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Prerequisites

For ODAS to work in GCP, and GKE specifically, there are a few requirements that need to be addressed at some point in time. This includes access to storage buckets as well as a transactional database instance. The following topics address these dependencies and how to acquire them in a general manner. Okera is aware that, in practice, a lot of these resources are already deployed and shared with other services. In that case, it is required to work with the owners of these services to agree to an access pattern.

Google Cloud Storage (GCS)

ODAS requires a GCS path where it can store audit and operational logs, e.g. gs://mycompany-odas/odas-cluster-123. We will refer to this as the ODAS GCS Storage. If you do not already have GCS storage created, please refer to the online documentation to create it.

Resource Project

You will need a resource project where you will create ODAS resources such as your GKE cluster.

To create a resource project, navigate to the New Project page. See the online documentation for more details.

Database (Cloud SQL)

ODAS is backed by a relational database, and we strongly recommend using Google Cloud SQL. ODAS supports MySQL 5.6 and 5.7.

To create a Cloud SQL database instance, navigate to the Create an instance page. Consult the online documentation for more information.

After the database is created, navigate to the Cloud SQL page:

  1. Select your database, e.g. odas-gcp-sql.
  2. In "Overview", write down the "Connect to this instance" details, this will be used later as part of your "Catalog DB URL".
  3. In "Connections", ensure that "Allow only SSL connections" is selected.
  4. In "Users", create a new admin user that can manage the ODAS databases. Write down the new admin name and password, this will be used later as your "Catalog DB User".

Google Kubernetes Engine (GKE)

ODAS runs on top of Kubernetes, and on GCP, we leverage GKE as our managed Kubernetes runtime.

You should follow official documentation for creating GKE clusters.

Once the GKE cluster is created, you will need to be able to access it using kubectl from a machine, which we call the deployer node. To do this, install and configure the Google SDK CLI on that machine, and then execute the following command:

$ gcloud container clusters get-credentials <your gke cluster> --region=<region>

Also see the online documentation for details.

Once complete, you should be able to use kubectl normally, e.g.:

$ kubectl get nodes -owide
NAME                                       STATUS   ROLES    AGE   VERSION             INTERNAL-IP   EXTERNAL-IP      OS-IMAGE                             KERNEL-VERSION   CONTAINER-RUNTIME
gke-cluster-1-odas-default-309f3494-chhm   Ready    <none>   10m   v1.15.12-gke.6002   10.128.0.12   35.123.123.321   Container-Optimized OS from Google   4.19.112+        docker://19.3.1
gke-cluster-1-odas-default-309f3494-d1vl   Ready    <none>   20d   v1.15.12-gke.6002   10.128.0.10   34.321.321.123   Container-Optimized OS from Google   4.19.112+        docker://19.3.1
gke-cluster-1-odas-default-309f3494-t7m0   Ready    <none>   10m   v1.15.12-gke.6002   10.128.0.11   34.123.321.123   Container-Optimized OS from Google   4.19.112+        docker://19.3.1

You can also see all available Kubernetes contexts:

$ kubectl config get-contexts
CURRENT   NAME                                            CLUSTER                                         AUTHINFO                                            NAMESPACE
...
*         gke_vivid-lane-285120_us-central1-c_cluster-1   gke_vivid-lane-285120_us-central1-c_cluster-1   gke_vivid-lane-285120_us-central1-c_cluster-1
...