The price is reasonable, considering the value it delivers. In all honesty, once you have your optimal design, you could just turn it off and then activate it maybe once every six months or once every year to make a check again. You only need it in the beginning. Once people are optimized and fine-tuned, you can stop monitoring. So, it's very well designed. It's a good product. It's it's running nicely. It gives us fair numbers of advice on how to improve costs. There's a small licensing fee, but you don't need to run it 24/7. Initially, you might use it full-time for a few months to gather data, then switch to periodic monitoring like monthly or bi-monthly. Ultimately, the cost savings from optimization outweigh the licensing fee. The price scales based on your monitoring parameters, such as the frequency and duration of data collection. The more data you collect, the more you pay for it.
We opted for the open-source version as our team comprised Kubernetes specialists with certifications in the field. Although we didn't personally use the paid version, I acknowledge that it could be a worthwhile investment. The cost of the tool may seem nominal compared to the potential savings in infrastructure expenses. The decision to go for the paid version might depend on the scale of your environment. For smaller clusters, the open-source version can provide sufficient insights. However, for larger environments with hundreds of nodes and thousands of containers, exploring the paid version could be a beneficial consideration.
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The price is reasonable, considering the value it delivers. In all honesty, once you have your optimal design, you could just turn it off and then activate it maybe once every six months or once every year to make a check again. You only need it in the beginning. Once people are optimized and fine-tuned, you can stop monitoring. So, it's very well designed. It's a good product. It's it's running nicely. It gives us fair numbers of advice on how to improve costs. There's a small licensing fee, but you don't need to run it 24/7. Initially, you might use it full-time for a few months to gather data, then switch to periodic monitoring like monthly or bi-monthly. Ultimately, the cost savings from optimization outweigh the licensing fee. The price scales based on your monitoring parameters, such as the frequency and duration of data collection. The more data you collect, the more you pay for it.
The cost is cheap. Kubecost has an open-source core.
We opted for the open-source version as our team comprised Kubernetes specialists with certifications in the field. Although we didn't personally use the paid version, I acknowledge that it could be a worthwhile investment. The cost of the tool may seem nominal compared to the potential savings in infrastructure expenses. The decision to go for the paid version might depend on the scale of your environment. For smaller clusters, the open-source version can provide sufficient insights. However, for larger environments with hundreds of nodes and thousands of containers, exploring the paid version could be a beneficial consideration.