Arangodb ui upgrade#
Arangodb ui code#

Note that these particular URLs contain the version which is current at the time of this writing, but the latest command is always available on this page, where you also find instructions to set up our storage operator and the one for DC2DC replication.įurthermore, note that the custom resource definitions are global to the k8s cluster, whereas our deployment operator is deployed into a particular namespace. To deploy the custom resource definitions as well as the operator itself. Once your kubectl tool is installed and credentials are sorted, you can essentially just do kubectl apply -f kubectl apply -f Therefore, we have put together detailed tutorials for the steps to set up the k8s cluster and authentication for individual cloud platforms, see this page for details, so far we have GKE, EKS and AKS (Azure Kubernetes Service), but we are going to extend this to other platforms soon. With the above mentioned cloud platforms, this is essentially just a few clicks away, but one needs administrator rights for a few steps, for example for the deployment of the custom resource definitions.

The first to sort out is access to a Kubernetes cluster with the right credentials. In this article I would like to highlight again how convenient deployment and maintenance of a distributed ArangoDB cluster has become with the help of k8s, custom resources and our operator.

Arangodb ui upgrade#

In the context of k8s this means that performing a fully automatic rolling upgrade from 3.3.20 to 3.4 is as easy as editing the name of the Docker image used in the k8s specs. However, experience shows that one has to test every single platform individually, in particular with respect to volume support, networking (load balancer services etc.) and access control.įurthermore, the ArangoDB 3.4 release has finally happened and we have put particular emphasis on a seamless upgrade path from 3.3. We have developed a semi-automatic “acceptance test” to validate production readiness for each new platform, and therefore you can expect quick progress on this topic in the near future. Since then, quite a few things have happened.įor example, we have done a lot of testing, fixed bugs, and by now the operator is declared to be production ready for three popular public Kubernetes offerings, namely Google Kubernetes Engine (GKE), Amazon Elastic Kubernetes Service (EKS) and Pivotal Kubernetes Service (PKS) ( see here for the current state of affairs). It has been a few months since we first released the Kubernetes operator for ArangoDB and started to brag about it. In addition, there are actionįor the built-in example queries, there is only Copy to editor available.Steps for deploying ArangoDB on Kubernetes

Arangodb ui code#

Here you can select a previously stored customĬlick on a query title to get a code preview. The editor or use the shortcut (see below).īy pressing the Queries button in the top left corner of the editor youĪctivate the custom queries view. To save the current query use the Save button in the top left corner of You can thenĮdit the bind parameters in raw JSON format. If you are used to work with JSON, you may want to switch the bind parameterĮditor to JSON mode by clicking on the upper right toggle button. This will mostly be what you want.īut if you want to force something to be treated as string, use quotation marksġ23 // interpreted as number ' 123 ' // interpreted as string // interpreted as array // interpreted as string

Values have to be surrounded by double quotes). Squareīrackets can be used to define arrays, and curly braces for objects (keys and Numbers will be treatedĪs numbers, true and false as booleans, null as null-type value. Use quote marks around string, just write them as-is. The input fields are equipped with type detection. By default, the entered bind parameter willĪutomatically be recognized and shown in the bind parameter table in the right The left pane is your regular query input field, where you can edit and thenĮxecute or explain your queries. The editor is split into two parts, the query editor pane and the bind The web interface offers a AQL Query Editor: The query view offers you three different subviews:

Upgrading an Active Failover deployment.Deployment Replication Resource Reference.