Susana  Stark

Susana Stark

1595821800

DevOps for Database

DevOps for Database

#database #devops

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DevOps for Database

How to Extend your DevOps Strategy For Success in the Cloud?

DevOps and Cloud computing are joined at the hip, now that fact is well appreciated by the organizations that engaged in SaaS cloud and developed applications in the Cloud. During the COVID crisis period, most of the organizations have started using cloud computing services and implementing a cloud-first strategy to establish their remote operations. Similarly, the extended DevOps strategy will make the development process more agile with automated test cases.

According to the survey in EMEA, IT decision-makers have observed a 129%* improvement in the overall software development process when performing DevOps on the Cloud. This success result was just 81% when practicing only DevOps and 67%* when leveraging Cloud without DevOps. Not only that, but the practice has also made the software predictability better, improve the customer experience as well as speed up software delivery 2.6* times faster.

3 Core Principle to fit DevOps Strategy

If you consider implementing DevOps in concert with the Cloud, then the

below core principle will guide you to utilize the strategy.

  • It is indispensable to follow a continuous process, including all stages from Dev to deploy with the help of auto-provisioning resources of the target platform.
  • The team always keeps an eye on major and minor application changes that can typically appear within a few hours of development to operation. However, the support of unlimited resource provisioning is needed at the stage of deployment.
  • Cloud or hybrid configuration can associate this process, but you must confirm that configuration should support multiple cloud brands like Microsoft, AWS, Google, any public and private cloud models.

Guide to Remold Business with DevOps and Cloud

Companies are now re-inventing themselves to become better at sensing the next big thing their customers need and finding ways with the Cloud based DevOps to get ahead of the competition.

#devops #devops-principles #azure-devops #devops-transformation #good-company #devops-tools #devops-top-story #devops-infrastructure

DevOps Basics: What You Should Know

Once an industry term becomes popular, particularly in technology, it can be difficult to get an accurate definition. Everyone assumes that the basics are common knowledge and moves on. However, if your company has been discussing DevOps, or if you are interested in learning more about it, here are some basics you should know.

What Is DevOps?

DevOps refers to the restructuring of the traditional software application cycle to support Agile development and continuous improvement/continuous delivery. Traditionally, the software was created in large-scale, monolithic bundles. New features and new releases were created in large packages and released in full-scale, infrequent, major deployments.

This structure is no longer effective in the modern business environment. Companies are under increasing pressure to be agile. They must respond rapidly to changes in the business environment to remain competitive. Software development needs to be completely changed as a process so that incremental improvements can be made frequently – ideally, several times per day.

However, changing a development lifecycle completely requires major changes – in people and culture, process, and enabling tooling – to be effective. DevOps was created by the breaking down of cycles between development and operations, combining two separate functions in application development. These changes intend to support agile, secure, continuous improvements, and frequent releases.

#devops #devops adoption #devops benefits #q& #a #devops goals #devops migration #devops questions

Ruth  Nabimanya

Ruth Nabimanya

1620633584

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

Houston  Sipes

Houston Sipes

1603177200

Measuring DevOps Metrics: A How-To Guide

DevOps is supposed to help streamline the process of taking code changes and getting them to production for users to enjoy. But what exactly does it mean for the process to be “streamlined”? One way to answer this is to start measuring metrics.

Why metrics are important to track

Metrics give us a way to make sure our quality stays the same over time because we have numbers and key identifiers to compare against. Without any metrics being measured, you don’t have a way to measure improvements or regressions. You just have to react to them as they come up.

When you know the indicators that show what condition your system is in, it lets you catch issues faster than if you don’t have a steady-state to compare to. This also helps when you get ready for system upgrades. You’ll be able to give more accurate estimates of the number of resources your systems use.

After you’ve recorded some key metrics for a while, you’ll start noticing places you could improve your application or ways you can reallocate resources to where they are needed more. Knowing the normal operating state of your system’s pipeline is crucial and it takes time to set up a monitoring tool.

The main thing is that you decide to watch some metrics to get an idea of what’s going on when you start the deploy process. In the beginning, it might seem hard to figure out what the best metrics for a pipeline are.

Figuring out which metrics are important to you

You can conduct chaos engineering experiments to test different conditions and learn more about which metrics are the most important to your system. You can look at things like, time from build to deploy, number of bugs that get caught in different phases of the pipeline, and build size.

Thinking about what you should measure can be one of the harder parts of the effectiveness of the metrics you choose. When you’re considering metrics, look at what the most important results of your pipeline are.

Do you need your app to get through the process as quickly as possible, regardless of errors? Can you figure out why that sporadic issue keeps stopping the deploy process? What’s blocking you from getting your changes to production with confidence?

That’s how you’re going to find those key metrics quickly. Running experiments and looking at common deploy problems will show you what’s important early on. This is one of the ways you can make sure that your metrics are relevant.

#devops #devops-principles #devops-tools #devops-challenges #devops-adoption-challenges #devops-adoption #continuous-deployment #continuous-integration

Humberto  Ratke

Humberto Ratke

1589644080

What is DevOps Lifecycle? | How to manage yours

From conceptualization to deployment, the process of developing software applications or web applications is complex. By going through several intricate phases of development, a web application or software is tested on multiple levels before being proceeded into production.

In most cases, software application development becomes time-consuming due to its specifications and complexities. In order to deliver the application in a short span of time, software developers are following a universal set of practices called the DevOps lifecycle.

So, what is DevOps in the world of software application development? Let’s deep dive into its meaning, uses, as well as each critical phase in the DevOps lifecycle.

#devops #devops tutorial #devops lifecycle tools #devops lifecycle blocks #devops lifecycle phases #lifecycle of devops