RAID Levels Explained

RAID Levels - @SeniorDBA

What is RAID?

RAID stands for Redundant Array of Inexpensive Disks. It is a technology used to distribute data across multiple hard drives in one of several ways called “RAID levels”, depending on what level of redundancy and performance is required.

Wikipedia defines RAID as “a data storage virtualization technology that combines multiple physical disk drive components into one or more logical units for the purposes of data redundancy, performance improvement, or both. Data is distributed across the drives in one of several ways, referred to as RAID levels, depending on the required level of redundancy and performance. The different schemes, or data distribution layouts, are named by the word “RAID” followed by a number, for example RAID 0 or RAID 1. Each schema, or RAID level, provides a different balance among the key goals: reliability, availability, performance, and capacity. RAID levels greater than RAID 0 provide protection against unrecoverable sector read errors, as well as against failures of whole physical drives.”

In environments were speed and redundancy are required, you need to select the proper RAID level that matches your requirements and budget. In general, a RAID-enabled system uses two or more hard disks to improve the performance or provide some level of fault tolerance for a NAS or server.

There are several RAID concepts that you must also understand:

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Common Database Design Mistakes

Project Management

When creating a new database instance, people will often make mistakes. While I can’t list all the mistakes that people can or will make, I hope this brief list will help you know what mistakes are possible, and help guide you to not making as many mistakes. Sometimes we attack a design problem with the idea that we will just get the work done, but most times it is better to take the extra time to do it right.

I’m not perfect, and I have made these (any many other) mistakes in database design. I’m not trying to tell you what to do or even how to do it. I’m just trying to take my lessons learned and provide a simple list so that you might not make the same mistakes. I also want to point out that no list will ever be the only way to do anything. With database design questions, the best answer is usually “it depends”. When considering the many variables that make up your environment, you will need to make many decisions that help your database instance work best in your unique environment. You have to take into account the personnel you are working with, limits of your hardware, company policies, etc.

Database design and implementation is the cornerstone of any database related project and should be treated will the importance that deserves. If you do your job really well, people will tend to minimize how important your job is in getting their  projects completed. Like a police department that does a good job catching and locking up criminals, people start wondering why they need so many policemen when the crime rate goes down. People might start asking why they need your help in getting good database design, but it will only take a few failed projects for them to come back to you for your professional help.

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Understanding SQL Server Databases

dba

To manage a database server, you need to understand the types of databases available and the location of those databases. There are two types of databases available in SQL Server:

  1. System Databases
  2. User Databases

System Databases

The system databases are default databases that are created when SQL Server is installed. These databases are used for various operational and management activities for SQL Server, and you have no control over the contents of those databases when they are originally created.

Types of System Databases

There are four system databases in SQL Server:

  • master
  • msdb
  • model
  • tempdb

There is also a fairly recent addition to the group called the resource database. It is very similar to the standard system databases but you need to know that it is hidden from your traditional view through the SQL Server Management Studio (SSMS) GUI and you have read-only access to the data it contains.

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Rebuild and Restore Master Database in SQL Server

database - @SeniorDBA

The Master database is important to your SQL Server instance. This database records all the system-level information for your SQL Server system. This includes instance-wide metadata like logon accounts, endpoints, linked servers, system configuration settings, and records for the existence of all other databases and their file locations.

SQL Server cannot start if the Master database is unavailable. The core information of master database is recorded in a physical file called master.MDF files, and the transaction logs are stored on to the masterlog.LDF file. This means the all user and login details for the instance and the information about all the other databases on that instance are stored on the master database.

If anything happens to the master database you can’t start or use your SQL Server instance. As a Database or System Administrator, it is essential that you to know the symptoms that may indicate the corruption or damage in your Master database so you can troubleshoot those types of issues correctly.

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Update: Cloud Comparison AWS vs. Azure vs. GCP

Cloud Computing - @SeniorDBA

Update: When discussing market growth and sales review, Microsoft is gaining on Amazon but Azure has a very long way to go before they match sales dollar-for-dollar with AWS. These charts from Seeking Alpha, revenue at top and market share at bottom, show Azure is growing but has a long way to go to beat AWS. Google is in a distant third.

AWS Market share

Original Post (12/03/2018):

Three vendors, Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP),  dominate the public cloud computing market. When it comes to infrastructure as a service (IaaS) and platform as a service (PaaS), these three huge vendors have a significant lead on other contenders in the field. Lets talk about the services provided and compare the major features offered by each vendor.

Many IT experts recommend that enterprise teams evaluate their public cloud needs to match specific applications and workloads with the vendor that offers the best fit for their needs. Each vendor has particular strengths and weaknesses that make them a good choice for certain projects.

Compute

Compute is described as the processing power that the cloud service offers to support your business workloads. In general, the more compute power offered the better is can be for your business. Since more compute can cost more money, the price also plays a significant role in understanding the offered compute power.

Startups can find the cloud-based compute model most beneficial because this approach allows them to order extra compute power anytime they want without worrying about long-term installation, maintenance, and hardware costs. You can start small and move to more compute power as required to keep compute costs as small as possible.

AWS – Elastic Compute Cloud: Amazon’s flagship compute service is Elastic Compute Cloud, or EC2. Amazon describes EC2 as “a web service that provides secure, resizable compute capacity in the cloud.” EC2 offers a wide variety of options, including a huge assortment of instances, support for both Windows and Linux, bare metal instances (currently a preview), GPU instances, high-performance computing, auto scaling and more. AWS offers a free tier for EC2 that includes 750 hours per month of t2.micro instances for up to twelve months.

Azure – Virtual Machines: Microsoft’s primary compute service is simply known as Virtual Machines. Azure supports Linux, Windows Server, SQL Server, Oracle, IBM, and SAP. Like AWS, Azure has an extremely large catalog of available instances, including GPU and high-performance computing options. Azure has also added instances optimized for artificial intelligence and machine learning. Azure has a free tier with 750 hours per month of Windows or Linux B1S virtual machines for a year.

GCPCompute Engine: Google’s catalog of compute services is somewhat shorter than AWS or Azure. Their primary service is called Compute Engine, which includes both custom and predefined machine types, per-second billing, Linux and Windows support, automatic discounts, and carbon-neutral infrastructure that uses half the energy of typical data centers. GCP offers a free tier that includes one f1-micro instance per month for up to 12 months.

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Five Years Later

Happy Anniversary - SeniorDBA

It has been over five full years since I started this technology blog. I originally created this blog as an easy to search reference for SQL Server information, really for my own personal use. This started as a place to store example scripts, techniques, and information about SQL Server. It has grown to include information about many of the subjects I deal with in my professional life, including programming, security, and project management.

Here are some basic facts to entertain you on this historic occasion:

  • This site has been in place for five years, and I have posted over 1350 individual posts.
  • I was posting at least one post for each calendar day for the first three years, but now I try to post each Monday.
  • The site now gets about 420 visitors per week, with about 80 page views per weekday. There doesn’t seem to be as much interest on the weekend.
  • When this blog started on December 8, 2013, I was getting an average of 4 visitors per day.
  • The top 5 counties that have visited this site is the USA, India, United Kingdom, Hong Kong SAR China, and Canada.
  • Someone from over 110 counties has visited this site in the last 12 months, with over 22,000 individual page visits.

Year One

Year Two

Year Three

Year Four

I hope you continue to visit this site and you should encourage your friends to visit as well. I really appreciate your support. Thanks.

Cloud Comparison: AWS vs. Azure vs. GCP

Cloud Computing - @SeniorDBA

Three vendors, Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP),  dominate the public cloud computing market. When it comes to infrastructure as a service (IaaS) and platform as a service (PaaS), these three huge vendors have a significant lead on other contenders in the field. Lets talk about the services provided and compare the major features offered by each vendor.

Many IT experts recommend that enterprise teams evaluate their public cloud needs to match specific applications and workloads with the vendor that offers the best fit for their needs. Each vendor has particular strengths and weaknesses that make them a good choice for certain projects.

Compute

Compute is described as the processing power that the cloud service offers to support your business workloads. In general, the more compute power offered the better is can be for your business. Since more compute can cost more money, the price also plays a significant role in understanding the offered compute power.

Startups can find the cloud-based compute model most beneficial because this approach allows them to order extra compute power anytime they want without worrying about long-term installation, maintenance, and hardware costs. You can start small and move to more compute power as required to keep compute costs as small as possible.

AWS – Elastic Compute Cloud: Amazon’s flagship compute service is Elastic Compute Cloud, or EC2. Amazon describes EC2 as “a web service that provides secure, resizable compute capacity in the cloud.” EC2 offers a wide variety of options, including a huge assortment of instances, support for both Windows and Linux, bare metal instances (currently a preview), GPU instances, high-performance computing, auto scaling and more. AWS offers a free tier for EC2 that includes 750 hours per month of t2.micro instances for up to twelve months.

Azure – Virtual Machines: Microsoft’s primary compute service is simply known as Virtual Machines. Azure supports Linux, Windows Server, SQL Server, Oracle, IBM, and SAP. Like AWS, Azure has an extremely large catalog of available instances, including GPU and high-performance computing options. Azure has also added instances optimized for artificial intelligence and machine learning. Azure has a free tier with 750 hours per month of Windows or Linux B1S virtual machines for a year.

GCPCompute Engine: Google’s catalog of compute services is somewhat shorter than AWS or Azure. Their primary service is called Compute Engine, which includes both custom and predefined machine types, per-second billing, Linux and Windows support, automatic discounts, and carbon-neutral infrastructure that uses half the energy of typical data centers. GCP offers a free tier that includes one f1-micro instance per month for up to 12 months.

Continue reading “Cloud Comparison: AWS vs. Azure vs. GCP”