Transform the way your business designs applications. Atlasticity helps you build the most secure, reliable, scalable way to run containers with deep integrations on AWS.
Boost operational efficiencies. AWS Containers streamline application migration to the cloud without time consuming or costly code changes to your applications.
There are lots of options with how to run containers in AWS.
Amazon Elastic Kubernetes Service (EKS) or Amazon Elastic Container service (ECS) helps reduce the complexity of running your own container orchestration infrastructure. AWS Fargate allows you to run containers in a serverless environment, allowing you to focus on your application and not worry about how to run and scale it.
Faster delivery of software applications on a scalable and modern platform. Docker is the containerization software that helps you build and deploy your applications inside containers. Once your application lives inside containers, orchestration software like Kubernetes provides a way to deploy, manage and scale them.
Standardization of application code, configurations, and dependencies into single object containers ensure portable and reliable application deployments in any environment. Many applications benefit from containerization, but machine learning, batch processing and migrating from on-premise to a cloud environment are particularly well suited use cases.
Microservices
Containers provide process isolation that makes it easy to break apart and run applications as independent components. Microservices architectures allow applications to make the best use of specialized cloud services tailored to the particular needs of the component. It also allows for scaling and resources to be applied to the areas of an application that need it, allowing for more efficient use of resources.
Batch processing
When you need to analyze a large amount of data, batch processing can be extremely effective. However, managing and scaling a cluster of compute to run batch processing jobs can be very complex. Package batch processing and ETL jobs into containers to start jobs quickly and scale them dynamically in response to demand. AWS Batch helps you manage the complexity and ensure your batch processing jobs are run efficiently and cost effectively.
Machine learning
Use containers to quickly scale machine learning models for training and inference. Run them close to your data sources on any platform. AWS Deep leaning Containers (AWS DL Containers) are Docker images which are pre-installed with common deep learning frameworks and libraries like Tensorflow, PyTorch and MXNet. It is tightly integrated with Amazon Sagemaker, EKS or ECS, allowing you to deploy and scale complex ML workloads with ease.
Hybrid applications
Containers let you standardize how code is deployed, making it easy to build workflows for applications that run between on-premises and cloud environments. Now, with Amazon ECS and EKS Anywhere, you can use the same orchestration engines both inside your cloud environment as well as on-premise to maintain a consistent environment for your containerized workloads no matter where you run them.
Application migration to the cloud
Containers make it easy to package entire applications and move them to the cloud without needing to make any code changes. They create an abstraction between the application code and the environment they run on, which makes them easily portable. Such flexibility allows for swift prototype and proof of concept (POC) workloads, and greatly reducing the risk and uncertainty of migrations and cloud adoption.
Platform as a service
Use containers to build platforms that remove the need for developers to manage infrastructure. Standardize how your applications are deployed and managed. Focus on your application, feature development and customer needs and spend less time and resources on infrastructure and the complexities of scaling.