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Amazon Elastic Inference Logo
210 views|193 comparisons
StackStorm Logo
625 views|347 comparisons
Ranking
11th
out of 13 in Compute Service
Views
210
Comparisons
193
Reviews
0
Average Words per Review
0
Rating
N/A
9th
out of 13 in Compute Service
Views
625
Comparisons
347
Reviews
0
Average Words per Review
0
Rating
N/A
Find out what your peers are saying about Apache, Amazon, StackStorm and others in Compute Service. Updated: February 2021.
464,369 professionals have used our research since 2012.
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Overview

Amazon Elastic Inference allows you to attach low-cost GPU-powered acceleration to Amazon EC2 and Amazon SageMaker instances or Amazon ECS tasks to reduce the cost of running deep learning inference by up to 75%. Amazon Elastic Inference supports TensorFlow, Apache MXNet, and ONNX models, with more frameworks coming soon.
In most deep learning applications, making predictions using a trained model—a process called inference—can drive as much as 90% of the compute costs of the application due to two factors. First, standalone GPU instances are designed for model training and are typically oversized for inference. While training jobs batch process hundreds of data samples in parallel, most inference happens on a single input in real time that consumes only a small amount of GPU compute. Even at peak load, a GPU's compute capacity may not be fully utilized, which is wasteful and costly. Second, different models need different amounts of GPU, CPU, and memory resources. Selecting a GPU instance type that is big enough to satisfy the requirements of the most demanding resource often results in under-utilization of the other resources and high costs.
Amazon Elastic Inference solves these problems by allowing you to attach just the right amount of GPU-powered inference acceleration to any EC2 or SageMaker instance type or ECS task with no code changes. With Amazon Elastic Inference, you can now choose the instance type that is best suited to the overall CPU and memory needs of your application, and then separately configure the amount of inference acceleration that you need to use resources efficiently and to reduce the cost of running inference.

StackStorm is a powerful open-source automation platform that wires together all of your apps, services and workflows. It’s extendable, flexible, and built for DevOps and ChatOps.
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Sample Customers
Expedia, Intuit, Royal Dutch Shell, Brooks Brothers
Cisco, Netflix, NASA, Cybera
Find out what your peers are saying about Apache, Amazon, StackStorm and others in Compute Service. Updated: February 2021.
464,369 professionals have used our research since 2012.

Amazon Elastic Inference is ranked 11th in Compute Service while StackStorm is ranked 9th in Compute Service. Amazon Elastic Inference is rated 0.0, while StackStorm is rated 0.0. On the other hand, Amazon Elastic Inference is most compared with AWS Fargate, Amazon EC2 Auto Scaling, AWS Lambda and AWS Batch, whereas StackStorm is most compared with AWS Lambda, Apache NiFi, Google Cloud Dataflow, Apache Spark and Apache Storm.

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