What Is Cloud-Native Architecture?

Today, every IT resource or product is offered as a service. As such, cloud-native software development becomes a key requirement for every business, regardless of its size and nature. Before jumping onto the cloud bandwagon, it is important to understand what cloud-native architecture is and how to design the right architecture for your cloud-native app needs.

Cloud-native architecture is an innovative software development approach specially designed to leverage the cloud computing model fully. It enables organizations to build applications as loosely coupled services using microservices architecture and run them on dynamically orchestrated platforms. As a result, applications built on the cloud-native application architecture are reliable, deliver scale and performance, and offer faster time to market.

The traditional software development environment relied on a so-called "waterfall" model powered by monolithic architecture wherein software was developed in sequential order.

1. The designers prepare the product design along with related documents.
2. Developers write the code and send it to the testing department.
3. The testing team runs different types of tests to identify errors as well as gauge the performance of the cloud-native application.
4. When errors are found, the code is sent back to the developers.
5. Once the code successfully passes all the tests, it is deployed to a test production environment and deployed to a live environment.

If you have to update the code or add/remove a feature, you have to go through the entire process again. When multiple teams work on the same project, coordinating with each other on code changes is a big challenge. It also limits them to the use of a single programming language. Moreover, deploying a large software project requires a huge infrastructure set up along with an extensive functional testing mechanism. The entire process is inefficient and time-consuming.

Microservices architecture was introduced to resolve most of these challenges. Microservices architecture is a service-oriented architecture wherein applications are built as loosely coupled, independent services that can communicate with each other via APIs. It enabled developers to work on different services and use different languages independently. With a central repository that acts as a version control system, organizations were able to work on different parts of the code simultaneously and update specific features without disturbing the software or causing any downtime to the application. In addition, when automation is implemented, businesses can easily and frequently make high-impact changes with minimal effort.

Cloud-native app augmented by microservices architecture leverages the highly scalable, flexible, and distributed cloud nature to produce customer-centric software products in a continuous delivery environment. The striking feature of the cloud-native architecture is that it allows you to abstract all the layers of the infrastructure, such as databases, networks, servers, OS, security, etc., enabling you to automate and manage each layer using a script independently. At the same time, you can instantly spin up the required infrastructure using code. As a result, developers can focus on adding features to the software and orchestrating the infrastructure instead of worrying about the platform, OS, or the runtime environment.

Benefits of a Cloud-Native Architecture

There are plenty of benefits offered by cloud-native architecture. Here are some of them:

Accelerated Software Development Lifecycle (SDLC)

A cloud-native application complements a DevOps-based continuous delivery environment with automation embedded across the product lifecycle, bringing speed and quality to the table. Cross-functional teams comprising members from design, development, testing, operations, and business are formed to collaborate and work together through the SDLC seamlessly. With automated CI/CD pipelines in the development segment and IaC-based infrastructure in the operations segment working in tandem, there is better control over the entire process, making the whole system quick, efficient, and error-free. Transparency is maintained across the environment as well. All these elements significantly accelerate the software development lifecycle.

A software development lifecycle (SDLC) refers to various phases involved in the development of a software product. A typical SDLC comprises 7 different phases.

1. Requirements Gathering / Planning Phase: Gathering information about current problems, business requirements, customer requests, etc.
2. Analysis Phase: Define prototype system requirements, market research for existing prototypes, analyze customer requirements against proposed prototypes, etc.
3. Design Phase: Prepare product design, software requirement specification docs, coding guidelines, technology stack, frameworks, etc.
4. Development Phase: Writing code to build the product as per specifications and guidelines documents
5. Testing Phase: The code is tested for errors/bugs, and the quality is assessed based on the SRS document.
6. Deployment Phase: Infrastructure provisioning, software deployment to the production environment
7. Operations and Maintenance Phase: product maintenance, handling customer issues, monitoring the performance against metrics, etc.

Faster Time to Market

Speed and quality of service are two important requirements in today's rapidly evolving IT world. Cloud-native application architecture augmented by DevOps practices helps you to easily build and automate continuous delivery pipelines to deliver software out faster and better. IaC tools make it possible to automate infrastructure provisioning on-demand while allowing you to scale or takedown infrastructure on the go. With simplified IT management and better control over the entire product lifecycle, SDLC is significantly accelerated, enabling organizations to gain faster time to market. DevOps focuses on a customer-centric approach, where teams are responsible for the entire product lifecycle. Consequently, updates and subsequent releases become faster and better as well. The reduced development time, overproduction, overengineering and technical debt can lower the overall development costs as well. Similarly, improved productivity results in increased revenues as well.

High Availability and Resilience

Modern IT systems have no place for downtimes. If your product undergoes frequent downtimes, you are out of business. By combining a cloud-native architecture with Microservices and Kubernetes, you can build resilient and fault-tolerant systems that are self-healing. During downtime, your applications remain available as you can simply isolate the faulty system and run the application by automatically spinning up other systems. As a result, higher availability, improved customer experience, and uptime can be achieved.

Low Costs

The cloud-native application architecture comes with a pay-per-use model meaning that organizations involved only pay for the resources used while hugely benefiting from economies of scale. As CapEx turns into OpEx, businesses can convert their initial investments to acquire development resources. When it comes to OpEx, the cloud-native environment takes advantage of containerization technology, managed by an open-source Kubernetes software. Other cloud-native tools are available in the market to efficiently manage the system. With serverless architecture, standardization of infrastructure, and open-source tools, operation costs come down as well, resulting in a lower TCO.

Turns Your Apps Into APIs

Today, businesses are required to deliver customer-engaging apps. Cloud-native environments enable you to connect massive enterprise data with front-end apps using API-based integration. Since every IT resource is in the cloud and uses the API, your application also turns into an API. As a result, it delivers an engaging customer experience and allows you to use your legacy infrastructure, which extends it into the web and mobile era for your cloud-native app.

Cloud-Native Architecture Patterns

Due to the popularity of cloud-native application architecture, several organizations came up with different design patterns and best practices to facilitate smoother operation. Here are the key cloud-native architecture patterns for cloud architecture:

Pay-As-You-Go

In cloud architecture, resources are centrally hosted and delivered over the internet via a pay-per-use or pay-as-you-go model. Customers are charged based on resource usage. It means you can scale resources as and when required, optimizing resources to the core. It also gives flexibility and choice of services with various rates of payment. For instance, the serverless architecture enables you to provision resources only when the code is executed, which means you only pay when your application is in use.

Self-Service Infrastructure

Infrastructure as a service (IaaS) is a key attribute of cloud-native application architecture. Whether you deploy apps on an elastic, virtual or shared environment, your apps are automatically realigned to suit the underlying infrastructure, scaling up and down to suit changing workloads. It means you don't have to seek and get permission from the server, load balancer, or a central management system to create, test or deploy IT resources. While this waiting time is reduced, IT management is simplified.

Managed Services

Cloud architecture allows you to fully leverage cloud-managed services in order to efficiently manage the cloud infrastructure, right from migration and configuration to management and maintenance, while optimizing time and costs to the core. Since each service is treated as an independent lifecycle, managing it as an agile DevOps process is easy. You can work with multiple CI/CD pipelines simultaneously as well as manage them independently.

For instance, AWS Fargate is a serverless compute engine that lets you build apps without the need to manage servers via a pay-per-usage model. Amazon lambda is another tool for the same purpose. Amazon RDS enables you to build, scale and manage relational databases in the cloud. Amazon Cognito is a powerful tool that helps you securely manage user authentication, authorization, and management on all cloud apps. With the help of these tools, you can easily set up and manage a cloud development environment with minimal costs and effort.

Globally Distributed Architecture

Globally distributed architecture is another key component of the cloud-native architecture that allows you to install and manage software across the infrastructure. It is a network of independent components installed at different locations. These components share messages to work towards achieving a single goal. Distributed systems enable organizations to massively scale resources while giving the impression to the end-user that he is working on a single machine. In such cases, resources like data, software, or hardware are shared, and a single function is simultaneously run on multiple machines. These systems come with fault tolerance, transparency, and high scalability. While the client-server architecture was used earlier, modern distributed systems use multi-tier, three-tier, or peer-to-peer network architectures. Distributed systems offer unlimited horizontal scaling, fault tolerance, and low latency. On the downside, they need intelligent monitoring, data integration, and data synchronization. Avoiding network and communication failure is a challenge. The cloud vendor takes care of the governance, security, engineering, evolution, and lifecycle control. You don't have to worry about updates, patches, and compatibility issues in your cloud-native app.

Resource Optimization

Organizations have to purchase and install the entire infrastructure in a traditional data center beforehand. During peak seasons, the organization has to invest more in the infrastructure. Once the peak season is gone, the newly purchased resources lie idle, wasting your money. You can instantly spin up resources whenever needed and terminate them after using cloud architecture. Moreover, you will be paying only for the resources used. It gives the luxury for your development teams to experiment with new ideas as they don't have to acquire permanent resources.

Amazon Autoscaling

Autoscaling is a powerful feature of a cloud-native architecture that lets you automatically adjust resources to maintain applications at optimal levels. The good thing about autoscaling is that you can abstract each scalable layer and scale specific resources. There are two ways to scale resources. Vertical scaling increases the machine's configuration to handle the increasing traffic, while horizontal scaling adds more machines to scale out resources. Vertical scaling is limited by capacity. Horizontal scaling offers unlimited resources.

For instance, AWS offers horizontal auto-scaling out of the box. Whether it Elastic Compute Cloud (EC2) instances, DynamoDB indexes, Elastic Container Service (ECS) containers, or Aurora clusters, Amazon monitors and adjusts resources based on a unified scaling policy for each application you define. You can either define scalable priorities such as cost optimization or high availability or balance both. The Autoscaling feature of AWS is free, but you will be paying for the scaled-out resources.

12-Factor Methodology

To facilitate seamless collaboration between developers working on the same app and efficiently manage dynamic organic growth of the app over time while minimizing software erosion costs, developers at Heroku came up with a 12-factor methodology that helps organizations easily build and deploy apps in cloud-native application architecture. The key takeaways of this methodology are that the application should use a single codebase for all deployments and should be packed with all dependencies isolated from each other. The configuration code should be separated from the app code. Processes should be stateless so that you can separately run them, scale them and terminate them. Similarly, you should build automated CI/CD pipelines while managing build, release, and run stateless processes individually. Another key recommendation is that the apps should be disposable so that you can start, stop and scale each resource independently. The 12-factor methodology perfectly suits the cloud architecture.

Automation and Infrastructure as Code (IaC)

With containers running on microservices architecture powered by a modern system design, organizations can achieve speed and agility in business processes. To extend this feature to production environments, businesses are now implementing Infrastructure as Code (IaC). Organizations can manage the infrastructure via configuration files by applying software engineering practices to automate resource provisioning. With testing and versioning deployments, you can automate deployments to maintain the infrastructure at the desired state. When resource allocation needs to be changed, you can simply define it in the configuration file and automatically apply it to the infrastructure. IaC brings disposable systems into the picture in which you can instantly create, manage and destroy production environments while automating every task. It brings speed and resilience, consistency, and accountability while optimizing costs.

The cloud design highly favors automation. You can automate infrastructure management using Terraform or CloudFormation, CI/CD pipelines using Jenkins/Gitlab, and autoscale resources with AWS built-in features. A cloud-native architecture enables you to build cloud-agnostic apps which can be deployed to any cloud provider platform. Terraform is a powerful tool that helps you in creating templates using Hashicorp Configuration Language (HCL) for automatic provisioning of apps on popular cloud platforms such as AWS, Azure, GCP, etc. CloudFormation is a popular feature offered by AWS to automate the workload configuration of resources running on AWS services. It allows you to easily automate the setup and deployment of various IaaS offerings on AWS services. If you use various AWS services, infrastructure automation becomes easy with CloudFormation.

Automated Recovery

Today, customers expect your applications always to be available. To ensure the high availability of all your resources, it is important to have a disaster recovery plan in hand for all services, data resources, and infrastructure. Cloud architecture allows you to incorporate resilience into the apps right from the beginning. You can design self-healing applications and can recover data, source code repository, and resources instantly.

For instance, IaC tools such as Terraform or CloudFormation allow you to automate the provisioning of the underlying infrastructure in case the system crashes. Right from provisioning EC2 instances and VPCs to admin and security policies, you can automate all phases of the disaster recovery workflows. It also helps you instantly roll back changes made to the infrastructure or recreate instances whenever needed. Similarly, you can roll back changes made to the CI/CD pipelines using CI automation servers such as Jenkins or Gitlab. It means that disaster recovery is quick and cost-effective.

Immutable Infrastructure

Immutable infrastructure or immutable code deployments is a concept of deploying servers so that they cannot be edited or changed. If a change is required, the server is destroyed, and a new server instance is deployed in that place from a common image repository. Not Every deployment is dependent on a previous one, and there are no configuration drifts. As every deployment is time-stamped and versioned, you can roll back to an earlier version if needed.

Immutable infrastructure enables administrators to replace problematic servers easily without disturbing the application. In addition, it makes deployments predictable, simple, and consistent across all environments. It also makes testing straightforward. Auto Scaling becomes easy too. Overall, it improves deployed environments' reliability, consistency, and efficiency. Docker, Kubernetes, Terraform, and Spinnaker are some of the popular tools that help with immutable infrastructure. Furthermore, implementing the 12-factor methodology principles can also help maintain an immutable infrastructure.

DevOps Tools for Cloud-Native Architecture on AWS

DevOps complements the cloud-native architecture by providing a success-driven software delivery approach that combines speed, agility, and control. AWS augments this approach by providing the required tools. Here are some of the key tools offered by AWS for adopting cloud-native architecture.

Docker and Microservices Architecture

Docker is the most popular containerization platform that enables organizations to package applications with all the required runtime resources, such as the source code, dependencies, and libraries. In addition, this open-source container toolkit makes it easy to automate and control the tasks of building, deploying, and managing containers using simple commands and APIs.

Containers are lightweight, optimize resource usage, and increase developer productivity. Docker is popular as it facilitates the seamless movement of containers across different platforms and environments. In addition, their containers are lightweight and reusable. Docker comes with an automated container creation feature that automatically builds and deploys containers based on the source code along with versioning to allow you to roll back if needed. In addition, it offers a massive shared library with containers built by various users for developers.

Microservices architecture is a software development model which entails building an application that is a collection of small, loosely coupled, and independently deployable services that communicate with other services via APIs. As such, you can independently build and deploy each process without dependencies on other services, making every service autonomous. This model enables you to build each service for a specific purpose. It brings agility and speed to development while facilitating seamless collaboration between various teams. You can enjoy the flexibility in scaling required resources instead of mounting the entire application. The code can be reused as well.

Amazon Elastic Container Service (ECS)

Amazon Elastic Container Service (ECS) is a powerful container orchestration tool to manage a cluster of Amazon EC2 instances. ECS leverages the serverless technology of AWS Fargate to autonomously manage containerization tasks which means you can quickly build and deploy applications instead of spending time on patches, configurations, and security policies. It easily integrates with your popular CI/CD tools as well as with AWS native management and compliance solutions. In addition, you can pay only for the resources used.

The good thing about Amazon ECS is that it creates your scaling plan if you provide your target capacity, allowing you to better control scaling tasks. With Amazon CloudWatch, you can gain container insights. It also supports 3rd party tools such as Prometheus and Grafana. ECS is easy to use with no learning curve and minimizes overhead to optimize costs. Amazon ECS is deeply integrated with IAM and offers higher security. If you mostly work with AWS cloud environments, ECS is a good choice as it comes integrated with other Amazon services.

Amazon Kubernetes Service (Amazon EKS)

Amazon Kubernetes Service (EKS) is a containerized orchestration tool for container applications managed by Kubernetes on the AWS cloud. It uses the open-source Kubernetes software, which means you gain more extensibility to manage container environments when compared with Amazon ECS. Another advantage of EKS is that it comes with a range of tools to manage container clusters. For instance, Helm and Istio help you create templates for deployments, while Prometheus, Jaeger, and Grafana help you gain container insights. In addition, Jet-stack serves as a certification manager. It also offers further service meshes that you don't get with ECS. EKS works with Fargate and CloudWatch as well.

Amazon Fargate

Amazon Fargate is a popular tool from AWS that enables administrators to run container clusters in the cloud without having to worry about the management of the underlying infrastructure. Fargate works along with ECS and abstracts the containers from the underlying infrastructure, allowing users to manage containers while Fargate takes care of the underlying stack. Developers specify access policies and parameters while packaging an application into a container, and Fargate picks it up and manages the environment. Moreover, It takes care of scaling requirements. You can simultaneously run thousands of containers to manage critical applications easily. Fargate charges are based on the memory and vCPU resources used per container application. It is easy to use and offers better security but is less customizable and limited by regional availability.

To use Fargate, build a container and host it in a DockerHub or ECR registry. Then choose a container orchestration service such as ECS or EKS and create a cluster opting for Fargate. If your environment requires high memory, compute resources, and demands performance, Fargate is a good option.

Serverless Computing

Serverless Computing is a cloud-native model wherein developers can write code and deploy applications without the need to manage servers. As the servers are abstracted from the application, the cloud provider handles provisioning, scaling, and server infrastructure management. It means developers can simply build applications and deploy them using containers. In this architecture, resources for applications are launched only when the code is in execution. When an app is launched, an event is triggered, and the required infrastructure is automatically provisioned and terminated once the code stops running. It means users pay only when the code is in execution.

AWS Lambda

AWS Lambda is a popular serverless computing tool that lets you run code without the need to provision and manage servers. Lambda enables developers to upload code as a container image and automatically provisions the underlying stack on an event-based model. In addition, Lambda lets you run app code in parallel and scales resources individually for each trigger. So, resource usage is optimized to the core, and the administrative burden becomes zero.

AWS Lambda can be used for the real-time processing of data and files. For instance, you can write a function that triggers an event when there is a change in data or the desired state of the environment. Along with Amazon Kinesis, Lambda takes care of application activities. For example, using Lambda, developers can build serverless mobile backends and IoT backends wherein Amazon API Gateway performs the authentication of API requests. In addition, Lambda can be combined with other AWS services to build web applications that can be deployed across multiple locations.

AWS DevOps Tools for Cloud-Native Architecture

Cloud-Native Architecture Diagram

Here is an example of a cloud-native architecture diagram:

How does it work?

External Users

1. External users request access to cloud resources via the Amazon Route 53 DNS Web server.
2. The request is sent to the Amazon CloudFront Content Delivery Network (CDN) service.
3. As depicted in the cloud-native application architecture diagram, Amazon Cognito, a secure sign-on and authentication service, authenticates user credentials.
4. The user data is also sent to clickstream analysis, powered by Amazon Kinesis and AWS Lambda serverless technology, and the processed data is stored in the Amazon S3 service.
5. The traffic is sent to the virtual private cloud via an Internet gateway
6. The network load balancer will route the traffic to the available servers.
7. External users can access the API / App services powered by Fargate technology, as shown in the cloud-native architecture diagram.

The role of the Development/Operations Team in Cloud Native Architecture Diagram

1. The development and operations team uses the AWS CodePipeline.
2. They write code and commit to the private Git repositories managed by the AWS CodeCommit service.
3. The AWS CodeBuild continuous interaction service picks up the code and compiles it into deployable software packages.
4. Software packaged into containers using CloudFormation templates is uploaded to the Amazon Elastic Container Registry.
5. Containers are deployed to the production environment powered by Fargate.
6. Amazon S3 Glacier is used for file storage and archival purposes in this cloud-native architecture diagram.
7. Amazon ElastiCache for Redis is used for in-memory storage and cache for primary and secondary servers.
8. Amazon RDS or Amazon Aurora, which is compatible with PostgreSQL and MySQL, is used for relational database services in this cloud-native architecture diagram.
9. Amazon CloudWatch can be used for application and infrastructure monitoring.

Provisioning AWS Resources Using CloudFormation and Fargate

CloudFormation is a powerful IaC tool for provisioning and managing resources on AWS. Fargate is a serverless computing engine that handles the provisioning of the underlying infrastructure for your AWS resources. CloudFormation and Fargate technologies help you seamlessly deploy and manage resources in the AWS cloud.

Here is how you can automatically manage your infrastructure with CloudFormation

1. A DevOps admin creates a Fargate profile as a JSON file using the CloudFormation template with a valid EKS cluster name, the logical ID of the profile resource, profile property, etc.
2. The admin commits the profile to the AWS CodeCommit repository.
3. When a change is detected in the CloudFormation template repo, the AWS CodePipeline is triggered, and tasks are executed, after which the profile is pushed to the deployment.
4. The stack is launched, and the EKS service is updated about the changes to the infrastructure.

Using CloudFormation and Fargate, organizations can automatically create and manage new environments during production and development.

Case Studies of Cloud Native Architecture

Prosple

Prosple is a careers and education technology company, and their tech is used by leading universities and organizations to connect students with education and employment opportunities. Prosple designed the architecture of a Multi-tenant and Software-as-a-service application with Amazon ECS, Amazon Lambda, and the serverless framework that helps it have 99% faster deployment and configuration of new tenants inside the cloud infrastructure.

ArcusFi

ArcusFi began to develop a technology that enabled immigrants to pay bills. Now, it is a Fintech inc5000 company that helps the business make fintech accessible for consumers across the Americas. ArcusFi used ECS to reduce 40% of their application downtime and increased their deployment procedure up to 30%.

Conclusion of Cloud-Native Application Architecture

In today's rapidly changing technological world, cloud-native architecture is not optional anymore-it is a necessity. Change is the only thing that is constant in the cloud, which means your software development environment should be flexible enough to quickly adapt to new technologies and methodologies without disturbing business operations. Cloud-native architecture provides the right environment to build applications using the right tools, technologies, and processes. The key to fully leveraging the cloud revolution is designing the right cloud architecture for your software development requirements. Implementing the right automation in the right areas, making the most of managed services, incorporating DevOps best practices, and applying the best cloud-native application architecture patterns are recommended.