New – AWS Fargate for Amazon EKS now supports Amazon EFS

AWS Fargate is a serverless compute engine for containers available with both Amazon Elastic Kubernetes Service (EKS) and Amazon Elastic Container Service (ECS). With Fargate, developers are able to focus on building applications, eliminating the need to manage the infrastructure related undifferentiated heavy lifting.

Developers specify resources for each Kubernetes pod, and are charged only for provisioned compute resource. When using Fargate, each EKS pod runs in its own kernel runtime environment and CPU, memory, storage, and network resources are never shared with other pods, providing workload isolation and increased security.

Containers are ephemeral in nature. They are dynamically scaled in and out, and their saved state or data is cleared on exit. We’ve had many requirements from our customers about data persistence and shared storage of containerized applications since launching EKS support for Fargate in 2019, and announced Amazon Elastic File System(EFS) support for Fargate on ECS in April 2020. Now many customers are operating stateful workloads on it, and others have requested support for EFS with Fargate when used with EKS. Today we are happy to announce this EFS support.

EFS provides a simple, scalable, and fully managed shared file system for use with AWS cloud services, and can also help Kubernetes applications be highly available because all data written to EFS is written to multiple AWS Availability Zones. EFS is built for on-demand petabyte growth without application interruption, and it automatically grows and shrinks as files are added and removed, eliminating the need to provision and manage capacity to accommodate growth. EFS Access Points is also ideal for security sensitive workloads as it can encrypt data in the file system and data in transit.

Kubernetes supports “Container Storage Interface (CSI)” which is a standard for exposing block and file storage systems to containerized workloads. The EFS CSI driver makes it simple to configure elastic file storage for Kubernetes clusters, and before this update customers could to use EFS via Amazon EC2 worker nodes connected to a cluster. Now customers can also configure their pods running on Fargate to access an EFS file system using standard Kubernetes APIs. With this update, customers can run stateful workloads that require highly available file systems as well as workloads that require access to shared storage. Using the EFS CSI driver, all data in transit is encrypted by default.

We released a generally available version of the Amazon EFS CSI driver for EKS in July 2020. The Amazon EFS CSI driver makes it easy to configure elastic file storage for both EKS and self-managed Kubernetes clusters running on AWS using standard Kubernetes interfaces. If a Kubernetes pod is terminated and relaunched, the CSI driver reconnects the EFS file system, even if the pod is relaunched in a different AWS Availability Zone.​ When using standard EC2 worker nodes, the EFS CSI driver needs to be deployed as a set of pods and DaemonSets. With this new update, for Fargate this step is not required and you do not need to install the EFS CSI driver, as it is installed in the Fargate stack and support for EFS is provided out of the box. Customers can use EFS with Fargate for EKS without spending the time and resources to install and update the CSI driver.

#amazon elastic kubernetes service #aws fargate #compute #storage #kubernetes

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AWS Fargate for Amazon Elastic Kubernetes Service | Caylent

On-demand cloud computing brings new ways to ensure scalability and efficiency. Rather than pre-allocating and managing certain server resources or having to go through the usual process of setting up a cloud cluster, apps and microservices can now rely on on-demand serverless computing blocks designed to be efficient and highly optimized.

Amazon Elastic Kubernetes Service (EKS) already makes running Kubernetes on AWS very easy. Support for AWS Fargate, which introduces the on-demand serverless computing element to the environment, makes deploying Kubernetes pods even easier and more efficient. AWS Fargate offers a wide range of features that make managing clusters and pods intuitive.

Utilizing Fargate
As with many other AWS services, using Fargate to manage Kubernetes clusters is very easy to do. To integrate Fargate and run a cluster on top of it, you only need to add the command –fargate to the end of your eksctl command.

EKS automatically configures the cluster to run on Fargate. It creates a pod execution role so that pod creation and management can be automated in an on-demand environment. It also patches coredns so the cluster can run smoothly on Fargate.

A Fargate profile is automatically created by the command. You can choose to customize the profile later or configure namespaces yourself, but the default profile is suitable for a wide range of applications already, requiring no human input other than a namespace for the cluster.

There are some prerequisites to keep in mind though. For starters, Fargate requires eksctl version 0.20.0 or later. Fargate also comes with some limitations, starting with support for only a handful of regions. For example, Fargate doesn’t support stateful apps, DaemonSets or privileged containers at the moment. Check out this link for Fargate limitations for your consideration.

Support for conventional load balancing is also limited, which is why ALB Ingress Controller is recommended. At the time of this writing, Classic Load Balancers and Network Load Balancers are not supported yet.

However, you can still be very meticulous in how you manage your clusters, including using different clusters to separate trusted and untrusted workloads.

Everything else is straightforward. Once the cluster is created, you can begin specifying pod execution roles for Fargate. You have the ability to use IAM console to create a role and assign it to a Fargate cluster. Or you can also create IAM roles and Fargate profiles via Terraform.

#aws #blog #amazon eks #aws fargate #aws management console #aws services #kubernetes #kubernetes clusters #kubernetes deployment #kubernetes pods

New – AWS Fargate for Amazon EKS now supports Amazon EFS

AWS Fargate is a serverless compute engine for containers available with both Amazon Elastic Kubernetes Service (EKS) and Amazon Elastic Container Service (ECS). With Fargate, developers are able to focus on building applications, eliminating the need to manage the infrastructure related undifferentiated heavy lifting.

Developers specify resources for each Kubernetes pod, and are charged only for provisioned compute resource. When using Fargate, each EKS pod runs in its own kernel runtime environment and CPU, memory, storage, and network resources are never shared with other pods, providing workload isolation and increased security.

Containers are ephemeral in nature. They are dynamically scaled in and out, and their saved state or data is cleared on exit. We’ve had many requirements from our customers about data persistence and shared storage of containerized applications since launching EKS support for Fargate in 2019, and announced Amazon Elastic File System(EFS) support for Fargate on ECS in April 2020. Now many customers are operating stateful workloads on it, and others have requested support for EFS with Fargate when used with EKS. Today we are happy to announce this EFS support.

EFS provides a simple, scalable, and fully managed shared file system for use with AWS cloud services, and can also help Kubernetes applications be highly available because all data written to EFS is written to multiple AWS Availability Zones. EFS is built for on-demand petabyte growth without application interruption, and it automatically grows and shrinks as files are added and removed, eliminating the need to provision and manage capacity to accommodate growth. EFS Access Points is also ideal for security sensitive workloads as it can encrypt data in the file system and data in transit.

Kubernetes supports “Container Storage Interface (CSI)” which is a standard for exposing block and file storage systems to containerized workloads. The EFS CSI driver makes it simple to configure elastic file storage for Kubernetes clusters, and before this update customers could to use EFS via Amazon EC2 worker nodes connected to a cluster. Now customers can also configure their pods running on Fargate to access an EFS file system using standard Kubernetes APIs. With this update, customers can run stateful workloads that require highly available file systems as well as workloads that require access to shared storage. Using the EFS CSI driver, all data in transit is encrypted by default.

We released a generally available version of the Amazon EFS CSI driver for EKS in July 2020. The Amazon EFS CSI driver makes it easy to configure elastic file storage for both EKS and self-managed Kubernetes clusters running on AWS using standard Kubernetes interfaces. If a Kubernetes pod is terminated and relaunched, the CSI driver reconnects the EFS file system, even if the pod is relaunched in a different AWS Availability Zone.​ When using standard EC2 worker nodes, the EFS CSI driver needs to be deployed as a set of pods and DaemonSets. With this new update, for Fargate this step is not required and you do not need to install the EFS CSI driver, as it is installed in the Fargate stack and support for EFS is provided out of the box. Customers can use EFS with Fargate for EKS without spending the time and resources to install and update the CSI driver.

#amazon elastic kubernetes service #aws fargate #compute #storage #kubernetes

AWS Introduces Batch Support for AWS Fargate

During the first week of the annual re:invent, AWS introduced the ability to specify AWS Fargate as a computing resource for AWS Batch jobs. With the AWS Batch support for AWS Fargate, customers will have a way to run jobs on serverless compute resources, fully-managed from job submission to completion.

AWS first introduced AWS Batch back in December 2016 as a fully managed batch computing service that enables developers, scientists, and engineers to quickly and efficiently run hundreds of thousands of batch computing jobs on AWS. With AWS Batch, customers no longer had to do the heavy lifting of batch workload management by creating compute environments, managing queues, and launching the appropriate compute resources for their jobs.

With the integration of AWS Batch with Fargate, users can run compute-intensive workloads such as ML inference, map-reduce analysis, and other batch workloads without spending time on image maintenance and right-sizing of compute and monitoring. By selecting Fargate or Fargate Spot as a compute resource type in Batch, submitting a Fargate-compatible job definition, users can immediately benefit from the serverless computing engine. With Fargate, every job receives the exact amount of CPU and memory that it requests (within allowed Fargate SKUs); hence, there is no wasted resource time or need to wait for EC2 instance launches.

#amazon #amazon web services #cloud #aws #aws fargate

AWS Fargate for Amazon Elastic Kubernetes Service

On-demand cloud computing brings new ways to ensure scalability and efficiency. Rather than pre-allocating and managing certain server resources or having to go through the usual process of setting up a cloud cluster, apps and microservices can now rely on on-demand serverless computing blocks designed to be efficient and highly optimized.

Amazon Elastic Kubernetes Service (EKS)already makes running Kubernetes on AWS very easy. Support for AWS Fargate, which introduces the on-demand serverless computing element to the environment, makes deploying Kubernetes pods even easier and more efficient. AWS Fargate offers a wide range of features that make managing clusters and pods intuitive.

Utilizing Fargate

As with many other AWS services, using Fargate to manage Kubernetes clusters is very easy to do. To integrate Fargate and run a cluster on top of it, you only need to add the command –fargate to the end of your eksctl command.

EKS automatically configures the cluster to run on Fargate. It creates a pod execution role so that pod creation and management can be automated in an on-demand environment. It also patches coredns so the cluster can run smoothly on Fargate.

A Fargate profile is automatically created by the command. You can choose to customize the profile later or configure namespaces yourself, but the default profile is suitable for a wide range of applications already, requiring no human input other than a namespace for the cluster.

There are some prerequisites to keep in mind though. For starters, Fargate requires eksctl version 0.20.0 or later. Fargate also comes with some limitations, starting with support for only a handful of regions. For example, Fargate doesn’t support stateful apps, DaemonSets or privileged containers at the moment. Check out this link for Fargate limitations for your consideration.

Support for conventional load balancing is also limited, which is why ALB Ingress Controller is recommended. At the time of this writing, Classic Load Balancers and Network Load Balancers are not supported yet.

However, you can still be very meticulous in how you manage your clusters, including using different clusters to separate trusted and untrusted workloads.

Everything else is straightforward. Once the cluster is created, you can begin specifying pod execution roles for Fargate. You have the ability to use IAM console to create a role and assign it to a Fargate cluster. Or you can also create IAM roles and Fargate profiles via Terraform.

#aws #kubernetes #containers #cluster management #eks #fargate #amazon eks

Containers on AWS: Which Service Is Right for Your Workload

Due to their lightweight, portable nature, using containers allows optimal cloud-native application builds. Now, running ten containers is relatively straightforward, but when you consider running containers at scale, i.e., hundreds and thousands of containers comprising hundreds of services, this can get out of hand quickly.

At this point, enterprises reach for a service or tool that can handle this challenge, which is where container orchestration tools come into the picture. Since 2014, AWS has launched more than 50 new features and multiple services to help engineers run containers in the cloud. At first, these tools aimed at optimizing how to run containers. The evolution of that tech has moved towards granular management and orchestration of container workloads.

Today, AWS is one of the best places to run any containerized application because it removes the heavy lifting of underlying infrastructure management and container orchestration. The reason for this popularity is the comprehensive suite of services available to users, check out a top three platform comparison for these services here: Cloud Services Comparison: AWS vs. Google vs. Azure.

The Cloud-Native Computing Foundation completed a study, and determined that 63% of companies are running their container workloads on AWS. These organizations range from optimizing container services for super small-scale dev and test environments right up to enterprise-scale mission-critical applications demonstrating how AWS still remains the most popular platform for such business critical applications. In this article, we’ll discuss the most popular AWS container services to see which best suits your requirements.

So, let’s get started.

#aws #amazon ecs #aws eks #aws fargate #containers on aws