A container is a unit of software that bundles up code and all its dependencies into a single package so that an application can run quickly and reliably from one computing environment to another (e.g. moving from staging to production, moving from a physical machine in a data center to a virtual machine in a private/public cloud).
Containers are great for application development because developers and IT Ops teams can trust that their application’s environment will be consistent no matter where that application is eventually deployed. This means spending less time diagnosing and debugging and more time shipping new functionality to users.
In today’s software environment, where majority tasks are running on the cloud and in a DevOps culture, application delivery needs a special attention to keep the business running.
In the process of streamlining infrastructure, Cloud and Virtualization are a means of enhancing server efficiencies and maximizing server resources.
Further, in line with the application-centric business transformation, running apps at a faster rate, smoothly and secured, has emerged to become a key point of focus. Eventually, firms began their migration journey to better perform with higher efficiency and competitive operating costs.
That’s where the containerization technology made the difference! Some call it ‘a replacement to virtualization’ while others say it’s ‘an advancement to the concept of ‘Virtual Machines (VM)’.
Containerization arrived as a sophisticated approach for the effective utilization of server efficiencies with minimum additional resources.
Containerization for Cloud and DevOpsAs the trends show, containerization holds a strong influence on Cloud Computing and DevOps trends. With its advanced solution for boosting infrastructure efficiency, Containerization-as-Service is already leaving its mark in the cloud’s as-a-service models.
Public cloud containers are already making some significant impact in addressing the needs of Dev and Ops teams, thus also adding to the successful functioning of DevOps culture.
Meanwhile, increasing DevOps adoption is pushing many firms to look at ‘Microservices architecture’ for the next level of optimization in software releases and quality enhancement.
It has to be noteworthy that container applications have already emerged as the best choice to run microservices application architecture. Containers are already reporting a high success rate in migrating workloads to AWS and Azure!
Moreover, Container Orchestration is a proven methodology in applying containers at the enterprise level, especially for load balancing, scheduling, and other tasks.
A perfect container strategy, with proper tools, framework and proper implementation across application and software development lifecycle is known to offer high agility, shorten productivity time.
Cloud Container Services Comparison
The rise of adopting cloud container services is on demand and rising steadily. According to a recent survey, it was found that 80% of IT professionals and teams are utilizing container technology. This is a major jump from 58% in 2017. With the rise of adopting container services, there are various options to choose in the market. We researched the market of container services from the top cloud providers; AWS, Azure, and Google Cloud Platform.
AWS Cloud Container ServicesAmazon Elastic Container Service: One can manage and deploy containers distributed across many AWS virtual machines using Amazon Elastic Container Service (Amazon ECS). If combined with AWS Fargate, you can run containers without selecting servers. The cost of ECS depends on the launch model, for EC2 model you pay for the EC2 instances and EBS volumes. For the Fargate model, the cost is applicable for vCPU and memory that your containerized application requests.
Amazon Elastic Container Registry: Amazon ECR is an AWS managed solution to store, manage, and deploy Docker container images. ECR is highly scalable, available, and integrated with ECS. Cost of the ECR depends on the amount of data stored in repositories and transferred to the Internet.
Amazon Elastic Container Service for Kubernetes: This is one of the AWS services that can be used to manage and deploy containers via Kubernetes container orchestration service. The cost is $0.20 per hour for each EKS clusters and the cost of any AWS resources used such as EC2 instance that was created to run Kubernetes worker nodes.
AWS Fargate: Fargate is an AWS solution for Amazon ECS that will allow you to run containers without managing infrastructure or servers. Using Fargate it becomes easier to focus on applications instead of infrastructure that runs them. Cost of Fargate depends on the vCPU and memory resources used.
AWS Batch: AWS users can launch large quantities of batch computing jobs using AWS Batch. You pay only for the AWS resources that you use to store, create, and run your application with no additional fees.
Azure Cloud Container Services
Azure Kubernetes Service: Azure Kubernetes Service (AKS) is Microsoft Azure’s fully managed solution to deploy and manage containers through Kubernetes container orchestration service. You pay only for the storage, Virtual Machines, and networking resources that are used for the Kubernetes cluster.
Azure Container Registry: They are used to store and managed the container images for deploying across Kubernetes, Docker Swarm, DC/OS, and Azure services including Batch, App Service, and Service Fabric. The cost of Azure Container Registry is per day, depending on the number of web hooks and storage needed.
Azure Container Instances (ACI): ACI allows you to run containers on Azure without managing infrastructure or servers. This makes it simpler to build applications without focusing on infrastructure. Cost is based on the container groups with vCPU and Memory resources and is on a per-second basis.
Azure Batch: Using Azure Batch one can run a large number of compute jobs, where users can choose to run directly on Docker-compatible containers or Virtual Machines. Charges applicable only for the compute and other resources used to run the batch jobs.
Azure App Service: One can create cloud-based web apps and APIs using Azure App Service. Similar to Azure Batch they have options for running in virtual machines or in containers. Billed for every hour, with several tiers depending on your needs for disk space, auto-scaling, number of instances, and network isolation.
Azure Service Fabric: It is a way to lift, shift, and modernize .NET applications to microservices using Windows Server containers. Azure Service Fabric is an open source project. It powers core Azure infrastructure and other Microsoft services include Azure SQL database, Cortana, Skype for Business and more. You pay for volumes, compute, and collections used, although their complex pricing model makes it hard to measure.
Google Cloud Container Services>
Google Kubernetes Engine: GKE is Google’s fully managed solution to deploy and manage containers through Kubernetes container orchestration service. Billing includes the cost of Google Compute Engine instances used, at no additional charges.
Google Container Registry: This allows users to manage and store the Docker container images for container deployment. You pay only for the network and storage used by your Docker resources.
Google App Engine Flexible Environment: Google App Engine Flexible Environment is a platform where you can deploy APIs and web apps, which you can do on Docker containers or on VM instances. Pricing is based on the storage, compute, and other resources used for the apps.