How Does the Cloud Change a Database Administrator’s Job?

BuckWoody — Tue, 29 Jan 2013 15:08:32 GMT

I recently posted a blog entry on how cloud computing would change the Systems Architect’s role in an organization. In a way, the Systems Architect has the easiest transition to a new way of using computing technologies. In fact, that’s actually part of the job description. I mentioned that a Systems Architect has three primary vectors to think about for cloud computing, as it applies to what they should do:

Knowledge - Which options are available to solve problems, and what are their strengths and weaknesses.
Experience - What has the System Architect seen and worked with in the past.
Coordination - A system design is based on multiple factors, and one person can't make all the choices. There will need to be others involved at every level of the solution, and the Systems Architect will need to know who those people are and how to work with them.

The Database Administrator Role

But a Database Administrator (DBA) is probably one of the harder roles to think about when it comes to cloud computing. First, let’s define what a Database Administrator usually thinks about as part of their job:

Planning, Installing and Configuring a Database Platform
Planning, designing and creating databases
Planning, designing and implementing High Availability and Disaster Recovery for each database (HADR) based on requirements for its workload
Maintaining and monitoring the database platform
Implementing performance tuning on the databases based on monitoring
Re-balancing workloads across database servers based on monitoring
Securing databases platforms and individual databases based on requirements and implementation

That’s just a short list, and each of those unpacks into a larger set of tasks.

The issue is that I’ve never actually met a DBA that does all of those things, or just all of those things. Many times they do much more, sometimes the systems are so large they specialize on just a few of them.

And as you can see from the list, some of these areas are shared with other roles. For instance, in some shops, the DBA plans, purchases, sets up and configures the hardware for database servers. In others that’s done
by the Infrastructure Team. In some shops the DBA designs databases from software requirements, and in others the developers do that – or perhaps it’s done as a joint effort. The same holds true for database code – sometimes the
DBA does it, other times the developer, and still others it’s a shared task.

In fact, you could argue that there are few other roles in IT where the roles are so intermixed. Also, the DBA works with software the company develops, and software the company buys. They work with hardware, networking, security and software. There are certain aspects of design and tuning that are outside the purview of some of those things, and inside the others.

With all of these variables, simply telling a DBA that they should “use the cloud” is not the proper approach.

How the Cloud Changes Things

To be sure, the DBA has the same vectors as the Systems Architect. They need to educate themselves on the options within this new option (Knowledge), try a few test solutions out (Experience) and of course work with others on various parts of the implementation (Coordination). But it goes beyond that.

There are three big buckets of cloud computing, dealing with simply using a Virtual Machine (IaaS) to writing code without worrying about the virtualization or even the operating system (PaaS) and using software that’s already written and being delivered via an Application Programming Interface (API). Each of these has so many options and configurations that it’s often better to think about the problem you’re trying to solve rather than all of the technology within a given area - although some of that is certainly necessary anyway.

Database Platform Architecture

I’ll start with when the DBA should even consider cloud computing for a solution. Once again, it’s not an “all or nothing” paradigm, where you either run something on premises or in the cloud – it’s often a matter of selecting the right components to solve a problem. In my design sessions with DBA’s I break these down into three big areas where they might want to consider the cloud –and then we talk about how to implement each one:

Audiences
HADR
Data Services

Audiences

If the users of your database systems all sit in the same facility, you own the servers and networking, and the application servers are separate from the database server, it doesn’t usually make sense to take that database workload and place it on Windows Azure – or any other cloud provider. The latency alone prevents a satisfactory performance profile, and in some cases won’t work at all. It doesn’t matter if the cloud solution is cheaper or easier – if you’re moving a lot of data every second between an on-premises system and the cloud it won’t work well.

However – if your users are in multiple locations, especially globally, or you have a mix of company and external customer users, it might make sense to evaluate a shared data location. You still need to consider the implications of how much data the application server pushes back and forth, but you may be able to locate both the application server and SQL Server in an IaaS role. Assuming the data sent to the final client will work across public Internet channels, there may be a fit. There are security implications, but unless you have point-to-point connections for your current solution you’re faced with the same security questions on both options.

Your audience might also be developers looking for a way to quickly spin up a server and then turn it down when they are done, paying for the time and not the hardware or licenses. This is also a prime case for evaluating IaaS. And there are others that you'll find in your own organization as you work through the requirements you have.

Resources: Windows Azure Virtual Machines: http://www.windowsazure.com/en-us/manage/windows/tutorials/virtual-machine-from-gallery/ and Windows Azure SQL Server Virtual Machines: http://www.windowsazure.com/en-us/manage/windows/common-tasks/install-sql-server/

HADR

The next possible place to consider using cloud computing with SQL Server is as a part of your High Availability and Disaster Recovery plans. In fact, this is the most common use I see for cloud computing and the Database Administrator. The key is the Recovery Point Objective (RPO) and Recovery Time Objective (RTO). Based on each application’s requirements, you may find that using Windows Azure or even supplementing your current plan is
the right place to evaluate options. I’ve covered this use-case in more detail in another article.

References: SQL Server High Availability and Disaster Recovery options with Windows Azure: http://blogs.msdn.com/b/buckwoody/archive/2013/01/08/microsoft-windows-azure-disaster-recovery-options-for-on-premises-sql-server.aspx

Data Services

Windows Azure, along with other cloud providers, offers another way to design, create and consume data. In this use-case, however, the tasks DBA’s normally perform for sizing, ordering and configuring a system don’t apply.

With Windows Azure SQL Databases (the artist formerly known as SQL Azure), you can simply create a database and begin using it. There are places where this fits and others where it doesn’t, and there are differences, limitations and enhancements, so it isn’t meant as replacement for what you could do with “Full-up” SQL Server on a Windows Azure Virtual Machine or an on-premises Instance. If a developer needs an Relational Database Management
(RDBMS) data store for a web-based application, then this might be a perfect fit.

But there is more to data services than Windows Azure SQL Databases. Windows Azure also offers MySQL as a service, RIAK and MongoDB (among others) and even Hadoop for larger distributed data sets. In addition you can use Windows Azure Reporting Services, and also tap into datasets and data functions in the Windows Azure Marketplace.

The key for the DBA with this option is that you will have to do a little investigation this time, and potentially without a specific workload in mind this time. I think that’s acceptable thing to ask – DBA’s constantly keep up with data processing trends, and most will consider different ways to solve a problem.

References:

Windows Azure SQL Databases: http://www.windowsazure.com/en-us/home/features/data-management/

Windows Azure Reporting Services: http://www.windowsazure.com/en-us/manage/services/other/sql-reporting/

HDInsight Service (Hadoop on Azure): https://www.hadooponazure.com/

MongoDB Offerings on Windows Azure: http://www.windowsazure.com/en-us/manage/linux/common-tasks/mongodb-on-a-linux-vm/

Windows Azure Marketplace: http://www.windowsazure.com/en-us/store/overview/

Big Data and the Cloud - More Hype or a Real Workload?

BuckWoody — Tue, 18 Oct 2011 13:57:36 GMT

Last week Microsoft announced several new offerings for “Big Data” - and since I’m a stickler for definitions, I wanted to make sure I understood what that really means. What is “Big Data”? What size hard drive is that? After all, my laptop has 1TB of storage - is my laptop “Big Data”?

There are actually a few definitions for this term, most notably those involving the “Four V’s” Volume, Velocity, Variety and Variability. Others disagree with this definition. I tend to try and get things into their simplest form, so I’m using this definition for myself:

Big data is defined as a large set of computationally expensive data that is worked on simultaneously.

Let me flesh that out a little. To be sure, “Big Data” has a larger size than say a few megabytes. The reason this is important is that it takes special hardware to be able to move large sets of data around, store it, process it and so on. (large set)

If you store a LOT of data, but only use a small portion of it at a time, that really isn’t super-hard to do. It’s mainly a storage issue at that point. But, if you do need to work with a large portion of the data at one time, then the memory, CPU and transfer components of the system have to adapt to be responsive - new ways to work with that data (game theory, knot-algorithms, map-reduce, etc.) need to be brought into play. (computationally expensive)

Once that data is loaded into the processing area (memory or whatever other mechanism is used) it must be worked on in parallel to come back in a reasonable time. You have two options here - you can scale the system up with more internal hardware (CPU’s, memory and so on) or you can scale it out to have multiple systems work on it at the same time using paradigms such as map/reduce and so on. Actually, when you lay this out in an architecture diagram, scale up or out doesn’t actually change the logical structure of the process - in scale out the network becomes the bus, and the nodes become more RAM and computing power. Of course, there are changes in code for how you stitch the workload back together. (worked on simultaneously)

So back to the original question. Is Big Data, as I have defined it here, a workload for Windows and SQL Azure? Absolutely! In fact, it’s probably one of the main workloads, and I believe it represents the latest, and perhaps also the earliest frontier of computing. Jim Gray, a former researcher here at Microsoft and a hero of mine, was working on this very topic. I believe as he did - all computing is simply an interface over data.

Microsoft has multiple offerings on the topic of Big Data. In posts that follow from myself and my co-workers, we’ll explore when and where you use each one. Whether you are a data professional or a developer, this is the new frontier - don’t wait to educate yourself on how to leverage Big Data for your organization.

Hadoop on Windows Azure and SQL Server - Microsoft’s partnership to include Hadoop workloads on Windows Azure and SQL Server/Parallel Data Warehouse (PDW)

LINQ to HPC - Microsoft’s High-Performance Computing SKU of HPC is now in Azure

Windows Azure Table Storage - A key/value pair type storage with full partitioning that is immediately consistent, able to handle huge loads of data and works with any REST-compatible language

Other offerings - Including the new Data Explorer, Project Daytona (with a Big Data Toolkit for Scientists and researchers), Power View and more.

The era of Big Data is here. And you can use Windows and SQL Azure to bring it to your organization.

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