Root cause detection in Kubernetes has become faster and troubleshooting is now centralized
What is our primary use case?
I use
Komodor for troubleshooting the platform, focused on tracking logs and also things like crashes and configuration. We use it in our
Kubernetes in the CI/CD pipeline.
After a new deployment, sometimes the pod crashes and fails, so we use Komodor to open it in the timeline and see the deployment, the config, and understand the config that was changed right before the failure. For example, once we deployed something and the pod crashed, we tried to understand why it crashed, and thanks to Komodor, we found out that the environment variable was missing. In conclusion, we use Komodor to trace a production issue in the deployment, and the timeline showed the configuration change that caused the pod crashes, allowing us to roll back immediately.
Komodor also provides us the ability to see all the services we have, giving us a full picture of everything. It helps us understand why our CI/CD pipeline was not stable. Our cluster changed, we found new images version deployed, and that was a real bug. Thanks to Komodor, we found this flaky situation in our CI/CD and fixed it.
What is most valuable?
The best features Komodor offers include visibility, the ability to see your services, and control your pods.
Visibility and the ability to see services and control pods helped our workflow significantly by allowing me to debug quickly. For example, we use it for debugging. I used to jump between logs and do things manually, and that took time. That is how we worked in my previous position. But in this company, we use Komodor, and I see everything in one timeline. I immediately understand what changed, and it takes me straight to the root cause.
The investigation is reduced thanks to Komodor, which makes it more clear to understand the whole picture. Otherwise, I would need to curl every request to check if it is alive or just run ps to understand if it is alive. But with Komodor, I see everything in one timeline.
The real impact in terms of time savings is in debugging. For example, instead of spending thirty to sixty minutes jumping between logs and different commands, I can usually define the root cause within a minute by using Komodor timeline. We can easily see what has changed between deploys, allowing us to pinpoint the root cause directly and removing the guesswork so I can focus on the actual issue.
What needs improvement?
Perhaps a deeper integration with logs and metrics would help. Today, I still need to jump to an external tool such as a logging or monitoring platform to fully understand the issue. Although Komodor is really good, having richer logs and metrics directly inside Komodor would reduce context switching. I really appreciate the timeline; it is great, but it still requires manual analysis. If Komodor could highlight it or perhaps give some artificial intelligence insights, that would be helpful. Sometimes I need to spend a lot of time to find specific issues, especially when I have different microservices that I need to drill down to find. If there were artificial intelligence insights available where I could write down my problem, it could really improve the experience, especially for junior developers who struggle since they do not know exactly what services are available.
Solving the issue of reducing the switching between tools would be beneficial. I still need to switch tools, not so much, but I do use different logs such as Splunk.
For how long have I used the solution?
In the current company, from the day I arrived, we have used Komodor. In other companies, I used different solutions and various logging tools.
What do I think about the stability of the solution?
What do I think about the scalability of the solution?
We use Komodor with many services, so I believe the scalability is really fine.
Which solution did I use previously and why did I switch?
In this company, we did not evaluate any other solutions besides Komodor; I came in and it was already in use. In my previous company, we used
Coralogix, which is similar but different.
What was our ROI?
It saves us time in investigating, providing a clear root cause on a timeline, which is a significant time-saving aspect.
What other advice do I have?
My advice for others looking into using Komodor is that it helps you quickly find a root cause in
Kubernetes without guesswork. That is my belief regarding its effectiveness.
If you have many services, frequent deployments, and constant changes, Komodor will be a great solution for understanding the root cause when something goes wrong. You can see all the changes in a timeline, figure out the crashes, reduce the time investment in understanding problems, and minimize the need to jump between different log tools. I would rate this product an eight out of ten. Therefore, I recommend choosing Komodor.
DAP experience with Komondor
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.
Effortless Onboarding and Time-Saving for Kubernetes Monitoring & Troubleshooting
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.
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.
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
Unified cloud workloads have become visible and teams manage kubernetes issues efficiently
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.
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.
Komodor: An Effective Solution with AI, but at a High Cost
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.
Komodor is great for leaner k8s teams
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.
Komdoor review as a Kubernetes admin
What do you like best about the product?
User-friendly interface.
Users with little knowledge had an easy way of querying Kubernetes object in a graphical interface.
Basic metrics are easy to query.
What do you dislike about the product?
When it comes to visualizing Kubernetes object a lot of similar functionality is also offered by free tools such as Headlamp and OpenLens.
For monitoring information we would still require our Prometheus / Grafana stack for our specific dashboarding / historical queries. We would prefer means of providing a single pane of glass.
What problems is the product solving and how is that benefiting you?
We have a lot of non-technical user that need to query information inside the Kubernetes cluster.
Komodor provided an intuitive way to do that.
Making managing production deployments easy
What do you like best about the product?
The ability to quickly find problems amongst hundreds or thousands of running containers. The AI-assisted troubleshooting tool is very useful, and can quickly scan logs and find the root cause of problems.
What do you dislike about the product?
Searching for a service amongst lots of similarly named services is not as easy as I would like. If I have a lot of copies of the same service in different environments, then sometimes the search doesn't immediately bring back exactly what I want, especially if I'm not sure of the exact name of the k8s namespace or environment where the service lives.
What problems is the product solving and how is that benefiting you?
Monitoring to confirm everything is working after an upgrade is easy, as is identifying problems if something goes wrong.
Komodor Gives Valuable Insight into our Clusters
What do you like best about the product?
Having a UI to explore kubernetes resources is nice. It has also been helpful in troubleshooting. Moreover, it gives some of our developers the ownership to triage their own issues without needing to rope in SRE.
What do you dislike about the product?
Sometimes it lacks detail that is available in kubectl.
What problems is the product solving and how is that benefiting you?
Container management and cost savings have been huge. Also being able to see some basic metrics at a glance is nice. The AI as also helped us solve a few issues.
Smooth Setup, Effective Monitoring UI
What do you like best about the product?
I appreciate Komodor's easy setup process and its user-friendly interface, which simplifies monitoring services in my Kubernetes clusters. The GUI is helpful, making it straightforward to browse and monitor deployments and resources at a glance. I also value the ability to open a shell in any running Kubernetes pod without relying on the CLI, streamlining the process further. Komodor's features make retrieving metrics and monitoring status efficient and manageable, contributing greatly to my workflow.
What do you dislike about the product?
I find that Komodor could be a bit snappier in its performance. Additionally, it lacks the functionality to persist logs for pods that have already been deleted for a certain amount of time.
What problems is the product solving and how is that benefiting you?
Komodor allows me to easily monitor and retrieve metrics for Kubernetes deployments, offering a UI to view services and resources, which enhances flexibility over just using the Kubernetes API.
