We performed a comparison between AWS Auto Scaling and Sumo Logic Observability based on real PeerSpot user reviews.
Find out in this report how the two Application Performance Monitoring (APM) and Observability solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The solution helps optimize the cost of the AWS environment."
"AWS Auto Scaling is cost-effective and very useful for businesses."
"The various scaling options available, such as step scaling, are particularly useful."
"It efficiently handles traffic, ensuring we are not running expenses and the infrastructure is strong enough to handle the load."
"I like the graphs provided by the tool."
"When a lot of traffic comes into our organization, the product scales our instances based on our environment’s requirements."
"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."
"The most valuable feature of the solution is that it scales automatically without manual intervention based on the metrics we provide."
"I have not seen any stability issues in the product."
"The product is easy to learn."
"Alerting and consistency are key. We have different tiers with log collectors, and continuous querying provides near-real-time updates. It's almost like instantly when something happens, like pending transactions or error fees. This helps reduce incident resolution time compared to waiting for thresholds on other platforms. We can continue logging in with them seamlessly and quickly get into action."
"Sumo Logic Observability presents a range of valuable features, including well-crafted dashboards and a diverse selection of helpful apps. However, personally, I don't hold a favorable opinion of the solution. While I don't struggle with writing queries, my main difficulty lies in recruiting competent individuals and ensuring their proficiency in utilizing the solution. This often leads to additional challenges and complexities. From my perspective, when compared to Microsoft Sentinel or even Splunk, Sumo Logic Observability has a steeper learning curve. One contributing factor to this disparity is the solution's long existence in the market compared to Synlogic. Nevertheless, I acknowledge that there are capable and knowledgeable professionals employed at Sumo Logic Observability. The effectiveness of the solution largely depends on how it is integrated into your internal operations and environment. Its utility and benefits can vary significantly. It is worth noting that organizations like the NSA and, I believe, the CIA used it in the past, primarily for rapidly searching and analyzing large volumes of data. To leverage its capabilities effectively, you must determine how to tailor it to your specific needs."
"The solution allows multiple groups to converge on a unified platform, allowing for different utilization by various teams."
"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 tool must include AI features."
"The setup can be a bit complex in some situations."
"The solution is not out-of-the-box and you have to study to use it. It should be more easier to use."
"The product’s security features need improvement."
"In comparison to other public clouds, the product is costly."
"The speed of the solution must be improved."
"Documentation could be better. While it's generally good, sometimes finding what you need requires extensive searching. It's not always clear where to look for specific things."
"Implementing a more streamlined enrichment process, and conceptualizing the observability data collection as an ETL pipeline would be helpful."
"Fine-grained data can be quite frustrating to work with and should be made easier."
"SearchUI.exe is a bit clunky in the product, making it an area where the product needs improvements."
AWS Auto Scaling is ranked 15th in Application Performance Monitoring (APM) and Observability with 18 reviews while Sumo Logic Observability is ranked 29th in Application Performance Monitoring (APM) and Observability with 5 reviews. AWS Auto Scaling is rated 8.8, while Sumo Logic Observability is rated 8.0. The top reviewer of AWS Auto Scaling writes "The product helps reduce costs and avoids interruptions to the customer experience". On the other hand, the top reviewer of Sumo Logic Observability writes "Easy creation of custom fields, no need to alter applications; supports ten active logging applications simultaneously and faster than aster than default search tools". AWS Auto Scaling is most compared with , whereas Sumo Logic Observability is most compared with Dynatrace, New Relic, Prometheus and Chronosphere. See our AWS Auto Scaling vs. Sumo Logic Observability report.
See our list of best Application Performance Monitoring (APM) and Observability vendors.
We monitor all Application Performance Monitoring (APM) and Observability 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.
