What is serverless?

The first thing you should consider is what Serverless cloud computing is and why we appreciate it. The term serverless cloud computing may appear contradictory, as software available via the cloud always involves some form of server someplace. Essentially, serverless is a design approach that lets you build and run entire server-based applications without managing servers directly. With a traditional infrastructure-as-a-service offering, you are responsible for the care and feeding of the operating systems and any server-based applications that live on that server. Now, with serverless, cloud providers still have servers and server lists abstracted in the background, but you will never have to worry about their capacity, performance patching, or fault tolerance.

Technically, any cloud service you can call a pay-per-use API could be considered serverless. Hence, where do we draw the line? It is going to be around the services like compute services, storage services, database services, integration services, AI, and ML services that the provider has packaged up into APIs.

Why Build serverless Applications?

Serverless architectures are becoming a game-changer for organizations that need to scale their applications rapidly and efficiently. Serverless use cases span a wide range of industries like fintech, insurance, media, e-commerce, healthcare providers, retailer chains, aviation, logistics, and many more. All these industries always want to be on top in a competitive market by managing the large customer base and volume of transactions and serving their frequently changing demands by accelerating time to market. And this could only be possible with the scalable and resilient platform, which would be achieved through the serverless architecture.

Traditional enterprise web application architecture using Azure serverless platform

The below architecture is the typical enterprise web application architecture. It shows the different infrastructure resources required to run the end-to-end application. The Virtual Machines (VMs) are primarily being used to host web apps, APIs, Database servers, Datawarehouse, and AI & ML workloads. It involves high maintenance, regular patching, limited compute resources, no flexibility in terms of scalability and high availability, less scope to fault tolerance, and slower time to market

Diagram #1 – Traditional Enterprise Web Application Architecture

On the other hand, this entire platform can be moved to the end-to-end serverless architecture platform to leverage the serverless benefits. Will see how the Azure Serverless computing services will replace the respective infrastructure services.

Azure serverless platform provides a series of fully managed services ranging from computing, storage, database, orchestration, monitoring, analytics, intelligence, and so on to help construct end-to-end serverless applications for any kind of scenario.

The below diagram depicts how the different categories of Azure serverless services fit in different layers of the typical enterprise web application.

Diagram #2 – Serverless Architecture Approach for Enterprise Web Application

The above serverless architecture supports the legacy codebase alongside newer serverless backends.
It is a scalable and sesilient event-driven microservices architecture with low cost by only paying per use of computing resources. This architecture includes the following components, which come under different serverless categories in Azure.

Azure serverless compute

Azure serverless compute allows users to create an endless number of connections, allowing them to use multiple functionalities from various sources. Azure serverless compute enables developers to create powerful applications by removing the need for infrastructure provisioning and management.

• App Service: Used to host the Web Apps which are behind the front door for high availability with autoscaling feature enabled.
• Function App: Serverless Function Apps are used for an event-driven computing experience. Those are used to run background tasks that are invoked/triggered by an HTTP trigger, time trigger, and service bus trigger.
• Azure Kubernetes (AKS): For hosting the containerized microservices APIs on Kubernetes clusters for enterprise-grade container orchestration for scalability and automated management.

Azure serverless workflow and integrations

• Azure API Management: Used to publish, secure, transform, maintain, and monitor Backend microservices APIs. Helps to manage API lifecycle, usage quota, and rate limits.
• Logic Apps: Used to integrate with third-party apps/services by leveraging the capability of Azure Integration account for EDI communications.
• Service Bus Queue: The application queues background tasks by putting a message onto an Azure Service Bus queue. The message triggers a Logic App or function app for further processing, either backed DB operations or external service calls.

Serverless databases

• Azure SQL Database: Used to store the relational data. Enabled with automated scaling of computing power based on workload demand. Only need to pay for computing power consumed per second. Automated serverless database pausing and storage-only billing for inactive periods will further reduce costs.
• Azure Cosmos DB: Used to store non-relational data. It is a globally distributed, massively scalable, and multi-model database service.

Azure serverless storage

• Azure Blob Storage: To store static web content and unstructured data. It is a massively scalable storage service for semi-structured and unstructured data.

Security and access control – serverless

• Azure Active Directory: Used for identity and access management. Also, leveraging to enable communication among the services through managed identity.

Azure Serverless Analytics

• Azure Stream Analytics and Power BI: To easily develop and run massively parallel real-time analytics using Stream Analytics and quickly build the real-time dashboard using Power BI.
• Azure serverless Artificial Intelligence (AI) and Azure serverless Machine Learning (MI)
  Azure serverless Machine Learning enables data scientists and developers to build, deploy, and manage high-quality models quickly and confidently.

1. Azure Cognitive Services: Utilized Azure Cognitive Services through an API to enable serverless apps to understand and interpret user needs through verbal and nonverbal communication.

2. Machine Learning Models: To create, train, and deploy models from the cloud to the edge.

Advantages of Azure serverless computing

1. Improve developer’s productivity

In serverless architecture, the developer doesn’t need to worry about infrastructure provisioning to host their code/services to run. Developer can focus on business logic and deliver the functionality in less time with quality.

2. Event Driven App Scalling

Azure auto-scaling feature enables the serverless applications to scale up or down automatically according to the frequency of the events to meet the demand.

3. Shorter Time To Market

Azure’s Serverless offerings allow developers to build and deploy elastic-scale applications faster than ever. Azure provides unique serverless tools to accelerate development and deployment by seamlessly tapping into the benefits of the cloud.

4. Seamless Deployment

The Azure DevOps serverless capabilities and the Infrastructure as Code (IaC) practice accelerate the deployment. It delivers the stable test environments rapidly at scale. Helps the developers to test the
serverless applications in production-like environments early in the development cycle. Teams
can provision multiple test environments reliably on demand.

5. Pay per Use Only

Going serverless is a great way of cutting cost. The serverless computing enables you to pay for the services which you’ve used by running your code. You pay only for the resources used by your app. To run the enterprise apps/services on the end-to-end serverless platform has significant cost benefit.

6. Improved Flexibility

Azure provides more flexibility in choosing series of options from different categories of services. Azure Serverless enables the oganizations to become more agile and innovate faster by unlocking flexible infrastructure, easier development, and shorter release cycle. It’s easier to pivot in situations
where you need to restructure.

Why choose Azure serverless computing?

Microsoft named a Leader in 2021-2022 Gartner® Magic Quadrant™

Gartner Magic Quadrant reports playing a pivotal role in helping industries to understand the cloud service providers’ capabilities by providing a holistic review of every fundamental aspect.

For the ninth consecutive year, Microsoft was named a Leader, and it placed furthest on the Completeness of Vision axis and almost top in the Ability to Execute axis in the Cloud Database Management Systems. Simimillary, Microsoft was named a leader in the Cloud Infrastructure & Platform Services, and Enterprise Integration Platform as a Service.

The rate of innovation is faster

Considering the current innovation demands in the market, Microsoft is constantly focusing on building and strengthening the platform to help and move faster in the innovation space. The Azure serverless platform helps to faster innovation in different areas considering the market trends.

Largest community and partner support

Microsoft has a significant market presence in every industry globally and has the largest community, which helps and supports continuous improvements and innovations. Microsoft has the Cloud Solution provider partner Community, which helps to unlock new opportunities and accelerate cloud business growth.

How can LTIMindtree help with Azure serverless?

LTIMindtree’s cloud-driven modernization services will enable clients to jumpstart their Transformation Journey by performing an in-depth code-level analysis of your application to determine cloud readiness, discover incompatible code blocks, identify any remediation work needed, and develop a detailed use case for App Modernization.

• An end-to-end tool-led transformation solution that identifies use cases & accelerates the journey towards serverless.
• Detailed evaluation of technologies & multiple parameters to align with Business NorthStar.
• Combine technical analysis with Business imperatives & create the Cloud readiness score with a serverless approach.
• Templatized Migration Planning and execution with seamless handover to target operating model.

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