AWS Auto Scaling vs Datadog comparison

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AWS Auto Scaling

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Executive SummaryUpdated on Jan 25, 2026

Datadog and AWS Auto Scaling both offer solutions in the monitoring and resource management category. Datadog appears to have the upper hand in terms of its extensive feature set and user-friendliness, while AWS Auto Scaling stands out for its effective scalability and automation capabilities.

Features: Datadog offers extensive integration options, real-time analytics, and custom dashboards that provide a comprehensive monitoring solution. It is noted for its user-friendly interface, which is beneficial for both technical and non-technical users. AWS Auto Scaling provides seamless integration with AWS CloudWatch, allowing automatic server scaling based on demand to ease resource management during high traffic.

Room for Improvement: Datadog could enhance its service with more granular usage metrics, better data representation options, and improved front-end monitoring. Users also desire more pre-built alerts and smoother integrations with other solutions. AWS Auto Scaling can improve in areas of pricing flexibility and configuration simplicity, also possibly adding more AI features and automation.

Ease of Deployment and Customer Service: Datadog is relatively easy to set up across public, private, and hybrid clouds but faces some challenges due to its complex UI. Customer service experiences vary in responsiveness and efficiency. AWS Auto Scaling simplifies deployment in public cloud settings and is backed by proactive and efficient customer service, facilitating smoother integrations within the AWS ecosystem.

Pricing and ROI: Datadog's pricing is often considered high with a complex structure, but it provides significant ROI in large environments where its feature set is fully utilized. AWS Auto Scaling's pay-per-use model is generally seen as cost-effective, directly contributing to operational savings by efficiently scaling resources according to demand. Both solutions offer pricing advantages depending on specific use cases and organizational size.

To learn more, read our detailed AWS Auto Scaling vs. Datadog Report (Updated: December 2025).

AWS Auto Scaling vs. Datadog

December 2025

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Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

ROI

Sentiment score

1.0

AWS Auto Scaling optimizes costs and delivers significant ROI, reducing expenses for businesses and proving its financial value.

Sentiment score

6.4

Datadog increases efficiency with improved monitoring and incident response, reducing downtime and costs despite difficulty in quantifying exact financial benefits.

No quotes available

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Previously we had thirteen contractors doing the monitoring for us, which is now reduced to only five.

Prakash Pandey

IT Manager at Liberty Mutual Insurance

Datadog has delivered more than its value through reduced downtime, faster recovery, and infrastructure optimization.

reviewer2767362

Sr. Cloud Infrastructure Engineer at a tech vendor with 51-200 employees

I believe features that would provide a lot of time savings, just enabling you to really narrow down and filter the type of frustration or user interaction that you're looking for.

Carson Waldrop

QA Engineer at Townsquare Interactive

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Customer Service

Sentiment score

4.4

Users praise AWS Auto Scaling's customer service for being efficient and helpful, despite occasional slow response times.

Sentiment score

6.7

Datadog's support is generally responsive and effective, though occasionally slow, with valuable customer service and knowledgeable assistance.

AWS support is very good.

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AWS Cloud at AeonX Digital Solutions Pvt. Ltd.

When I have additional questions, the ticket is updated with actual recommendations or suggestions pointing me in the correct direction.

Laurie Mordick

Applications Web Services Technical Engineer at Ace Hardware

Overall, the entire Datadog comprehensive experience of support, onboarding, getting everything in there, and having a good line of feedback has been exceptional.

Thomas Harrison

Systems Administrator at Townsquare Interactive

I've had a couple instances where I reached out to Datadog's support team, and they have been really super helpful and very kind, even reaching back out after resolving my issues to check if everything's going well.

Nikki L.

Security Engineer at Invitation Homes

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Scalability Issues

Sentiment score

7.2

AWS Auto Scaling offers easy, robust scalability for medium to large enterprises, efficiently handling user increases and traffic spikes.

Sentiment score

7.6

Datadog efficiently scales and integrates with cloud infrastructures, though some users face challenges with cost management.

Scalability is impressive, as it allowed us to go from 1,000 to 10,000 active users within a week during a traffic spike.

Mbula Mboma

AWS Cloud Re-Start Program Specialist at Orange RDC (Congo)

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Datadog's scalability has been great as it has been able to grow with our needs.

Prakash Pandey

IT Manager at Liberty Mutual Insurance

We did, as a trial, engage the AWS integration, and immediately it found all of our AWS resources and presented them to us.

Thomas Harrison

Systems Administrator at Townsquare Interactive

Datadog's scalability is strong; we've continued to significantly grow our software, and there are processes in place to ensure that as new servers, realms, and environments are introduced, we're able to include them all in Datadog without noticing any performance issues.

Corey Peoples

Senior Custom Software Development Consultant at a tech vendor with 501-1,000 employees

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Stability Issues

Sentiment score

5.9

AWS Auto Scaling is stable and reliable, though occasional scaling delays and server issues require effective deployment and management.

Sentiment score

8.0

Datadog is praised for its reliability, minimal downtime, improved stability, and light resource usage, with quick resolution of issues.

No quotes available

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Datadog is very stable, as there hasn't been any downtime or issues since I've been here, and it's always on time.

Nikki L.

Security Engineer at Invitation Homes

Datadog seems stable in my experience without any downtime or reliability issues.

Daniel Dolan

Full Stack Developer at Townsquare Interactive

Datadog seems to be more stable, and I really want to have a complete demo before making a call to decide on this.

Aman

Enterprise solution architect at a manufacturing company with 10,001+ employees

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Room For Improvement

AWS Auto Scaling requires faster launches, better usability, improved documentation, enhanced security, automation, scalability, cost optimization, and clearer instructions.

Customers seek improved performance, simplified interface, predictable pricing, enhanced integration, and intuitive features in Datadog for better usability.

This complexity led me to migrate to CloudFormation, which simplifies the deployment process.

Mbula Mboma

AWS Cloud Re-Start Program Specialist at Orange RDC (Congo)

It requires a downtime before deploying the Auto Scaling group.

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AWS Cloud at AeonX Digital Solutions Pvt. Ltd.

If you could add more training on how to use it correctly and on the functions that I haven't used before or some people have not really used before, that would help.

Ishaka Michael Efe

DevOps Engineer Intern at HNG Tech

It would be great to see stronger AI-driven anomaly detection and predictive analytics to help identify potential issues before they impact performance.

reviewer2767305

Operations Manager at a financial services firm with 1,001-5,000 employees

We want to be able to customize the cost part, and we would appreciate more granular access control.

Andrei Mita

Service Manager at PwC

The documentation is adequate, but team members coming into a project could benefit from more guided, interactive tutorials, ideally leveraging real-world data.

Timothy Spangler

Senior Software Engineer at Los Angeles Times Communications, LLC

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Setup Cost

AWS Auto Scaling costs vary; perceived as reasonable or expensive, depending on scaling extent, application needs, and usage.

Datadog's pricing is flexible, influenced by organization size and usage, but monitoring is essential to manage potential extra costs.

The pricing of Auto Scaling is medium range, neither high nor low.

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AWS Cloud at AeonX Digital Solutions Pvt. Ltd.

The setup cost for Datadog is more than $100.

reviewer1599867

Senior Performance and Architecture Analyst at a manufacturing company with 10,001+ employees

Everybody wants the agent installed, but we only have so many dollars to spread across, so it's been difficult for me to prioritize who will benefit from Datadog at this time.

Laurie Mordick

Applications Web Services Technical Engineer at Ace Hardware

My experience with pricing, setup cost, and licensing is that it is really expensive.

reviewer2767245

Senior Site Reliability Engineer at a wholesaler/distributor with 5,001-10,000 employees

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Valuable Features

AWS Auto Scaling offers automated scaling, integrates with CloudWatch, supports Kubernetes, and enhances performance through efficient resource management.

Datadog delivers real-time monitoring and insights with intuitive UI, enhancing performance optimization, scalability, and cross-team collaboration.

During peak traffic times, the Auto Scaling group can be deployed to ensure that the client works well, and the traffic remains average.

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AWS Cloud at AeonX Digital Solutions Pvt. Ltd.

The automation aspect where you can automate it to whatever you want is what I value the most about Auto Scaling.

Ishaka Michael Efe

DevOps Engineer Intern at HNG Tech

Its automatic scaling capabilities are very useful.

Mbula Mboma

AWS Cloud Re-Start Program Specialist at Orange RDC (Congo)

Our architecture is written in several languages, and one area where Datadog particularly shines is in providing first-class support for a multitude of programming languages.

Timothy Spangler

Senior Software Engineer at Los Angeles Times Communications, LLC

Having all that associated analytics helps me in troubleshooting by not having to bounce around to other tools, which saves me a lot of time.

reviewer2767245

Senior Site Reliability Engineer at a wholesaler/distributor with 5,001-10,000 employees

Datadog was able to find the alerts and trigger to notify our team in a very prompt manner before it got worse, allowing us to promptly adjust and remediate the situation in time.

Nikki L.

Security Engineer at Invitation Homes

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Categories and Ranking

AWS Auto Scaling

Ranking in Application Performance Monitoring (APM) and Observability

14th

Average Rating

8.8

Reviews Sentiment

6.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Datadog

Ranking in Application Performance Monitoring (APM) and Observability

1st

Average Rating

8.6

Reviews Sentiment

6.9

Number of Reviews

211

Ranking in other categories

Network Monitoring Software (3rd), IT Infrastructure Monitoring (2nd), Log Management (3rd), Container Monitoring (2nd), Cloud Monitoring Software (2nd), AIOps (1st), Cloud Security Posture Management (CSPM) (5th), AI Observability (1st)

Mindshare comparison

As of January 2026, in the Application Performance Monitoring (APM) and Observability category, the mindshare of AWS Auto Scaling is 0.4%, up from 0.1% compared to the previous year. The mindshare of Datadog is 5.5%, down from 9.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Application Performance Monitoring (APM) and Observability Market Share Distribution
Product	Market Share (%)
Datadog	5.5%
AWS Auto Scaling	0.4%
Other	94.1%

Application Performance Monitoring (APM) and Observability

Featured Reviews

Ishaka Michael Efe

DevOps Engineer Intern at HNG Tech

Automation has simplified traffic management and improved workload efficiency

I'm not really sure what improvements I would want to see in AWS Auto Scaling because I haven't really used it extensively or explored most of it. To the extent that I've used it so far, I think it is very good. I can't really say for certain what should be improved because I haven't really explored it a lot. However, what I've been using it for has been very good. If there could be training for AWS Auto Scaling, that would be fine. If you could add more training on how to use it correctly and on the functions that I haven't used before or some people have not really used before, that would help. If there could be more documentation and training on it, that would be beneficial.

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Dhroov Patel

Site Reliability Engineer at Grainger

Has improved incident response with better root cause visibility and supports flexible on-call scheduling

Datadog needs to introduce more hard limits to cost. If we see a huge log spike, administrators should have more control over what happens to save costs. If a service starts logging extensively, I want the ability to automatically direct that log into the cheapest log bucket. This should be the case with many offerings. If we're seeing too much APM, we need to be aware of it and able to stop it rather than having administrators reach out to specific teams. Datadog has become significantly slower over the last year. They could improve performance at the risk of slowing down feature work. More resources need to go into Fleet Automation because we face many problems with things such as the Ansible role to install Datadog in non-containerized hosts. We mainly want to see performance improvements, less time spent looking at costs, the ability to trust that costs will stay reasonable, and an easier way to manage our agents. It is such a powerful tool with much potential on the horizon, but cost control, performance, and agent management need improvement. The main issues are with the administrative side rather than the actual application.

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Use our free recommendation engine to learn which Application Performance Monitoring (APM) and Observability solutions are best for your needs.

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Top Industries

By visitors reading reviews

No data available

Financial Services Firm

14%

Computer Software Company

12%

Manufacturing Company

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	12
Midsize Enterprise	2
Large Enterprise	11

By reviewers
Company Size	Count
Small Business	80
Midsize Enterprise	46
Large Enterprise	99

Questions from the Community

What do you like most about AWS Auto Scaling?

The tool's most valuable feature is vertical auto-scaling, which is easy to use. However, most companies now prefer horizontal scaling. I set up the health check integration to monitor CPU usage. W...

What is your experience regarding pricing and costs for AWS Auto Scaling?

I'm not sure about the pricing aspect of AWS Auto Scaling or the cost of it.

What needs improvement with AWS Auto Scaling?

Any advice about APM solutions?

There are many factors and we know little about your requirements (size of org, technology stack, management systems, the scope of implementation). Our goal was to consolidate APM and infra monitor...

Datadog vs ELK: which one is good in terms of performance, cost and efficiency?

With Datadog, we have near-live visibility across our entire platform. We have seen APM metrics impacted several times lately using the dashboards we have created with Datadog; they are very good c...

Which would you choose - Datadog or Dynatrace?

Our organization ran comparison tests to determine whether the Datadog or Dynatrace network monitoring software was the better fit for us. We decided to go with Dynatrace. Dynatrace offers network ...

Akamai mPulse vs AWS Auto Scaling

Comparisons

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Compared 30% of the time

Splunk ITSI (IT Service Intelligence) vs AWS Auto Scaling

Compared 22% of the time

Splunk Enterprise Security vs AWS Auto Scaling

Compared 18% of the time

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Dynatrace vs Datadog

Compared 9% of the time

Azure Monitor vs Datadog

Compared 5% of the time

New Relic vs Datadog

Compared 4% of the time

Splunk Enterprise Security vs Datadog

Compared 3% of the time

Splunk AppDynamics vs Datadog

Compared 3% of the time

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Product Reports

Application Performance Monitoring (APM) and Observability

January 2026

Download AWS Auto Scaling product report

Download Datadog product report

January 2026

Also Known As

AWS Auto-Scaling

No data available

Overview

AWS Auto Scaling monitors your applications and automatically adjusts capacity to maintain steady, predictable performance at the lowest possible cost. Using AWS Auto Scaling, it’s easy to setup application scaling for multiple resources across multiple services in minutes. The service provides a simple, powerful user interface that lets you build scaling plans for resources including Amazon EC2 instances and Spot Fleets, Amazon ECS tasks, Amazon DynamoDB tables and indexes, and Amazon Aurora Replicas. AWS Auto Scaling makes scaling simple with recommendations that allow you to optimize performance, costs, or balance between them. If you’re already using Amazon EC2 Auto Scaling to dynamically scale your Amazon EC2 instances, you can now combine it with AWS Auto Scaling to scale additional resources for other AWS services. With AWS Auto Scaling, your applications always have the right resources at the right time.

Amazon Web Services (AWS)

Datadog integrates extensive monitoring solutions with features like customizable dashboards and real-time alerting, supporting efficient system management. Its seamless integration capabilities with tools like AWS and Slack make it a critical part of cloud infrastructure monitoring.

Datadog offers centralized logging and monitoring, making troubleshooting fast and efficient. It facilitates performance tracking in cloud environments such as AWS and Azure, utilizing tools like EC2 and APM for service management. Custom metrics and alerts improve the ability to respond to issues swiftly, while real-time tools enhance system responsiveness. However, users express the need for improved query performance, a more intuitive UI, and increased integration capabilities. Concerns about the pricing model's complexity have led to calls for greater transparency and control, and additional advanced customization options are sought. Datadog's implementation requires attention to these aspects, with enhanced documentation and onboarding recommended to reduce the learning curve.

What are Datadog's Key Features?

Sharable Dashboards: Facilitate collaboration with customizable, intuitive dashboards.
Extensive Integrations: Seamlessly connects with tools like Slack and AWS to support workflows.
APM and RUM: Provides deep insights into application performance and user interactions.
Real-Time Tools: Enables agile responses to system issues with real-time monitoring.
Unified Tagging and Visualization: Eases management of complex systems with simplified visualization.

What Benefits and ROI Should Users Look For?

Efficient Troubleshooting: Centralized logging speeds up the identification and resolution of issues.
Streamlined Workflows: Integrations with popular tools enhance operational efficiency.
Improved Observability: Comprehensive monitoring improves system reliability and performance.
Resource Optimization: Efficient microservices and container management leads to better cloud resource utilization.
Responsive Alerts: Customizable alerts ensure timely identification of critical issues.

In industries like finance and technology, Datadog is implemented for its monitoring capabilities across cloud architectures. Its ability to aggregate logs and provide a unified view enhances reliability in environments demanding high performance. By leveraging real-time insights and integration with platforms like AWS and Azure, organizations in these sectors efficiently manage their cloud infrastructures, ensuring optimal performance and proactive issue resolution.

Sample Customers

Expedia, Intuit, Royal Dutch Shell, Brooks Brothers

Adobe, Samsung, facebook, HP Cloud Services, Electronic Arts, salesforce, Stanford University, CiTRIX, Chef, zendesk, Hearst Magazines, Spotify, mercardo libre, Slashdot, Ziff Davis, PBS, MLS, The Motley Fool, Politico, Barneby's