Update Blog “hpe-greenlake-for-private-cloud-enterprise-scaling-and-orchestrating-modern-applications-for-the-enterprise”

Author: sseshachala

content/blog/hpe-greenlake-for-private-cloud-enterprise-scaling-and-orchestrating-modern-applications-for-the-enterprise.md

@@ -5,6 +5,8 @@ date: 2023-10-19T14:34:37.983Z
 author: Sudheendra Seshachala
 authorimage: https://media.licdn.com/dms/image/D5603AQGMJCplt_LTFQ/profile-displayphoto-shrink_800_800/0/1695127848528?e=1703116800&v=beta&t=4gbr2tD1-sH5-mhFh6O05iibw3B0UMHnL-1CPVF_2uU
 disable: false
+tags:
+  - hpe-greenlake-for-private-cloud-enterprise
 ---
 In my blog post on [HPE GreenLake for Private Cloud Enterprise: Deploying and scaling traditional applications](https://developer.hpe.com/blog/hpe-greenlake-for-private-cloud-enterprise-glpce-deploying-and-scaling-traditional-applications/), I highlighted how HPE GreenLake for Private Cloud Enterprise seamlessly integrates traditional applications with modern demands, transforming infrastructure into programmable code for optimal flexibility and security. Its strategic approach to scalability ensures businesses consistently operate at their best, making applications resilient to ever-changing requirements. In this post, I'll delve into the features and capabilities of HPE GreenLake for Private Cloud Enterprise, with a specific focus on its support for scaling containers using Kubernetes (K8s). Let's explore the advancements and offerings of the HPE GreenLake for Private Cloud Enterprise platform.
 
@@ -47,4 +49,47 @@ In essence, whether your workload requires the adaptable environment of VMs or t
 **K8s in Action on HPE GreenLake for Private Cloud Enterprise**
 In the evolving landscape of enterprise IT, scalability isn't just a luxury; it's a necessity. With HPE GreenLake for Private Cloud Enterprise and Kubernetes at its helm, businesses are equipped to meet dynamic demands head-on. When administrators first work with HPE GreenLake, they can manually allocate resources based on anticipated needs. But as traffic unpredictably rises, Kubernetes springs into action, enabling it to scale. 
 Kubernetes, with its sophisticated orchestration capabilities, monitors workloads in real-time on HPE GreenLake for Private Cloud Enterprise. Should traffic surge unexpectedly, Kubernetes autonomously scales containers, ensuring optimal performance without overburdening resources. 
-The combined prowess of manual fine-tuning with Kubernetes' automated scalability represents the future-forward approach of HPE GreenLake for Private Cloud Enterprise, promising enterprises reliability, efficiency, and adaptability all in one package.
+The combined prowess of manual fine-tuning with Kubernetes' automated scalability represents the future-forward approach of HPE GreenLake for Private Cloud Enterprise, promising enterprises reliability, efficiency, and adaptability all in one package.
+
+**Kubernetes Cluster blueprints:**
+
+![Screenshot 1: Creation of Kubernetes cluster blueprint](/img/screenshot-4-creation-of-kubernetes-cluster-blueprint.png "Screenshot 1: Creation of Kubernetes cluster blueprint")
+
+In screenshot 1, Kubernetes cluster blueprints in containers service serve as templates to simplify cluster deployments, including K8s setups. They set configurations like the Kubernetes version, storage class, and node details. Blueprints ensure consistent deployments and allow users to use standard templates or create their own for specific needs. Let me show you a concise demo on how to effortlessly configure clusters and optimize auto-scaling parameters!
+
+**How to create K8s clusters and scale worker nodes (up or down) in a running cluster**
+
+![Screenshot 2: K8s Cluster creation and configuring scaled worker nodes](/img/screenshot-2-k8s-cluster-creation-and-configuring-scaled-worker-nodes.png "Screenshot 2: K8s Cluster creation and configuring scaled worker nodes")
+
+In screenshot 2 , I created a cluster. I selected configurations and resources, set parameters, and containers service provisions and initialized the cluster. 
+
+**Scaling worker nodes in containers service**: With containers service, you can scale worker nodes based on workload. You just increase or decrease the number of worker nodes in a running cluster to align with resource requirements.
+
+**Autoscaler in Kubernetes clusters**
+The Autoscaler adjusts the Kubernetes cluster's size based on specific conditions. It scales up when pods can't be scheduled due to resource limitations and scales down if nodes are underutilized for over 10 minutes.
+
+**Key points:**
+•	Scaling range: Defined by a minimum and maximum node count. The range is between 1 and 200 nodes. By default, autoscaling is off with equal min-max values.
+
+**Scaling criteria**: 
+
+1. Pending pods due to limited resources trigger a scale-up.
+2. Underutilized nodes for 10 minutes prompt a scale-down, but certain conditions can prevent this:
+   •	Recent scale-up within 10 minutes
+   •	Failed scale-down in the last 3 minutes
+   •	Nodes with critical pods or those facing specific constraints
+3. Autoscaler operates from the control plane, checking conditions every minute.
+
+   ![Screenshot 3: Scale cluster](/img/screenshot-3-scale-cluster.png "Screenshot 3: Scale cluster")
+
+**How to use configure:**
+
+1. Ensure the cluster is ready and familiarize yourself with autoscaler guidelines.
+2. Navigate to HPE GreenLake for Private Cloud Enterprise > Containers > Selected Cluster.
+3. Choose Scale from Actions. 
+4. Set the min-max node count values to either enable or disable autoscaling as shown in Screenshot 3.
+5. Optionally, add or remove node pools.
+6. To see the autoscaler logs, utilize the given kubectl command.
+
+**Conclusion – The perfect synergy**
+HPE GreenLake for Private Cloud Enterprise, in conjunction with Kubernetes, addresses a broad spectrum of enterprise applications. Whether dealing with brownfield applications that have evolved over time or greenfield applications that are freshly developed, this combination ensures seamless integration and deployment. containers service’s ability to scale resources up or down based on workload demands ensures that businesses can respond effectively to varying operational requirements. Additionally, the integrated framework provides a secure stack, reinforcing infrastructure integrity, governance, compliance, and application security. In essence, the union of HPE GreenLake for Private Cloud Enterprise and Kubernetes provides a comprehensive solution that caters to both existing and new enterprise applications, fostering a flexible, responsive, and secure environment.