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    <title>autoscaling</title>
    <link rel="self" type="application/atom+xml" href="https://links.biapy.com/guest/tags/990/feed"/>
    <updated>2026-06-29T07:21:16+00:00</updated>
    <id>https://links.biapy.com/guest/tags/990/feed</id>
            <entry>
            <id>https://links.biapy.com/links/11803</id>
            <title type="text"><![CDATA[Overprovisioning Helm Chart]]></title>
            <link rel="alternate" href="https://github.com/codecentric/cluster-overprovisioner" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11803"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Helm chart, that enables scheduled scaling of a target resource, intended to be add overprovisioning to an autoscaling k8s cluster. 

Helm Chart for overprovisioning an autoscaling Kubernetes Cluster, based on the Cluster Proportional Autoscaler and a deployment, that&amp;#039;s acting as a &amp;quot;placeholder&amp;quot; for overprovisioning which is inspired by Cluster Overprovisioning Helm Chart from Delivery Hero.

Related contents:

- [Scaling Nodes From Zero - The Bottleneck @ Labyrinth Labs](https://lablabs.io/blog/scaling-nodes-from-zero-the-bottleneck).]]>
            </summary>
            <updated>2026-02-13T12:58:20+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1072</id>
            <title type="text"><![CDATA[Zeropod]]></title>
            <link rel="alternate" href="https://github.com/ctrox/zeropod" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1072"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[pod that scales down to zero.

Zeropod is a Kubernetes runtime (more specifically a containerd shim) that automatically checkpoints containers to disk after a certain amount of time of the last TCP connection. While in scaled down state, it will listen on the same port the application inside the container was listening on and will restore the container on the first incoming connection.

Related contents:

- [zeropod: scale-to-zero with container checkpointing @ Zwindler&amp;#039;s Reflection](https://blog.zwindler.fr/en/2025/06/20/zeropod-scale-to-zero-with-container-checkpointing/).]]>
            </summary>
            <updated>2025-11-18T13:33:59+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1454</id>
            <title type="text"><![CDATA[ScaleOps]]></title>
            <link rel="alternate" href="https://scaleops.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1454"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Automated Kubernetes Resource Optimization.

Reduce Kubernetes costs by up to 80% and enhance cluster reliability by using real-time, application context-aware, automation for your most critical production environments

Related contents:

- [Unevictable Kubernetes Nodes And Smart Pod Placement @ overcast blog&amp;#039;s Medium](https://overcast.blog/unevictable-kubernetes-nodes-and-smart-pod-placement-a47e53182fdb).]]>
            </summary>
            <updated>2025-08-28T19:59:19+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1583</id>
            <title type="text"><![CDATA[Memorystore Cluster Autoscaler  Autoscaler]]></title>
            <link rel="alternate" href="https://github.com/GoogleCloudPlatform/memorystore-cluster-autoscaler" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1583"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Automatically scale the capacity of your Memorystore Cluster instances based on their utilization. 

The Cloud Memorystore Cluster Autoscaler is a companion tool that allows you to automatically increase or reduce the number of nodes/shards in one or more Memorystore Cluster instances, based on their utilization.

Related contents:

- [Rightsize your Memorystore for Redis Clusters with open-source Autoscaler @ Google Cloud Blog](https://cloud.google.com/blog/products/databases/memorystore-cluster-autoscaler-now-on-github/).]]>
            </summary>
            <updated>2025-08-28T20:19:36+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2589</id>
            <title type="text"><![CDATA[kube-green]]></title>
            <link rel="alternate" href="https://kube-green.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2589"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A K8s operator to reduce CO2 footprint of your clusters.

How many of your dev/preview pods stay on during weekends? Or at night? It&amp;#039;s a waste of resources! And money! But fear not, kube-green is here to the rescue.

kube-green is a simple k8s addon that automatically shuts down (some of) your resources when you don&amp;#039;t need them.

- [kube-green @ GitHub](https://github.com/kube-green/kube-green).

Related contents:

- [Newsletter du 16 Février 2026 @ Rudeops :fr:](https://www.rudeops.com/newsletter/2026-02-16-rudeops-newsletter/).]]>
            </summary>
            <updated>2026-02-20T13:33:18+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3397</id>
            <title type="text"><![CDATA[Escalator]]></title>
            <link rel="alternate" href="https://github.com/atlassian/escalator/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3397"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Escalator is a batch or job optimized horizontal autoscaler for Kubernetes.

It is designed for large batch or job based workloads that cannot be force-drained and moved when the cluster needs to scale down - Escalator will ensure pods have been completed on nodes before terminating them. It is also optimized for scaling up the cluster as fast as possible to ensure pods are not left in a pending state.]]>
            </summary>
            <updated>2025-08-29T01:22:57+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3401</id>
            <title type="text"><![CDATA[KEDA]]></title>
            <link rel="alternate" href="https://keda.sh/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3401"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Kubernetes Event-driven Autoscaling.

 KEDA is a Kubernetes-based Event Driven Autoscaling component. It provides event driven scale for any container running in Kubernetes 

- [KEDA @ GitHub](https://github.com/kedacore/keda).

Related contents:

- [Veille de la semaine du 23 septembre 2024 @ Veille de la semaine&amp;#039;s Substack :fr:](https://guikingone.substack.com/p/veille-de-la-semaine-du-23-septembre).
- [Predictive Autoscaling in Kubernetes with Keda and Prophet @ Minimal Devops&amp;#039; Medium](https://minimaldevops.com/predictive-autoscaling-in-kubernetes-with-keda-and-prophet-cbccd96cf881).
- [Scaling Nodes From Zero - The Bottleneck @ Labyrinth Labs](https://lablabs.io/blog/scaling-nodes-from-zero-the-bottleneck).]]>
            </summary>
            <updated>2026-02-13T12:58:54+00:00</updated>
        </entry>
    </feed>
