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Displaying posts with tag: aws (reset)
MySQL Benchmark in the Cloud

 

Testing functionalities and options for a database can be challenging at times, as a live production environment might be required. As I was looking for different options, I was directed by Derek Downey to this post in the Percona blog.

The blog discussed an interesting and fun tool from Percona, tpcc-mysql. I was interested in testing the tool so I decided to play around with it in an AWS EC2 server.

In this post I will expand on the Percona blog post, since the tool lacks documentation, as well as explain how I used it to create a MySQL Benchmark in AWS.

Why tpcc-mysql?

There are various reasons why tpcc-mysql could be a good …

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5 core pieces of the Amazon Cloud puzzle to get your project off the ground

One of the most common engagements I do is working with firms in and around the NYC startup sector. I evaluate AWS infrastructures & applications built in the Amazon cloud. Join 32,000 others and follow Sean Hull on twitter @hullsean. I’ve seen some patterns in customers usage of Amazon. Below is a laundry list of … Continue reading 5 core pieces of the Amazon Cloud puzzle to get your project off the ground →

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Amazon EBS volume lazy loading: how it influences MySQL recovery performance

Amazon EBS volumes come with a very cool feature called "lazy loading". In a nutshell: if a volume is created from an existing snapshot, it can become available almost immediately without waiting for all data to be restored. This allows for extremely fast provisioning of large data sets as long as you don't explicitly require the entire data set to be present before you start using it.
When an EBS volume is restored from snapshot, its blocks are fetched from Amazon S3. It happens either lazily in the background or explicitly on demand (think of a pagefault-like mechanism) and of course, fetching pieces of data from Amazon S3 is going to be one-two orders of magnitude slower than reading blocks directly from a volume.
In this short article, I will try to give you an idea of how this may impact the crash recovery time of your MySQL databases. Why talk about this? Depending on the workload and data set layout, crash recovery of a MySQL …

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When hosting data on Amazon turns bloodsport

There’s a strong trend to automation across the cloud. That’s a great thing for startups because it reduces operational headaches & lets them focus on building products. Join 31,000 others and follow Sean Hull on twitter @hullsean. But as that trend begins to touch the database tier, all sorts of complications emerge. Let’s take a … Continue reading When hosting data on Amazon turns bloodsport →

MySQL performance optimization: 50% more work with 60% less latency variance

When I joined Pinterest, my first three weeks were spent in Base Camp, where the newest engineering hires work on real production issues across the entire software stack. In Base Camp, we learn how Pinterest is built by building it, and it’s not uncommon to be pushing code and making meaningful contributions within just a few days. At Pinterest, newly hired engineers have the flexibility to choose which team they’ll join, and working on different parts of the code as part of the Base Camp experience can help with this decision. Base Campers typically work on a variety of tasks, but my project was a deep dive into a MySQL performance optimization project.

Pinterest, MySQL and AWS, oh my!

We work with MySQL running entirely inside Amazon Web Services (AWS). Despite using fairly high-powered instance types with RAID-0 SSDs and a fairly simple workload (many point selects by PK or simple ranges) that peaks around 2,000 …

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Auditing MySQL with McAfee and MongoDB

Greetings everyone! Let’s discuss a 3rd Party auditing solution to MySQL and how we can leverage MongoDB® to make sense out of all of that data.

The McAfee MySQL Audit plugin does a great job of capturing, at low level, activities within a MySQL server. It does this through some non-standard APIs which is why installing and configuring the plugin can be a bit difficult. The audit information is stored in JSON format, in a text file, by default.

There is 1 JSON object for each action that takes place within MySQL. If a user logs in, there’s an object. If that user queries a table, there’s an object. Imagine 1000 active connections from an application, each doing 2 queries per second. That’s 2000 JSON objects per second being written to the audit log. After 24 hours, that would be almost 173,000,000 audit entries!

How does one make sense of that many JSON objects? One option would be to write your own parser in …

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fsfreeze in Linux

The fsfreeze command, is used to suspend and resume access to a file system. This allows consistent snapshots to be taken of the filesystem. fsfreeze supports Ext3/4, ReiserFS, JFS and XFS.

A filesystem can be frozen using following command:

# /sbin/fsfreeze -f /data

Now if you are writing to this filesystem, the process/command will be stuck. For example, following command will be stuck in D (UNINTERUPTEBLE_SLEEP) state:

# echo “testing” > /data/file

Only after the filesystem is unfreezed using the following command, can it continue:

# /sbin/fsfreeze -u /data

As per the fsfreeze main page, “fsfreeze is unnecessary for device-mapper devices. The device-mapper (and LVM) automatically freezes filesystem on the device when a snapshot creation is requested.”

fsfreeze is provided by the util-linux package in RHEL systems. Along with userspace support, fsfreeze also …

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Licensing Oracle in a public cloud: the CPU calculation impact

First of all a disclaimer: I don’t work for Oracle nor do I speak for them. I believe this information to be correct, but for licensing questions, Oracle themselves have the final word.

With that out of the way, followers of this blog may have seen some of the results from my testing of actual CPU capacity with public clouds like Amazon Web Services, Microsoft Azure, and Google Compute Engine. In each of these cases, a CPU “core” was actually measured to be equivalent to an x86 HyperThread, or half a physical core. So when provisioning public cloud resources, it’s important to include twice as many CPU cores as the equivalent …

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Increasing Cloud Database Efficiency – Like Crows in a Closet

In Mo’ Data, Mo’ Problems, we explored the paradox that “Big Data” projects pose to organizations and how Tokutek is taking an innovative approach to solving those problems. In this post, we’re going to talk about another hot topic in IT, “The Cloud,” and how enterprises undertaking Cloud efforts often struggle with idea of “problem trading.” Also, for some reason, databases are just given a pass as traditionally “noisy neighbors” and that there is nothing that can be done about it. Lets take a look at why we disagree.

With the birth of the information age came a coupling of business and IT. Increasingly strategic business projects and objectives were reliant on information infrastructure to provide information storage and retrieval instead of paper and filing cabinets. This was the dawn of the database and what gave rise to companies like Oracle, Sybase and MySQL. With the appearance of true Enterprise Grade …

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Is upgrading RDS like a shit-storm that will not end?

Join 29,000 others and follow Sean Hull on twitter @hullsean. Can RDS worsen an outage ?? That’s another way to think about this question. In my experience, it very clearly increases outages, by tying one or both hands behind your back. Believe me when I say, that is terribly frustrating when you’re putting out fires! […]

Showing entries 31 to 40 of 101
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