In our previous blog post, we discussed how we can apply different changelogs to different database environments. It is more than often, that when applying a changelog, changeset writer assumes database in a certain state. Like when you are adding a column to the database, you would assume that corresponding table is present. Or when you are dropping a table, it has no data in it. Or we assume that underlying database connection is of a particular nature. We can check for and decide what to do by using the concept of Preconditions in the Liquibase. Using preconditions allows to validate underlying assumption and decide the course of action. Read More »
In our previous post, we learned how to use Liquibase to export and compare databases. That brings us to another important question: how do we deploy separate changes on separate database environments like dev, qa, prod etc. Often times, developers would want to push certain changes in the dev environment more frequently and often and not all of them necessarily make it into the production. For example, dev database may have a special ERRORLOG table which stores the debugging information, but there is no requirement of that in the QA or production environment. Similarly, QA team would like to insert some data and modify certain values Read More »
Vagrant is an open source command line tool for building and managing virtual machine environments. By default Vagrant can provision machines on top of VirtualBox, Hyper-V and Docker but many other providers such as Libvirt (KVM), VMware and AWS can be installed via the Vagrant plugin system.
Vagrant is mostly used by developers to easily set up a development environment, that matches the production environment. In this blog post, we’ll discuss how to install Vagrant on Ubuntu 18.04 Operating System. We’ll be using the VirtualBox provider, which is the default provider for Vagrant.
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In our previous post, we learned how to make use of Begin, Process and End blocks to implement proper pipeline support. Building on to that, in this blog post, we’ll learn further about when to make use of ValueFromPipeline property and when to make use of ValueFromPipelineByPropertyName and what happens behind the scenes.
Multiple parameters that accept Pipeline Input
What if there are multiple parameters that can accept pipeline input and we need to run the Process block for them. Let’s consider below code:Read More »
Of many things that make PowerShell stand apart in the world of scripting languages, perhaps two are most fundamental to it: first, its treats everything as Objects and second, the ability to pipe objects from one cmdlet to another. Using this capability, we can effortlessly link multiple cmdlets together. Doing this will also throttle the amount of memory that is being allocated (in most cases) that the current session is using for the commands. So, its very natural that you would want to implement pipeline support for your own function, that you just wrote.
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In previous post, we discussed how we can use Liquibase to deploy changeLogs to databases. Often times, when you start implementing Liquibase, you would already have a database which is being used by the application. Though Liquibase does not depend upon the existing schema, it is still a good idea to export all of the existing schema and possibly data (to some extent) and also put that information in the version control. Also, sometimes you would like to compare databases (both schema and data, again to some extent) Read More »