We performed a comparison between Amazon EC2 Auto Scaling and AWS Batch based on real PeerSpot user reviews.
Find out in this report how the two Compute Service solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."One of the most important benefits is that a company can optimize resources because Auto Scaling deploys resources when needed. For example, for Black Friday, a company can deploy 100 servers for a couple of days. When Black Friday is over, the company can delete those servers."
"The initial setup of Amazon EC2 Auto Scaling is easy...Since we are an enterprise-sized company and a client of Amazon, the response from the technical support team was immediate."
"Amazon EC2 Auto Scaling has good integration."
"The auto-scaling feature is particularly useful. Additionally, CloudWatch and CloudTrail are also important features for us."
"The initial setup is straightforward."
"It's good performance-wise."
"The product’s most valuable feature is the seamless resizing of web connection."
"The solution incorporates ease of maintenance and reduction in operational overhead and costs. Patching is also easy."
"AWS Batch manages the execution of computing workload, including job scheduling, provisioning, and scaling."
"There is one other feature in confirmation or call confirmation where you can have templates of what you want to do and just modify those to customize it to your needs. And these templates basically make it a lot easier for you to get started."
"We can easily integrate AWS container images into the product."
"AWS Batch's deployment was easy."
"The solution's pricing is expensive. You pay based on how much you use it, like paying for the time or hours you use the service. There's no need to buy hardware separately."
"Scalability can be improved."
"The product should improve vertical scaling features."
"We have found that the sizing in Amazon EC2 Auto Scaling is far off. For example, we will see some at one terabyte and the other one is two terabytes. There is nothing between one and two terabytes. Sometimes it's a struggle if I need one and a half, I still am supposed to pay for two. There are five terabytes, six terabytes, and 12 terabytes, and if I need something at eight or nine, I'm still paying 30 to 40 percent more by taking the one which is 12 terabytes. Microsoft Azure does similar sizes but the gap can be more, such as six terabytes, and the next one is 12 terabytes."
"Amazon EC2 Auto Scaling can provide more discounts when using the machines the solution uses."
"Could integrate more with other platforms."
"The technical support needs to be improved."
"I would like to see the security portal improved in the future."
"The main drawback to using AWS Batch would be the cost. It will be more expensive in some cases than using an HPC. It's more amenable to cases where you have spot requirements."
"AWS Batch needs to improve its documentation."
"The solution should include better and seamless integration with other AWS services, like Amazon S3 data storage and EC2 compute resources."
"When we run a lot of batch jobs, the UI must show the history."
Amazon EC2 Auto Scaling is ranked 2nd in Compute Service with 37 reviews while AWS Batch is ranked 3rd in Compute Service with 4 reviews. Amazon EC2 Auto Scaling is rated 8.8, while AWS Batch is rated 9.0. The top reviewer of Amazon EC2 Auto Scaling writes "Well-documented setup process and highly stable solution". On the other hand, the top reviewer of AWS Batch writes "User-friendly, good customization and offers exceptional scalability, allowing users to run jobs ranging from 32 cores to over 2,000 cores". Amazon EC2 Auto Scaling is most compared with AWS Fargate, AWS Lambda, Amazon Elastic Inference, Oracle Compute Cloud Service and Apache NiFi, whereas AWS Batch is most compared with AWS Lambda, Apache Spark, AWS Fargate, Oracle Compute Cloud Service and Amazon EC2. See our AWS Batch vs. Amazon EC2 Auto Scaling report.
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We monitor all Compute Service reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
