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.
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) is an enterprise Kubernetes management solution that simplifies provisioning, operations, and lifecycle management of Kubernetes.
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.