As the title implies, I would like to be able to simulate traffic to a collection of webpages that I have created for loadbalancing and bottleneck issues. I would like to mimic typical HTTP requests relative to the upload/download speed of the user. Furthermore, I would like to be able to perform extreme tests assuming a certain amount of storage and bandwidth on a server(s).
How I should go about doing this?
Look at Apache Flood: hhttp://httpd.apache.org/test/flood/
Good description: http://www.clove.org/flood-presentation/flood.pdf
Related
I'm using nginx reverse proxy to cache content from two endpoints, one of which is very reliable; the other has frequent timeouts.
I've found that those timeouts can sometimes use up all available connections or cause other issues, degrading performance for the server as a whole and leading to increased latency for the reliable endpoint as well.
I've tweaked some settings (worker_rlimit_nofile, worker_connections), but what I'd really like to do is isolate the caching and connections for the two endpoints as much as possible: give each a share of the available cache, and a share of the available connections, and operate as if they're hitting two separate servers, to reduce the chances that issues with one endpoint affect the performance of the other.
If I were to create two location blocks, one for each endpoint, can I designate each block's share of the cache (e.g. number of files, or total size) and share of available connections?
Or is there a better way of achieving this goal of isolation to ensure reliable performance for the good endpoint, even if the bad endpoint is experiencing lots of timeouts?
Most of the proxy_cache_* directives can be specific to location blocks and will allow you to do just that.
https://nginx.org/en/docs/http/ngx_http_proxy_module.html#proxy_cache
It may also help others answer if an example config is provided that reflects what you're currently doing.
I have a system that will generate image optimization and resizing for a client who has a news portal with lots of pageviews. We will provide only the images to this portal, but users are all on the same country as the our server. The question is, whats the best strategy thinking about cost-benefit:
Route all(most) image traffic via some paid CDN
Setup an internal image server using nginx and a loadbalancer
Monthly we estimate a bandwidth of 11TB, with millions of requests. (images only)
It is not a questions if it is possible or what is more cost efficient.
You need to calculate the costs based on many factors: Actual sizing of your servers. Amount of servers. Bandwith. Where are the servers located and much more.
It will be a lot of work to setup and maintain / monitor your own CDN probaly but sure you can do it.
I dont think that anybody can create this calculation for you. See the comment fro Rob. It is not realy a question for SO.
Is it possible to simulate a load test on a HTTP endpoint from different geo-locations. e.g. I want to simulate requests to http endpoint from US, Canada, Mexico, China...
Yes. You'll either need to employ a testing service for this (either full-service or self-service) or obtain your own computing resources to do this. One of the cloud providers can give you the short-term resources you need a minimal cost. For example, Amazon EC2 has datacenters in 7 (8?) parts of the world. We use it in our testing services and it is integrated into our load testing software and it works great. The testing software you choose (and your site's performance requirements) will determine the kind and quantity of resources you'll need.
Are you interested on having the actual requests coming from the different geo-locations or your interest is related to the latency associated with having requests coming form those locations?
If you real need is the second one, then you have a couple of options:
Software based network emulation: E.g. Visual Studio load testing allows you to simulate latency during load tests.
Hardware based network emulation: solutions to simulate latency, also called WAN Emulators. E.g. SHUNRA
I hope this helps.
I saw that it's possible to specify geographical location in Load Testing Cloud which is compatible with JMeter. Use parameter 'Load Origin Location' when create load test.
We are making an application involving a server(tomcat, apache, linux) and multiple mobile clients(Android, iPhone, Windows, Nokia J2ME).
Normally the clients and the server will communicate using http.
I would like to know the download and upload speeds of the client from the http request that it made.
Ideally I would not like to upload a file and download a file to come up with these speeds. I am assuming that there might be some thing at the HTTP protocol level that can give me this, or some lower layer of the network.
If only it were that simple.
Even where the bandwidth and latency of a network are very well defined, the actual throughput will be limited by the congestion window and where the end points are in establishing the slow start threshold. These can affect throughput by a factor of 20 or more.
There's nothing in HTTP which will provide metrics for these. Some TCP stacks will expose limited information about throughput (as used by iftop, iptraf).
However if you really want to gather useful metrics on HTTP throughput, then you need to start shoving data across the network - have a look at yahoo boomerang for an implementation.
If the http connection goes to the Apache server first, you can use Apache Bench to do all sorts of load testing. It comes with apache and can be invoked with something like the following.
Suppose we want to see how fast Yahoo can handle 100 requests, with a maximum of 10 requests running concurrently:
ab -n 100 -c 10 http://www.yahoo.com/
HTTP does not deal with connection speeds. Although I could imagine some solution that involves some HTTP (reverse) proxy that estimates speeds on a connection and sets custom headers to pass this info. You would also need to to associate stats of different connections with particular client. I have not seen yet a readily available solution for this.
Also note that
network traffic can be buffered or shaped so download speed may depend on amount of data transferred or previous load of network. So even downloading file would not be accurate.
Amount of data transferred depends on protocol level (payload wrapped in HTTP wrapped in gzip wrapped in TLS wrapped TCP). Which one do you want to measure? Or what do you want to achieve with this measured speed?
I've seen some Real User Monitoring (RUM) tools that can do this passively (they get a feed from a SPAN port or network TAP infront of the servers at the data centre)
There are probably ways of integrating the data they produce into your applications but I'm not sure it would be easy or perhaps given the way latency and bandwidth can 'dynamically' change on a mobile network that accurate.
I guess the real thing to focus on is the design of the app, how much data is travelling across the network, how you can minimise it etc.
Other thing to consider is whether you could offer a solution that allows some of the application to be hosted in the telco's POPs (some telcos route all their towers back to a central pop, others have multiple POPs)
I have a slowly evolving dynamic website served from J2EE. The response time and load capacity of the server are inadequate for client needs. Moreover, ad hoc requests can unexpectedly affect other services running on the same application server/database. I know the reasons and can't address them in the short term. I understand HTTP caching hints (expiry, etags....) and for the purpose of this question, please assume that I have maxed out the opportunities to reduce load.
I am thinking of doing a brute force traversal of all URLs in the system to prime a cache and then copying the cache contents to geodispersed cache servers near the clients. I'm thinking of Squid or Apache HTTPD mod_disk_cache. I want to prime one copy and (manually) replicate the cache contents. I don't need a federation or intelligence amongst the slaves. When the data changes, invalidating the cache, I will refresh my master cache and update the slave versions, probably once a night.
Has anyone done this? Is it a good idea? Are there other technologies that I should investigate? I can program this, but I would prefer a configuration of open source technologies solution
Thanks
I've used Squid before to reduce load on dynamically-created RSS feeds, and it worked quite well. It just takes some careful configuration and tuning to get it working the way you want.
Using a primed cache server is an excellent idea (I've done the same thing using wget and Squid). However, it is probably unnecessary in this scenario.
It sounds like your data is fairly static and the problem is server load, not network bandwidth. Generally, the problem exists in one of two areas:
Database query load on your DB server.
Business logic load on your web/application server.
Here is a JSP-specific overview of caching options.
I have seen huge performance increases by simply caching query results. Even adding a cache with a duration of 60 seconds can dramatically reduce load on a database server. JSP has several options for in-memory cache.
Another area available to you is output caching. This means that the content of a page is created once, but the output is used multiple times. This reduces the CPU load of a web server dramatically.
My experience is with ASP, but the exact same mechanisms are available on JSP pages. In my experience, with even a small amount of caching you can expect a 5-10x increase in max requests per sec.
I would use tiered caching here; deploy Squid as a reverse proxy server in front of your app server as you suggest, but then deploy a Squid at each client site that points to your origin cache.
If geographic latency isn't a big deal, then you can probably get away with just priming the origin cache like you were planning to do and then letting the remote caches prime themselves off that one based on client requests. In other words, just deploying caches out at the clients might be all you need to do beyond priming the origin cache.