A Guide on How to Choose the Right Cloud-Native Technology for Your Solutions

With the explosive growth of the cloud coupled with its advantages, it has become the de-facto choice for most software developments. Whether it’s a new development or an overhaul, migrating an existing development to cloud has become the most attractive choice. In this article, let’s look at how to choose the right cloud-native technology stack for your solution.

What are cloud-native technologies?

Cloud-native technologies refer to technologies designed to take advantage of the flexibility, scalability, and resilience offered by the cloud computing model. Cloud-native technologies typically power micro-services oriented, containerized, and dynamically orchestrated applications with APIs acting as the communication mechanism between these components.

How are cloud-native technologies different from traditional ones?

The primary difference between cloud-native and traditional technologies is the type of applications they are targeting. Traditional technologies are primarily suited for on-premise desktop or server-based applications that are more monolithic in nature. On the other hand, Cloud-native technologies tend to be more in tune with web-based applications that are distributed in nature.

This distributed nature allows cloud-native technologies to cater to a wide range of users, distributed globally, without encountering performance bottlenecks. Cloud-native technologies also allow users to utilize many different services, providers, and platforms easily, then incorporate their strengths in the application.

Benefits of cloud-native

• The consumption-based pricing model allows users to manage their resources cost-effectively. They can avoid overprovisioning and pay only for the resources consumed by the application.
• The near-limitless scalability enables applications to scale according to user demands, essentially eliminating performance bottlenecks. In microservices-based architecture, this scalability correlates to the independent scaling of each service.
• Increased portability as applications can be easily migrated to different providers without undergoing drastic changes. This is especially the case with containerized applications and also avoids vendor lock-in.
• Well suited for automation. Most aspects from development to deployment and management can be easily automated, leading to a relatively easier management experience.
• A better security posture can be achieved with cloud-native technologies like containers and microservices by creating isolated services. This isolation minimizes the impact on the overall solution even if a single component is compromised.

What is the best choice for cloud-native development?

The selection of the technology is completely dependent on the exact requirements of users. However, we can categorize the available technologies for generalized use cases as follows.

• Containerization — Docker, LXD, Containerd
• Orchestration — Kubernetes, Rancher, Openshift
• Service Mesh — Istio, Lankerd, Cosul
• CI/CD — Jenkins, GitLab, GitHub Actions, Microtica, Flux, ArgoCD
• Infrastructure (IaC) — Terraform, Plumi, Ansible

A cloud-native application cannot rely on a single technology. It will always be a combination of technologies for specific use-cases.

What parameters are important when choosing a cloud-native technology?

Cloud services have brought data center capabilities to general consumers without the management responsibilities or costs associated with maintaining a data center. Even for services like Kubernetes, there are managed solutions that alleviate the need for the daily management of these services. However, there are some key parameters to consider when selecting the right technology.

First is the type of solution and its architecture. The technology stack can vastly differ depending on the particular use case. For example, a service like AWS Elasticbeanstalk can facilitate a simple web app, while containers in a Kubernetes cluster will be ideal for a more complex solution with their greater control.

Next comes the ease of use of the technology. Even if the technology is well suited for the requirement, if it has a larger or a complex learning curve, it can affect the delivery of the solution. In some cases, utilizing multiple comparatively simpler technologies may provide a better solution.

Security and compliance are also key parameters of the cloud-native technology selection process. The selected technology should comply with compliance requirements such as data redundancy, access control, and encryption before moving forward. Additionally, a technology that is unproven or highly vulnerable to attacks should not be used to power your solution without readily available security services or support to mitigate security threats. A proven technology with a large community or commercial support will be more suitable for secure and robust development. Even when a vulnerability has been detected, a technology with a greater support structure has a higher chance of quickly getting patches to fix the vulnerability.

The last parameters will be maintenance effort and cost. The cost consideration is not only limited to the technology itself but also includes ancillary factors like human resources and time constraints to learn and adapt the technology. Thus, if the selected technology cannot be managed within given cost constraints, it should not be selected. Maintenance involves monitoring the application and managing its day-to-day maintenance activities. The ability of the technology to expose to monitoring aspects like metrics, logs, as well as its inbuilt monitoring tools should be considered when it comes to maintenance.

How to choose?

Now we have a good understanding of cloud-native technologies and what should be considered when selecting the right tech stack. So let’s see how we power up all aspects of your cloud-native application.

Selecting the Core Application Technologies

The primary task will be to drill down the exact requirements of the solution. What is the primary objective of the application? What problem is it trying to solve? What is the target audience? etc. By understanding and defining the requirement, you can focus on defining the application architecture.

System Architecture will determine what kind of tech stack can be used. A technology like containers can be used for virtually any kind of development. With their self-contained and portable nature, you can develop and deploy your application relatively easily. A simple application running in a single container can be easily deployed using a fully managed service like AWS ECS. However, as the complexity grows you will need more and more containers powering different components and even multiple deployments in different regions. Thus requiring additional functionality like load balancing, service discovery, security, error handling, deployment management, etc… This is where services like Kubernetes come in by offering a complete container orchestration engine to manage the lifecycle of your containers.

Taking this step further, if your application has multiple independent components performing a dedicated business functionality you should go with a microservices-based architecture. Microservice-based architecture can be scaled independently and it is a fault-tolerant service-oriented structure.

As these services grow in complexity, routing traffic between services within a cluster or multiple clusters will become increasingly complex. Then a service mesh solution like Istio is suitable to provide a dedicated infrastructure layer to facilitate secure service-to-service communication, load balancing, failovers, pluggable policies, etc… Increasing the observability of the environment will be required to properly meet the growing management demands of the application. Even if your application does not require all these capabilities, creating an architecture that can integrate different technologies will be beneficial in the longer run.

As microservices and service mesh leads to more secure application architectures by default. Adopting such a structure would be beneficial on multiple fronts from scalability, availability, security, and ease of management.

Implement Infrastructure as Code or Manual Management

Once you have sorted out the architecture the next goal is to find the supporting infrastructure services. Even for managed services, there will be requirements to provision or configure them. As such infrastructure management technology should also be included in your stack. This leads to IaC or infrastructure as code, this is essential for implementing practices like GitOps and is invaluable for managing large-scale infrastructure configuration in a standardized manner. But IaC should not be included in your stack unless it brings tangible benefits like time savings, environmental standardization, etc… as this can lead to unwanted management overheads for smaller developments.

IaC also comes in different flavors with cloud providers offering their own tools and third-party solutions offering platform-agnostic tools like Terraform or Pulumi. Although you can consider a platform-specific tool like AWS CloudFormation or Azure Resource Templates, it leads to vendor-lock-in. Thus it’s always advisable to use an IaC tool that can be used across different platforms and services.

Facilitating the Development Environment

Once you have decided on the technologies that power up your application, next you should consider what tools to be used for governing your development environment and which practices should be used in the delivery process. Practices like DevOps and GitOps will require putting more emphasis on continuous integration and CI/CD tools will become the backbone of the delivery pipeline.

Continuous Monitoring

The final part of the puzzle is application maintenance. After the application is in the production environment, it should be monitored to identify issues ranging from security vulnerabilities to performance issues. So you have to monitor logs and metrics of the application and all the supporting infrastructure. Therefore, a tool that offers native monitoring capabilities would be preferable. Kubernetes, Istio are examples of such tools that offer increased observability across the environment as well as provide monitoring capabilities for all entities within the environment.

Even if all the above-mentioned factors are agreed upon, users must have the flexibility to switch technologies as they may face unexpected complications like limited extendibility, feature depreciations, cost constraints that would limit the usability of a tech stack. Therefore, it’s always advisable to have a trial run with your chosen tech stack before committing to it fully.

Conclusion

Choosing the right cloud-native technology can make or break a development. This cheat sheet covers all the main aspects developers should consider when selecting their cloud-native technology stack. I hope it gives you a leg up in choosing the right technology for your next cloud-native development.