Why and how to use Kubernetes for scaling of your multi-tier (n-tier) applications?
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Kubernetes can be used to scale multi-tier applications by providing tools for container orchestration, including service discovery, load balancing, storage orchestration, and self-healing capabilities. It addresses challenges with traditional monolithic architectures by allowing microservices that are isolated, declarative, and can autoscale horizontally and vertically through features like horizontal pod autoscaling, vertical pod autoscaling, and cluster autoscaling. This allows applications to dynamically add or remove pods and nodes as needed to meet changing workload demands.
Why and how to use Kubernetes for scaling of your multi-tier (n-tier) applications?
- 1. Why and how to use Kubernetes for scaling of your multi-tier (n-tier) applications?
- 2. Changing workloads in the industry and the scalability we require today
- 3. The Evolution of Infrastructure Architecture IT Infrastructure Architecture level Physical Boxes Virtual Boxes Cloud Computing Monolithic SOA Microservices
- 4. • Non agile • Difficult to scale • In isolation • High maintenance cost • No new enhancement • Integration issues The Challenges in traditional applications
- 5. Microservices Architecture with Kubernetes
- 6. • Isolation of your workloads • Service Discovery and Load Balancing • Storage Orchestration • Declarative orchestration of containers • Declarative resource utilization • Self Healing • Secret and Configuration Management • Scalability Why is the industry using Kubernetes today?
- 7. • Horizontal Pod Scalability (HPA) Check Metrics Thresholds Met Scale pods • Vertical Pod Scalability (VPA) Check Metric Thresholds Met Increase Resources (CPU/ Memory) Restart Cluster for allocation • Cluster Auto Scaler (CA) Pods need to increase and are in pending state Additional node(s) needed New node granted (Infra as a Code) Pods rescheduled Achieving Auto Scalability with Kubernetes
- 9. THANK YOU FOR ATTENDING THE WEBINAR
Editor's Notes
- #7: Service discovery and load balancing: Kubernetes can expose a container using the DNS name or using their own IP address. If traffic to a container is high, Kubernetes is able to load balance and distribute the network traffic so that the deployment is stable. Storage orchestration: Kubernetes allows you to automatically mount a storage system of your choice, such as local storage, public cloud providers, and more. Automated rollouts and rollbacks: You can describe the desired state for your deployed containers using Kubernetes, and it can change the actual state to the desired state at a controlled rate. For example, you can automate Kubernetes to create new containers for your deployment, remove existing containers, and adopt all their resources to the new container. Automatic bin packing: You provide Kubernetes with a cluster of nodes that it can use to run containerized tasks. You tell Kubernetes how much CPU and memory (RAM) each container needs. Kubernetes can fit containers onto your nodes to make the best use of your resources. Self-healing: Kubernetes restarts containers that fail, replaces containers, kills containers that don’t respond to your user-defined health check, and doesn’t advertise them to clients until they are ready to serve. Secret and configuration management: Kubernetes lets you store and manage sensitive information, such as passwords, OAuth tokens, and SSH keys. You can deploy and update secrets and application configuration without rebuilding your container images, and without exposing secrets in your stack configuration.