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Scale machine learning models

Quickly scale machine learning (ML) models for training and inference and run them close to your data sources on any platform with containers.

Leverage batch processing

Package batch processing and extract, transform, and load (ETL) jobs into containers to start jobs quickly and scale them dynamically in response to demand.

Build microservices

Break apart application and run them as independent components, called microservices, using containers to isolate processes.

AWS Containers services

Our containers toolset

Sub-category

Use case

AWS service

Container orchestration

Run containerized applications or build microservices

Amazon Elastic Container Service (ECS)

Manage containers with Kubernetes

Amazon Elastic Kubernetes Service (EKS)

Compute options

Run containers without managing servers

AWS Fargate

Run fault-tolerant workloads for up to 90 percent off

Amazon EC2 Spot Instances

Run containers with server-level control

Amazon Elastic Compute Cloud (EC2)

Tools & services with containers support

Quickly launch and manage containerized applications

AWS Copilot

Share and deploy container software, publicly or privately

Amazon Elastic Container Registry (ECR)

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Schedule Assessment

Common solutions

Use Amazon ECS to implement microservices with native, managed AWS integrations

Amazon ECS lets you run batch workloads with managed or customer schedulers on Amazon EC2 On-demant, reserved, or spot instances.

Amazon ECS lets you run batch workloads with managed or customer schedulers on Amazon EC2 On-demant, reserved, or spot instances.

clients’ Success stories

MULTI STAGE DATA PIPELINE

Being a powerful player in the wellness & fitness niche, Naring Health handles multiple diet-related services under one roof. On the one hand, they evaluate DNA, microbiome, and metabolic reaction to particular meals or dietary practices to define a sufficient eating program to prevent or treat disease.

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AWS NATIVE KUBERNETES SOLUTION

As one of the most influential humanitarian organizations, Adra specializes in managing diversified services, each of which is intended to help individuals, communities, and society as a whole. Such a charity-oriented mission undeniably requires a robust technical foundation.

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A HIGHLY AVAILABLE MICROSERVICE ARCHITECTURE

In the modern business ecosystem, it is essential to constantly improve your services in order to engage potential clients and keep pace with the competitors. Growing means consistently examining your current infrastructure for weak areas and considering whether what you have in place is not only meeting the basic needs of your company today but also setting you up for triumph in the increasingly cloud-focused future.

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INFRASTRUCTURE & DEVOPS SERVICES FOR FINTECH PRODUCT

The client experienced the need to automate the deployment process of microservices and simplify the release process. One of the requirements was to migrate Docker containers to AWS ECS and move existing infrastructure to Terraform.

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CLOUD & DEVOPS SERVICES FOR CLOUD NATIVE PRODUCT

The client had a manual multi-environment infrastructure deployment аnd no continuous integration & continuous deployment automation. That significantly impacted the speed of product development, release, and delivery cadence of new application versions in general. Besides, it required a considerable part of the development team capacity to process it manually.

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CLOUD & DEVOPS SERVICES FOR REAL ESTATE PRODUCT

The client faced the need to automate multi-environment continuous integration and deployment process of microservices, move the front-end part to CDN as well as deploy multi-environment infrastructure as a code.

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SERVERLESS DATA & ML PIPELINES

The client had high costs for development, deployment, and, most importantly, operation of the data platform including Data Lake, Ingestion, and ML Pipelines. The pipelines were mostly running in EC2 instances, which led to the increased cost of operations and required a significant amount of time to deploy and test the pipelines in lower environments.

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SERVERLESS DEPLOYMENT AUTOMATION

The client came with a request to automate and unify the deployment process of serverless applications on AWS Lambda. Having manual deployments before, the customer was facing inconveniences and difficulties, including non-uniform environment setup (versions of Serverless, Python, Node, and so on were inconsistent) and inability to control the environment changes in one place.

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DATA SCIENCE INFRASTRUCTURE

The client needed to strengthen collaboration within the data scientists team by moving research capabilities into cloud workloads. Besides, they wanted to automate and unify the deployment process of AWS resources. That, in turn, would decrease the time and effort required for a team of data scientists to build and test their models.

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CI/CD FOR MOBILE CROSS PLATFORM APPLICATION

Initially, the client’s development team performed continuous integration and continuous deployment processes manually. Consequently, it was time- and effort-consuming to build cross-platform mobile applications. Besides, they used the legacy tools stack – that doesn’t have built-in mobile-specific continuous integration and deployment capabilities.

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SERHII YELCHENKO

Delivery Director

We are cloud native company who visions cloud computing as the home for tech products. Our team of top-notch engineers specialize in Cloud solutions, we develop scalable cloud native applications, provide DevOps services which facilitate innovations and allow release products faster, build reliable and secure cloud infrastructure for our clients from the US and Europe.

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