AWS Auto Scaling vs OpenText Diagnostics comparison

Why PeerSpot?

Amazon Web Services (AWS) and OpenText are both solutions in the Application Performance Monitoring (APM) and Observability category. Amazon Web Services (AWS) is ranked #42 with an average rating of 8.5, while OpenText is ranked #65. Amazon Web Services (AWS) holds a 0.5% mindshare in APM, compared to OpenText’s 0.7% mindshare. Additionally, 92% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 75% of OpenText users who would recommend it.

AWS Auto Scaling

Read 22 AWS Auto Scaling reviews

2,590 Views
2,486 Comparison Views

92% willing to recommend

OpenText Diagnostics

Read 4 OpenText Diagnostics reviews

2,312 Views
2,266 Comparison Views

75% willing to recommend

AWS Auto Scaling

OpenText Diagnostics

Comparison Buyer's Guide

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Executive SummaryUpdated on Jul 24, 2024

OpenText Diagnostics and AWS Auto Scaling are competitive solutions for diagnostics and auto-scaling needs. AWS Auto Scaling appears to have the upper hand due to its feature-rich offerings, superior customer support, and scalability, despite higher pricing.

What features are offered by OpenText Diagnostics in comparison to AWS Auto Scaling?

OpenText Diagnostics offers comprehensive diagnostic analytics, detailed reporting capabilities, and valuable detailed insights. AWS Auto Scaling provides seamless horizontal scaling, robust automation features, and extensive scalability options.

What areas of improvement can be found in OpenText Diagnostics in comparison to AWS Auto Scaling?

OpenText Diagnostics could enhance its integration capabilities, improve performance during peak loads, and refine customer service responsiveness. AWS Auto Scaling users recommend better customizability, more user-friendly configuration options, and more extensive integration possibilities.

How is the ease of deployment and customer service of OpenText Diagnostics in comparison to AWS Auto Scaling?

OpenText Diagnostics is noted for its straightforward deployment, complemented by mixed feedback on customer service responsiveness. AWS Auto Scaling has a smooth deployment process and excellent customer service, making it favorable for users.

What setup costs and ROI can be seen with OpenText Diagnostics in comparison to AWS Auto Scaling?

OpenText Diagnostics users highlight its affordable setup costs and strong ROI, especially for SMEs. AWS Auto Scaling's higher pricing is justified by its extensive features, providing significant ROI in scalability and automation benefits. AWS Auto Scaling delivers better value despite the higher cost.

To learn more, read our detailed AWS Auto Scaling vs. OpenText Diagnostics Report (Updated: September 2026).

Buyer's Guide

AWS Auto Scaling vs. OpenText Diagnostics

September 2026

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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:

Categories and Ranking

AWS Auto Scaling

Ranking in Application Performance Monitoring (APM) and Observability

42nd

Average Rating

8.8

Reviews Sentiment

6.6

Number of Reviews

Ranking in other categories

No ranking in other categories

OpenText Diagnostics

Ranking in Application Performance Monitoring (APM) and Observability

65th

Average Rating

7.8

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of October 2026, in the Application Performance Monitoring (APM) and Observability category, the mindshare of AWS Auto Scaling is 0.5%, up from 0.3% compared to the previous year. The mindshare of OpenText Diagnostics is 0.7%, up from 0.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Application Performance Monitoring (APM) and Observability Mindshare Distribution
Product	Mindshare (%)
AWS Auto Scaling	0.5%
OpenText Diagnostics	0.7%
Other	98.8%

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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Ravi Suvvari

Performance and Fault-tolerance Architect with 1,001-5,000 employees

Very good for transaction level monitoring, but expensive and HP needs better support and training

HP Diagnostics is a very good monitoring tool especially for transaction level monitoring -- it shows hot spots which can be drilled down to DB level, table, query, SP's, record and field level and also at Object level, Classes level,method or Augment levels instead of pinpointing bottlenecks at layer level it goes deep inside for information. It has very good tracing capabilities despite being an agent based tool compared to other agent less monitoring tools. Overall a very good tool for monitoring application diagnostics for quick and easy resolution with help of thread information. Drills down from slow, end-user transactions to the bottle necked component, method, or SQL statement, helping to solve memory, exception, and other common problems Key features and benefits • Automatically detects all components touched by a business process and traces them with no user intervention • Provides complete application visibility across the application lifecycle, enabling higher application quality when applications go live • Reduces mean time to resolution (MTTR) in your J2EE, .NET, ERP, or CRM (SAP, Oracle®, PeopleSoft) environment • Integrates fully with HP Business Availability Center software, HP LoadRunner, and HP Performance Center.

Read full review

Quotes from Members

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

Pros

"It can scale."

"The solution helps optimize the cost of the AWS environment."

"The various scaling options available, such as step scaling, are particularly useful."

"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. When it reaches seventy percent, it sends me an email notification."

"Once we moved them to AWS and created the appropriate architecture, it solved the problem."

"The most valuable feature is the ability to select a minimum amount of active servers so that a new server automatically launches if one fails."

"I would highly recommend Auto Scaling to others because it is a fantastic feature that simplifies scaling processes and makes deployment efficient."

"I like the graphs provided by the tool."

More AWS Auto Scaling pros

"The information from the diagnostics is detailed."

"For banking and telecom solutions, it's been quite useful."

"The diagnostics and configuration are the solution's most valuable aspects."

"HP Diagnostics is a very good monitoring tool especially for transaction level monitoring -- it shows hot spots which can be drilled down to DB level, table, query, SP's, record and field level and also at Object level, Classes level, method or Augment levels instead of pinpointing bottlenecks at layer level it goes deep inside for information."

"The most valuable feature of Micro Focus Diagnostics is the information reported from an application that has timed out. For example, when you're Googling, or you're booking a ticket for Burj Khalifa here, the longest tower in the world, there are situations where the system can time out. There are times when you might not receive a response on the payment gateway or you are not able to find the reservation. The customer only receives the information that the session has timed out."

Cons

"It has latency issues. It depends on the distribution used, whether it's Amazon Linux, Windows Linux, etc. Occasionally, there are latency issues, which might lead to slower performance."

"The billing and cost optimization of the solution could be improved."

"The solution's infrastructure scalability and elasticity could be improved."

"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."

"It requires a downtime before deploying the Auto Scaling group."

"The setup can be a bit complex in some situations."

"It could be cheaper."

"Setting up the configuration involves too much work for the cloud engineer, like configuring the ALB, the target group, and all the steps."

More AWS Auto Scaling cons

"Price is little expensive for number of license points and HP Diagnostics trainers are not available in market and no proper support from HP for any diagnotics level queries or issues."

"The interface is very old, and not very user-friendly. Most of our clients don't like the UI."

"The GUI and metrics of Micro Focus Diagnostics can be improved. The metrics the solution gathers can be limited and could be enhanced by giving more details."

"The interface could be more user friendly."

Pricing and Cost Advice

"AWS Auto Scaling's price is high."

"The product is expensive."

"The product has moderate pricing."

"AWS Auto Scaling is a cheap solution."

"AWS Auto Scaling is a pay-per-use and pay-as-you-use service."

"The pricing is good. I have not had any customers that have complained about the price."

"AWS Auto Scaling is an expensive solution."

Information not available

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Top Industries

By visitors reading reviews

Construction Company

15%

Outsourcing Company

14%

Educational Organization

11%

Comms Service Provider

Construction Company

16%

Financial Services Firm

14%

Performing Arts

Comms Service Provider

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	13
Midsize Enterprise	2
Large Enterprise	12

No data available

Questions from the Community

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.

See all answers

What needs improvement with AWS Auto Scaling?

AWS Auto Scaling can be improved in many ways, such as providing better visibility into scaling decisions and clarifying why exactly scaling happens. Sometimes, I am not sure why scaling occurs. Ea...

See all answers

What is your primary use case for AWS Auto Scaling?

My main use case for AWS Auto Scaling is automatically scaling EC2 instances behind a load balancer based on traffic, CPU, and memory usage, as well as custom CloudWatch metrics. I also use it with...

See all answers

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Comparisons

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Snyk vs AWS Auto Scaling

Compared 5% of the time

Splunk Enterprise Security vs AWS Auto Scaling

Compared 5% of the time

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Compared 15% of the time

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Compared 13% of the time

Broadcom DX Application Performance Management vs OpenText Diagnostics

Compared 7% of the time

Splunk Observability Cloud vs OpenText Diagnostics

Compared 6% of the time

OpenText SiteScope vs OpenText Diagnostics

Compared 5% of the time

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Product Reports

Buyer's Guide

Application Performance Monitoring (APM) and Observability

September 2026

Download AWS Auto Scaling product report

Buyer's Guide

Application Performance Monitoring (APM) and Observability

September 2026

Download OpenText Diagnostics product report

Also Known As

AWS Auto-Scaling

Micro Focus Diagnostics, MF Diagnostics

Overview

AWS Auto Scaling optimizes resource use by automatically adjusting instances based on demand. It integrates with CloudWatch for seamless monitoring, enhancing system reliability and cost efficiency without manual intervention.

AWS Auto Scaling is designed to dynamically scale resources in response to demand, supporting horizontal and vertical scaling for optimal performance. It integrates well with AWS services like EC2 and ECS, allowing for flexible and scalable solutions. Predictive scaling and intelligent automation reduce costs and ensure reliability, particularly during unpredictable traffic variations. Users implement it to maintain efficiency and minimize downtime, benefiting from features such as self-healing and health checks.

What are the key features of AWS Auto Scaling?

Automatic Scaling: Adjusts resources based on real-time demand metrics.
CloudWatch Integration: Seamless monitoring integration for efficient resource management.
Target Tracking: Maintains desired performance levels by adjusting resources as needed.
Scheduled Scaling: Pre-configure adjustments based on expected demand changes.
Self-Healing: Automatically replaces unhealthy instances to ensure maximum uptime.

What benefits should users expect from AWS Auto Scaling?

Cost Efficiency: Reduces cost by adjusting resources based on fluctuating demand.
Reliable Performance: Ensures consistent performance even with varying traffic levels.
Minimal Downtime: Automatically adapts to traffic changes to keep services running smoothly.
User-Friendly Interface: Simple operation with intuitive controls and configurations.
Flexibility: Supports a range of AWS services, adapting to different use cases and demands.

In industries with variable demand, AWS Auto Scaling is deployed to manage real-time traffic surges, ensuring efficient use of resources during periods such as events and festive seasons. Users grow dynamic environments while balancing costs and maintaining stability, integrating the tool with CI/CD processes for continuous and efficient deployment.

Amazon Web Services (AWS)

OpenText Diagnostics offers detailed transaction-level monitoring, providing insights at database, object, and method levels. It aims to improve application visibility and reduce mean time to repair (MTTR) while integrating smoothly with HP's software suite.

OpenText Diagnostics automatically detects components, allows for flexible configuration, and provides detailed diagnostic information of application timeouts. It is particularly useful in identifying root causes like database or network issues. However, there are challenges with its interface, high pricing, lack of trainers, and insufficient cloud-based environment support. It is widely used in finance and government sectors for examining application code.

What are the most important features?

Transaction-Level Monitoring: Provides deep insights at DB, object, and method levels.
Automatic Component Detection: Enhances application visibility by detecting components automatically.
Integration with HP Software: Fully integrates with HP's software for a seamless experience.
Performance Configuration: Allows adjustments for better performance.

What benefits should users look for?

Reduced MTTR: Quick identification and resolution of issues.
Detailed Diagnostics: Offers insights into timeouts and root causes.
Efficient Issue Identification: Valuable for pinpointing and understanding session timeouts.

In finance and government sectors, OpenText Diagnostics is used to efficiently view application data and code inspection. Organizations transitioning to cloud platforms like AWS for improved data management often use it alongside tools like Micro Focus BPM to enhance functionality across environments including SAP, Java, and MQ.

OpenText

Sample Customers

Expedia, Intuit, Royal Dutch Shell, Brooks Brothers

BSkyB, Alior Bank

Buyer's Guide

AWS Auto Scaling vs. OpenText Diagnostics

September 2026

Free Report: AWS Auto Scaling vs. OpenText Diagnostics

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