Green Tea Matcha Cookies

For a team event during the Christmas season we decided to completely reinterpret the topic cookies. :-)

Matcha cookies have the delicate flavor and color of green tea. These soft, pillowy and chewy green tea cookies are perfect with tea. And of course they fit perfectly to our logo.

Ingredients

• 1 stick butter, softened
• ⅞ cup of granulated sugar
• 1 cup + 2 tablespoons all-purpose flour
• 2 eggs
• 1¼ tablespoons culinary grade matcha powder
• 1 teaspoon baking powder
• pinch of salt

Instructions

1. Cream together the butter and sugar in a large mixing bowl - it should be creamy colored and airy. A hand blender or stand mixer works well for this. This helps the cookie become fluffy and chewy.
2. Gently incorporate the eggs to the butter mixture one at a time.
3. In a separate bowl, sift together all the dry ingredients.
4. Add the dry ingredients to the wet by adding a little at a time and folding or gently mixing the batter together. Keep going until you’ve incorporated all the remaining flour mixture. The dough should be a beautiful green color.
5. Chill the dough for at least an hour - up to overnight. The longer the better!
6. Preheat your oven to 325 F.
7. Roll the dough into balls the size of ping pong balls and place them on a non-stick cookie sheet.
8. Bake them for 12-15 minutes until the bottoms just start to become golden brown and the cookie no longer looks wet in the middle. Note: you can always bake them at 350 F for a less moist, fluffy cookie. It will bake faster by about 2-4 minutes 350 F so watch them closely.
9. Remove and let cool on a rack and enjoy!

Note

Make sure you get culinary grade matcha powder. You should be able to find this in Asian or natural grocers.

Do you want to understand how Gardener creates and updates Kubernetes clusters (Shoots)? Well, it’s complicated, but if you are not afraid of large diagrams and are a visual learner like me, this might be useful to you.

Introduction

In this blog post I will share a technical diagram which attempts to tie together the various components involved when Gardener creates a Kubernetes cluster. I have created and curated the diagram, which visualizes the Shoot reconciliation flow since I started developing on Gardener. Aside from serving as a memory aid for myself, I created it in hopes that it may potentially help contributors to understand a core piece of the complex Gardener machinery. Please be advised that the diagram and components involved are large. Although it can be easily divided into multiple diagrams, I want to show all the components and connections in a single diagram to create an overview of the reconciliation flow.

The goal is to visualize the interactions of the components involved in the Shoot creation. It is not intended to serve as a documentation of every component involved.

Background

Taking a step back, the Gardener READ.me states

In essence, Gardener is an extension API server that comes along with a bundle of custom controllers. It introduces new API objects in an existing Kubernetes cluster (which is called garden cluster) in order to use them for the management of end-user Kubernetes clusters (which are called shoot clusters). These shoot clusters are described via declarative cluster specifications which are observed by the controllers. They will bring up the clusters, reconcile their state, perform automated updates and make sure they are always up and running.

This means that Gardener, just like any Kubernetes controller, creates Kubernetes clusters (Shoots) using a reconciliation loop.

The Gardenlet contains the controller and reconciliation loop responsible for the creation, update, deletion and migration of Shoot cluster (there are more, but we spare them in this article). In addition, the Gardener Controller Manager also reconciles Shoot resources, but only for seed-independent functionality such as Shoot hibernation, Shoot maintenance or quota control.

This blog post is about the reconciliation loop in the Gardenlet responsible for creating and updating Shoot clusters. The code can be found here. The reconciliation loops of the extension controllers can be found in their individual repositories.

Shoot reconciliation flow diagram

When Gardner creates a Shoot cluster, there are three conceptual layers involved: the Garden cluster, the Seed cluster and the Shoot cluster. Each layer represents a top-level section in the diagram (similar to a lane in a BPMN diagram).

It might seem confusing, that the Shoot cluster itself is a layer, because the whole flow in the first place is about creating the Shoot cluster. I decided to introduce this separate layer to make a clear distinction between which resources exist in the Seed API server (managed by Gardener) and which in the Shoot API server (accessible by the Shoot owner).

Each section contains several components. Components are mostly Kubernetes resources in a Gardener installation (e.g. the gardenlet deployment in the Seed cluster).

This is the list of components:

(Virtual) Garden Cluster

• Gardener Extension API server
• Validating Provider Webhooks
• Project Namespace

Seed Cluster

• Gardenlet
• Seed API server
  • every Shoot Control Plane has a dedicated namespace in the Seed.
• Cloud Provider (owned by Stakeholder).
  • Arguably part of the Shoot cluster but used by components in the Seed cluster to create the infrastructure for the Shoot.
• Gardener DNS extension
• Provider Extension (such as gardener-extension-provider-aws)
• Gardener Extension ETCD Druid
• Gardener Resource Manager
• Operating System Extension (such as gardener-extension-os-gardenlinux)
• Networking extension (such as gardener-extension-networking-cilium)
• Machine Controller Manager
• ContainerRuntime Extension (such as gardener-extension-runtime-gvisor)
• Shoot API server (in the Shoot Namespace in the Seed cluster)

Shoot Cluster

• Cloud Provider compute API (owned by Stakeholder) - for VM/Node creation.
• VM / Bare metal node hosted by Cloud Provider (in Stakeholder owned account).

How to use the diagram

The diagram

• should be read from top to bottom - starting in the top left corner with the creation of the Shoot resource via the Gardener Extension API server.
• should not require an encompassing documentation / description. More detailed documentation on the components itself, can usually be found in the respective repository.
• does not show which activities execute in parallel (many) and also does not describe the exact dependencies between the steps. This can be found out by looking at the source code. It however tries to put the activities in a logical order of executing during the reconciliation flow.

Occasionally, there is an info box with additional information next to parts in the diagram that in my point of view require further explanation. Large example resource for the Gardener CRDs (e.g Worker CRD, Infrastructure CRD) are placed on the left side and are referenced by a dotted line (—–).

Be aware, that Gardener is an evolving project, so the diagram will most likely be already outdated by the time you are reading this. Nevertheless, it should give a solid starting point for further explorations into the details of Gardener.

Flow diagram

The diagram can be found below and on Github.com. There are multiple formats available (svg, vsdx, draw.io, html).

Please open an issue or open a PR in the repository if information is missing or is incorrect. Thanks!

STACKIT is a digital brand of Europe’s biggest retailer, the Schwarz Group, which consists of Lidl, Kaufland, as well as production and recycling companies. Following the industry trend, the Schwarz Group is in the process of a digital transformation. STACKIT enables this transformation by helping to modernize the internal IT of the company branches.

What is STACKIT and the STACKIT Kubernetes Engine (SKE)?

STACKIT started with colocation solutions for internal and external customers in Europe-based data centers, which was then expanded to a full cloud platform stack providing an IaaS layer with VMs, storage and network, as well as a PaaS layer including Cloud Foundry and a growing set of cloud services, like databases, messaging, etc.

With containers and Kubernetes becoming the lingua franca of the cloud, we are happy to announce the STACKIT Kubernetes Engine (SKE), which has been released as Beta in November this year. We decided to use Gardener as the cluster management engine underneath SKE - for good reasons as you will see – and we would like to share our experiences with Gardener when working on the SKE Beta release, and serve as a testimonial for this technology.

Why we chose Gardener as a cluster management tool

We started with the Kubernetes endeavor in the beginning of 2020 with a newly formed agile team that consisted of software engineers, highly experienced in IT operations and development. After some exploration and a short conceptual phase, we had a clear-cut opinion on how the cluster management for STACKIT should look like: we were looking for a highly customizable tool that could be adapted to the specific needs of STACKIT and the Schwarz Group, e.g. in terms of network setup or the infrastructure layer it should be running on. Moreover, the tool should be scalable to a high number of managed Kubernetes clusters and should therefore provide a fully automated operation experience. As an open source project, contributing and influencing the tool, as well as collaborating with a larger community were important aspects that motivated us. Furthermore, we aimed to offer cluster management as a self-service in combination with an excellent user experience. Our objective was to have the managed clusters come with enterprise-grade SLAs – i.e. with “batteries included”, as some say.

With this mission, we started our quest through the world of Kubernetes and soon found Gardener to be a hot candidate of cluster management tools that seemed to fulfill our demands. We quickly got in contact and received a warm welcome from the Gardener community. As interested potential adopter, but in the early days of the COVID-19 lockdown, we managed to organize an online workshop during which we got an introduction and deep dive into Gardener and discussed the STACKIT use cases. We learned that Gardener is extensible in many dimensions, and that contributions are always welcome and encouraged. Once we understood the basic Gardener concepts of Garden, Shoot and Seed clusters, its inception design and how this extends Kubernetes concepts in a natural way, we were eager to evaluate this tool in more detail.

After this evaluation, we were convinced that this tool fulfilled all our requirements - a decision was made and off we went.

How Gardener was adapted and extended by SKE

After becoming familiar with Gardener, we started to look into its code base to adapt it to the specific needs of the STACKIT OpenStack environment. Changes and extensions were made in order to get it integrated into the STACKIT environment, and whenever reasonable, we contributed those changes back:

• To run smoothly with the STACKIT OpenStack layer, the Gardener configuration was adapted in different places, e.g. to support CSI driver or to configure the domains of shoot API server or ingress.
• Gardener was extended to support shoots and shooted seeds in dual stack and dual home setup. This is used in SKE for the communication between shooted seeds and the Garden cluster.
• SKE uses a private image registry for Gardener installation to resolve dependencies to public image registries and to have more control over the used Gardener versions. To install and run Gardener with the private image registry, some new configurations need to be introduced into Gardener.
• Gardener is a first-class API based service what allowed us to smoothly integrate it into the STACKIT User Interface. We were able to jump-start and utilize also the Gardener Dashboard for our Beta release by merely adjusting the look-&-feel, i.e. colors, labels and icons.

Experience with Gardener operations

As no OpenStack installation is identical to one another, getting Gardener to run stable on the STACKIT IaaS layer revealed some operational challenges. For instance, it was challenging to find the right configuration for Cinder CSI.

To test for its resilience, we tried to break the managed clusters with a Chaos Monkey test, e.g. by deleting services or components needed by Kubernetes and Gardener to work properly. The reconciliation feature of Gardener fixed all those problems automatically, so that damaged Shoot clusters became operational again after a short period of time. Thus, we were not able to break Shoot clusters from an end user perspective permanently, despite our efforts. Which again speaks for Gardener’s first-class cloud native design.

We also participated in a fruitful community support: For several challenges we contacted the community channel and help was provided in a timely manner. A lesson learned was that raising an issue in the community early on, before getting stuck too long on your own with an unresolved problem, is essential and efficient.

Summary

Gardener is used by SKE to provide a managed Kubernetes offering for internal use cases of the Schwarz Group as well as for the public cloud offering of STACKIT. Thanks to Gardener, it was possible to get from zero to a Beta release in only about half a year’s time – this speaks for itself. Within this period, we were able to integrate Gardener into the STACKIT environment, i.e. in its OpenStack IaaS layer, its management tools and its identity provisioning solution.

Gardener has become a vital building block in STACKIT’s cloud native platform offering. For the future, the possibility to manage clusters also on other infrastructures and hyperscalers is seen as another great opportunity for extended use cases. The open co-innovation exchange with the Gardener community member companies has also opened the door to commercial co-operation.