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Building Serverless APIs with Azure Functions

With the upcoming release of serverless computing services, cloud service providers have brought a revolution to the market across the web. A wide assortment of cloud service providers, like Google Cloud Platform, Microsoft Azure, and Amazon Web Services, has released serverless computing.

Severe computing refers to a kind of computing that does not include any sort of server. The servers are known to run in the background and can handle different operations. However, the cloud service providers have the responsibility to manage, scale up and down, and maintain such servers.

What are serverless APIs?

Serverless computing provides a suitable choice for developers to concentrate on the application’s development without worrying about its infrastructure. Thus, the developers are capable of coding for the specific app, whereas serverless computing takes care of different server-related needs with utter flexibility.

Hence, you do not need to worry about any kind of purchasing, provisioning, or managing the backend servers. It is known to follow the architecture, whereas the vendors offer the prerequisite backend services to the developers.

What are Azure functions?

Azure functions refer to the serverless compute service by Microsoft, which is known to execute the code in response to different predetermined conditions and events, like the arrival of the order on the IoT system on a certain queue that receives the message. Thus, it is responsible for the automatic management of different computing resources as needed by the processes.

Though the Azure function provides a bunch of benefits to business organizations that want to reap the benefits of serverless APIs, the enhanced dependency on different cloud environments, containerized microservices, and open source technologies adds to the complexity and creates observability issues for the DevOps teams to deal with the end-user experience and app performance.

The growth in Azure cloud computing

Azure is recognized as a widely growing cloud computing ecosystem that provides empowerment to potential users to seek access to databases, develop mobile apps and sites, release virtual servers, train machine learning models, and execute the Kubernetes cluster.

Different serverless options allow you to create anything within the cloud. Such a platform is known to reserve a specific number of virtual machines and add instances, catering to their needs during heavy usage. As Azure is equipped with so many features, it is increasing in popularity among government agencies and corporations.

Functioning of the Azure platform

The Azure Functions serverless platform provides a suitable choice for teams to create event-driven applications that execute the code as dictated by the present system conditions and events. Such a platform is responsible for managing different computing resources and processes.

Thus, the serverless on azure cloud frees up the DevOps team so that they can concentrate on the creation and delivery of different functions and features. In addition, Azure functions allow the teams to execute custom-written code so that they can connect several services in Python, C#, JavaScript, and PHP within the containerized environment on an as-needed basis.

Using the Azure functions

Azure functions are known to work at the cloud edge. Thus, it is a suitable choice for the smaller applications, which work with other sites independently. A few of the tasks performed by Azure functions include processing IoT data and orders, sending messages, emails, and notifications, scheduling tasks like database cleanups, and starting backups.

 Thus, you will be capable of creating the APIs and web applications within the function application, with the use of functions for different routine tasks, like querying the database and setting the application users. Thus, Microsoft allows you to create the serverless code in individual product-based clouds. Azure IoT functions are known to process different requests for the Azure IoT Edge.

The observability issue in the serverless approach

Monitoring the functions in Azure is restricted to the Azure applications and on-premise services they are interacting with. Thus, you will be able to enable and look through the logs per service and per function. But if you want to work through the bugs and alerts, you need to navigate through different logs manually.

Distributed tracing provides an ideal opportunity for teams to map and understand different dependencies across the software stack. As the latest IT environments employ different technologies, including open-source technologies and cloud environments, the teams need to depend on different monitoring solutions, which enhance the complications, thereby creating different blind spots for SRE teams and DevOps.

The cloud-native apps of the present depend on various microservices, which are known to perform different processes, such as pushing event data to the analytics service, pushing notifications, and establishing the database connection. End-to-end observability maintenance of the whole software stack is essential to recognizing and resolving different performance problems.

Benefits of Azure serverless computing

Here, we will discuss some of the benefits of Azure serverless microservices computing:

  •         The developers here are capable of coding in their favorite language without the need to worry about the servers.
  •         The potential users will use Azure Cosmos B to store the serverless application data. Hence, the Cosmos DB will replicate data across different regions, thereby offering the best services to the app’s users.
  •         Microsoft Azure offers top-notch security to its developers. Hence, Azure Active Directory is useful to developers in accessing resources in a secure manner and managing serverless apps.
  •         Microsoft Azure offers scalable cloud storage for different developers.
  •         Azure functions provide empowerment to business organizations in creating dynamic serverless applications that are created on different functions that are known to execute on the cloud edge without the need to manage the prerequisite infrastructure.

serverless vs Kubernetes

The potential audience adopting the Kubernetes strategy needs to setup certain clusters. From the serverless vs Kubernetes comparison, it is evident that they are meant to prototype and thus maintain it like other environments.

Serverless vs microservices are two related and still different concepts. Both of them are meant to increase the scalability, modularity, and agility of different apps. However, certain differences exist between them. The microservice-based architecture is known to operate at a certain, finer-grained level. The serverless architecture goes a little way above with regards to granularity. 

By choosing a singular view across different services and interacting with and leveraging the Azure functions applications, the developer team will be able to find out which functions can experience the highest processing time and failure rate. It allows the team to concentrate on offering efficient and smooth apps, which provides benefits to the end-user experience. Thus, it plays an integral role in improving business outcomes.

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