ADF Client Side Validation with JavaScript

In my previous post I explained how to use JS client side formatter for ADF Faces input components - ADF Goes Client Side - UI Performance Boost with JavaScript. The same principle can be applied for client side validation. Most likely you are not going to implement complex validation rules on the client side, but for simple checks - it will be perfect. There will be no roundtrip to the server and this will allow to improve user experience.

Client side validation check runs instantly when value is changed and there is no need to set Auto Submit = true to send value to the server. This rule checks value to be in certain range, similar simple checks can be implemented on client side (I'm sure you will find similar rules in your project):

If value is in range, client side formatter is applied as expected:

Custom JSF converter is registered in faces-config.xml and can be added to the input field either manually or dropped through the wizard:

Converter is based on ID, which is defined in faces-config.xml:

Definition in faces-config.xml:

Customer converter class defines range values, these properties will be consumed in JS logic:

Range check is done in JS. If validation fails, we display JSF error message. All happens on client side, without request to the server:

Download sample application with client side validation logic - ADFFormattingApp_v2.zip.

Oracle Java Cloud Service - Scaling and Cluster Setup for ADF

Last couple of weeks I was busy preparing to my OOW'17 session about estimating Java Cloud Service performance for ADF application. I was running stress tests against various JCS instance configurations to be able to create performance estimation methodology. I will describe this methodology on OOW, but here today will list key steps required to scale up JCS instance.

Let's assume you are running single cloud node with 1 CPU and 7.5 GB RAM. This node contains WLS admin and managed server:

To scale up cloud node, simply invoke Scale Up command from the menu. Select new compute shape and confirm scale up operation:

Scale up completed:

Now go to WebLogic console and update Managed Server startup parameters, to adjust heap size to higher value:

Managed server memory can be increased up to certain amount. If more resources will be needed, at some point you will need to create multiple managed servers and connect them into cluster. This would require to define Load Balancer instance (to have single entry point to the cluster):

Cluster node must run in dedicated cloud node. If cluster is based on two managed servers, there must be two cloud nodes:

Managed servers from cloud nodes can be connected into single cluster, this can be done in WebLogic console:

Once cluster is defined, deployment becomes easy - you can deploy ADF application into cluster and it will be propagated to all nodes:

Traffic director running in load balancer instance will be automatically configured to route traffic to cluster nodes:

My Blog Samples Download Repository (For Samples Before 2014 January)

I have been asked, where to download my blog sample applications, posted before 2014 January. If you try to download such sample - you will get error about sample not found. Thats because Google discontinued their support for Google Code repository.

However, you can still download all my samples posted before 2014 January from Google Code archive. Go to archive URL - Google Code Archive for jdevsamples and you can browse all old samples there by date:

All new samples (after 2014 January) are hosted from Google Drive or from GitHub and are accessible directly from blog by URL.