AWS EMR Pricing : Guide Step before you deploy an Instance

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Amazon EMR pricing can be daunting, but it doesn’t have to be. You just need the right guide. In this blog post, we’ll cover the different types of Amazon EMR pricing and how they work. We’ll also show you how to optimize your AWS EMR costs by using Spot Instances and Reserved Instances, along with other strategies that can lower your AWS bill.

How is AWS EMR Priced?

In this section, you’ll learn how to estimate the cost of running an EMR cluster. You can use this information to decide whether it makes sense for your application.

EMR pricing is based on three factors:

  • The number of instances that your cluster uses (also called compute nodes)
  • The amount of memory, storage, and CPU that each instance requires
  • How long you keep your cluster running

AWS EMR: Pricing for 3 Deployment Options

As you can see, pricing is calculated based on your chosen cluster size (which determines the number of nodes) and your instance type.

  • The smallest cluster size is two nodes and this will cost $142.88 per hour.
  • The next step up is four nodes and this will cost $248.63 per hour.
  • Then eight, sixteen, thirty-two, sixty-four and one hundred twenty-eight nodes are all available options for clusters. The larger the cluster size you choose the lower your hourly prices will be: 2 x 4 x 8 x 16 x 32 x 64 x 128 Nodes = 1160 Nodes Total / Hourly Cost Per Node = $0.067 USD / Hourly Cost Per Node = $0.467 USD

1. EMR Pricing on Amazon EC2

Amazon EMR pricing on Amazon EC2 is based on the number of vCPUs and the amount of memory. The total cost for a cluster depends on many factors, including:

  • The amount of data you’re analyzing
  • Whether or not you need dedicated hardware for your workloads
  • The number of tasks that each task needs to perform at a given time

2. EMR Pricing on AWS Outposts

If you are not a fan of the EC2 based architecture, AWS Outposts is a new option for running EMR clusters in the cloud. AWS Outposts is a private, dedicated cloud infrastructure built on AWS. It provides the same benefits as EMR on EC2:

  • You can run your workloads on private hardware that’s optimized for Amazon VPC and Amazon EMR
  • You can deploy or migrate your existing applications to AWS Outposts with minimal changes to code or configuration files
  • You have tight integration between your existing applications and other services such as RDS, S3, DynamoDB etc

3. EMR Pricing on Amazon EKS

Amazon EKS is a managed service that automatically scales the number of nodes in your cluster based on the actual workload you are running. It also uses Spot instances to reduce costs if you need to run a lower capacity cluster than what’s available (for example, during off-peak hours). The cost model for Amazon EKS is set up so that you pay only for what you use.

This gives you more control over pricing and allows you to scale up or down as needed without having to plan ahead for expensive capacity spikes.

AWS EMR Cost Optimization

AWS EMR cost optimization is a crucial part of running a successful data science project. AWS provides many ways to optimize your usage and save money, but it also means you need to know what tools are available and how to use them. Let’s cover some of the most important ways you can optimize your AWS costs for EMR:

  • Use Spot Instances: If you’re running tasks that are CPU-intensive, swap out your on-demand instances for spot instances (if available).
  • Buy Reserved Instances: Buy reserved instances up front instead of paying per hour or minute. This will give you a lower overall cost by locking in prices well into the future (3 years at this point). The longer term contracts also allow Amazon to negotiate better pricing with hardware vendors over time while still offering consumers more flexibility than they could get anywhere else.

1. AWS Spot Instances

The Spot Instance is a great way to reduce your AWS EMR cost. When you bid on an instance, the price can be as low as the market price. However, when the Spot instance runs out of bids before it expires, it will be terminated and Amazon Web Services (AWS) will charge you for that usage. Therefore it is important to set up a strategy for managing your Spot instances so that you don’t get charged too much or even worse get overcharged by Amazon Web Services (AWS).

2. EMR Reserved Instances

Reserved instances are discounted upfront payments for the right to use a specific instance type during a one- or three-year term. Reserved instances are available for purchase in all AWS regions.

Reserved instances can be purchased by customers or by cloud providers on behalf of their customers.

2. 1 All upfront

  • One-time fee that covers all of your Amazon EMR usage, without any refunds.
  • No refunds for unused hours or instances.
  • No refunds for unused storage capacity on Amazon S3 (Standard and Throughput) buckets hosted by Amazon EMR.

2.2 Partial upfront

Partial upfront payment is only available for EMR on-demand, not reserved instances or spot instances. The partial upfront payment feature is also not available for DynamoDB.

When you choose to pay in full, you’ll be charged the balance due when you first create the reservation. If you opt for partial upfront payment, then the remaining balance will be charged at the time of creating a reservation and again when it renews after three months or earlier if you cancel the instance before renewal occurs (see Cancelling Partial Upfront Payment).

If your account has been suspended due to non-payment, no action will be taken on behalf of AWS until your account becomes active again by paying any outstanding charges; however, partial upgrades are still supported and can be completed during this time period as long as there are no other outstanding costs associated with running these upgrades (such as Spot Instance fees).

2.3 No upfront payment

The second major benefit of the Amazon EMR pricing model is that you don’t have to pay upfront. Rather than making a large investment in servers up front and then paying on an hourly basis, with no upfront payment, you’re just paying for what you use and billing is based on that usage.

3. EMR Cluster Sharing

The EMR cluster sharing capability allows you to share an EMR cluster with other AWS accounts. You can share the cluster with up to 10 accounts, and it’s important to note that these accounts must have access policies in place that are identical to yours. If you want to share the cluster with accounts that have different access policies, contact Amazon Web Services (AWS) Support.

The process of sharing a cluster is simple: choose the option when launching a new EMR instance or importing an existing one into your account.

4. EMR Auto Scaling

Auto Scaling is a feature of EMR where you can scale up or down the number of instances in your cluster automatically. You can specify a minimum and maximum number of instances, as well as whether to scale up or down based on CPU utilization, RAM utilization, and any other metrics that are important to your application. The default configuration is to maintain at least 3 active EC2 instances in every cluster; however, this feature provides flexibility by allowing you to set parameters specific to your workloads and needs.

Auto Scaling schedules are managed directly within EMR using CloudWatch alarms that trigger the Auto Scaling Group policy changes when certain thresholds are exceeded. For example, if an alarm triggers due to high CPU utilization across all nodes, then all running clusters will be scaled down automatically according to their specified settings (minimum/maximum numbers). Additionally some queues require an instance type with more memory than others; therefore scaling them back up may not be possible if there aren’t enough available resources with sufficient RAM size available during peak hours (e.g., during daytime hours).

Amazon EMR Pricing Optimization with Spot by NetApp

Spot instances are the most cost-effective way to run your workloads on AWS. Spot is an auction-based market for unused EC2 capacity, where you can bid on unused EC2 capacity with a low price and pay a small fee if your instance runs into problems or is terminated. If you’re successful in winning the spot request and your bid is accepted, you’ll pay the lowest rate possible for the duration of your contract.

If you have excess On-Demand compute resources available, consider offering them through Spot! You can extend utilization of existing hardware resources while providing additional revenue from selling Spot Instances through NetApp’s Cloud Volumes ONTAP solution.

Additionally, AWS has recently announced that it will start charging for idle EBS volumes that are attached to running instances (otherwise known as “stale” volumes). So be sure to keep track of these volumes in order to avoid any unexpected charges!

Make sure you know what you are getting from your EMR.

It is important to know what you are getting from your EMR. You need to know that it is capable of handling your workload, and have a plan for when you need to scale up or down. You also need a plan for when you need to increase or decrease the number of nodes in your cluster.

Conclusion

We hope this guide has given you a better understanding of AWS EMR. It is important to be aware of the different pricing options available for your deployments and how they affect the cost of running your workloads. In addition, there are several ways that you can optimize costs when using Amazon Elastic MapReduce and Auto Scaling, such as using Spot instances or sharing clusters with other customers.

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