multi-cloud | SODA Strato project | Cloud Storage library

Cloud Composer uses managed GKE instance and it is managed for you by Google team. It has built-in scalability etc. (there is a talk about it at the summit next week BTW https://airflowsummit.org/sessions/2021/autoscaling-airflow/)

It uses Celery Executor exclusively though and you cannot change it to KubernetesExecutor

Yes it is possible with istio multi cluster single mesh model.

According to istio documentation:

Multiple clusters

You can configure a single mesh to include multiple clusters. Using a multicluster deployment within a single mesh affords the following capabilities beyond that of a single cluster deployment:

• Fault isolation and fail over: cluster-1 goes down, fail over to cluster-2.
• Location-aware routing and fail over: Send requests to the nearest service.
• Various control plane models: Support different levels of availability.
• Team or project isolation: Each team runs its own set of clusters.

A service mesh with multiple clusters

Multicluster deployments give you a greater degree of isolation and availability but increase complexity. If your systems have high availability requirements, you likely need clusters across multiple zones and regions. You can canary configuration changes or new binary releases in a single cluster, where the configuration changes only affect a small amount of user traffic. Additionally, if a cluster has a problem, you can temporarily route traffic to nearby clusters until you address the issue.

You can configure inter-cluster communication based on the network and the options supported by your cloud provider. For example, if two clusters reside on the same underlying network, you can enable cross-cluster communication by simply configuring firewall rules.

Single mesh

The simplest Istio deployment is a single mesh. Within a mesh, service names are unique. For example, only one service can have the name mysvc in the foo namespace. Additionally, workload instances share a common identity since service account names are unique within a namespace, just like service names.

A single mesh can span one or more clusters and one or more networks. Within a mesh, namespaces are used for tenancy.

Hope it helps.

Kuma defines the so-called zone as a domain of control isolation, i.e. all workload connections are managed by a single control plane. Such a control plane is called remote. The overall view and policy management is done in a global control plane, which unifies all zones.

When one starts planning a distributed deployment, they have to enlist the following items:

• Where the Global control plane will be deployed and its type. The latter can be either Universal (VM/BareMetal/Container) or Kubernetes(on-premise/cloud).
• Number and type of zones to add. These can be changed over time.

Follow the instructions to install the global control plane following the steps specific for the chose type of deployment. Gather the relevant IP address/ports as described.

Installing remote control plane is fairly trivial. This process can be repeated as needed during the lifetime of the whole multi-zone deployment.

Cross-zone service consumption is described in brief here. In short, we do recommend using the following syntax to access a service echo-server, deployed in a Kubernetes namespace echo-example and exposed on port 1010:

There are no examples. Service accounts are absolutely required, even if hidden from view, to deal with Google Cloud products. They're part of the IAM system for authenticating and authorizing various pieces of software for use with various products. I strongly suggest that you become familiar with the mechanisms of providing a service account to a given program. For code running outside of Google Cloud compute and serverless products, the current preferred solution involves using environment variables to point to files that contain credentials. For code running Google (like Cloud Run, Compute Engine, Cloud Functions), it's possible to provide service accounts by configuration so that the code doesn't need to do anything special.

When we use Azure Blob rest api to upload something to Azure blob storage with sas token, We need to specify x-ms-blob-type in request headers. For more details, please refer to the document. Now you upload image to Azure blob, we can use BlockBlob as its value.

For example 1. Install SDK