Wildfly Custom Authentication with JAAS (MongoDB)

 In this post, we will demonstrate how to configure custom login on wildfly by using JAAS. Wildfly provides most common use for login method such as database, LDAP or even flat file. But in the practical situation, there are some requirements that need to combine or customize logic procedure, for example, using multiple source of user management systems, using NO-SQL database for user management, connecting with the legacy system to perform user authentication, etc. To meet these requirement, customize logic mechanism in application server is required. Fortunately, Wildfly also provide module to customize login. Read more.

Secure EJB Access on Wildfly Application Server With JDBC Authentication Realm

 EJB is used to create business logic in Java EE application. Setting up authorization to limit the access to your business execution base on the role. In the enterprise level, security concern is very crucial to ensure the authorized user shall be the only on who those business logic is available to. EJB provide two types of methodologies for securing business logic for instance, declarative and programmatic. Read more

Sharding Table with postgres_fwd on PostgreSQL-12

 In previous post, we have create table partitioning to scale out database. Table partition is stored in the same server, data will store in the single database. In case, we need to distribute data across remote database, we need to use sharding to distribute data in the table. Bellow is the figure of sharding concept. read more

PostgreSQL Connection Pooling with Pgbouncer on CentOS 6

PostgreSQL is quite heavy to establish connection. PostgreSQL deploy concept of process to establish connection from clients. If your connection just connect to database for short period of time, it will consume a lot of resource for each connection. To overcome this issue, connection pooling concept is utilized to handle short-time connection. Connection pooling enble connection resource reusable, so connection will be reuse among incoming connections from clients. Pgbouncer is one of the connection pooling solution that is available. It is very light weight and very easy to setup. In this post I will show how to install and configure pgbouncer to pgpool that I have created in previous post. My deployment concept is shown following . Read more.

Scale out table by partitioning with Postgresql-12

Partition and Sharding is the method to scale out your database when you are dealing with huge volume of data. Table partition and sharding come up with pros and cons, it is the technique to break data table in to multiple pieces and spread them across databases. It will improve database performance and query runtime to be more faster. I think post I'll demonstrate how to partition table and sharding table. Read more.

Load Balancing PostgreSQL Cluster with Repmgr and Pg-Pool-II

In the previous post, I have demonstrate how to create PostgreSQL-12 replication server. I will work well for distribute the connection to both master and slave. But problem is when you create a resource to connect to both databases you need to create two data sources separately which is not realistic the practical application. You need to access to single point of the resource and your connection will be distributed automatically. You don't need to manage connection to the datasource manually. Postgresql provides the solution for this problem by Pg-Pool-II which you have multiple databases (master / slave). You can access to the datasource from one single point of access. Pg-Pool will handle distribution of the connection automatically. So, in this post I will show you how to use Pg-Pool-II to handle request to your database cluster automatically. Read more

Wildfly JPA enable Second Level Cache

Caching is very import technique to improve performance on inquiry. Especially, if you are working with a heavy query that need to join many tables or to retrieve huge amount of the data from the database. Without caching, every single time that data query is executed, disk access happened. This is not a practical manner to handle data inquiry and lead to poor system performance. Accessing data without fetching data directly from the disk could increase data inquiring speed dramatically. Caching inquiry result in the memory and reuse that data is very common practice once it come to handle heavy query or huge amount of data. Read more