connectors to integrate other third-party services like twitter, sendgrid, dropbox, etc. It is used to automate the workflows and write a custom application for business.
Related Article: Azure Analysis Services
Applications, data, and devices can be connected in the cloud or in an on-premises environment with creating logic apps that perform simple automated tasks like saving an attachment to one drive from outlook or send an email when a new tweet is created.
Logic apps perform an action based on an event or control flow. Azure portal has thousands of predefined templates and connectors to create Logic apps.
Disadvantage:
Azure Service Fabric is a distributed systems platform for packaging, deploying and managing microservice that are scalable and reliable. Service fabric also used for native cloud application development.
In-Service Fabric application can be deployed in two ways.
Service Fabric supports application life cycle management, continuous integration and continuous deployment of cloud applications and containers.
Service Fabric can be integrated with CI/CD tools like Visual Studio Team Services, Jenkins, and Octopus Deploy.
Service Fabric enables simpler application administration, monitoring and patch update. Most applications contain both stateless and stateful microservices and service fabric enables the deployment of multiple instances of the application along with the container and run-time stack.
Related Article: Azure Monitor
Disadvantage:
You have to pay extra for using service fabric.
Azure Batch:
Azure Batch is a platform service for running large-scale parallel and high-performance computing (HPC) applications efficiently in the cloud. It schedules high compute-intensive workloads to be performed on a managed collection of virtual machines. It can automatically scale up or scale down resources as required.
Azure batch automates the job. We can easily define compute resources to execute the application in parallel. It is managed service for batch processing of a high volume of data.
Related Article: A Complete Guide On Microsoft Azure Batch
Example: Video file transcoding.
Let assume we have to transcode large numbers of video files. We upload and configure our application in azure batch.
Upload the input video files to the Azure storage account.
Create a Batch pool of compute nodes in your Batch account with properties such as node size, Operating system, and location of the storage account.
Create a Batch job to run the workload on the pool of compute nodes and associate it with a Batch pool.
Add tasks to the job
As the tasks run, you can query Batch to monitor the progress of the job and its tasks.
As the tasks complete, they can upload their result data to Azure Storage. You can also retrieve files directly from the file system on a compute node.
When your monitoring detects that the tasks in your job have completed, your client application or service can download the output data for further processing or evaluation.
High performance and highly scalable
Fully managed service
You only pay for the resources you use
Azure batch supports Windows and Linux
Disadvantage:
Requires platform expertise in setting up tasks
More programmatically and less tooling.
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Anji Velagana is working as a Digital Marketing Analyst and Content Contributor for Mindmajix. He writes about various platforms like Servicenow, Business analysis, Performance testing, Mulesoft, Oracle Exadata, Azure, and few other courses. Contact him via anjivelagana@gmail.com and LinkedIn.