I am running varnish with nginx as proxy on ubuntu and I am getting (24: Too many open files) error every few days.
Restarting nginx solves the problem.
After researching about this error I found that the common solution is to increase worker_rlimit_nofile in nginx.conf.
I feel like this is not a real solution since the limit I will set might reach as well.
Why nginx keeps these files (I believe these are the sockets) open? and what will a solution to my situation?
UPDATE:
I just noticed there are hundreds of varnish sockets open when I run lsof. I believe my issue is that these sockets don't get closed.
It's a good practice to increase the standard max number of files open on your server when it is a web server, the same goes for the number of ephemeral ports.
I think the default number of opened files is 1024 which is way too small for varnish
I am setting it to 131072
ulimit -n 131072
Related
I have haproxy 2.5.1 in SSL termination config running in a container of a Kubernetes POD, the backend is an Scala App that runs in another container of same POD.
I have seen that I can put 500K connections in the setup and the RSS memory usage of HAProxy is 20GB. If I remove the traffic and wait 15 minutes the RSS memory drops to 15GB, but if I repeat the same exercise one or two more times, RSS for HAProxy will hit 30GB and HAProxy will be kill as I have a limit of 30GB in the POD for HAProxy.
The question here is if this behavior of continuous memory growth is expected?
Here is the incoming traffic:
And here is the memory usage chart which shows how after 3 cycles of Placing Load and Removing Load, the RSS memory reached 30GB and then got killed (Just as an observation the two charts have different timezone but they belong to same execution)
We switched from Alpine based image(musl) into libc based image and that solved the problem. We got 5X increase on connection rate and memory growth gone too.
I have set up Ganglia(Ganglia Core 3.6.0 and Ganglia Web 3.5.10) to monitor my cluster.
When gmond is restarted in a machine, metrics from all other gmond machines also gets stopped ie I am not able to see metrics getting published from other machines in Ganglia Web. And I can also see Hosts up going to 0 and Hosts down as 13(total number of machines). As time goes, the Hosts up comes back to 13.
Am I missing something ?? Can some one help me...
If it's always the same machine, it should be a gmond 'end-point'. The gmetad daemon is querying only one gmond (no redundancy), if he goes down everybody seems to be going down.
If there are a redundancy (eg. more than one host in a data source), you can expect some lag if the first one goes down because of the number of TCP queries before it timesout.
I am hosting a web application on Amazon's AWS Servers. I am currently in the process of load testing the application with JMeter. My main problem seems to be that when I go through an Elastic Load Balancer (ELB) to hit the Amazon server's rather than hitting the servers directly - I seem to hit a cap in my throughput.
If I hit my web application directly - for each server I am able to achieve a throughput of 50 RPS per server.
If I hit my web application via Amazon's ELB - I am only able to achieve a max throughput of 50 RPS (total)
I was wondering if anyone else has experienced similar behavior when load testing using Jmeter via Amazon's ELB.
For more context my web application is a REST application which allows users to download content (~150 kb) via HTTP requests.
I am running Jmeter with the following flag "-Dsun.net.inetaddr.ttl=0" and running it with 10 threads. I have tried running these tests with multiple clients on different machines.
Thanks for any help in advance.
Load balancers may be tricky to test as they may have different mechanisms of orchestrating traffic depending on origin. The most commonly used approach to distinguish origin of the request and redirect it to the same host, which served previous request is a cookie. You can look into HTTP Cookie Manager to correctly manipulate your cookies and make sure than you have different ones for each testing thread or thread group (depending on your use case). Another flaky area is origin host IP. You may require to bind each testing thread to different IP address in order to hit different servers behind the load balancer. There can be also some issues with DNS in regards to Amazon LBs. useful guide on how to test Amazon ELBs
Most probable cause would be DNS caching by jmeter. ELB returns IPs of additional servers depending on how autoscaling is set but JMeter does not use these additional servers. This problem can be solved by ensuring that Jmeter does not cache DNS results...
The ELB is a name, not IP, and can suffer from DNS caching. Make sure you use "-Dsun.net.inetaddr.ttl=0" when starting JMeter
http://wiki.apache.org/jmeter/JMeterAndAmazon
A really late response, and slightly different than the original question, but I hope this can help others as it took me a while to get it all straight. My original problem was not reduced throughput as a result of the ELB, but the introduction of HTTP 503 errors. Actually, the ELB increased my throughput as compared to querying the web application directly, though even with 1 hour tests, the results were sporadic to say the least.
First, the ELB has 2-staged load balancing going on. The first load balance is across the ELB's themselves. That's done by associating multiple IP addresses to the hostname provided by AWS for the ELB you provision. The second is then, of course, across your application instances behind the ELB.
Without trying to offend the SO gods, this is a really helpful article.
https://blazemeter.com/blog/dns-cache-manager-right-way-test-load-balanced-apps
The most helpful information in there was to use the DNS Cache Manager module in JMeter. This will query multiple DNS servers, and wipe out your DNS cache.
I implemented that module and then setup Wireshark, filtering on the two IP addresses belonging to the ELB hostname and sure enough, it was querying both IP addresses, though clearly favored one over the other.
That didn't make a big difference, at least not over short tests.
The real difference (2-3 times more throughput) came when I tweaked the ELB health settings. I initially had a high error rate, however after reducing the unhealthy threshold and the interval between health checks, my error rates dropped dramatically.
Additionally, whereas all my other tests had been 60 - 90 minutes in duration, this one was 8 hours. I started out with decent throughput and it then quickly dropped (by about 2/3). After about 20 minutes or more, the throughput then started ticking back up and by the end of the test, it had sustained throughput of about 5 times what I was getting without the ELB (which was similar to what the throughput was when it dropped shortly after beginning this test).
Does varnish keep a crash / restart log?
I am currently monitoring a varnish server and it seems to restart every week or so, when CPU usage reaches about 100% (load gets a bit high - about 6~7 on a 2 cores machine) and IO wait takes an avg of 45% of CPU time.
Am I missing any configuration or predefined behavior? Does it mean that I have a bottleneck in my hardware causing varnish failures?
Thanks!
When the child dies you should see a message in syslog. It will say something like Child exited.... Varnish is good about keeping track of the child, so when it does crash it will be immediately restarted and it should log it.
Load of 6-7 seems high. If you are using file backed storage I suggest switching to malloc. If you need more cache space, get a box with more memory. Use the nuking behavior as your guide (varnishstat -1 | grep nuke). If the value there reported by varnish is 0 your cache size is sufficient.
I have posted this to ServerFault, but the Node.js community seems tiny there, so I'm hoping this bring more exposure.
I have a Node.js (0.4.9) application and am researching how to best deploy and maintain it. I want to run it in the cloud (EC2 or RackSpace) with high availability. The app should run on HTTPS. I'll worry about East/West/EU full-failover later.
I have done a lot of reading about keep-alive (Upstart, Forever), multi-core utilities (Fugue, multi-node, Cluster), and proxy/load balancers (node-http-proxy, nginx, Varnish, and Pound). However, I am unsure how to combine the various utilities available to me.
I have this setup in mind and need to iron out some questions and get feedback.
Cluster is the most actively developed and seemingly popular multi-core utility for Node.js, so use that to run 1 node "cluster" per app server on non-privileged port (say 3000). Q1: Should Forever be used to keep the cluster alive or is that just redundant?
Use 1 nginx per app server running on port 80, simply reverse proxying to node on port 3000. Q2: Would node-http-proxy be more suitable for this task even though it doesn't gzip or server static files quickly?
Have minimum 2x servers as described above, with an independent server acting as a load balancer across these boxes. Use Pound listening 443 to terminate HTTPS and pass HTTP to Varnish which would round robin load balance across the IPs of servers above. Q3: Should nginx be used to do both instead? Q4: Should AWS or RackSpace load balancer be considered instead (the latter doesn't terminate HTTPS)
General Questions:
Do you see a need for (2) above at all?
Where is the best place to terminate HTTPS?
If WebSockets are needed in the future, what nginx substitutions would you make?
I'd really like to hear how people are setting up current production environments and which combination of tools they prefer. Much appreciated.
It's been several months since I asked this question and not a lot of answer flow. Both Samyak Bhuta and nponeccop had good suggestions, but I wanted to discuss the answers I've found to my questions.
Here is what I've settled on at this point for a production system, but further improvements are always being made. I hope it helps anyone in a similar scenario.
Use Cluster to spawn as many child processes as you desire to handle incoming requests on multi-core virtual or physical machines. This binds to a single port and makes maintenance easier. My rule of thumb is n - 1 Cluster workers. You don't need Forever on this, as Cluster respawns worker processes that die. To have resiliency even at the Cluster parent level, ensure that you use an Upstart script (or equivalent) to daemonize the Node.js application, and use Monit (or equivalent) to watch the PID of the Cluster parent and respawn it if it dies. You can try using the respawn feature of Upstart, but I prefer having Monit watching things, so rather than split responsibilities, I find it's best to let Monit handle the respawn as well.
Use 1 nginx per app server running on port 80, simply reverse proxying to your Cluster on whatever port you bound to in (1). node-http-proxy can be used, but nginx is more mature, more featureful, and faster at serving static files. Run nginx lean (don't log, don't gzip tiny files) to minimize it's overhead.
Have minimum 2x servers as described above in a minimum of 2 availability zones, and if in AWS, use an ELB that terminates HTTPS/SSL on port 443 and communicates on HTTP port 80 to the node.js app servers. ELBs are simple and, if you desire, make it somewhat easier to auto-scale. You could run multiple nginx either sharing an IP or round-robin balanced themselves by your DNS provider, but I found this overkill for now. At that point, you'd remove the nginx instance on each app server.
I have not needed WebSockets so nginx continues to be suitable and I'll revisit this issue when WebSockets come into the picture.
Feedback is welcome.
You should not bother serving static files quickly. If your load is small - node static file servers will do. If your load is big - it's better to use a CDN (Akamai, Limelight, CoralCDN).
Instead of forever you can use monit.
Instead of nginx you can use HAProxy. It is known to work well with websockets. Consider also proxying flash sockets as they are a good workaround until websocket support is ubiquitous (see socket.io).
HAProxy has some support for HTTPS load balancing, but not termination. You can try to use stunnel for HTTPS termination, but I think it's too slow.
Round-robin load (or other statistical) balancing works pretty well in practice, so there's no need to know about other servers' load in most cases.
Consider also using ZeroMQ or RabbitMQ for communications between nodes.
This is an excellent thread! Thanks to everyone that contributed useful information.
I've been dealing with the same issues the past few months setting up the infrastructure for our startup.
As people mentioned previously, we wanted a Node environment with multi-core support + web sockets + vhosts
We ended up creating a hybrid between the native cluster module and http-proxy and called it Drone - of course it's open sourced:
https://github.com/makesites/drone
We also released it as an AMI with Monit and Nginx
https://aws.amazon.com/amis/drone-server
I found this thread researching how to add SSL support to Drone - tnx for recommending ELB but I wouldn't rely on a proprietary solution for something so crucial.
Instead I extended the default proxy to handle all the SSL requests. The configuration is minimal while the SSL requests are converted to plain http - but I guess that's preferable when you're passing traffic between ports...
Feel free to look into it and let me know if it fits your needs. All feedback welcomed.
I have seen AWS load balancer to load balance and termination + http-node-proxy for reverse proxy, if you want to run multiple service per box + cluster.js for mulicore support and process level failover doing extremely well.
forever.js on cluster.js could be good option for extreme care you want to take in terms of failover but that's hardly needed.