https://RustRocket.rs -- Cloud Monk Losang Jinpa, Ph.D., MCSE / MCT, https://Rustaceans.rs, Full Stack Cloud Native Rust DevOps Engineer - Rocket Framework Rust Microservices on Kubernetes-AWS-Azure-GCP

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Let's start with a simple definition:

Cloud-native architecture and technologies are an approach to designing, constructing, and operating workloads that are built in the cloud and take full advantage of the cloud computing model.

The Cloud Native Computing Foundation provides the official definition:

Cloud-native technologies empower organizations to build and run scalable applications in modern, dynamic environments such as public, private, and hybrid clouds. Containers, service meshes, microservices, immutable infrastructure, and declarative APIs exemplify this approach.

These techniques enable loosely coupled systems that are resilient, manageable, and observable. Combined with robust automation, they allow engineers to make high-impact changes frequently and predictably with minimal toil.

Cloud native is about speed and agility. Business systems are evolving from enabling business capabilities to weapons of strategic transformation that accelerate business velocity and growth. It's imperative to get new ideas to market immediately.

At the same time, business systems have also become increasingly complex with users demanding more. They expect rapid responsiveness, innovative features, and zero downtime. Performance problems, recurring errors, and the inability to move fast are no longer acceptable. Your users will visit your competitor. Cloud-native systems are designed to embrace rapid change, large scale, and resilience

Here are some companies who have implemented cloud-native techniques. Think about the speed, agility, and scalability they've achieved.

Company Experience Netflix Has 600+ services in production. Deploys 100 times per day. Uber Has 1,000+ services in production. Deploys several thousand times each week. WeChat Has 3,000+ services in production. Deploys 1,000 times a day. As you can see, Netflix, Uber, and, WeChat expose cloud-native systems that consist of many independent services. This architectural style enables them to rapidly respond to market conditions. They instantaneously update small areas of a live, complex application, without a full redeployment. They individually scale services as needed.

The pillars of cloud native The speed and agility of cloud native derive from many factors. Foremost is cloud infrastructure. But there's more: Five other foundational pillars shown in Figure 1-3 also provide the bedrock for cloud-native systems.

Cloud-native foundational pillars

Figure 1-3. Cloud-native foundational pillars

Let's take some time to better understand the significance of each pillar.

The cloud Cloud-native systems take full advantage of the cloud service model.

Designed to thrive in a dynamic, virtualized cloud environment, these systems make extensive use of Platform as a Service (PaaS) compute infrastructure and managed services. They treat the underlying infrastructure as disposable - provisioned in minutes and resized, scaled, or destroyed on demand – via automation.

Consider the widely accepted DevOps concept of Pets vs. Cattle. In a traditional data center, servers are treated as Pets: a physical machine, given a meaningful name, and cared for. You scale by adding more resources to the same machine (scaling up). If the server becomes sick, you nurse it back to health. Should the server become unavailable, everyone notices.

The Cattle service model is different. You provision each instance as a virtual machine or container. They're identical and assigned a system identifier such as Service-01, Service-02, and so on. You scale by creating more of them (scaling out). When one becomes unavailable, nobody notices.

The cattle model embraces immutable infrastructure. Servers aren't repaired or modified. If one fails or requires updating, it's destroyed and a new one is provisioned – all done via automation.

Cloud-native systems embrace the Cattle service model. They continue to run as the infrastructure scales in or out with no regard to the machines upon which they're running.

The Azure cloud platform supports this type of highly elastic infrastructure with automatic scaling, self-healing, and monitoring capabilities.

Modern design How would you design a cloud-native app? What would your architecture look like? To what principles, patterns, and best practices would you adhere? What infrastructure and operational concerns would be important?

The Twelve-Factor Application A widely accepted methodology for constructing cloud-based applications is the Twelve-Factor Application. It describes a set of principles and practices that developers follow to construct applications optimized for modern cloud environments. Special attention is given to portability across environments and declarative automation.

While applicable to any web-based application, many practitioners consider Twelve-Factor a solid foundation for building cloud-native apps. Systems built upon these principles can deploy and scale rapidly and add features to react quickly to market changes.

The following table highlights the Twelve-Factor methodology:

Factor Explanation 1 - Code Base A single code base for each microservice, stored in its own repository. Tracked with version control, it can deploy to multiple environments (QA, Staging, Production). 2 - Dependencies Each microservice isolates and packages its own dependencies, embracing changes without impacting the entire system. 3 - Configurations Configuration information is moved out of the microservice and externalized through a configuration management tool outside of the code. The same deployment can propagate across environments with the correct configuration applied. 4 - Backing Services Ancillary resources (data stores, caches, message brokers) should be exposed via an addressable URL. Doing so decouples the resource from the application, enabling it to be interchangeable. 5 - Build, Release, Run Each release must enforce a strict separation across the build, release, and run stages. Each should be tagged with a unique ID and support the ability to roll back. Modern CI/CD systems help fulfill this principle. 6 - Processes Each microservice should execute in its own process, isolated from other running services. Externalize required state to a backing service such as a distributed cache or data store. 7 - Port Binding Each microservice should be self-contained with its interfaces and functionality exposed on its own port. Doing so provides isolation from other microservices. 8 - Concurrency When capacity needs to increase, scale out services horizontally across multiple identical processes (copies) as opposed to scaling-up a single large instance on the most powerful machine available. Develop the application to be concurrent making scaling out in cloud environments seamless. 9 - Disposability Service instances should be disposable. Favor fast startup to increase scalability opportunities and graceful shutdowns to leave the system in a correct state. Docker containers along with an orchestrator inherently satisfy this requirement. 10 - Dev/Prod Parity Keep environments across the application lifecycle as similar as possible, avoiding costly shortcuts. Here, the adoption of containers can greatly contribute by promoting the same execution environment. 11 - Logging Treat logs generated by microservices as event streams. Process them with an event aggregator. Propagate log data to data-mining/log management tools like Azure Monitor or Splunk and eventually to long-term archival. 12 - Admin Processes Run administrative/management tasks, such as data cleanup or computing analytics, as one-off processes. Use independent tools to invoke these tasks from the production environment, but separately from the application. In the book, Beyond the Twelve-Factor App, author Kevin Hoffman details each of the original 12 factors (written in 2011). Additionally, he discusses three extra factors that reflect today's modern cloud application design.

New Factor Explanation 13 - API First Make everything a service. Assume your code will be consumed by a front-end client, gateway, or another service. 14 - Telemetry On a workstation, you have deep visibility into your application and its behavior. In the cloud, you don't. Make sure your design includes the collection of monitoring, domain-specific, and health/system data. 15 - Authentication/ Authorization Implement identity from the start. Consider RBAC (role-based access control) features available in public clouds. We'll refer to many of the 12+ factors in this chapter and throughout the book.

Fair Use Sources:

• https://docs.microsoft.com/en-us/dotnet/architecture/cloud-native/definition