AWS Compute Optimizer vs StackStorm comparison

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151 views|61 comparisons
100% willing to recommend
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14 views|9 comparisons
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Executive Summary

We performed a comparison between AWS Compute Optimizer and StackStorm based on real PeerSpot user reviews.

Find out what your peers are saying about Amazon Web Services (AWS), Apache, Zadara and others in Compute Service.
To learn more, read our detailed Compute Service Report (Updated: April 2024).
768,578 professionals have used our research since 2012.
Featured Review
Shady Mogawer
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Pricing and Cost Advice
  • "I find the solution's pricing reasonable. You need to pay extra for IP and other miscellaneous costs."
  • More AWS Compute Optimizer Pricing and Cost Advice →

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    Questions from the Community
    Top Answer:I find the solution's scaling capability to be an important benefit. You can scale it vertically or horizontally, i.e., you can upgrade the hardware or clone the machine. The solution is also easy to… more »
    Top Answer:I find the solution's pricing reasonable. You need to pay extra for IP and other miscellaneous costs.
    Top Answer:I have two areas of improvement to comment on. Most of the product names in AWS are not indicative of what they are doing. Moreover, AWS is not organized and you do not have the full platform with… more »
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    Ranking
    10th
    out of 16 in Compute Service
    Views
    151
    Comparisons
    61
    Reviews
    1
    Average Words per Review
    463
    Rating
    8.0
    39th
    out of 51 in Workload Automation
    Views
    14
    Comparisons
    9
    Reviews
    0
    Average Words per Review
    0
    Rating
    N/A
    Comparisons
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    Overview

    AWS Compute Optimizer recommends optimal AWS Compute resources for your workloads to reduce costs and improve performance by using machine learning to analyze historical utilization metrics. Over-provisioning compute can lead to unnecessary infrastructure cost and under-provisioning compute can lead to poor application performance. Compute Optimizer helps you choose the optimal Amazon EC2 instance types, including those that are part of an Amazon EC2 Auto Scaling group, based on your utilization data.

    By applying the knowledge drawn from Amazon’s own experience running diverse workloads in the cloud, Compute Optimizer identifies workload patterns and recommends optimal compute resources. Compute Optimizer analyzes the configuration and resource utilization of your workload to identify dozens of defining characteristics, for example, if a workload is CPU-intensive, or if it exhibits a daily pattern or if a workload accesses local storage frequently. The service processes these characteristics and identifies the hardware resource headroom required by the workload. Compute Optimizer infers how the workload would have performed on various hardware platforms (e.g. Amazon EC2 instances types) and offers recommendations.

    StackStorm is a powerful open-source automation platform that wires together all of your apps, services and workflows. It’s extendable, flexible, and built with love for DevOps and ChatOps.

    Sample Customers
    Expedia, Intuit, Royal Dutch Shell, Brooks Brothers
    Cisco, Netflix, NASA, Cybera
    Buyer's Guide
    Compute Service
    April 2024
    Find out what your peers are saying about Amazon Web Services (AWS), Apache, Zadara and others in Compute Service. Updated: April 2024.
    768,578 professionals have used our research since 2012.

    AWS Compute Optimizer is ranked 10th in Compute Service with 1 review while StackStorm is ranked 39th in Workload Automation. AWS Compute Optimizer is rated 8.0, while StackStorm is rated 0.0. The top reviewer of AWS Compute Optimizer writes "Easy to manage, flexible, and has good scaling options". On the other hand, AWS Compute Optimizer is most compared with , whereas StackStorm is most compared with Apache NiFi.

    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.