The cloud-native infrastructure is a cloud environment that enables the entire life cycle of applications designed and developed to operate in the cloud. A classic cloud-native app consists of a mesh of isolated services ensuring the overall app stability as the app does not cease to operate when one service is down. The granular infrastructure of such apps enables their on-the-go improvement without operational downtimes and systemic failures.
Important aspects of the cloud-native infrastructure Containerization
For the deployment of cloud apps, I recommend using containers to package up software code with all the dependencies necessary to run an app or a service. Containers consume fewer cloud resources and can be easily configured, scaled, replicated, and orchestrated via such management systems as Kubernetes. The use of containers facilitates CI/CD implementation and infrastructure automation.
Paas
To make the cloud more attractive to users, major cloud providers offer PaaS services for developing, testing, deploying, managing, and updating cloud applications: AWS Lambda, Azure Functions, Google App Engine, etc. PaaS releases you from cumbersome server management and lets you extend your cloud infrastructure with special modules for AI, machine learning, IoT, blockchain, etc., with no extra development efforts.
IT infrastructure automation
With the Infrastructure as Code (IaC) approach, your DevOps team can automate cloud infrastructure setup and management of its components. They use configuration files to organize unified and instantly configured development environments and trace changes committed to the infrastructure.
Parallel development environments
As services of a cloud-native app are detached and have clear criteria for their functional operability, they enable a high level of automation and can be simultaneously developed and then assembled, tested, and deployed through the branching CI/CD pipelines.
Autoscaling
Cloud infrastructures are driven by virtual computing nodes like EC2s in AWS and VMs in Azure or Google Cloud Platform. Each component of a cloud infrastructure consumes CPU, RAM or storage capacities attributable to it and the consumption should timely follow the demandThat’s why I recommend automating resource orchestration to:
- Reduce cloud consumption by scaling down when a service is idle.
- Ensure sufficient performance of a service by scaling up.
Depending on the objectives, you can make the virtual instances scale dynamically against metrics of interest (including predictive metrics) or as scheduled if you expect load surges.
Load balancing
Application monitoring
Monitoring of a cloud-native app can be divide into two layers:
- Health checks to define whether a microservice is functional at all. because The functional state is automatically reported to a host platform, which can scale up
- Metrics analysis certainly gives an advanced picture of app performance. because It is mostly use by the developers to automate
Security
A cloud-native app lets you build perimeter and component-level security. However, the integration of access verification mechanisms into each app component may become a burden on performance. To avoid this, I suggest use intra-component authentication: a sign-up user gets a taken, which is then compare with a reference token cashed in each service to grant or deny access. This technique greatly contributes to app security with the least effect on its performance.
Tips for a robust cloud-native infrastructure
Tip 1: Get an experienced DevOps team skilled in:
- Automation. Isac infrastructure setups, CI/CD pipelines, infrastructure management automation.
- Containerization to make your infrastructure a resource-friendly system easily reproducible on any cloud platform.
- App monitoring to make sure your app adheres to the set business goals throughout its entire life cycle.