ec2base

http://loadstorm.com/

Type Monthly Max Concurrent Users
Breeze FREE (forever) 25

http://winnersdontlose.com/?tag=ec2-filesystem-performance

I’ve been posting lately about a tool named bonnie++, which will run a suite of tests against your linux filesystem to determine metrics in 3 important areas: data read/write speed, max random seeks, and max metadata operations. Last time I posted about profiling one of Linode.com’s “Linode 360″ instances. In this article I will profile a m1.small instance on Amazon Web Services’ (AWS) Elastic Compute Cloud (EC2) service.

http://www.mnxsolutions.com/blog/linux/amazon-ec2-benchmark-pystone.html

The pricing model for Amazon EC2 looks attractive from the surface, but when you get down to it — monthly pricing for similar performing hardware can be much cheaper at a dedicated server provider like Softlayer.com. The use of EC2 is climbing, but I am concerned that many of the current uses of EC2 are better served using leased hardware.

http://code.google.com/p/redis/wiki/Benchmarks

Redis includes the redis-benchmark utility that simulates SETs/GETs done by N clients at the same time sending M total queries (it is similar to the Apache’s ab utility). Below you’ll find the full output of the benchmark executed against a Linux box.

http://www.ruturaj.net/redis-memcached-tokyo-tyrant-mysql-comparison

I wanted to compare the following DBs, NoSQLs and caching solutions for speed and connections. Tested the following

* Redis
* Memcached
* Tokyo Tyrant / Tokyo Cabinet
* MySQL 5.1.40 (MyISAM)
* MySQL 5.1.40 (with Innodb Plugin 1.0.4), compiled into source of MySQL

http://bjclark.me/2009/08/04/nosql-if-only-it-was-that-easy/

So, does RDBMS scale? I would say the answer is: not any worse than lots of other things. Most of what doesn’t scale in a RDBMS is stuff people don’t use that often anyway. And does NoSQL scale: a couple solutions do, most don’t. You might even argue that it’s just as easy to scale mysql (with sharding via mysql proxy) as it is to shard some of these NoSQL dbs. And I think it’s a pretty far leap to declare the RDBMS dead.

http://nosql.mypopescu.com/post/335520054/memcachedb-bursting-blocking-writes

I’d really love to hear how other NoSQL solutions are behaving in this particular scenario. Based on the characteristics of Memcachedb, I’m looking for an answer at least from the key-value stores: Project Voldemort, Redis, SimpleDB, Tokyo Cabinet, M/DB, etc. But if others want to jump in and present their solution that would be great. You can either post your reply as a comment or send it over an emai and I’ll make sure it will get included here.

http://anyall.org/blog/2009/04/performance-comparison-keyvalue-stores-for-language-model-counts/

Here are timings for a single counting process: iterate over 45,000 short text messages, tokenize them, then increment counters for their unigrams and bigrams. (The speed of the data store is only one component of performance.) There are about 17 increments per tweet: 400k unique terms and 750k total count. This is substantially smaller than what I need, but it’s small enough to easily test. I used several very different architectures and packages, explained below.

http://www.mysqlperformanceblog.com/2009/10/15/mysql-memcached-or-nosql-tokyo-tyrant-part-1/

A classic example is a simple online game. An online game may only require that an application retrieve a single record from the database. The record may contain all the vital stats for the game, be updated and stuffed back into the database. You would be surprised how many people use this type of system as I run into this type of application frequently. Keeping it simple, ensures that application is generally mean and lean and performs well. The issue is even this simple design can start to have issues as the data size increases and you blow through your available memory. Is there a better architecture? Is there a way to get more scalability out of your database? Is the database even the best place for this data?

percona guys (one of the highest mysql authorities) put some nails in mysql coffin (innocently?)

http://alan.blog-city.com/has_amazon_ec2_become_over_subscribed.htm

One of our aw2.0 portfolio companies, has been a long term user of Amazon EC2 running a sizable 24×7 of core instances with a number of instances going up and down as scale demands it. Our monthly bill gets us the dubious honor of a first point of contact with an Amazon Account Manager (not that that has been much use). We’ve pushed the limits of many of their services and continue to do so.

After 3 years of production usage what we can tell you is this .. Amazon do have a breaking point.

Visual evidence of Amazon EC2 network issues

https://www.cloudkick.com/blog/2010/jan/12/visual-ec2-latency/

http://news.ycombinator.com/item?id=1048873

http://news.ycombinator.com/item?id=1048694

As my mother would say; “misery enjoys company”

http://alan.blog-city.com/amazon_ec2_latency_the_pretty_graphs.htm

Amazon: We Don’t Have Cloud Capacity Issues

http://www.datacenterknowledge.com/archives/2010/01/14/amazon-we-dont-have-cloud-capacity-issues/?utm-source=feedburner&utm-medium=feed&utm-campaign=Feed:%20DataCenterKnowledge%20%28Data%20Center%20Knowledge%29&utm-content=Google%20Reader

PLEASE SAY IT AIN’T SO, CLOUD OVER-SUBSCRIPTION?

http://www.examiner.com/x-33449-Chicago-Cloud-Computing-Examiner~y2010m1d16-PLEASE-SAY-IT-AINT-SO-CLOUD-OVERSUBSCRIPTION

http://vuksan.com/blog/2009/12/04/cloud-cartography-load-co-residence-detection/

I was actually quite surprised at the magnitude of degradation. I’d say this may be even a more successful co-residence detection attack than network probing since you could generate legitimate HTTP traffic to a site of interest (or a node of interest), throw tons of load at it and see if you notice response degradation.

What Clouds Can Learn From Airlines

http://consultingblogs.emc.com/simonmunro/archive/2010/01/18/what-clouds-can-learn-from-airlines.aspx

http://www.infoq.com/news/2010/01/ec2-oversubscribed

There have been various reports from the community of Amazon EC2 users, that their instances are suffering poor performance, as the result of high internal network latency. This has led to speculations that Amazon’s Cloud might be getting oversubscribed.

http://tech.slashdot.org/story/10/01/15/1350213/Amazon-EC2-May-Be-Experiencing-Growing-Pains

“Some developers using Amazon EC2 are wondering aloud whether the popularity of the cloud computing service is beginning to affect its performance. Amazon this week denied speculation that it was experiencing capacity problems after a veteran developer reported performance issues and suggested that EC2 might be oversubscribed. Meanwhile, a cloud monitoring service published charts showing increased latency on EC2 in recent weeks. The reports follow an incident over the holidays in which a DDoS on a DNS provider slowed Amazon’s retail and cloud operations.”

I have observed “noisy neighbor” effects.

Our scripts use c1.medium instances for the separate Zookeeper quorum ensemble as they need fewer resources in terms of RAM but are still sensitive to io and cpu scheduling latencies.

http://www.jonathanboutelle.com/mt/archives/2010/01/hadoophackday_w.html

-Hadoop is very resource-intensive! We started out using 1-node clusters to run our jobs against small subsets of data. Very quickly teams started upgrading to 5-node clusters due to the amount of time they were having to wait for results. Final runs against full data sets were powered by 10-node clusters of “medium” ec2 servers. You have no choice but to use cloud computing for these kinds of jobs, because it seems to me that production use could easily require 100s of nodes, and no one would want to buy that many servers for machines that they only use one hour a day.

http://blog.reddit.com/2010/01/why-did-we-take-reddit-down-for-71.html

Part of our setup uses what we call a “permacache”, which uses Memcachedb. Memcachedb is Memcached with a built-in permanent storage system using BDB. One of the “features” of this system is that it saves up its disk writes and then bursts them to the disk. Unfortunately, the single EBS volumes they were on could not handle these bursting writes. Memcachedb also has another feature that blocks all reads while it writes to the disk. These two things together would cause the site to go down for about 30 seconds every hour or so lately.

http://news.ycombinator.com/item?id=1037993