Karpenter vs. Cluster Autoscaler on AWS: Picking the Right Tool for Your Kubernetes Scaling

Mohammad Abu Mattar
DevOps , Kubernetes , Cloud Computing , AWS , Autoscaling
Published: 31 May, 2025
12 Mins read

You know how it is with modern apps – they can be super busy one minute and then quiet the next. If you’re using Kubernetes on Amazon Web Services (AWS), making sure your setup can handle these ups and downs automatically is a big deal. It keeps your apps running smoothly, uses your resources wisely, and saves you money. Trying to change the number of computers (nodes) in your Kubernetes setup by hand is a real headache. You might end up paying for computers you don’t need or your apps might slow down when things get busy. That’s where tools like Karpenter and Cluster Autoscaler come in. They automatically take care of adding and removing computers in your Kubernetes world on AWS. This article will give you a good look at both of these tools, what they do, what’s good about them, and what you should think about when choosing between them.

First Things First:

What’s Karpenter, and How Does It Work with AWS?

Karpenter is like a smart helper for your Kubernetes setup on AWS. It’s an open-source tool made by AWS that’s really good at managing your computer power. Unlike older ways of doing this, Karpenter figures out exactly what computer resources you need, right when you need them, based on what your apps are actually doing. To make this happen, Karpenter talks directly to AWS’s Elastic Compute Cloud (EC2) in a special way, so it can get new computers up and running really fast.

The way Karpenter works is based on two main things in your Kubernetes setup: NodePool (which used to be called Provisioner) and EC2NodeClass (which was AWSNodeTemplate). The EC2NodeClass is where you tell AWS-specific things about your computers, like what kind of operating system image to use, which networks to connect to, and what security settings to have. The NodePool is where you set broader rules and preferences for getting new computers, like what types of computers you’d prefer, which locations they should be in, and even how long they should stick around. One of the cool things about Karpenter is that it can work with lots of different kinds of computers on AWS, in different places, and even using cheaper options like Spot Instances, without you having to set up a bunch of different groups of computers beforehand. Karpenter keeps an eye on the apps in your Kubernetes setup that are waiting to start and, based on what they need and where they can run, it gets the best computers to run them, making sure you’re using your resources well and not spending too much.

What’s Cluster Autoscaler, and How Does It Work on AWS?

Cluster Autoscaler is another popular open-source tool that lots of people use to automatically change the size of their Kubernetes setup on AWS. It’s looked after by a special group in the Kubernetes community. Its main job is to make sure you have enough computers in your setup to run all your apps, but also to get rid of computers that aren’t doing much so you don’t waste resources.

Cluster Autoscaler works with groups of computers, usually by talking to AWS’s Auto Scaling Groups (ASGs) or Managed Node Groups (MNGs). It constantly checks your Kubernetes setup for apps that can’t start because there aren’t enough resources. If it finds some, it makes the cluster bigger by telling the ASGs to add more computers. It also makes the cluster smaller by finding computers that haven’t been used much for a while and trying to remove them after moving their apps to other computers safely.

How Are Their Ways of Getting Computers and Scaling Different?

The main difference between Karpenter and Cluster Autoscaler is how they’re set up and how they handle getting new computers and making the cluster bigger or smaller. Karpenter thinks about things from the app’s point of view. It talks directly to AWS to get individual computers exactly when and where they’re needed based on what the apps are asking for. This means it can get computers that are just the right size for the job. Cluster Autoscaler, on the other hand, thinks about groups of computers. It works with ASGs or MNGs, which are groups of computers that are all set up the same way. When it needs to make the cluster bigger, it just tells these groups to add more computers.

Feature	Karpenter	Cluster Autoscaler
How it Sees Things	App-focused, manages individual computers	Group-focused, manages groups of computers
How it Adds Computers	Gets computers based on what apps need, can combine apps on fewer nodes	Tells groups of computers to get bigger, removes computers that aren’t being used much
Manages Computer Groups?	No, manages individual computers	Yes, manages groups of computers
How Detailed is the Scaling	Very detailed, based on what each app needs	Works at the group level
How Much it Knows AWS	Knows AWS very well	Can work with different cloud providers

Karpenter watches the Kubernetes system for apps that are waiting to start but can’t because there aren’t enough resources. Then, it looks at what these apps need (like processing power and memory) and where they can run (based on rules you set) to get new computers that fit those needs exactly. When computers aren’t needed anymore, Karpenter can get rid of them. It even has smart ways to combine apps onto fewer computers to save money by finding and removing computers that aren’t being used much.

Cluster Autoscaler works by looking for apps that can’t start or computers in its groups that aren’t being used much. When it needs to make the cluster bigger, it usually just adds new computers to the group based on how the group was set up in the first place.

Which One is Faster at Getting New Computers?

When it comes to how fast they can get new computers up and running, Karpenter usually wins. Because it talks directly to AWS, it can often get new computers ready in less than a minute. This quick turnaround means Karpenter can react really fast when your apps need more power, and it helps keep things running smoothly even when there are sudden spikes in activity.

Cluster Autoscaler, because it works through ASGs, has an extra step in the process, which can make it a bit slower to get new computers. While it does watch for apps that need more resources and adds computers, the time it takes for ASGs to get those computers ready can be a little longer than Karpenter’s direct approach. If your apps need more power right away, Karpenter’s speed can be a big advantage.

Which One is Better at Saving Money and Using Resources Wisely?

Karpenter is generally better at saving money and using your computer resources effectively. Because it can get computers that are just the right size for the apps that need them, you’re less likely to end up paying for computer power you’re not using. Plus, Karpenter can combine apps onto fewer computers and get rid of the ones that aren’t doing much, which helps cut down on costs even more. It’s also good at packing apps tightly onto computers to make the most of the resources available. And because it can choose from lots of different types of computers, it can pick the ones that give you the best bang for your buck for what your apps need.

Cluster Autoscaler, on the other hand, adds computers based on groups that are set up beforehand. This might mean you end up with bigger computers than you actually need if the sizes in the group don’t match what your apps are asking for. While it can also remove computers that aren’t being used much, how well it saves you money depends a lot on how you set it up in the first place and how similar the demands of your apps are within each group.

How Much Can You Change and Customize Them?

Karpenter gives you more ways to change and customize things compared to Cluster Autoscaler. With its NodePool and EC2NodeClass settings, you can really fine-tune what your computers look like. You can choose specific types of computers, different kinds of processors (like AMD or ARM), operating systems, and whether to use regular or cheaper, but sometimes interrupted, Spot Instances. You can even tell it to prefer certain types of computers. Plus, Karpenter has lots of options for how it scales, including smart ways to combine apps, settings for how long computers should last before being replaced, and ways to make sure your computers stay the way you want them. Karpenter also pays attention to rules you set about how many apps can be disrupted at once, so you have control over how quickly it can make changes.

Cluster Autoscaler works with groups of computers that are set up beforehand, so you don’t have as much flexibility in choosing computer types within a single group. If you want to add new types, you often have to make changes to your initial setup. While Cluster Autoscaler does have some settings you can tweak, like how often it checks for changes and how long it waits before removing computers, it generally doesn’t give you as much detailed control as Karpenter. If you have multiple groups of computers, Cluster Autoscaler has some strategies to decide which group to make bigger, giving you some say in how new capacity is added.

How Do They Handle Spot Instances?

Karpenter is really good with Spot Instances, which can save you a lot of money. You can easily tell Karpenter to use Spot Instances first and then switch to regular ones if Spot capacity isn’t available. It even tries to pick Spot Instances that are cheap but also less likely to be interrupted. Karpenter can also replace one Spot Instance with another cheaper one without going back to regular instances. Plus, it knows how to handle notifications about Spot Instances being interrupted. When a Spot Instance is about to be stopped, Karpenter can automatically move the apps running on it to new computers.

While Cluster Autoscaler can use Spot Instances, it usually takes more work to set up within the groups of computers you manage. To handle Spot interruptions smoothly, you might need to use extra tools like the AWS Node Termination Handler. Also, if Spot Instance capacity isn’t available, switching to regular instances might not be as seamless as with Karpenter.

How Well Do They Fit with AWS and Other Kubernetes Tools?

Karpenter works really well with AWS, using services like EC2, IAM (for managing permissions), and EventBridge (for Spot Instance alerts) to make scaling on AWS easy. While it started with a focus on AWS, it’s also designed to work with other cloud providers like Azure and Alibaba Cloud.

Cluster Autoscaler can work with many different cloud providers, including AWS, Google Cloud, and Azure. Both tools work with other important Kubernetes features like the Horizontal Pod Autoscaler (HPA) and Vertical Pod Autoscaler (VPA), so you can have a complete system for scaling both your apps and the computers they run on.

How Easy Are They to Set Up and Manage?

Karpenter is generally easier to set up and manage, especially if you’re already using AWS. You can usually install it easily using Helm charts. You configure it mainly through Kubernetes settings, which feels natural if you’re used to Kubernetes. One of the big pluses of Karpenter is that you don’t have to manage lots of pre-defined groups of computers, which simplifies things when you have different kinds of apps running. Karpenter also has features like automatically replacing older computers and upgrading them, which can make managing your setup easier.

Cluster Autoscaler, while it’s been around for a while and lots of people use it, can take more steps to set up. This includes setting up AWS Auto Scaling Groups, giving the autoscaler permission to talk to AWS, and then installing the Cluster Autoscaler itself in your Kubernetes setup. If you have many different kinds of apps, managing multiple groups of computers with specific settings can also make things more complicated.

What About Performance and Potential Problems?

Both Karpenter and Cluster Autoscaler are designed to perform well, but they can have different kinds of issues. Karpenter might have trouble with really big setups or when apps are being created and deleted very quickly. Some users have mentioned that you don’t have a lot of control over how it balances things across different availability zones, which could be a concern for apps that need to be very fast. Also, the computer usage numbers from Karpenter don’t show up directly in AWS’s CloudWatch, so you might need to use other tools to keep an eye on things.

Cluster Autoscaler has been tested to work with up to 1000 computers, but it might slow down if you have a lot more than that. While it’s usually fast enough, the time it takes to add new computers can be a problem for apps that need to scale up immediately when demand changes quickly.

Karpenter is especially good for apps that have changing needs and different computer requirements, like when you’re processing a lot of data or doing machine learning. Cluster Autoscaler might not be as good for apps that change a lot or need specific types of computers that aren’t already set up in its groups.

Frequently Asked Questions:

Karpenter directly gets computers that are the right size for your apps and can combine apps on fewer computers, making it faster and more efficient. Cluster Autoscaler changes the size of groups of computers based on apps that are waiting to start and computers that aren’t being used much.

Karpenter is usually better at saving money because it gets computers that are just the right size and can combine apps to use resources more efficiently.

While you could technically do it, it’s generally not a good idea to run both Karpenter and Cluster Autoscaler on the same setup because they might interfere with each other and cause unexpected scaling.

Karpenter is often simpler to set up, especially if you’re using AWS, because it uses standard Kubernetes tools.

Karpenter typically performs better, especially when it comes to how quickly it can react to changes in your apps’ needs.

Karpenter doesn’t have as much built-in support for working with different cloud providers and you might not have as much control over some things like where it puts the computers. Cluster Autoscaler can be slower to react and might end up getting bigger computers than you need.

Pick Karpenter if you want faster scaling, to save more money, and if you need more flexibility with the types of computers you use on AWS. Go with Cluster Autoscaler if you need to work with different cloud providers or if you prefer the more predictable way it manages groups of computers.

Yes, while it started with AWS, Karpenter is designed to work with other cloud providers too, and it now supports Azure and Alibaba Cloud, with the possibility of adding more in the future.

Karpenter knows how to deal with notifications about Spot Instances being stopped. It can automatically move the apps to new computers and then shut down the interrupted ones.

Yes, Karpenter version 1.0 has been released and is considered ready for production use.

Usually, you’d start by installing Karpenter and setting up its configurations, and then you’d remove Cluster Autoscaler.

You can find lots of details on the official Karpenter website (karpenter.sh) and in the Kubernetes Autoscaling group’s information, as well as in AWS’s documentation.

Wrapping Up: Picking What’s Right for Your Kubernetes Scaling on AWS

Both Karpenter and Cluster Autoscaler are great tools for automatically scaling your Kubernetes setup on AWS, but they’re better for different situations. Karpenter is fast, flexible, and can save you money, making it a good fit if you’re really focused on using AWS and want a more modern way to handle scaling. It’s a solid choice if you need to scale quickly, want a lot of control over the types of computers you use (especially Spot Instances), and want to keep things simple by not managing lots of computer groups.

Feature	Karpenter	Cluster Autoscaler
Speed of Adding Computers	Faster	Slower
Cost Savings	Usually better because it gets the right size and combines apps well	Depends on how you set it up
Flexibility	Very flexible with lots of settings	Less flexible, works with pre-set computer groups
Handling Spot Instances	Excellent, built-in support for interruptions	Needs more manual setup and extra tools
Works with Other Clouds?	Growing support (AWS, Azure, Alibaba Cloud)	Works with many different cloud providers
How Easy to Manage	Easier, more automatic	More manual setup needed
Reacts to Changes	Reacts very quickly to changes in app needs	Checks periodically, might be slower to react to sudden changes
Combining Apps on Computers	Advanced, can even combine Spot Instances	Basic, focuses on removing empty or underused computers

Cluster Autoscaler is still a good, reliable option, especially if you need to work with different cloud providers or if you like the more traditional way of managing computer power through pre-defined groups. In the end, the best tool for you depends on what you need and what’s important for your Kubernetes setup on AWS. Think about what your apps do, how they need to scale, and what your goals are for saving money. It’s probably a good idea to try both tools out in a test environment to see which one fits best with your setup and how you like to work.