What is database continuous integration?

Have you ever longed for a way of making the delivery of databases more visible, predictable and measurable? Do you ever wish that they would be of better quality, quicker to change, and cost less? Grant Fritchey explains some of the secrets of doing Continuous Integration for Databases to relieve some of the pain-points of the Database Delivery process.

Continuous Integration (CI) is an essential step of application development for DevOps organisations. Whenever a developer commits code, a build is kicked off. The code must compile and pass automated testing before it is merged into the main branch. Developers have been working this way for years, but including the database in CI has lagged behind. Leaving the database out of CI has caused it to become the bottleneck that slows down the delivery of new features. Even though it’s more difficult to execute, many organizations have successfully implemented database CI with the right tools.

The purpose of Database CI is exactly the same as for application CI. The development team establish a working version of the database very early in the development cycle, and then continue to verify regularly that it remains in a working state as they expand and refactor the schema and database code objects. Developers integrate new and changed code into a shared version control repository several times a day. Development proceeds in small steps. Developers first write the tests that, if passed, will prove that a small new piece of functionality works. They then implement the code to make the tests pass. When the tests pass, they commit the code to “trunk” in the shared VCS, and their “commit tests” are added to the broader suite of tests for the application. Each commit, or check-in, is then verified by an automated database build or migration, and subsequent testing, allowing teams to detect problems early.

Where do you start with database CI? There are several requirements outlined here.

Maintain the database in version control

The first prerequisite for Database CI is that the source of “truth” for the database CI process and all subsequent database deployments must be the build and migration scripts in a version control system (VCS), such as Git or Subversion. In other words, the database CI process must always be triggered from the VCS. There must be no ad-hoc builds or database modifications that bypass this formal process.

There are several CI management software services available. Each one I’ve worked with has hooks into various version control systems. With these hooks you can set up mechanisms for automating your database CI processes.

#database delivery #database devops #continuous integration #database #dlm_ebook #sql

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What is database continuous integration?

Have you ever longed for a way of making the delivery of databases more visible, predictable and measurable? Do you ever wish that they would be of better quality, quicker to change, and cost less? Grant Fritchey explains some of the secrets of doing Continuous Integration for Databases to relieve some of the pain-points of the Database Delivery process.

Continuous Integration (CI) is an essential step of application development for DevOps organisations. Whenever a developer commits code, a build is kicked off. The code must compile and pass automated testing before it is merged into the main branch. Developers have been working this way for years, but including the database in CI has lagged behind. Leaving the database out of CI has caused it to become the bottleneck that slows down the delivery of new features. Even though it’s more difficult to execute, many organizations have successfully implemented database CI with the right tools.

The purpose of Database CI is exactly the same as for application CI. The development team establish a working version of the database very early in the development cycle, and then continue to verify regularly that it remains in a working state as they expand and refactor the schema and database code objects. Developers integrate new and changed code into a shared version control repository several times a day. Development proceeds in small steps. Developers first write the tests that, if passed, will prove that a small new piece of functionality works. They then implement the code to make the tests pass. When the tests pass, they commit the code to “trunk” in the shared VCS, and their “commit tests” are added to the broader suite of tests for the application. Each commit, or check-in, is then verified by an automated database build or migration, and subsequent testing, allowing teams to detect problems early.

Where do you start with database CI? There are several requirements outlined here.

Maintain the database in version control

The first prerequisite for Database CI is that the source of “truth” for the database CI process and all subsequent database deployments must be the build and migration scripts in a version control system (VCS), such as Git or Subversion. In other words, the database CI process must always be triggered from the VCS. There must be no ad-hoc builds or database modifications that bypass this formal process.

There are several CI management software services available. Each one I’ve worked with has hooks into various version control systems. With these hooks you can set up mechanisms for automating your database CI processes.

#database delivery #database devops #continuous integration #database #dlm_ebook #sql

System Databases in SQL Server

Introduction

In SSMS, we many of may noticed System Databases under the Database Folder. But how many of us knows its purpose?. In this article lets discuss about the System Databases in SQL Server.

System Database

Fig. 1 System Databases

There are five system databases, these databases are created while installing SQL Server.

• Master
• Model
• MSDB
• Tempdb
• Resource

Master

• This database contains all the System level Information in SQL Server. The Information in form of Meta data.
• Because of this master database, we are able to access the SQL Server (On premise SQL Server)

Model

• This database is used as a template for new databases.
• Whenever a new database is created, initially a copy of model database is what created as new database.

MSDB

• This database is where a service called SQL Server Agent stores its data.
• SQL server Agent is in charge of automation, which includes entities such as jobs, schedules, and alerts.

TempDB

• The Tempdb is where SQL Server stores temporary data such as work tables, sort space, row versioning information and etc.
• User can create their own version of temporary tables and those are stored in Tempdb.
• But this database is destroyed and recreated every time when we restart the instance of SQL Server.

Resource

• The resource database is a hidden, read only database that holds the definitions of all system objects.
• When we query system object in a database, they appear to reside in the sys schema of the local database, but in actually their definitions reside in the resource db.

#sql server #master system database #model system database #msdb system database #sql server system databases #ssms #system database #system databases in sql server #tempdb system database

Django-allauth: A simple Boilerplate to Setup Authentication

Django-Authentication 

A simple Boilerplate to Setup Authentication using Django-allauth, with a custom template for login and registration using django-crispy-forms.

Getting Started

Prerequisites

• Python 3.8.6 or higher

Project setup

# clone the repo
$ git clone https://github.com/yezz123/Django-Authentication

# move to the project folder
$ cd Django-Authentication

Creating virtual environment

• Create a virtual environment for this project:

# creating pipenv environment for python 3
$ virtualenv venv

# activating the pipenv environment
$ cd venv/bin #windows environment you activate from Scripts folder

# if you have multiple python 3 versions installed then
$ source ./activate

Configured Enviromment

Environment variables

SECRET_KEY = #random string
DEBUG = #True or False
ALLOWED_HOSTS = #localhost
DATABASE_NAME = #database name (You can just use the default if you want to use SQLite)
DATABASE_USER = #database user for postgres
DATABASE_PASSWORD = #database password for postgres
DATABASE_HOST = #database host for postgres
DATABASE_PORT = #database port for postgres
ACCOUNT_EMAIL_VERIFICATION = #mandatory or optional
EMAIL_BACKEND = #email backend
EMAIL_HOST = #email host
EMAIL_HOST_PASSWORD = #email host password
EMAIL_USE_TLS = # if your email use tls
EMAIL_PORT = #email port

change all the environment variables in the .env.sample and don't forget to rename it to .env.

Run the project

After Setup the environment, you can run the project using the Makefile provided in the project folder.

help:
 @echo "Targets:"
 @echo "    make install" #install requirements
 @echo "    make makemigrations" #prepare migrations
 @echo "    make migrations" #migrate database
 @echo "    make createsuperuser" #create superuser
 @echo "    make run_server" #run the server
 @echo "    make lint" #lint the code using black
 @echo "    make test" #run the tests using Pytest

Preconfigured Packages

Includes preconfigured packages to kick start Django-Authentication by just setting appropriate configuration.

Package	Usage
django-allauth	Integrated set of Django applications addressing authentication, registration, account management as well as 3rd party (social) account authentication.
django-crispy-forms	django-crispy-forms provides you with a crispy filter and {% crispy %} tag that will let you control the rendering behavior of your Django forms in a very elegant and DRY way.

Contributing

• Django-Authentication is a simple project, so you can contribute to it by just adding your code to the project to improve it.
• If you have any questions, please feel free to open an issue or create a pull request.

Download Details:
Author: yezz123
Source Code: https://github.com/yezz123/Django-Authentication
License: MIT License

#django #python 

SingleStore: The One Stop Shop For Everything Data

• SingleStore works toward helping businesses embrace digital innovation by operationalising “all data through one platform for all the moments that matter”

The pandemic has brought a period of transformation across businesses globally, pushing data and analytics to the forefront of decision making. Starting from enabling advanced data-driven operations to creating intelligent workflows, enterprise leaders have been looking to transform every part of their organisation.

SingleStore is one of the leading companies in the world, offering a unified database to facilitate fast analytics for organisations looking to embrace diverse data and accelerate their innovations. It provides an SQL platform to help companies aggregate, manage, and use the vast trove of data distributed across silos in multiple clouds and on-premise environments.

**Your expertise needed! **Fill up our quick Survey

#featured #data analytics #data warehouse augmentation #database #database management #fast analytics #memsql #modern database #modernising data platforms #one stop shop for data #singlestore #singlestore data analytics #singlestore database #singlestore one stop shop for data #singlestore unified database #sql #sql database

How to Efficiently Choose the Right Database for Your Applications

Finding the right database solution for your application is not easy. Learn how to efficiently find a database for your applications.

Finding the right database solution for your application is not easy. At iQIYI, one of the largest online video sites in the world, we’re experienced in database selection across several fields: Online Transactional Processing (OLTP), Online Analytical Processing (OLAP), Hybrid Transaction/Analytical Processing (HTAP), SQL, and NoSQL.

Today, I’ll share with you:

• What criteria to use for selecting a database.
• What databases we use at iQIYI.
• Some decision models to help you efficiently pick a database.
• Tips for choosing your database.

I hope this post can help you easily find the right database for your applications.

#database architecture #database application #database choice #database management system #database management tool