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."The auto-scaling feature is particularly useful. Additionally, CloudWatch and CloudTrail are also important features for us."
"The initial setup is straightforward."
"Amazon EC2 Auto Scaling has good integration."
"Applications deployed on EC2 instances can easily integrate with other AWS services. For example, you can connect your EC2 Auto Scaling group to a tool like CloudWatch for health checks and anomaly detection."
"Amazon EC2 Auto Scaling operates at a different level, working in parallel to efficiently manage workload distribution. Primarily, it focuses on orchestration rather than directly managing EC2 instances for deployment and configuration. It uses automated processes to deploy and manage ports, leveraging Application Load Balancers to effectively handle data communication and management."
"We use the solution to increase CPU and memory size."
"Amazon EC2 Auto Scaling has a cool-down time feature called the warmup start."
"What we have found most valuable are the purchasing of usage at the time and small storage."
"We can easily integrate AWS container images into the product."
"AWS Batch's deployment was easy."
"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."
"AWS Batch manages the execution of computing workload, including job scheduling, provisioning, and scaling."
"What could be improved in Amazon EC2 Auto Scaling is its fees."
"There should be an AWS instance in South Africa, where the latency would be even lower. It might happen soon since AWS has recently opened more data centres in Nigeria. AWS may extend its reach to South Africa, and offer hosted CLI servers there. Most of the problems with AWS are not to do with the solution itself but with configuration. It is something on design, more or less."
"Could integrate more with other platforms."
"The spinning up in the solution can be much faster...The product should have a faster scalability option."
"The product does not explain why a particular instance is terminated."
"Its stability and scalability need improvement."
"Scalability can be improved."
"It should work for the cloud, cloud monitoring features, and DevOps processes. It should automatically enable features for downscaling and upscaling."
"The solution should include better and seamless integration with other AWS services, like Amazon S3 data storage and EC2 compute resources."
"AWS Batch needs to improve its documentation."
"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."
"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 39 reviews while AWS Batch is ranked 4th 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, Oracle Compute Cloud Service and Amazon Elastic Inference, 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.
