I don't have a technical role, but we are a system integrator, so we sell solutions such as OpenShift and Kubernetes as part of the sales team. We are a reseller called eSky IT, and I serve as the Regional Manager. Our engineers have deployed Nutanix Kubernetes Engine NKE for testing purposes. The solution is very scalable, with the core of hyper-converged infrastructure being scalability with performance. Nutanix is very stable and reliable, based on my experience with many customers, including large banks and telcos. They have been operating reliably and scaling since their deployment. For Nutanix Kubernetes Engine NKE specifically, it makes more sense to implement it on-premises. The very few use cases I've seen were on-premises, not on the cloud, and it's unlikely you'll buy Nutanix on the cloud due to the extra costs involved. A valid use case I see is if you are running several on-prem NKP clusters and your cloud strategy is involves running some public cloud workloads as well. You want to be able to run a frictionless Kubernetes environment across all your sites, on-prem or cloud. You would opt in for NKP on a public cloud. Otherwise, it would be much more cost efficient to consume Kubernetes directly from your hyperscaler, such as EKS or AKS. I rate Nutanix Kubernetes Platform NKP five out of 10. Not for the product, for the constraints it has in addressing more customers looking for an enterprise Kubernetes platform.
Every six months, we upgrade AOS on all the clusters. I manage around 25 plus Nutanix clusters, which includes upgrading Prism Central and utilizing Lifecycle Manager (LCM) for the Nutanix clusters. After 10:00 PM Eastern Time, we have a maintenance window to implement changes. For critical application servers, we coordinate with the application team to get approvals and create change requests (CR) to proceed during off-business hours. If the DevOps team faces any computer resource crunch, they open a request, and I increase computer resources by adding new worker nodes to the cluster. If they cannot connect to the cluster, there's a possibility that the client's SSL certificate could expire, so I renew the client SSL certificate for each cluster as part of my daily troubleshooting tasks. I am not part of the DevOps team, as they handle application pod deployments and testing across different environments such as stage, development, and production. From my side as an infrastructure person, I solely manage the cluster level, not the application pods. However, I take care of Nutanix management pods, ensuring things like worker nodes or etcd nodes are operational. I have not yet utilized NKP, as I am just learning about it since a project is coming up to upgrade from Nutanix Kubernetes Engine NKE to NKP. The client has a minimal cloud footprint currently, but they plan to adopt NC2, the Nutanix Cloud Cluster, in the future, including moving some clusters from on-premises to the cloud. They also have a few Azure Kubernetes platforms but in very limited capacity, which the Windows team manages, so I do not have access to those environments. On a scale of 1-10, I rate Nutanix Kubernetes Engine NKE a 9.
Overall, I rate Nutanix Kubernetes Engine NKE as six to seven out of ten. I believe there is room for improvement, especially in terms of vendor certifications and industry integrations. However, I find Nutanix to be generally reliable and cost-effective.
Nutanix offers flexibility with NKE, allowing you to start with one hardware vendor, such as Lenovo, and later extend the cluster using a different vendor, like Dell. However, NKE supports only up to two different vendors in the same cluster and only accommodates that. Additionally, it is designed to support processes other than the initial phases of AI application development, such as data ingestion and model training, which often require large-scale data processing. However, it can be useful for managing and deploying AI models once trained and operational. I rate it a seven.
Head of Data Center at National Center of Informatics
Real User
Top 5
2024-02-14T15:30:19Z
Feb 14, 2024
NKE is straightforward for basic tasks. Integration can be beneficial when combining various tools, but in our case, as government service providers, we prioritize having a full-stack solution with NKE at the core. This approach ensures a comprehensive solution with a validated architecture covering Kubernetes, databases, AI, software-defined storage, networks, and computing. I rate it a seven out of ten.
Learn what your peers think about Nutanix Kubernetes Engine NKE [EOL]. Get advice and tips from experienced pros sharing their opinions. Updated: September 2025.
The applications are running smoothly. It provides a high-availability platform managed with good tools. I rate Nutanix Kubernetes Engine NKE a nine out of ten.
Nutanix Kubernetes Engine NKE [EOL] offers easy deployment, efficient resource management, and seamless integration with existing infrastructure, supporting virtualization and configurable RBAC.Nutanix Kubernetes Engine NKE [EOL] simplifies Kubernetes cluster deployment and management, offering robust features such as health checks and seamless upgrades. It integrates with existing systems, supports virtualization, and provides a unified console. Automatic load management and scalability...
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I don't have a technical role, but we are a system integrator, so we sell solutions such as OpenShift and Kubernetes as part of the sales team. We are a reseller called eSky IT, and I serve as the Regional Manager. Our engineers have deployed Nutanix Kubernetes Engine NKE for testing purposes. The solution is very scalable, with the core of hyper-converged infrastructure being scalability with performance. Nutanix is very stable and reliable, based on my experience with many customers, including large banks and telcos. They have been operating reliably and scaling since their deployment. For Nutanix Kubernetes Engine NKE specifically, it makes more sense to implement it on-premises. The very few use cases I've seen were on-premises, not on the cloud, and it's unlikely you'll buy Nutanix on the cloud due to the extra costs involved. A valid use case I see is if you are running several on-prem NKP clusters and your cloud strategy is involves running some public cloud workloads as well. You want to be able to run a frictionless Kubernetes environment across all your sites, on-prem or cloud. You would opt in for NKP on a public cloud. Otherwise, it would be much more cost efficient to consume Kubernetes directly from your hyperscaler, such as EKS or AKS. I rate Nutanix Kubernetes Platform NKP five out of 10. Not for the product, for the constraints it has in addressing more customers looking for an enterprise Kubernetes platform.
Every six months, we upgrade AOS on all the clusters. I manage around 25 plus Nutanix clusters, which includes upgrading Prism Central and utilizing Lifecycle Manager (LCM) for the Nutanix clusters. After 10:00 PM Eastern Time, we have a maintenance window to implement changes. For critical application servers, we coordinate with the application team to get approvals and create change requests (CR) to proceed during off-business hours. If the DevOps team faces any computer resource crunch, they open a request, and I increase computer resources by adding new worker nodes to the cluster. If they cannot connect to the cluster, there's a possibility that the client's SSL certificate could expire, so I renew the client SSL certificate for each cluster as part of my daily troubleshooting tasks. I am not part of the DevOps team, as they handle application pod deployments and testing across different environments such as stage, development, and production. From my side as an infrastructure person, I solely manage the cluster level, not the application pods. However, I take care of Nutanix management pods, ensuring things like worker nodes or etcd nodes are operational. I have not yet utilized NKP, as I am just learning about it since a project is coming up to upgrade from Nutanix Kubernetes Engine NKE to NKP. The client has a minimal cloud footprint currently, but they plan to adopt NC2, the Nutanix Cloud Cluster, in the future, including moving some clusters from on-premises to the cloud. They also have a few Azure Kubernetes platforms but in very limited capacity, which the Windows team manages, so I do not have access to those environments. On a scale of 1-10, I rate Nutanix Kubernetes Engine NKE a 9.
Overall, I rate Nutanix Kubernetes Engine NKE as six to seven out of ten. I believe there is room for improvement, especially in terms of vendor certifications and industry integrations. However, I find Nutanix to be generally reliable and cost-effective.
I rate the overall solution an eight out of ten.
Nutanix offers flexibility with NKE, allowing you to start with one hardware vendor, such as Lenovo, and later extend the cluster using a different vendor, like Dell. However, NKE supports only up to two different vendors in the same cluster and only accommodates that. Additionally, it is designed to support processes other than the initial phases of AI application development, such as data ingestion and model training, which often require large-scale data processing. However, it can be useful for managing and deploying AI models once trained and operational. I rate it a seven.
NKE is straightforward for basic tasks. Integration can be beneficial when combining various tools, but in our case, as government service providers, we prioritize having a full-stack solution with NKE at the core. This approach ensures a comprehensive solution with a validated architecture covering Kubernetes, databases, AI, software-defined storage, networks, and computing. I rate it a seven out of ten.
I recommend the product to enterprise customers. I rate it a seven out of ten.
The applications are running smoothly. It provides a high-availability platform managed with good tools. I rate Nutanix Kubernetes Engine NKE a nine out of ten.
Overall, I rate the solution an eight out of ten.
We are customers and end-users. I'd recommend the solution to others. It's a very good solution. I'd rate the solution eight out of ten.
I would rate the tool an eight out of ten.
I rate this solution seven out of 10.
I would recommend using this product, it's very good. I would rate this solution an eight out of ten.