Kubernetes Autoscaling - Frequently Asked Questions
Autoscaling is a key part of running Kubernetes efficiently but setting it up can be tricky. In this FAQ, we break down Horizontal Pod Autoscaler (HPA), Vertical Pod Autoscaler (VPA), and cluster-level scaling. With Devtron, you can monitor workloads in real-time and automate scaling decisions to balance performance and cost.
What is autoscaling in Kubernetes?
Autoscaling in Kubernetes automatically adjusts the number of pods or nodes based on resource usage or custom metrics to ensure optimal performance and cost-efficiency.
What is autoscaling in Kubernetes?
Autoscaling in Kubernetes automatically adjusts the number of pods or nodes based on resource usage or custom metrics to ensure optimal performance and cost-efficiency.
What is autoscaling in Kubernetes?
Autoscaling in Kubernetes automatically adjusts the number of pods or nodes based on resource usage or custom metrics to ensure optimal performance and cost-efficiency.
What are the types of autoscaling in Kubernetes?
Kubernetes supports Horizontal Pod Autoscaler (HPA), Vertical Pod Autoscaler (VPA), and Cluster Autoscaler (CA).
Learn more about: Types of Autoscaling
What are the types of autoscaling in Kubernetes?
Kubernetes supports Horizontal Pod Autoscaler (HPA), Vertical Pod Autoscaler (VPA), and Cluster Autoscaler (CA).
Learn more about: Types of Autoscaling
What are the types of autoscaling in Kubernetes?
Kubernetes supports Horizontal Pod Autoscaler (HPA), Vertical Pod Autoscaler (VPA), and Cluster Autoscaler (CA).
Learn more about: Types of Autoscaling
What is Horizontal Pod Autoscaler (HPA)?
HPA automatically scales the number of pods in a deployment based on observed CPU/memory usage or custom metrics.
What is Horizontal Pod Autoscaler (HPA)?
HPA automatically scales the number of pods in a deployment based on observed CPU/memory usage or custom metrics.
What is Horizontal Pod Autoscaler (HPA)?
HPA automatically scales the number of pods in a deployment based on observed CPU/memory usage or custom metrics.
What is Vertical Pod Autoscaler (VPA)?
VPA automatically adjusts the CPU and memory requests/limits of containers based on usage patterns.
What is Vertical Pod Autoscaler (VPA)?
VPA automatically adjusts the CPU and memory requests/limits of containers based on usage patterns.
What is Vertical Pod Autoscaler (VPA)?
VPA automatically adjusts the CPU and memory requests/limits of containers based on usage patterns.
What is Cluster Autoscaler?
Cluster Autoscaler adds or removes nodes in a Kubernetes cluster depending on pending pods and underutilized nodes.
What is Cluster Autoscaler?
Cluster Autoscaler adds or removes nodes in a Kubernetes cluster depending on pending pods and underutilized nodes.
What is Cluster Autoscaler?
Cluster Autoscaler adds or removes nodes in a Kubernetes cluster depending on pending pods and underutilized nodes.
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Need a tailored walkthrough? Schedule a 1:1 demo with our product team.
How do platforms like Devtron simplify autoscaling configuration?
Tools like Devtron provide a graphical interface to configure HPA, VPA, and time-based scaling policies—removing the need to manually edit YAML files and offering centralized monitoring of scaling behavior.
How do platforms like Devtron simplify autoscaling configuration?
Tools like Devtron provide a graphical interface to configure HPA, VPA, and time-based scaling policies—removing the need to manually edit YAML files and offering centralized monitoring of scaling behavior.
How do platforms like Devtron simplify autoscaling configuration?
Tools like Devtron provide a graphical interface to configure HPA, VPA, and time-based scaling policies—removing the need to manually edit YAML files and offering centralized monitoring of scaling behavior.
How do you configure autoscaling in Kubernetes?
You can define autoscalers using manifests or kubectl commands by setting target thresholds (e.g., CPU ≥ 80%) and specifying min/max replica counts.
How do you configure autoscaling in Kubernetes?
You can define autoscalers using manifests or kubectl commands by setting target thresholds (e.g., CPU ≥ 80%) and specifying min/max replica counts.
How do you configure autoscaling in Kubernetes?
You can define autoscalers using manifests or kubectl commands by setting target thresholds (e.g., CPU ≥ 80%) and specifying min/max replica counts.
Can you autoscale based on custom metrics?
Yes, using custom metrics from tools like Prometheus via the Prometheus Adapter, Kubernetes can autoscale based on application-specific or business-related indicators.
Can you autoscale based on custom metrics?
Yes, using custom metrics from tools like Prometheus via the Prometheus Adapter, Kubernetes can autoscale based on application-specific or business-related indicators.
Can you autoscale based on custom metrics?
Yes, using custom metrics from tools like Prometheus via the Prometheus Adapter, Kubernetes can autoscale based on application-specific or business-related indicators.
What is time-based autoscaling in Kubernetes?
Time-based autoscaling adjusts resources based on fixed schedules, ideal for predictable workloads like office-hour surges.
What is time-based autoscaling in Kubernetes?
Time-based autoscaling adjusts resources based on fixed schedules, ideal for predictable workloads like office-hour surges.
What is time-based autoscaling in Kubernetes?
Time-based autoscaling adjusts resources based on fixed schedules, ideal for predictable workloads like office-hour surges.
How do platforms like Devtron enhance time-based autoscaling?
Devtron supports time-based autoscaling policies through an easy-to-use interface, helping users manage scaling schedules without scripting or cron-based workarounds.
How do platforms like Devtron enhance time-based autoscaling?
Devtron supports time-based autoscaling policies through an easy-to-use interface, helping users manage scaling schedules without scripting or cron-based workarounds.
How do platforms like Devtron enhance time-based autoscaling?
Devtron supports time-based autoscaling policies through an easy-to-use interface, helping users manage scaling schedules without scripting or cron-based workarounds.
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Simplify application management and troubleshooting to unlock the full value of K8s, and drive innovation at scale.
Simplify application management and troubleshooting to unlock the full value of K8s, and drive innovation at scale.