I'm interested in running NUMA experiments on various hardware. Ideally there'd be documentation by AWS listing how many physical cores each instance has, but I haven't been able to find such information.
Is there a way to get such information without spinning up each instance type and running lscpu to see the socket count?
Thank you.
Related
Does anyone have an experience running clustered Tigase XMPP servers on Amazon's EC2, primarily I wish to know about anything that might trip me up that is non-obvious. (For example apparently running Ejabberd on EC2 can cause issues due to Mnesia.)
Or if you have any general advice to installing and running Tigase on Ubuntu.
Extra information:
The system I’m developing uses XMPP just to communicate (in near real-time) between a mobile app and the server(s).
The number of users will initially be small, but hopefully will grow. This is why the system needs to be scalable. Presumably for a just a few thousand users you wouldn’t need a cc1.4xlarge EC2 instance? (Otherwise this is going to be very expensive to run!)
I plan on using a MySQL database hosted in Amazon RDS for the XMPP server database.
I also plan on creating an external XMPP component written in Python, using SleekXMPP. It will be this external component that does all the ‘work’ of the server, as the application I’m making is quite different from instant messaging. For this part I have not worked out how to connect an external XMPP component written in Python to a Tigase server. The documentation seems to suggest that components are written specifically for Tigase - and not for a general XMPP server, using XEP-0114: Jabber Component Protocol, as I expected.
With this extra information, if you can think of anything else I should know about I’d be glad to know.
Thank you :)
I have lots of experience. I think there is a load of non-obvious problems. Like the only reliable instance to run application like Tigase is cc1.4xlarge. Others cause problems with CPU availability and this is just a lottery whether you are lucky enough to run your service on a server which is not busy with others people work.
Also you need an instance with the highest possible I/O to make sure it can cope with network traffic. The high I/O applies especially to database instance.
Not sure if this is obvious or not, but there is this problem with hostnames on EC2, every time you start instance the hostname changes and IP address changes. Tigase cluster is quite sensitive to hostnames. There is a way to force/change the hostname for the instance, so this might be a way around the problem.
Of course I am talking about a cluster for millions of online users and really high traffic 100k XMPP packets per second or more. Generally for large installation it is way cheaper and more efficient to have a dedicated servers.
Generally Tigase runs very well on Amazon EC2 but you really need the latest SVN code as it has lots of optimizations added especially after tests on the cloud. If you provide some more details about your service I may have some more suggestions.
More comments:
If it comes to costs, a dedicated server is always cheaper option for constantly running service. Unless you plan to switch servers on/off on hourly basis I would recommend going for some dedicated service. Costs are lower and performance is way more predictable.
However, if you really want/need to stick to Amazon EC2 let me give you some concrete numbers, below is a list of instances and how many online users the cluster was able to reliably handle:
5*cc1.4xlarge - 1mln 700k online users
1*c1.xlarge - 118k online users
2*c1.xlarge - 127k online users
2*m2.4xlarge (with 5GB RAM for Tigase) - 236k online users
2*m2.4xlarge (with 20GB RAM for Tigase) - 315k online users
5*m2.4xlarge (with 60GB RAM for Tigase) - 400k online users
5*m2.4xlarge (with 60GB RAM for Tigase) - 312k online users
5*m2.4xlarge (with 60GB RAM for Tigase) - 327k online users
5*m2.4xlarge (with 60GB RAM for Tigase) - 280k online users
A few more comments:
Why amount of memory matters that much? This is because CPU power is very unreliable and inconsistent on all but cc1.4xlarge instances. You have 8 virtual CPUs but if you look at the top command you often see one CPU is working and the rest is not. This insufficient CPU power leads to internal queues grow in the Tigase. When the CPU power is back Tigase can process waiting packets. The more memory Tigase has the more packets can be queued and it better handles CPU deficiencies.
Why there is 5*m2.4xlarge 4 times? This is because I repeated tests many times at different days and time of the day. As you can see depending on the time and date the system could handle different load. I guess this is because Tigase instance shared CPU power with some other services. If they were busy Tigase suffered from CPU under power.
That said I think with installation of up to 10k online users you should be fine. However, other factors like roster size greatly matter as they affect traffic, and load. Also if you have other elements which generate a significant traffic this will put load on your system.
In any case, without some tests it is impossible to tell how really your system behaves or whether it can handle the load.
And the last question regarding component:
Of course Tigase does support XEP-0114 and XEP-0225 for connecting external components. So this should not be a problem with components written in different languages. On the other hand I recommend using Tigase's API for writing component. They can be deployed either as internal Tigase components or as external components and this is transparent for the developer, you do not have to worry about this at development time. This is part of the API and framework.
Also, you can use all the goods from Tigase framework, scripting capabilities, monitoring, statistics, much easier development as you can easily deploy your code as internal component for tests.
You really do not have to worry about any XMPP specific stuff, you just fill body of processPacket(...) method and that's it.
There should be enough online documentation for all of this on the Tigase website.
Also, I would suggest reading about Python support for multi-threading and how it behaves under a very high load. It used to be not so great.
I'm using LIBSVM for regression analysis. Works like a champ. But a 3-parameter grid search to optimize parameters for the model maxes out all four cores on my 2.66 GHz Intel box, and I still have to wait a couple of hours to generate a single model.
This seems like a job for Amazon EC2.
I've seen plenty of tutorials and introductory material on using EC2 for web-related tasks.
But what if you have a small compute-intensive custom ANSI-C program that you want to run multiple instances of on EC2? Can anyone provide pointers on how to do that (or even just buzzwords to search for)?
I don't think your quest is too different from that of a web application. Your stack is different of course, but regardless – the principles remain the same.
As someone commented on your question: Elastic Map Reduce might be what you're looking for the parallelize your work easily, etc.. If that is too limited, you could look into Cloudera. A ready-to-rumble hadoop distribution with support for EC2 as well.
If map-reduce is not to your liking, then you need to setup your own instance. Roughly speaking, the keypoints are as follows:
You want to figure out a way to start EC2 instances.
You want to figure out a way to bootstrap and configure them.
Cluster/network?
Starting EC2 instances
If you don't require something like auto-scaling or a custom interface, the AWS Console does an extremely good job. You have to select an AMI (Amazon Machine Image) suitable for your project. I'd probably look into either the official AMI or something Ubuntu-based (If I remember correctly, Ubuntu is the most used Linux on EC2).
But that is up to you and your liking. (And I don't know enough about your project.)
Once you figured out a setup that works for you, the easiest way to clone your work is to setup your own AMI and start instances with it, etc..
Bootstrapping
Bootstrapping can be using what EC2 calls user-script. It allows you to pass shell script to the instance, which would execute calls to setup your stack, etc.. I'm not sure what is required in this case, etc.. So in case you comment or extend your answer, I could go into detail here.
Cluster/Networking
This is a wild guess since I'm not sure what your code does, or how it works, etc.. If it's not necessary, I'd probably scale this out using a single instance first. You can get a lot of cores and RAM provisioned easily with EC2. Depending if your work requires more RAM or CPU, look into high-cpu and high-memory instance types.
You can start off with a t1.micro, which you can currently get for free even and go from there.
Let me know if this helps!
I would like to monitor the following on Amazon ec2 instances loaded with amazon linux, every X minutes :
disk statistics
process stats (similar to what top does)
ram usage
check if my scripts are running fine
should I use my own scripts and things or are there any tools that already achieve this ?
I searched and there was a suggestion about munin
what seems to be the better approach ?
Here is a great article on scale. About halfway down, the author lists monitoring tools and how they differ.
http://highscalability.com/blog/2010/8/16/scaling-an-aws-infrastructure-tools-and-patterns.html
We've implemented Cacti, it was very easy, it creates all sorts of graphs/reports (most of what you mentioned). Munin is one that he lists as well, but we have not tried that solution yet.
I've been tasked with determining if Amazon EC2 is something we should move our ecommerce site to. We currently use Amazon S3 for a lot of images and files. The cost would go up by about $20/mo for our host costs, but we could sell our server for a few thousand dollars. This all came up because right now there are no procedures in place if something happened to our server.
How reliable is Amazon EC2? Is the redundancy good, I don't see anything about this in the FAQ and it's a problem on our current system I'm looking to solve.
Are elastic IPs beneficial? It sounds like you could point DNS to that IP and then on Amazon's end, reroute that IP address to any EC2 instance so you could easily get another instance up and running if the first one failed.
I'm aware of scalability, it's the redundancy and reliability that I'm asking about.
At work, I've had something like 20-40 instances running at all times for over a year. I think we've had 1-3 alert emails come from amazon suggesting that we terminate and boot another instance (presumably because they are detecting possible failure in the underlying hardware). We've never had an instance go down suddenly, which seems rather good.
Elastic IP's are amazing and are part of the solution. The other part is being able to rapidly bring up new instances. I've learned that you shouldn't care about instances going down, that it's more important to use proper load balancing and be able to bring up commodity instances quickly.
Yes, it's very good. If you aren't able to put together a concurrent redundancy (where you have multiple servers fulfilling requests simultaneously), using the elastic IP to quickly redirect to another EC2 instance would be a way to minimize downtime.
Yeah I think moving from inhouse server to Amazon will definitely make a lot of sense economically. EBS backed instances ensure that even if the machine gets rebooted, the transient memory is not lost. And if you have a clear separation between your application and data layer and can have them on different machines, then you can build even better redundancy for your data.
For ex, if you use mysql, then you can consider using Amazon RDS service - which gives you a highly available and reliable MySQL instance, fully managed (patches and all). The application layer then can be made more resilient by having more smaller instances rather than one larger instance, through load balancing.
The cost you will save on is really hardware maintenance and the cost you would have to incur to build in disaster recovery.
I've just joined a research lab at my University and been given access to a Cluster to compile and run the c++ code that I write. I use SSH to access it and simply use the cluster like a Linux terminal.
I often have to wait a relatively long time while my code runs. I'm trying to figure out if there's a more efficient way use the Cluster. For example, there are different CPUs/Nodes in the cluster, some of which are more in use and others less in use. How do I access a specific CPU? I have access to the "Ganglia" overview page which gives information about the different Nodes.
Also, if I run 2 processes in a different SSH windows will it automatically use different processors or nodes, or do I have to manually specify that.
I couldn't find any documentation to help me with these issues, so I'd appreciate a little help.
Thanks
Simply running something on a cluster does not mean it is taking advantage of the cluster at all. By default, it will probably just run on the head node. Software needs to be written specifically for a cluster.
There is likely to be some kind of scheduler running that you need to interface with. Perhaps you could also see if distcc is installed and configured for your particular cluster (for doing the compilation across multiple machines). There may also be a particular flavour of MPI running to allow processes on different nodes to communicate.
Clusters software setups tend to be very specialised to the hardware and computing environment. Really, I would recommend that you ask someone who has used the machine before these kinds of questions, because any advice you receive here is unlikely to be completely accurate for your particular cluster.