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https://github.com/elementtech/kube-reqsizer

A Kubernetes controller for automatically optimizing pod requests based on their continuous usage. VPA alternative that can work with HPA.
https://github.com/elementtech/kube-reqsizer

autoscaler autoscaling controller k8s kubernetes optimization pod vpa

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A Kubernetes controller for automatically optimizing pod requests based on their continuous usage. VPA alternative that can work with HPA.

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README 

        


  



A Kubernetes controller to optimize pod requests. A VPA Alternative.


















  




**kube-reqsizer** is a kubernetes controller that will measure the usage of pods over time and optimize (reduce/increase) their requests based on the average usage.



When all required conditions meet, the controller calculates the result requirements based on all the samples taken so far a pod and its peers in the same deployment controller.

It then goes "upstream" to the parent controller of that pod, for example *Deployment*, and updates the relevant containers for the pods inside the deployment as a reconciliation, as if its desired state is the new state with the new requirements.






**Note:** This is an alternative to [Vertical-Pod-Autoscaler](https://github.com/kubernetes/autoscaler/tree/master/vertical-pod-autoscaler). The intended use of this project is to provide a simpler, more straightforward install and mechanism, without CRDs, **and that can work with [Horizontal-Pod-Autoscaler](https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale/).**

## Deploy - Helm



```bash

helm repo add kube-reqsizer https://elementtech.github.io/kube-reqsizer/

helm repo update

helm install kube-reqsizer/kube-reqsizer

```



**Core Values:**



```yaml

enabledAnnotation: true

sampleSize: 1

minSeconds: 1

enableIncrease: true

enableReduce: true

maxMemory: 0

minMemory: 0

maxCPU: 0

minCPU: 0

minCPUIncreasePercentage: 0

minCPUDecreasePercentage: 0

minMemoryIncreasePercentage: 0

minMemoryDecreasePercentage: 0

cpuFactor: 1

memoryFactor: 1

logLevel: info

concurrentWorkers: 10

persistence:

  enabled: true

```

## Prerequisites

- The metrics server must be deployed in your cluster. Read more about [Metrics Server](https://github.com/kubernetes-sigs/metrics-server). This controller uses the **metrics.k8s.io** extension API group (apis/metrics.k8s.io/v1beta1)



## Usage



**kube-reqsizer** has primary custom flags:



```bash

# Enable a annotation filter for pod scraping. 

# True will only set requests of controllers of which PODS or NAMESPACE 

# have the annotation set to "true".

# If "false", will ignore annotations and work 

# on all pods in the cluster unless

# they have "false".



# reqsizer.jatalocks.github.io/optimize=true

# reqsizer.jatalocks.github.io/optimize=false

--annotation-filter bool (default true)



# The sample size to create an average from when reconciling.

--sample-size int (default 1)



# Minimum seconds between pod restart.

# This ensures the controller will not restart a pod if the minimum time

# has not passed since it has started.

--min-seconds float (default 1)



# Allow controller to reduce/increase requests

--enable-increase (default true)

--enable-reduce (default true)



# Min and Max CPU (m) and Memory (Mi) the controller can set a pod request to. 0 is infinite

--max-cpu int (default 0)

--max-memory int (default 0)

--min-cpu int (default 0)

--min-memory int (default 0)



# Min CPU and Memory (%) the controller will count as a condition to resize requests.

# For Example:

# If reqsizer wants to increase from 90m to 100m, that's a 10% increase. 

# It will ignore it if min-cpu-increase-percentage is more than 10.

# If reqsizer wants to decrease from 100m to 10m, that's a 90% decrease. 

# It will ignore it if min-cpu-decrease-percentage is more than 90.

--min-cpu-increase-percentage int (default 0)

--min-memory-increase-percentage int (default 0)

--min-cpu-decrease-percentage int (default 0)

--min-memory-decrease-percentage int (default 0)



# Multiply requests when reconciling

--cpu-factor float (default 1)

--memory-factor float (default 1)



# How many pods to sample in parallel. This may affect the controllers stability.

--concurrent-workers (default 10)



# Persistence using Redis

--enable-persistence (default false)

--redis-host (default "localhost")

--redis-port (default "6379")

--redis-password (default "")

--redis-db (default 0)

```



### Annotations 



*If **annotation-filter** is **true**:*

```

reqsizer.jatalocks.github.io/optimize=true  # Optimize Pod/Namespace

reqsizer.jatalocks.github.io/optimize=false # Ignore Pod/Namespace

```

There are Pod/Namespace annotations available *Regardless of **annotation-filter**:*

```

reqsizer.jatalocks.github.io/optimize=false # Ignore Pod/Namespace when optimizing entire cluster

reqsizer.jatalocks.github.io/mode=average   # Default Mode. Optimizes based on average. If ommited, mode is average

reqsizer.jatalocks.github.io/mode=max       # Sets the request to the MAXIMUM of all sample points

reqsizer.jatalocks.github.io/mode=min       # Sets the request to the MINIMUM of all sample points

```

### Disclaimer



`sample-size` is the amount of data-points the controller will store in cache before constructing an average for the pod. After a requests resizing, the cache will clean itself and a new average will be calculated based on the sample size. If `min-seconds` have not yet passed since the pod has been scheduled, the controller will keep sampling the pod until `min-seconds` have been reached and only then zero the sample and restart from cache.



### Monitoring - Prometheus

| Metric  | Type | Description |

| ------------- | ------------- | ------------- |

| kube_reqsizer_cpu_offset  | Gauge  | Number of milli-cores that have been increased/removed since startup. Can be a positive/negative value.  |

| kube_reqsizer_memory_offset  | Gauge  | Number of megabits that have been increased/removed since startup. Can be a positive/negative value.  |

| kube_reqsizer_cache_size  | Gauge  | Number of pod controllers currently in cache.  |

### Edge Cases



1. All samples in a certain cycle report `0` (less than 1):

   1. **mode=average**: The controller will ignore the pod and not reconcile.

   2. **mode=min**: The controller will put `1m` or `1Mi` as a value.

   3. **mode=max**: The controller will ignore the pod and not reconcile.

1. One or more of the samples in a certain cycle reports `0` (less than 1):

   1. **mode=average**: Will take the `0` into consideration.

   2. **mode=min**: Will consider the `0` as `1`.

   3. **mode=max**: Will ignore the sample.

2. **annotation-filter** is `true` (`optimize=false` is as strong as **deny**):

   1. A namespace has `optimize=false` but a pod has `optimize=true`:

      1. The controller will ignore the pod and not reconcile.

   2. A namespace has `optimize=true` but a pod has `optimize=false`:

      1. The controller will ignore the pod and not reconcile.



## Limitations



- Does not work with CRD controllers (such as Argo Rollouts)

# Development

## Getting Started

You’ll need a Kubernetes cluster to run against. You can use [KIND](https://sigs.k8s.io/kind) to get a local cluster for testing, or run against a remote cluster.

**Note:** Your controller will automatically use the current context in your kubeconfig file (i.e. whatever cluster `kubectl cluster-info` shows).



### Running on the cluster



1. Run the controller:

```sh

go run main.go

```



**OR**



2. Build and push your image to the location specified by `IMG`:

	

```sh

make docker-build docker-push IMG=/kube-reqsizer:tag

```

	

2. Deploy the controller to the cluster with the image specified by `IMG`:



```sh

make deploy IMG=/kube-reqsizer:tag

```

### Undeploy controller

UnDeploy the controller to the cluster:



```sh

make undeploy

```



## Support



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