In a previous post I wrote ARM based servers. Since then, and thanks to all the comments and responses I got, I looked more into this ARM thing and it's absolutely fascinating...

Look at this beauty (taken from the site of Calxeda, the manufacturer):

What is it? A chip? A server? No, it's a cluster of 4 servers...

And this:







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In my previous post I covered the shard-disk paradigm's pros and cons, but the conclusion that is that it cannot really qualify as a scale-out solution, when it comes to massive OLTP, big-data, big-sessions-count and mixture of reads and writes.

Read/Write splitting is achieved when numerous replicated database servers are used for reads. This way the system can scale to cope with increase in concurrent load. This solution qualifies as a scale-out solution as it allow expansion beyond the boundaries of one DB, DB machines are shared-nothing, can be added as a slave to the replication "group" when required.



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Yesterday I was asked by a customer for the reason why he had failed to achieve scale with a state-of-the-art "shared-storage" cluster. "It's a scale-out to 4 servers, but with a shared disk. And I got, after tons of work and efforts, 130% throughput, not even close to the expected 400%" he said.

Well, scale-out cannot be achieved with a shared storage and the word "shared" is the key. Scale-out is done with absolutely nothing shared or a "shared-nothing" architecture. This what makes it linear and unlimited. Any shared resource, creates a tremendous burden on each and every database server in the cluster.

In a previous post, I identified database engine activities such as buffer management, locking, thread locks/semaphores,



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Today, I think we witnessed a small sign for a big revolution...

http://www.pcworld.com/businesscenter/article/256383/dell_reaches_for_the_cloud_with_new_prototype_arm_server.html

"Dell announced a prototype low-power server with ARM processors, following a growing demand by Web companies for custom-built servers that can scale performance while reducing financial overhead on data centers"

In short, ARM (see Wikipedia definition here) is an architecture standard for processors. ARM processors are slower compared to good old x86 processors from Intel and AMD, but have power-efficiency, density and price attributes that intrigue


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Read the original article at Best of Guide – Highlights of Our Popular Content

We cherry pick the top 5 most popular posts of various topics we’ve covered in recent months.

• 5 Things Toxic to Scalability

We use a broad brush to highlight the biggest no-nos in web application scalability.

• 5 Ways to Boost Scalability for MySQL

We dig into scalability, steering to the richest areas to focus on.

• 8 Best Practices for Deploying MySQL

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Yesterday (4/19) I attended the AWS Summit in NYC (http://aws.amazon.com/aws-summit-2012/nyc).

I'm a big fan and also a heavy user of AWS especially S3, EC2, and naturally, RDS. In every point in time I have several dozens of AWS machines running for me out there in the East region, and in some cases when we do some special benchmarks and tests, number of EC2 and RDS machines can easily reach 3-digit. As I said, I'm a fan...

A few quotes I was able to catch and document on my laptop, on my laps...:

"When you develop an app for facebook, you must be prepared (and be afraid) that to your party, not noone will show up, but everybody will show up!"

So true! Simple and true. We all want to succeed, to have success with our app. We have to think about scaling




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There are ways to scale databases, unfortunately some are limited, some introduce complexities, some are do not fit the cloud...

By scaling solution I mean a solutions that help me scale my existing environment, my existing RDBMS. Some magic or technology that will take my existing Oracle or MySQL for example, to the next level, without porting to a new DB engine/vendor and without completely recoding my app.

Let's try to organize things a bit in this very summarized table, just to get the hunch of it. I can't imagine to cover it all in 1 table or even 100 pages, but that should be a start of a meaningful discussion to continue in next posts:

Solution Scales reads? Scales writes? Scales data? Scales sessions? Cloud? Bottom line Scale-Up: faster HW, CPU, memory,





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In my heart, I'm a DBA, always was and always will be. People say I'm a database guy by the way I think, keep my car, and file my music and also bank statements... However I did great deal of development, design, architecture on the apps side. I (hope to) have some perspective.

Applications come and go. The second programming language I've ever learned and worked on was COBOL, some still say most of the world's lines of code are written in this language, maybe so, but anyway I since then have known and written in dozens of programming languages, from Assembly to Force.com, from Pascal to Delphi, from functional C to Object Oriented SmallTalk, C++, Java and , from compiled C/CGI to interpreted Perl, ASP and Ruby back to compiled node.js... My first applications ran on Main-Frame with green screen, later I created beautiful graphic

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This is a cross-post from the MySQL Performance Blog. I thought it would be interesting to users of PostgreSQL, Redis, Memcached, and $system-of-interest as well.

For about the past year I’ve been formulating a series of tools and practices that can provide deep insight into system performance simply by looking at TCP packet headers, and when they arrive and depart from a system. This works for MySQL as well as a lot of other types of systems, because it doesn’t require any of the contents of the packet. Thus, it works without knowledge of what the server and client are conversing about. Packet headers contain only information that’s usually regarded as non-sensitive (IP address, port, TCP flags, etc), so it’s

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Read the original article at Scalability Rules for managers and startups

Abbott and Fisher’s previous book, The Art of Scalability received good reviews for shifting the way we think about scalability from merely splitting databases and adding servers, to include the human factors that weigh heavily on its success. Together with the authors’ distinguished pedigree (PayPal, Amazon, and eBay between them), I picked up a copy of their second book, Scalability Rules - 50 Principles for Scaling Web Sites without a second

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Read the original article at What Ops doesn’t tell you about your MySQL Database

MySQL is a very scalable platform which has proven robust even in the most dense and complex data environments. MySQL’s indispensable replication function is ‘sold’ as being fail-safe so you have little to sweat about as long as your backups are running regularly. But what the ops guys aren’t telling you is MySQL performs replication with tiny margins of error that could cause big problems in times of disaster.

The Scenario

Imagine the scene, you use replication to backup your data. Your secondary database is your peace of mind. It’s the always-on

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Working with replication, you come across many topologies, some of them sound and established, some of them less so, and some of them still in the realm of the hopeless wishes. I have been working with replication for almost 10 years now, and my wish list grew quite big during this time. In the last 12 months, though, while working at Continuent, some of the topologies that I wanted to work with have moved from the cloud of wishful thinking to the firm land of things that happen. My quest for star replication starts with the most common topology. One master, many slaves.

Fig 1. Master/Slave topology

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Read the original article at Book Review – Effective MySQL

Effective MySQL: Optimizing SQL Statements by Ronald Bradford No Nonsense, Readable, Practical, and Compact I like that this book is small; 150 pages means you can carry it easily.  It’s also very no nonsense.  It does not dig too deeply into theory unless it directly relates to your day-to-day needs.  And those needs probably cluster [...]

For more articles like these go to iHeavy, Inc +1-212-533-6828

Read the original article at 5 Tips to Cache Websites and Boost Speed

Often when we think about speeding up and scaling, we focus on the application layer itself.  We look at the webserver tier, and database tier, and optimize the most resource intensive pages.

There's much more we can do to speed things up, if we only turn over the right stones.  Whether you're using WordPress or not, many of these principals can be applied.  However we'll use WordPress as our test case.

Test Your Website speed

There are web-based speed testing tools that will help with this

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Recently at Surge 2011, the annual  conference on scalability  and performance, Google's CIO Ben Fried gave an illuminating keynote address. His main insight was that generalists are the people that will lead engineering teams in successfully scaling the web.

In a world where the badge of Specialist or Expert is prized, this was refreshing perspective from an industry bigwig. As tech professionals, or any professional for that matter, we don't welcome the label of generalist. The word suggests a jack-of-all-trades and master of none. But the generalist is no less an expert than the specialist. Generalists can get their hands greasy with the tools to fix bugs in the

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I’ve been seeing a few occasions where Neil J. Gunther’s Universal Scalability Law doesn’t seem to model all of the important factors in a system as it scales. Models are only models, and they’re not the whole truth, so they never match reality perfectly. But there appear to be a small number of cases where systems can actually scale a bit better than linearly over a portion of the domain, due to what I’ve been calling an “economy of scale.” I believe that the Universal Scalability Law might need a third factor (seriality, coherency, and the new factor, economy of scale). I don’t think that the results I’m seeing can be modeled adequately with only two parameters.

Here are two publicly available cases that appear to demonstrate this phenomenon: Robert Haas’s

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This year’s Surge conference was a great sophomore event to follow up last year’s inaugural conference. A lot of very smart people were there, and the hallway track was great.

I presented on three things: a lightning talk about causes of MySQL downtime; I chaired a panel on Big Data and the Cloud; and I showed how to derive scalability and performance metrics from TCP traffic. I’ve sent my slides to the Surge organizers, and I understand that they will be posting them as well as integrating them into the video of my session. In the meanwhile you can download my slides from Percona’s presentations page.

Further Reading:

• I’m speaking at

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Restaurant Scalability

Could pro-waitering serve up some lessons on web scalability? Observing peak hour dining at a New York restaurant gave us some insight.

I was dining at a restaurant the other day with friends. It was a warm and cozy place, nicely decorated with a long, narrow dining room.  The food was scrumptious, yet we were getting increasingly frustrated by the service as the night went along.

With some waiting experience behind me, I could immediately see the problem. The waiters, probably through lack of experience, were making the mistake of doing one thing at a time.  They would go to a table, respond to one

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Read the original article at Scale Quickly Like Birchbox – Startup Scalability 101

One of the great things about the Internet is how it has made it easier to put great ideas into practice. Whether the ideas are about improving people’s lives or a new way to sell and old-fashioned product, there’s nothing like a good little startup tale of creative disruption to deliver us from something old and tired.

We work with a lot of startup firms and we love being part of the atmosphere of optimism and ingenuity, peppered with a bit of youthful zeal - something very indie-rock-and-roll about it. But whether they are just starting out or already picking up pace every startup faces the same challenges to scale a business. Recently, we were reminded of this

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MySQL Cluster* is one of the most advanced and scalable databases available today and, despite what its name might suggest, it is also a brilliant NoSQL database**.
Let me discuss this statement!
First, let’s discuss the high level issues that NoSQL databases try to address:-     Scalability. Traditional RDBMS technology was designed four decades ago, and is not appropriate for today’s Big Data requirements. Database systems today need to be able to scale horizontally over multiple machines to handle millions of users. As the CAP theorem states, it is not possible to achieve availability, scalability and consistency in one system. Several NoSQL databases sacrifice consistency for availability and scalability. -     RDBMS has a rigid data model. Once a


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Scalability is about application, architecture and infrastructure design, and careful management of server components.

1. Object Relational Mappers

ORMs are popular among developers but not among performance experts.  Why is that?  Primarily these two engineers experience a web application from entirely different perspectives.  One is building functionality, delivering features, and results are measured on fitting business requirements.  Performance and scalability are often low priorities at this stage.  ORMs allow developers to be much more productive, abstracting away the SQL difficulties of interacting with the backend datastore, and allowing them to concentrate on building the features and functionality.

On the performance side the picture is a bit different.  By leaving SQL query writing to an ORM, you are faced with complex queries that

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1. This page or area of the website is very slow, why?

There are a lot of components that make up modern internet websites, and a lot of places to get stuck in the mud.  Website performance starts with the browser, what caching it is doing, their bandwidth to your server, what the webserver is doing (caching or not and how), if the webserver has sufficient memory, and then what the application code is doing and lastly how it is interacting with the backend database.

With all this complexity, it's no wonder so many sites struggle.  Typically these types of analysis start with some load testing, to stress test your setup, so you can watch for leaks.  Then

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Amazon EC2 and cloud computing offer great promise for startups to ramp up their online presence quickly.  Navigate those challenges with an strong partner.  We bring 20 years experience to the table with each new client.

• Scaling Web Applications
• MySQL High Availability in Amazon EC2
• Amazon Multi-AZ Deployments
• Amazon RDS Deployments
• Migrating to Amazon EC2
• Migrating to MySQL
• Managing Backups and Disaster Recovery in the Cloud
• Horizontal Scalability of MySQL on EC2
• Horizontal Scalability on Cloud Hosted Servers
• Evaluating Cloud Providers
• Evaluating MySQL

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Deploying in the Amazon cloud is touted as a great way to achieve high scalability while paying only for the computing power you use. How do you get the best scalability from the technology?

1. Use Auto-scaling

Auto-scaling is a unique feature of cloud computing and Amazon's EC2 offering. Setup a load balancer and a couple of webservers for your application as you normally would. Design your webserver based on a template AMI that you'll reuse over and over. Then setup auto-scaling and set thresholds based on the traffic you forecast. When a threshold is passed, AWS will spinup a new instance of your webserver, and roll it into the load balancer pool

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