Stable Diffusion WebUI on GKE Autopilot

I recently set out to run Stable Diffusion on GKE in Autopilot mode, building a container from scratch using the AUTOMATIC1111‘s webui. This is likely not how you’d host a stable diffusion service for production (which would make for a good topic of another blog post), but it’s a fun way to try out the… Continue reading Stable Diffusion WebUI on GKE Autopilot

LLM Model Serving on Autopilot

When building your business using LLMs as a key component, you may wish to be a master of your own domain and run your own model. Running your own LLM protects you from changes like pricing increases or API availability with third-party services, guarantees the privacy of your data (no data needs to leave your… Continue reading LLM Model Serving on Autopilot

CUDA 12 on GKE Autopilot

Per the NVIDIA docs, CUDA 12 applications require driver 525.60.04+. This driver is available as part of GKE 1.28. To upgrade an existing cluster to the latest version of 1.28: This upgrades the control plane, and schedules the nodes to follow, which generally completes within a day or two (depending on how many nodes you… Continue reading CUDA 12 on GKE Autopilot

Isolating namespaces with NetworkPolicy

Kubernetes allows for multi-tenancy within the cluster using namespaces. You can host multiple different applications each in their own namespace that at times can feel almost like a separate cluster. If you configure RBAC you can grant users and service accounts access to specific namespaces and even control what objects they can modify within. However,… Continue reading Isolating namespaces with NetworkPolicy

BYO Service Mesh on GKE Autopilot

Did you know you can now run any service mesh on Autopilot? That’s right! Even though Autopilot is a fully managed Kubernetes platform which by nature means you don’t have full root access to the node, that doesn’t mean you’re limited in what service mesh you can install. How does it work? Service Meshes require… Continue reading BYO Service Mesh on GKE Autopilot

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Categorized as Autopilot

Mapping Machine Types to Autopilot Compute Classes

Autopilot offers a slightly more abstract view of compute infrastructure than GKE’s Standard mode. The idea is to focus more on the different use-cases than the minutiae of individual machine configurations. However, if you’re coming from GKE Standard or GCE, and know those machine types well, you might want to understand the mapping between the… Continue reading Mapping Machine Types to Autopilot Compute Classes

Multi-Cluster Services on GKE

Connect internal services from multiple clusters together in one logical namespace. Easily connect services running in Autopilot to Standard and vice versa, share services between teams running on their own services, and back an internal service by replicas in multiple clusters for cross-regional availability. All with the Multi-cluster Service support in GKE. For this demo,… Continue reading Multi-Cluster Services on GKE

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Categorized as GKE

Strict Pod Co-location

Pod affinity is a useful technique in Kubernetes for expressing a requirement that a pod, say with the “reader” role, is co-located with another pod, say with the “writer’ role. You can express that requirement by adding something like the following to the reader pod. The catch is, if there is no space on the… Continue reading Strict Pod Co-location

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Categorized as Autopilot

Reducing GKE Log Ingestion

[Update (2023-12-20): You can now turn off workload logging in Autopilot. That is the recommended approach if you want to remove all workload logs. To disable workload logs for Autopilot (for example, if you use a third-party logging agent like DataDog), pass this value at cluster creation: Or update The remainder of this blog post… Continue reading Reducing GKE Log Ingestion

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Categorized as GKE

HA 3-zone Deployments with PodSpreadTopology on Autopilot

PodSpreadTopology is a way to get Kubernetes to spread out your pods across a failure domain, typically nodes or zones. Kubernetes platforms typically have some default spread built in, although it may not be as aggressive as you want (meaning, it might be more tolerant of imbalanced spread). Here’s an example Deployment with a PodSpreadToplogy… Continue reading HA 3-zone Deployments with PodSpreadTopology on Autopilot

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Categorized as Autopilot

TensorFlow on GKE Autopilot with GPU acceleration

Last week, GKE announced GPU support for Autopilot. Here’s a fun way to try it out: a TensorFlow-enabled Jupyter Notebook with GPU-acceleration! We can even add state, so you can save your work between sessions. Autopilot makes all this really, really easy, as you can configure everything as a Kubernetes object. Update: this post is… Continue reading TensorFlow on GKE Autopilot with GPU acceleration

Provisioning one-off spare capacity for GKE Autopilot

I previously documented how to add spare capacity to an Autopilot Kubernetes cluster, whereby you create a placeholder Deployment to provision some scheduling headroom. This works to constantly give you a certain amount of headroom, so for example if you have a 2vCPU placeholder (a.k.a. balloon) Deployment, and use that capacity it will get rescheduled.… Continue reading Provisioning one-off spare capacity for GKE Autopilot

High-Performance Compute on Autopilot

This week, Autopilot announced support for the Scale-Out Compute Class, for both x86 and Arm architectures. The point of this compute class is to give you cores for better single-threaded performance, and improved price/performance for “scale-out” workloads — basically for when you are saturating the CPU, and/or need faster single-threaded performance (e.g. remote compilation, etc).… Continue reading High-Performance Compute on Autopilot

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Categorized as Autopilot

Arm on Autopilot

Arm was made available in Preview on Google Cloud, and GKE Autopilot today! As this is an early stage Preview, there’s a few details to pay attention to if you want to try it out, like the version, regions and quota. I put together this quickstart for trying out Arm in Autopilot today. Arm nodes… Continue reading Arm on Autopilot

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Categorized as Autopilot

Minimizing Pod Disruption on Autopilot

There are 3 common reasons why a Pod may be terminated on Autopilot: node upgrades, a cluster scale-down, and a node repair. PDBs and graceful termination periods modify the disruption to pods when these events happen, and maintenance windows and exclusions control when upgrade events can occur. Upgrade gracefulTerminationPeriod: limited to one hourPDB: is respected… Continue reading Minimizing Pod Disruption on Autopilot

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Categorized as Autopilot

Building GKE Autopilot

Last month gave a presentation at KubeCon Europe in Valencia on “Building a Nodeless Kubernetes Platform”. In it, I shared the details about the creation of GKE Autopilot including some key decisions that we made, how the product was implemented, and why I believe that the design leads to an ideal fully managed platform. Autopilot… Continue reading Building GKE Autopilot

Preferring Spot in GKE Autopilot

Spot Pods are a great way to save money on Autopilot, currently 70% off the regular price. The catch is two-fold: Your workload can be disrupted There may not always be spot capacity available For workload disruption, this is simply a judgement call. You should only run workloads that can accept disruption (abrupt termination). If… Continue reading Preferring Spot in GKE Autopilot

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Categorized as Autopilot

Separating Workloads in Autopilot

Autopilot while being operationally nodeless, still creates nodes for your workloads behind the scenes. Sometimes it may be desirable as an operator to separate your workloads so that certain workloads are scheduled on their separates nodes, a technique known as workload separation. One example I heard recently was a cluster that primarily processes large batch… Continue reading Separating Workloads in Autopilot

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Categorized as Autopilot

Kubernetes Nodes and Autopilot

One of the key design decisions of GKE Autopilot is the fact that we kept the same semantic meaning of the Kubernetes node object. It’s “nodeless” in the sense that you don’t need to care about, or plan for nodes—they are provisioned and managed automatically based on your PodSpec. However, the node object still exists… Continue reading Kubernetes Nodes and Autopilot

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Categorized as Autopilot

Install kn on Cloud Shell

Want to run the Knative CLI tool kn in Google Cloud’s Cloud Shell? It’s easy: Download the latest release from github. linux-amd64 is the platform you want for CloudShell. Here I download version 1.3.0: Then, move it into place, and add it to your PATH: [Updated 2024-02-15 with version 1.3.0]

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Categorized as Kubernetes

Creating an Autopilot cluster at a specific version

Sometimes you may wish to create or update a GKE Autopilot cluster with a specific version. For example, the big news this week is that mutating webhooks are supported in Autopilot (from version 1.21.3-gke.900). Rather than waiting for your desired version to be the default in your cluster’s release channel, you can update ahead of… Continue reading Creating an Autopilot cluster at a specific version

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Categorized as Autopilot

GKE Autopilot: how to know if Pending pods will be scheduled

GKE Autopilot is pretty magical. You create a cluster just by picking a region and giving it a name, schedule Kubernetes workloads and the compute resources are provisioned automatically. While Kubernetes is provisioning resources, your Pods will be in the Pending state. This is all well and good, except… there are other reasons that your… Continue reading GKE Autopilot: how to know if Pending pods will be scheduled

Configuring phpMyAdmin with CloudSQL, RDS, and Docker

I still have a place in my heart for phpMyAdmin, that tool that I was introduced when developing PHP on my shared hosting provider many moons ago. It’s just a great way to inspect your MariaDB/MySQL databases. These days I don’t install any web applications (or databases) on my local machine, I use Docker for… Continue reading Configuring phpMyAdmin with CloudSQL, RDS, and Docker

Provisioning spare capacity in GKE Autopilot with placeholder balloon pods

Autopilot is a new mode of operation for Google Kubernetes Engine (GKE) where compute capacity is dynamically provisioned based on your pod’s requirements. Among other innovations, it essentially functions as a fully automatic cluster autoscaler. Update: GKE now has an official guide for provisioning spare capacity. When you deploy a new pod in this environment,… Continue reading Provisioning spare capacity in GKE Autopilot with placeholder balloon pods

AppAuth

See: http://appauth.io/

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Categorized as OAuth