Sold by: Applied Computing Research Labs
Deployed on AWS
Run one or more Kubernetes simulations in your GitHub CI pipeline; catch regressions in your scaling logic or custom controller behaviour before deploying to production.
Overview
SimKube is designed to allow users to simulate the behaviour of Kubernetes control plane components in a safe, isolated local environment. It is a "record-and-replay" simulator, which means that users can record the behaviour of a production cluster and then save that data for future analysis.
SimKube accomplishes this by running in a cluster with a real control plane; however, all pod behaviours are mocked out using Kubernetes WithOut Kubelet (KWOK). This means that anything that happens inside a pod can be simulated away. This enables users to simulate extremely large (1000+ node) Kubernetes clusters on a single AWS EC2 instance.
This version of the SimKube AMI allows you to run simulations inside your GitHub Actions, providing more confidence in your autoscaling, scheduling, or custom controller code. You can try a free version of this AMI (without the GitHub runner) at https://aws.amazon.com/marketplace/pp/prodview-m7imofdta3tla .
Highlights
- Run Kubernetes simulations inside your CI pipelines to identify regressions and incompatible changes
- Replay data from production outages in your simulations to ensure that fixes remain fixed
- Simulate thousand-node Kubernetes clusters on a single AWS EC2 instance in your GitHub actions
Details
Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 24.04
Deployed on AWS
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Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Cost/hour |
|---|---|
c7a.2xlarge Recommended | $0.10 |
c6a.16xlarge | $0.10 |
c7a.48xlarge | $0.10 |
m7i.4xlarge | $0.10 |
m6i.4xlarge | $0.10 |
c7a.16xlarge | $0.10 |
m7i.large | $0.10 |
m7i.8xlarge | $0.10 |
m6i.8xlarge | $0.10 |
m6i.large | $0.10 |
Dimensions summary
You pay by the hour based on the EC2 instance type that runs the software. Each dimension maps to a specific instance from the compute-optimized (c6a, c6i, c7a, c7i) and general-purpose (m6a, m6i, m7a, m7i) families. Within each family, pricing scales with instance size, from large up to 48xlarge. Larger sizes carry more vCPUs and memory, so their hourly rate rises accordingly. You choose the instance that fits your workload, then run it as long as needed. There is no upfront commitment; billing follows actual hours of use.
Top-of-mind questions for buyers
Each instance runs a GitHub Runner AMI built around SimKube. SimKube creates a simulated replica of your Kubernetes cluster. You replay recorded production event traces to test scaling limits and configuration changes safely, before they reach production.
Software charges accrue per running instance-hour. A fully stopped instance does not incur hourly software fees. Underlying AWS storage or other AWS resource fees may still apply while the instance is stopped, but the software license meters running time only.
The c-family instances (c6a, c6i, c7a, c7i) are compute-optimized, favoring higher vCPU-to-memory ratios for CPU-heavy simulation runs. The m-family instances (m6a, m6i, m7a, m7i) are general-purpose, balancing vCPU and memory. You pick the family that matches your workload profile.
simkube.dev
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Vendor refund policy
We do not offer refunds for this AMI.
Legal
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Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
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Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
Additional details
Usage instructions
To use this AMI, first launch a supported AWS EC2 instance with your chosen configuration. You will need SSH access to the instance: a security group that allows access over port 22 and either a public IP address or a way to access hosts inside your private VPC. The SSH username is ubuntu, and you will need a keypair configured on the host in order to access it.
The launched instance will have a running kind cluster with SimKube configured; you can use kubectl to inspect the state of this cluster and confirm that it works correctly. The launched instance also has the skctl CLI tool installed for interacting with SimKube.
The launched instance will have the ability to serve as a self-hosted runner for GitHub CI; you will need a GitHub Personal Access Token (PAT) with read and write access for Actions and Administration. Add that PAT to your repository as a secret named SIMKUBE_RUNNER_PAT. You can then use the custom GitHub action located at https://github.com/acrlabs/simkube-ci-action to set up, tear down, and run simulations on your runner.
Resources
Vendor resources
Support
Vendor support
Find a bug? File an issue on GitHub: https://github.com/acrlabs/simkube/issues
Need additional support? Reach out to our team at simkube@appliedcomputing.io and we'll be happy to help you get your action working.
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Similar products
SimKube is a simulation environment for Kubernetes used for cost forecasting, capacity planning, scalability analysis, or more.
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