# KodeKloud: Beta Courses Kubernetes Autoscaling

## Kubernetes Autoscaling

### Manual Scaling

- [Course Overview](https://notes.kodekloud.com/docs/Kubernetes-Autoscaling/Manual-Scaling/Course-Overview/page.md): Overview of Kubernetes autoscaling covering HPA VPA Cluster Autoscaler CPA and KEDA, with practical patterns, hands-on examples, and best practices for resilient scalable workloads
- [Why Do We Need to Autoscale](https://notes.kodekloud.com/docs/Kubernetes-Autoscaling/Manual-Scaling/Why-Do-We-Need-to-Autoscale/page.md): Explains why autoscaling matters and how Kubernetes uses cluster and pod autoscalers like Cluster Autoscaler, HPA, VPA, and KEDA to improve cost efficiency, availability, and resilience
- [Manual HPA](https://notes.kodekloud.com/docs/Kubernetes-Autoscaling/Manual-Scaling/Manual-HPA/page.md): Hands-on lab showing manual scaling of a Kubernetes Deployment, observing pod creation and ephemeral hostnames, and explaining effects on application behavior and when to use Services or StatefulSets.
- [Manual VPA](https://notes.kodekloud.com/docs/Kubernetes-Autoscaling/Manual-Scaling/Manual-VPA/page.md): Hands-on lab demonstrating how Vertical Pod Autoscaler updates Pod resource requests, causing Kubernetes to recreate Pods when resource requests change.

### Horizontal Pod Autoscaler (HPA)

- [What Is HPA](https://notes.kodekloud.com/docs/Kubernetes-Autoscaling/Horizontal-Pod-Autoscaler-HPA/What-Is-HPA/page.md): Describes Kubernetes Horizontal Pod Autoscaler that automatically adjusts pod replicas based on resource, custom, and external metrics while enforcing min/max and stabilization behaviors.
- [HPA Architecture](https://notes.kodekloud.com/docs/Kubernetes-Autoscaling/Horizontal-Pod-Autoscaler-HPA/HPA-Architecture/page.md): Explains Kubernetes Horizontal Pod Autoscaler architecture, metric sources, adapters, control loop, and examples for resource custom and external metrics to enable automated pod scaling.
- [Custom Metrics Mechanisms](https://notes.kodekloud.com/docs/Kubernetes-Autoscaling/Horizontal-Pod-Autoscaler-HPA/Custom-Metrics-Mechanisms/page.md): Using application-specific custom metrics with Kubernetes Horizontal Pod Autoscaler via instrumentation, collectors, and adapters to enable autoscaling on business or performance signals.
- [External Metrics Mechanisms](https://notes.kodekloud.com/docs/Kubernetes-Autoscaling/Horizontal-Pod-Autoscaler-HPA/External-Metrics-Mechanisms/page.md): Explains using external metrics from outside Kubernetes with metrics adapters and monitoring systems to enable HPA autoscaling based on external signals like queue backlogs or external request rates
- [HPA Multiple Metrics](https://notes.kodekloud.com/docs/Kubernetes-Autoscaling/Horizontal-Pod-Autoscaler-HPA/HPA-Multiple-Metrics/page.md): How to configure HPA with multiple metrics to scale Kubernetes services using CPU and custom application metrics, including architecture, examples, and best practices
- [HPA Scaling Policy](https://notes.kodekloud.com/docs/Kubernetes-Autoscaling/Horizontal-Pod-Autoscaler-HPA/HPA-Scaling-Policy/page.md): Kubernetes Horizontal Pod Autoscaler scaling policies and configuration for predictable, stable autoscaling covering policy types, periodSeconds, selectPolicy, stabilization windows, and tuning guidance
- [Scaling Behavior](https://notes.kodekloud.com/docs/Kubernetes-Autoscaling/Horizontal-Pod-Autoscaler-HPA/Scaling-Behavior/page.md): Explains Kubernetes Horizontal Pod Autoscaler scaling behavior, policies, stabilization windows, rate limits, metric types, configuration knobs, and best practices for stable autoscaling.

### Vertical Pod Autoscaler (VPA)

- [VPA Architecture](https://notes.kodekloud.com/docs/Kubernetes-Autoscaling/Vertical-Pod-Autoscaler-VPA/VPA-Architecture/page.md): Describes Vertical Pod Autoscaler architecture, components, operation modes, and best practices for right-sizing pod CPU and memory requests and coordinating with horizontal autoscaling
- [VPA Setup Demo](https://notes.kodekloud.com/docs/Kubernetes-Autoscaling/Vertical-Pod-Autoscaler-VPA/VPA-Setup-Demo/page.md): Describes Vertical Pod Autoscaler CRDs, their purposes, checkpoints, installation steps, and VPA controller roles
- [VPA Memory Lab](https://notes.kodekloud.com/docs/Kubernetes-Autoscaling/Vertical-Pod-Autoscaler-VPA/VPA-Memory-Lab/page.md): Demonstrates using Kubernetes Vertical Pod Autoscaler to collect and validate memory recommendations for a Flask app by observing baseline, applying memory-only VPA, and testing under load.
- [VPA CPU Lab](https://notes.kodekloud.com/docs/Kubernetes-Autoscaling/Vertical-Pod-Autoscaler-VPA/VPA-CPU-Lab/page.md): Hands-on lab demonstrating CPU-focused Vertical Pod Autoscaler using a Flask app to monitor usage, generate VPA recommendations (updateMode Off), and validate recommendations under load
- [VPA CPU Memory in Action Demo](https://notes.kodekloud.com/docs/Kubernetes-Autoscaling/Vertical-Pod-Autoscaler-VPA/VPA-CPU-Memory-in-Action-Demo/page.md): A hands-on lab demonstrating Kubernetes Vertical Pod Autoscaler recommendations and automatic pod evictions by deploying a Flask app, generating load, and observing VPA updater behavior.
- [Summary Closure and Limitation of HPA VPA](https://notes.kodekloud.com/docs/Kubernetes-Autoscaling/Vertical-Pod-Autoscaler-VPA/Summary-Closure-and-Limitation-of-HPA-VPA/page.md): Comparison and guidance on Kubernetes Horizontal Pod Autoscaler and Vertical Pod Autoscaler, differences, limitations, interactions, and practical recommendations for choosing and combining them

### Cluster Proportional Autoscaler (CPA)

- [CPA Introduction](https://notes.kodekloud.com/docs/Kubernetes-Autoscaling/Cluster-Proportional-Autoscaler-CPA/CPA-Introduction/page.md): Explains Kubernetes Cluster Proportional Autoscaler that adjusts cluster-level Deployment replicas based on node and CPU metrics using ladder and linear scaling modes and ConfigMap configuration
- [Pod Priority and Preemption](https://notes.kodekloud.com/docs/Kubernetes-Autoscaling/Cluster-Proportional-Autoscaler-CPA/Pod-Priority-and-Preemption/page.md): Explains Kubernetes Pod Priority and Preemption, using PriorityClass and preemptionPolicy to control scheduling and evictions so critical workloads run when cluster resources are scarce.

### Kubernetes Event-Driven Autoscaling (KEDA)

- [KEDA Introduction](https://notes.kodekloud.com/docs/Kubernetes-Autoscaling/Kubernetes-Event-Driven-Autoscaling-KEDA/KEDA-Introduction/page.md): Explains KEDA, an event-driven Kubernetes autoscaler, its architecture, components, benefits, and comparisons to HPA VPA CPA, highlighting fast event-based scaling and scale-to-zero support.
- [Installation Details](https://notes.kodekloud.com/docs/Kubernetes-Autoscaling/Kubernetes-Event-Driven-Autoscaling-KEDA/Installation-Details/page.md): Explains installing KEDA with Helm, what Kubernetes resources the chart creates, verification commands, RBAC considerations, and troubleshooting tips.
- [KEDA CPU Scaling](https://notes.kodekloud.com/docs/Kubernetes-Autoscaling/Kubernetes-Event-Driven-Autoscaling-KEDA/KEDA-CPU-Scaling/page.md): Guide to configuring KEDA to autoscale Kubernetes workloads based on CPU utilization, requiring the Metrics Server, proper CPU resource requests, and ScaledObject CPU trigger configuration.
- [KEDA CRON Scaling](https://notes.kodekloud.com/docs/Kubernetes-Autoscaling/Kubernetes-Event-Driven-Autoscaling-KEDA/KEDA-CRON-Scaling/page.md): Explains KEDA Cron scaler for time-based Kubernetes pod scaling, using cron expressions and timezones to enforce desired replica counts during scheduled windows and revert afterward.
- [KEDA Scaling With Redis List](https://notes.kodekloud.com/docs/Kubernetes-Autoscaling/Kubernetes-Event-Driven-Autoscaling-KEDA/KEDA-Scaling-With-Redis-List/page.md): Using KEDA to autoscale Kubernetes worker services based on Redis list backlog and HPA behavior settings

### Introduction 

- [Course Introduction](https://notes.kodekloud.com/docs/Kubernetes-Autoscaling/Introduction/Course-Introduction/page.md): A practical course teaching Kubernetes autoscaling techniques including manual scaling, HPA, VPA, CPA and KEDA with hands on labs and debugging for production readiness