Sold by: Komodor
Deployed on AWS
The Only, Unified Dev-First Kubernetes Platform. Easily Operate, Troubleshoot & Optimize Your Application Costs.
4.4
Overview
Todays microservices systems are complex, distributed and they are constantly changing. Keeping track of so many moving parts in so many places often seems nearly impossible. Komodor is the missing piece in the DevOps tool chain, enabling teams to gain control over their entire stack. Komodor tracks alerts and changes (such as code, configs and deploys) across the entire K8s-based stack, analyzing their ripple effect and then providing devs, DevOps and SRE teams the context they need to troubleshoot efficiently. For private offers above 1 node contact awsmarketplace@komodor.com
Highlights
- Automatic Troubleshooting
- Kubernetes Observability
- Assisted Remediation
Details
Sold by
Delivery method
Deployed on AWS
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Pricing
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/12 months |
|---|---|---|
Additional vCPUs | Price per additional vCPU | $132.00 |
Komodor Enterprise - 1,000 vCPUs included | Enterprise platform pricing - including the first 1,000 vCPUs | $150,000.00 |
Vendor refund policy
No Refund
Legal
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Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
Resources
Vendor resources
Support
Vendor support
docs.komodor.com support@komodor.com
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Updated weekly
By Komodor
By Observe, Inc.
Top
100
In Monitoring
Top
10
In Issue & Bug Tracking, Monitoring and Observability
Top
10
In Application Performance and UX Monitoring
Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
Ease of use
Customer service
Cost effectiveness
Positive reviews
Mixed reviews
Negative reviews
AI generated from product descriptions
Kubernetes Monitoring
Real-time tracking of alerts and changes across Kubernetes-based infrastructure
Distributed System Analysis
Comprehensive tracking and analysis of microservices interactions and dependencies
Troubleshooting Automation
Intelligent system for identifying and correlating changes affecting application performance
Infrastructure Observability
Detailed visibility into configuration, deployment, and code changes across entire stack
Incident Context Generation
Automated contextual insights for development, DevOps, and SRE teams to diagnose system issues
Distributed Tracing
Autonomously deploys tracing in serverless and containerized environments with single-click configuration
Log Correlation
Automatically correlates log data with distributed tracing for enhanced performance and troubleshooting
System Architecture Mapping
Generates real-time, auto-updated system architecture map based on actual execution data
Transaction Monitoring
Provides comprehensive end-to-end transaction tracking with detailed context and performance insights
Smart Alerting
Preconfigured intelligent alerting mechanism that detects and notifies critical issues in application infrastructure
Data Ingestion Capability
Supports petabyte-scale telemetry ingestion with high-performance processing across logs, metrics, and traces
AI-Powered Troubleshooting
Utilizes natural language processing and AI-driven root cause analysis for complex incident investigation
Knowledge Graph Technology
Implements a proprietary Knowledge Graph for structured data correlation and advanced search capabilities
Open Data Lake Architecture
Built on Snowflake data lake infrastructure enabling flexible and scalable telemetry storage and analysis
Multi-Dimensional Telemetry Analysis
Enables context-aware correlation across different observability data types including logs, metrics, and distributed traces
Standard contract
No
Customer reviews
Nati S.
DAP experience with Komondor
Reviewed on Dec 25, 2025
Review provided by G2
What do you like best about the product?
We selected Komodor to support the launch of the Dell Automation Platform (DAP) SaaS control plane, using it as a mission control for managing customers’ private cloud, edge, and AI infrastructure. Unlike traditional APM tools, Komodor is purpose-built for Kubernetes management, making it highly intuitive and delivering deep insights with minimal overhead. Their support team has also been responsive and helpful throughout our implementation.
What do you dislike about the product?
There are areas in their UI such as the cost reports, that could be more intuitive
What problems is the product solving and how is that benefiting you?
Komodor has become the Dell Automation Platform’s first line of defense for Kubernetes troubleshooting and reliability engineering, as demonstrated by strong developer adoption and growing preference over traditional APM solutions. Its intuitive, AI-powered UI simplifies workflows and provides guided insights, enabling us to significantly reduce MTTR and minimize escalations to the SRE team. This allowed us to maintain high service quality and end-user support without increasing headcount.
Yuval R.
Effortless Onboarding and Time-Saving for Kubernetes Monitoring & Troubleshooting
Reviewed on Dec 23, 2025
Review provided by G2
What do you like best about the product?
Komodor has been a game-changer for our team. It significantly accelerates the RCA process for Kubernetes-related issues and even helps us troubleshoot our own applications. Adoption was quick, and the value became clear almost immediately.
Their AI agent, Klaudia, now supports uploaded context, allowing it to better understand your product and environment—an impressive feature that enhances troubleshooting efficiency.
On top of that, their support during onboarding and day-2 operations is truly top-class. The experience has been smooth, and the team is always responsive and helpful.
Their AI agent, Klaudia, now supports uploaded context, allowing it to better understand your product and environment—an impressive feature that enhances troubleshooting efficiency.
On top of that, their support during onboarding and day-2 operations is truly top-class. The experience has been smooth, and the team is always responsive and helpful.
What do you dislike about the product?
Komodor’s cost optimization capabilities are adaptable and precise. With the right configuration and enough time, it can deliver meaningful savings—even for complex applications and environments.
That said, I’d love to see deeper integration with multiple cloud providers to better handle edge cases like Reserved Instances or AWS Fargate. This would make cost estimation even more accurate and comprehensive.
That said, I’d love to see deeper integration with multiple cloud providers to better handle edge cases like Reserved Instances or AWS Fargate. This would make cost estimation even more accurate and comprehensive.
What problems is the product solving and how is that benefiting you?
RCA assistance for Devops and developers
Cost overview and optimization paths
Versioning of deployed charts and comparison
Better RBAC control than via AWS EKS IAM.
K8s clusters inventory
Cost overview and optimization paths
Versioning of deployed charts and comparison
Better RBAC control than via AWS EKS IAM.
K8s clusters inventory
reviewer2785698
Unified cloud workloads have become visible and teams manage kubernetes issues efficiently
Reviewed on Dec 10, 2025
Review from a verified AWS customer
What is our primary use case?
My main use case for Komodor is visualizing the workloads that we deploy onto the Kubernetes infrastructure across all three major clouds using Azure , EKS, AKS, and Google Cloud . We use Komodor to ensure application teams and other teams can visualize their applications running on the Kubernetes infrastructure.
A specific example of how my team uses Komodor to visualize those workloads is that there are application teams who do not have access to Kubernetes jump hosts, so they use Komodor for accessing their applications from the Komodor UI. They use Komodor on a day-to-day basis to check if their workloads are running properly or if there are any issues. If the workloads are not running and are experiencing issues, they use Cloud AI integrated in Komodor for debugging the logs.
What is most valuable?
This is the main task that we use Komodor for, and one additional benefit is that it is also helpful for platform and site reliability engineers to check how many clusters are up and running and how many clusters are accepting the workloads from the users.
One of the best features that Komodor offers is Cloud AI, which debugs all the logs and gives the exact root cause for the issue. From there, we know we do not need an engineer who is an expert in Kubernetes to debug the issue.
Cloud AI has definitely helped my team by saving time, not in a single instance but in multiple cases where we have used Cloud AI for debugging issues in the Kubernetes pods.
Komodor has positively impacted our organization. Since adopting it, all the issues we faced while managing Rancher are gone, and we are seeing 100% availability for Komodor.
100% availability with Komodor means there have been improvements in uptime and productivity. For instance, when application teams want to deploy their applications, if Rancher is not up or running, the deployments usually fail at the deployment stage. In the case of Komodor, there have been no such cases reported after adopting it. We saw 100% uptime most of the time, except for some issues with AWS outages.
What needs improvement?
There are some features related to the platform that are missing in Komodor, such as Tigera status or CNI pods. Including these features would be helpful for platform engineers.
For how long have I used the solution?
I have been using Komodor for managing workloads on Kubernetes and Kubernetes-related infrastructure for the past nine to twelve months.
What do I think about the stability of the solution?
Komodor is stable in my experience.
What do I think about the scalability of the solution?
Komodor is very highly scalable in terms of infrastructure and in terms of the number of nodes we use.
How are customer service and support?
Customer support from Komodor is very good. I would rate the customer support from Komodor a ten out of ten.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
We previously used Rancher, and we faced issues with availability, which is why we switched to Komodor.
What was our ROI?
We saw around ninety percent ROI using Komodor.
What's my experience with pricing, setup cost, and licensing?
I am not involved in the pricing, setup cost, and licensing for Komodor, so someone from my team will take care of that. Compared with Rancher or any other tools, Komodor is priced cheaply and available at a fair price.
Which other solutions did I evaluate?
We did not evaluate any other options except Komodor before choosing it.
What other advice do I have?
I would like to add that there are other features in Komodor as well. Whatever application teams need, all the features in Komodor are available for visualizing the Kubernetes environment, so not just one feature but everything is helpful for application teams.
My advice for others looking into using Komodor is that if their main intention is for 100% availability for their application teams, Komodor is completely suitable for their needs.
Overall, Komodor is a very good platform for managing Kubernetes-related infrastructure, and as of now, my experience with Komodor is very positive. I would rate this review a nine out of ten.
Pablo B.
Komodor: An Effective Solution with AI, but at a High Cost
Reviewed on Nov 01, 2025
Review provided by G2
What do you like best about the product?
Komodor effectively assists in the troubleshooting in POD executions, and provides significant help with its integrated AI.
What do you dislike about the product?
This is a great tool, though its costs are higher than those of other options available on the market.
What problems is the product solving and how is that benefiting you?
Komodor is a valuable tool for efficiently addressing problems when incidents occur or when troubleshooting issues arise on the platform where I work. It has made the process of resolving such challenges much more manageable.
Tiago B.
Komodor is great for leaner k8s teams
Reviewed on Oct 27, 2025
Review provided by G2
What do you like best about the product?
Komodor serves as an excellent single pane of glass for Kubernetes. In our large environment, which includes over 1,000 nodes and 20,000 pods, it has significantly reduced the time needed to find root causes. My team has become more productive and can proactively address issues before they turn into incidents, thanks to Komodor.
What do you dislike about the product?
I was initially critical of their Cost Optimization features, but fortunately, they have made improvements. Now, I am able to get real value from them.
What problems is the product solving and how is that benefiting you?
Komodor has significantly helped us address incidents more efficiently. With their AI analysis tools, our mean time to resolution (MTTR) has dropped from several hours to just a few minutes.