Modern Container Based Deployment Options Over Cloud for Microservices

In this modern era of software development, Microservices can be developed, packaged, and deployed using containers. In cloud computing, containers are image files that hold the libraries, configuration files, runtime, code, and environment variables required to run software’s. The picture below demonstrates a general comparison regarding deployment of applications using techniques:

In other words, we can say that cloud container is just a container that doesn’t run locally or in a data centre, instead, it runs on cloud infrastructure. Container contains a base image, which is typically a stripped-down version of an operating system, the images are built layer by layer according to instructions included in a container configuration file.

Pushing (or deploying) containers to their destination environment, whether a cloud or on-premises server, is known as container deployment. The majority of container deployments are actually multi-container deployments, which means you are pushing numerous containers to the target environment, even if a container may host a full application. It is possible to launch hundreds or even thousands of containers every day for larger, more dynamic systems.

Depending on the need, they are made to spin swiftly up and down. This is due to the fact that creating, packaging, and deploying microservices is frequently done using containers. A software architecture known as microservices divides a huge solution, often known as a monolith or monolithic program, into smaller logical components. After then, each of these microservices operates autonomously within an own container.

Type of Serverless Containers

Based on attributes like vendor lock-in, flexibility, and affordability, following comparison shows the distinctions between Cloud-native apps, Serverless containers, and Serverless containers that are powered by Kubernetes.

1. Serverless Containers

1. Vendor Lock-in: Moderate
   • Less lock-in because containers can be moved between different environments, in contrast to serverless functions.
   • A certain amount of reliance on particular supplier features for a smooth integration.
2. Flexibility: High
   • Support for any language, framework, or library.
   • Fit for a variety of uses, such as background workers, APIs, and web servers.
3. Cost : Moderate
   • Pay for the resources consumed based on actual computation (CPU and memory).
   • It is normally more cost effective for longer running processes

2) Kubernetes Powered Serverless Containers

a) Key Features:

• Kubernetes-based Serverless experience.
• Provides load balancing and automated scalability.
• Able to execute any containerized application and fully utilize all of Kubernetes’ functionalities.
• Integration with development workflows and CI/CD pipelines

b) Vendor Lock-in: Low to Moderate

• Kubernetes offers portability between on-premises and cloud providers.
• Potential lock-in due to Kubernetes managed services (such Azure AKS and GKE).

c) Flexibility: Very High

• Complete access to the features and ecosystem of Kubernetes.
• Fit for lengthy, stateful, and complex applications
• Permits multi-cloud and hybrid deployments.

3) Cloud-Native Applications
a) Key Features:

• Developed to take use of cloud computing approaches, such as DevOps, CI/CD, containers, and microservices.
• Stress manageability, scalability, and resilience.
• Constructed using contemporary cloud techniques like declarative APIs and immutable infrastructure.
  
  b) Vendor Lock-in: Low
• Usually created utilizing open standards and containerization with portability in mind.
• Is deployable both on-premises and across several cloud providers.

c) Flexibility: Very High

• Uses a range of cloud services (such as communications, storage, and databases) without being restricted to the exclusive products of a single supplier.
• Promotes fault tolerance, scalability, and operational efficiency best practices.

d) Cost: Moderate to High
o The price of further features (such networking and monitoring) and managed Kubernetes services.
o More predictable for workloads that are consistent, but higher due to operating and infrastructure expenses.

Summary Table