From http://directory.fsf.org/project/collectd/ : 'collectd' is a small daemon which collects system information every 10 seconds and writes the results in an RRD-file. The statistics gathered include: CPU and memory usage, system load, network latency (ping), network interface traffic, and system temperatures (using lm-sensors), and disk usage. 'collectd' is not a script; it is written in C for performance and portability. It stays in the memory so there is no need to start up a heavy interpreter every time new values should be logged. From the collectd website: Collectd gathers information about the system it is running on and stores this information. The information can then be used to do find current performance bottlenecks (i. e. performance analysis) and predict future system load (i. e. capacity planning). Or if you just want pretty graphs of your private server and are fed up with some homegrown solution you're at the right place, too ;). While collectd can do a lot for you and your administrative needs, there are limits to what it does: * It does not generate graphs. It can write to RRD-files, but it cannot generate graphs from these files. There's a tiny sample script included in contrib/, though. Also you can have a look at drraw for a generic solution to generate graphs from RRD-files. * It does not do monitoring. The data is collected and stored, but not interpreted and acted upon. There's a plugin for Nagios, so it can use the values collected by collectd, though. It's reportedly a reliable product that doesn't cause a lot load on your system. This enables you to collect data at a faster rate so you can detect problems earlier.
Compare: 1. MySQL Clustering(ndb-cluster stogare) 2. MySQL / GFS-GNBD/ HA 3. MySQL / DRBD /HA 4. MySQL Write Master / Multiple MySQL Read Slaves 5. Standalone MySQL Servers(Functionally seperated)
Update 2: Summize Computes Computing Resources for a Startup. Lots of nice graphs showing Amazon is hard to beat for small machines and become less cost efficient for well used larger machines. Long term storage costs may eat your saving away. And out of cloud bandwidth costs are high. Update: via ProductionScale, a nice Digital Web article on how to setup S3 to store media files and how Blue Origin was able to handle 3.5 million requests and 758 GBs in bandwidth in a single day for very little $$$. Also a Right Scale article on Network performance within Amazon EC2 and to Amazon S3. 75MB/s between EC2 instances, 10.2MB/s between EC2 and S3 for download, 6.9MB/s upload. Now that Amazon's S3 (storage service) is out of beta and EC2 (elastic compute cloud) has added new instance types (the class of machine you can rent) with more CPU and more RAM, I thought it would be interesting to take a look out how their pricing stacks up. The quick conclusion:the more you scale the more you save. A six node configuration in Amazon is about half the cost of a similar setup using a service provider. But cost may not be everything... EC2 gets a lot of positive pub, so if you would like a few other perspectives take a look at Jason Hoffman of Joyent's blog post on Why EC2 isn't yet a platform for "normal" web applications and Hostingfu's Short Comings of Amazon EC2. Both are well worth reading and tell a much needed cautionary tale. The upshot is batch operations clearly work well within EC2 and S3 (storage service), but the jury is still out on deploying large database centric websites completely within EC2. The important sticky issues seem to be: static IP addresses, load balancing/fail over, lack of data center redundancy, lack of custom OS building, and problematic persistent block storage for databases. A lack of large RAM and CPU machines has been solved with the new instance types. Assuming you are OK with all these issues, will EC2 cost less? Cost isn't the only issue of course. If dynamically scaling VMs is a key feature, SQS (message queue service) looks attractive, or S3's endless storage are critical, then weight accordingly. My two use cases are my VPS, for selfish reasons, and a quote from a leading service provider for a 6 node setup for a startup. Six nodes is small, but since the architecture featured horizontal scaling, the cost of expanding was pretty linear and incremental. Here's a quick summary of Amazon's pricing:
Single VPS ConfigurationI was very curious about the economics of moving this simple site(http://highscalability.com) from a single managed VPS to EC2. Currently my plan provides:
Six Node Configuration for StartupThis configuration is targeted at a real-life Web 2.0ish startup needing about 300GB of fast, highly available database storage. Currently there are no requirements for storing large quantities of BLOBs. There are 6 nodes overall: two database servers in failover configuration, two load balanced web servers, and two application servers. From the service provider:
Effective content caching is one of the key features of scalable web sites. Although there are several out-of-the-box options for caching with modern web technologies, a custom built cache still provides the best performance.
Hi... I have this idea to start a really great and scalable website, and I am building it! So far I'm doing everything myself - coding, networking, architecture planning, everything. I haven't even gotten into the legal aspects yet....... It would be MUCH easier if I had a technical person to handle that end of the operation. I'm a good coder, but like Bill Gates at Harvard for Math, I'm not the very best. I'd like to FIND that very best person available, to handle the technical aspects. For worse or better, I don't presently know somebody who fits this bill. I've posted a bazillion ads on Craig's List, with no really qualified responses. I've put out feelers among my own network, same result. Not sure what else I can do. Shoestring budget, so it's sweat equity in the beginning. That can actually be a plus, as it forces people to focus. Any ideas about what else I can do, to attract the right person? Thanks Jason
A very entertaining and somewhat educational article on IBM Poopheads say LAMP Users Need to "grow up". The physical three tier architecture turns out to be the root of all evil and shared nothing architectures brings simplicity and light. In the comments Simon Willison makes an insightful comment on why fine grained caching works for personalized pages and proxy's don't: Great post, but I have to disagree with you on the finely grained caching part. If you look at big LAMP deployments such as Flickr, LiveJournal and Facebook the common technology component that enables them to scale is memcached - a tool for finely grained caching. That's not to say that they aren't doing shared-nothing, it's just that memcached is critical for helping the database layer scale. LiveJournal serves around 50% of its page views "permission controlled" (friends only) so an HTTP proxy on the front end isn't the right solution - but memcached reduces their database hits by 90%.
I have an application with couple of web servers that uses MemcacheD. How can i synchronize concurrent put to the cache? The value of the entry is list. Atomic append operation could have been helpful, but unfortunately memcahe doesn't support atomic append.
Seems as though anonymous users can edit old posts w/o any authentication. This post was loaded with spam/porn links. Now it is not. /anonymous
Release It! author Michael Nygard tells a tale of two web sites, both brought low by unexpectedly huge unbounded results sets that slowed down their sites to the speed of a Christmas checkout line. I've committed this error more than a few times. During testing the results sets are often small, so you don't see problems. Or when a product is new you don't have a lot of data so everything is fine, until some magic line is crossed and you get that dreaded 2AM fix it call. My most embarrassing bug of this type caused a rather spectacular failure at a customer site as the variance in response times was out of spec and this kicked in penalty clauses. What happened was the customer had a larger network than we could even test (customers always get the good stuff). I took a lock and went to get all the data. Because the result set was so much larger in their larger system I took the lock for many more milliseconds than I should have. Unknown to me a chunk of code on the critical path also was in the lock path and all hell broke loose. I had to change the logic to process the result set in fixed size deterministic chunks, releasing locks as I went. I even had to measure CPU usage and back off after a certain amount of CPU was used. But all was well again. I then hunted down every other place I made the same mistake. And there were a few. To solve this problem in general I developed an architecture supporting scheduling work by CPU usage. A common theme in many of the profiles on this site is protecting your system from requests that can bring down the system. Mailinator has a lot resource exhaustion problems and does a good job solving them. Ebay has an interesting strategy of doing as little work as possible in the database which leads them to do joins in application space. Which is exactly the opposite of this strategy's conclusion. But I think this may be going too far. With proper indexes performing selects in the database to minimize the result sets would seem to be a win as databases are good at this sort of thing. Yah, relational databases suck at doing top 10 type of logic, so calculate that on the fly and cache it. How can you bound results sets?
This is a question asked on the ycombinator list and there are some good responses. I gave a quick response, but I particularly like neilk's knock out of the park insightful answer: