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What is Serverless?

Featured Serverless reviews

Serverless mindshare

As of April 2026, the mindshare of Serverless in the Enterprise Architecture Management category stands at 0.3%, according to calculations based on PeerSpot user engagement data.
Enterprise Architecture Management Mindshare Distribution
ProductMindshare (%)
Serverless0.3%
Sparx Systems Enterprise Architect8.6%
LeanIX8.1%
Other83.0%
Enterprise Architecture Management

PeerResearch reports based on Serverless reviews

TypeTitleDate
CategoryEnterprise Architecture ManagementApr 13, 2026Download
ProductReviews, tips, and advice from real usersApr 13, 2026Download
ComparisonServerless vs erwin Data ModelerApr 13, 2026Download
ComparisonServerless vs LeanIXApr 13, 2026Download
ComparisonServerless vs SAP PowerDesignerApr 13, 2026Download
 
 
Key learnings from peers
Last updated Apr 13, 2026

Valuable Features

Room for Improvement

ROI

Pricing

Popular Use Cases

Service and Support

Deployment

Scalability

Stability

Review data by company size

By reviewers
Company SizeCount
Small Business5
Midsize Enterprise2
Large Enterprise4
By reviewers
By visitors reading reviews
Company SizeCount
Small Business32
Midsize Enterprise57
Large Enterprise15
By visitors reading reviews

Top industries

By visitors reading reviews
Construction Company
38%
Financial Services Firm
12%
Comms Service Provider
7%
Outsourcing Company
7%
Healthcare Company
6%
Engineering Company
5%
Computer Software Company
4%
Transportation Company
4%
Energy/Utilities Company
3%
Manufacturing Company
3%
Insurance Company
2%
Educational Organization
2%
Religious Institution
2%
University
1%
Aerospace/Defense Firm
1%
Government
1%
Marketing Services Firm
1%
Performing Arts
1%
Pharma/Biotech Company
1%
Agriculture
1%

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Serverless Reviews Summary
Author infoRatingReview Summary
Software developer4.0We found Serverless excellent for API back-ends and data processing, offering significant cost savings and seamless auto-scaling. Its rapid deployment and minimal infrastructure management boosted our team's efficiency, despite minor cold start and debugging challenges.
Senior Software Engineer at Tech93.5I value Serverless for internal applications due to its flexibility, AWS integration, and significant cost/time savings. While stable and scalable, its unique syntax creates a steep learning curve. I recommend checking specific requirements and team readiness beyond just cost benefits.
Working For M Bank at a financial services firm with 51-200 employees4.5I find Serverless stable and scalable for AWS Lambda deployments, praising its plugins, debugging, and fast release speed over SAM. However, I believe the UI needs improvement and current licensing costs are too expensive, preventing a perfect score.
Software Engineer at CyberSquadInc4.5I use Serverless for deploying IoT APIs, valuing its serverless operations, easy deployment, and cost-efficiency. It saves time, reduces personnel needs, and is a stable, essential tool, though local development setup is complex.
Dev Ops Engineer at a engineering company with 5,001-10,000 employees3.5I use Serverless for cost-effective microservice testing, development, and compliance, valuing its auto-scaling and ROI. It's 7/10 for testing, but I warn against production use and advise careful coding to prevent high costs.
doing work to build health first health care solutions at Providence Healthcare4.0I use Serverless for building REST backends and data transformations, valuing its significant cost optimization and scalability. Despite cold start and memory limitations, its positive impact and ease of deployment earn it an 8/10 overall.
AI Engineer at a consultancy with 11-50 employees4.0I use Serverless for scalable back-end APIs and microservices, saving up to 50% on AWS costs by utilizing resources only when needed. It handles simultaneous jobs efficiently, though cold starts exist. I'd prefer more provider independence.
Full Stack Developer4.0I use Serverless for scalable API functions, valuing its pay-as-you-go model, quick deployment, and flexibility. It saves time and resources. While stable and scalable, I'd appreciate improved debugging and more holistic monitoring information.