My HTTP server can't take load tests... It gives really high latency when multiple connections are made.
Server Configuration:
5 instances of (CPU 0.5vCore, Memory 512MB, Disk 20GB)
A load balancer
10G shared bandwidth
When I transfer a 3.5mb zip, it takes about 1second when there is only one connection. However, when over 30 connections are made, it goes up to 20~50 seconds.
I am testing with JMeter on my laptop. Is there a possibility that my testing environment interferes with the load-testing?
If so, what would be a solution to improve my testing environment?
First of all you need to monitor and pin down the problem(s).
Start off by picking up information on these four layers:
CPU Usage
Memory Usage
Network Usage
I/O Usage
All of them on the OS layer. (Monitoring tools will vary depending on your OS).
Once you have this data and you can narrow the problem path (CPU bound, network latency, I/O latency or whatever) an answer will kick in. Also doing this (if it is the first time you are trying to test your app) will help you get scaling information on your environment and your application in general.
Related
I have come across a situation where I can`t decide what scenario would be best. I have written my test in JMeter as follows:
I have one test plan that runs test in consecutive.
I have 4 thread groups and each thread group has the following properties:
No of threads: 8000
Ramp-up period: 60 sec
Loop count : 10
Same user on each iteration: true
I was having connection error, connection time out error.
So, to make it work , when I test from localhost (same machine), I have to enter a response time out of 1800000 ms, whereas when I do the same test on a remote server, I have to enter the response time out of 3600000 ms.
Can someone please advise :
Is it a good idea to include response time? Is there any other issue I should look for instead of including a response time? Is it an alert for other issue?
Can I improve the test without using response time?
First of all, a couple of questions to you:
Do you really think that the real user will really wait for 1 hour for getting the response from the application?
How did you come to this 8000 users?
Now recommendations:
Never have JMeter and the system under test on the same machine, they are both resource intensive and they will start struggling for CPU cycles, memory pages, etc. and you won't be able to tell whether JMeter is not capable of sending requests fast enough or your application cannot respond properly
Follow JMeter Best Practices
Although the number of virtual users you can simulate with JMeter is very high it's limited by the machine/operating system resources so make sure JMeter has enough headroom to operate in terms of CPU, RAM, Network and Disk IO. The metrics can be checked using JMeter PerfMon Plugin. Once you notice that any of monitored metrics start exceeding i.e. 80% of total available capacity - mention how many users are online and this is how many you can simulate from this machine for this test. If you need more - go for Distributed Testing
The same for the system under test, if you hit the resources consumption limits you need either to upgrade the hardware or to deploy your application in clustered mode (if it supports such a mode)
I need to test 200.000 VU hitting an app in 10 seconds, so I started to make a test of 10.000 VU, running Jmeter in Non-GUI mode, to see the response of my computer, my internet connection and the site response, but I got 83.50% of Errors.
95% of the errors were these:
Non HTTP response code: java.net.ConnectException/Non HTTP response message: Connection timed out: connect
This means that the internet connection was not enough for the short time of the test?
Thanks.
Running 200K users
Generally speaking in traditional HTTP running 200.000 users from one machine is impossible: there isn't that many ports. I.e. if you maximize your port usage (and it's likely you need to change OS settings to do that, since usually OS will limit number of open ports to somehwere between 1000 and 10000), JMeter will have about 64500 ports to run requests on. Each JMeter HTTP sampler needs a separate port, so you need 200K ports. Thus you need to have at least 4 machines to run 200K requests concurrently.
But that may not be enough: if you have more than one request sequentially (like most performance tests do), you will be able to run even less concurrent requests, since ports are usually not closed right away after request is done, so next request has to use a different port.
Don't forget that server also must be able to receive similar load.
But even that may not be enough: JMeter needs to have enough memory to accommodate 10-30K threads. Size of thread in memory will depend on a few things, and how your script is designed among them.
Bottom line: with all the tweaking, realistically, port availability limits number of concurrent requests JMeter can run from one machine to 10-30K concurrent users. Thus to test 200K users, you need about 7-20 JMeter machines.
Running 10K users
If you were testing in a designated environment (where clients and servers are next to each other with optimized network between them), you should be able to run 10K users from one machine, if other limits, e.g. memory and max ports were properly tweaked. But sounds like you are trying to test them over the internet connection?
Well, 2 problems here:
Performance testing over internet connection is absolutely pointless. You don't know what is between you and servers, and how those things in between are changing the shape of the load. You won't know if it was 10K concurrent requests, or 10K sequential requests. And results will only tell you how fast your internet is.
Any ISP will have a limit on number of connections from one IP, and it will be well below 10K. Not to mention that some ISPs may flag / temporary ban your IP for such flood.
Bottom line: whoever asked you to test 10K or 200K concurrent users, should also provide a set of JMeter machines to run this test from. Those machines should be close to tested servers, preferably without any extra routing in between (or with well known and well configured routing)
I don't think that stressing your application by kicking off 200k users at once is a good idea (same applies to 10k users) as the results, even in case of success, won't tell the full story. Moreover, in case of error you will be able to state only that 10k users in 10 seconds is not possible, however you won't have the information like:
What was the number of users when errors start occurring
What is the correlation between number of concurrent users and response time and/or throughput
What is the saturation point (the maximum system performance)
So I would recommend re-running your test and increasing the load gradually from one virtual user to 10 000 and see when it breaks. The breaking point is called bottleneck and the cause can be determined like:
First of all make sure you're following JMeter Best Practices as default JMeter configuration is not suitable for high loads and if JMeter is not capable of sending requests fast enough you will not get accurate results. Most probably you will have to run JMeter in Distributed mode, it is highly unlikely you will be able to mimic 20k requests per second from a single machine (or it has to be a very powerful one)
Set up monitoring of the application under test in order to ensure that it has enough headroom in terms of CPU, RAM, Disk, etc. You can use JMeter PerfMon Plugin for this
Check your application infrastructure, like JMeter the majority of middleware components like web/application servers, load balancers, databases, etc. default configurations are suitable for development and debugging, they need to be tuned for high throughput.
Check your application code using profiler tools telemetry, the reason could be in i.e. slow DB query, inefficient algorithm, large object, heavy function, etc.
I want to simulate up to 100,000 requests per second and I know that tools like Jmeter and Locust can run in distributed mode to generate load.
But since there are cloud VMs with up to 64 vCPUs and 240GB of RAM on a single VM, is it necessary to run in a cluster of smaller machines, or can I just use 1 large VM?
Will I be able to achieve more "concurrency" with more machines due to a network bottleneck coming from the 1 large machine?
If I just use one big machine, would I be limited by the number of ports there are?
In the load generator, does every simulated "user" that sends a request also require a port on the machine to receive a 200 response? (Sorry, my understanding of how TCP ports work is a bit weak.)
Also, we use Kubernetes pretty heavily, but with Jmeter or Locust, I feel like it'd be easier to run it on bare VM, without containerizing (even in distributed mode) while still maintaining reproducibility. Should I be trying to containerize Jmeter or Locust and running in Kubernetes instead?
According to KISS principle it is better to go for a single machine assuming it is capable of conducting the required load.
Make sure you're following JMeter Best Practices
Make sure you have monitoring of baseline OS health metrics (CPU, RAM, swap, network and disk IO, JVM statistics, etc.)
Start with low number of users and gradually increase the load until you reach the desired throughput or limit of any of the monitored metrics, whatever comes the first. If there will be a lack of CPU or RAM or something - see what could be done to overcome the limitation.
More information: What’s the Max Number of Users You Can Test on JMeter?
My tests with standalone (single-threaded) Redis show that load from a number of parallel clients can drive Redis CPU usage to 100% (in my memory cache use case).
Starting it in cluster mode and sharding the content to multiple masters is a possible approach for speeding it up, if persistence is turned on.
I have a configuration without persistence (turned off RDB and AOF). Would starting multiple masters help performance (still using the same cummulative amount of RAM)?
Redis is single-threaded, so the performance of a standalone instance is limited by processing power of a single CPU core and the network bandwidth of a single machine. However, Redis is very very fast. So normally the bottleneck is network bandwidth, unless you run lots of slow commands/lua scripts.
If you deploy Redis cluster on multiple machines, the performance should be improved no matter whether the persistence is turned on or off. Since you have more CPU cores, and more network bandwidth.
If you deploy Redis cluster on a single machine (each node listen on a unique port), the performance might be improved. It depends... If the bottleneck is network bandwidth, it won't be improved. On the other hand, if the bottleneck is CPU processing power, the performance should be improved. So, in this case, you should do some benchmark with your specific data, specific environment, and specific commands/lua scripts.
I am running a mobile website to get the live running status of any train in India. It is http://www.spoturtrain.com . The full code is written in PHP and Nginx is used as the webserver, php-fpm is used as the application server. All php requests are proxied to the app server. During peak traffic hours in the morning, the system load shoots up to 4 but the CPU% and the memory usage is low. Please take a look at the snapshot of the top command of the server.
Th %CPU displayed in the bottom section is per-thread, which means the percentage of one CPU core used by the indicated thread. The CPU(s) section indicates the total amount of available CPU that is being utilized, so it is possible to have one thread reporting that it is using 100% CPU, while only 25% (4 core) or 12.5% (8 core) of the overall CPU cycles are being consumed.
Analyzing thread CPU usage on Linux
You don't really ask a question, so it's hard to tell if you are wanting some advice or just asking to have the numbers explained. As #Charles states, a typical "acceptable" load is 1 per CPU core before noticeable performance degradation occurs, but in the case of PHP running on most web servers, you may (but probably won't in most cases) start noticing problems at anything above 1. Whether or not you do will largely depend on your disk and network I/O.
Whether or not the performance is acceptable for your application isn't something I can answer, but you can take a look at this thread for more places to jump into the options for getting your web server to thread requests.
What is thread safe or non thread safe in PHP
Whether or not you can do anything about it depends on your hosting situation.