Issue: geth 1.8.22 starts mining from one of the first blocks instead of the last one on system reboot.
What we have
We have 3 synced private geth nodes using PoA(clique).
What happened
One day(a week ago) we had issues with our hosting provider so we had to restart 2 out of 3 nodes(each node is on separate VPS). Current block is 4 000 000. When node 1 and node 2 were restarted they started mining from block 372 instead of the last one 4 000 000.
Why it happened (my guess)
Geth 1.8.22 keeps some data with trie node data in RAM instead of a disk. On graceful node shutdown(for example from console) this trie node data is saved to hard drive from RAM. On forced system shutdown(for example from hosting admin panel) trie node data does not have time to be saved on a hard drive. We had our nodes running for 6 months without any reboot so I think that this trie node data was kept in RAM for the whole time and it was vanished on system reboot(though we still have node 3 which is up and running).
Logs
Here are the logs when I'm trying to run the backup version of one of the nodes:
vladimir#comp:~/Public/projects/ethereum/repro-geth-bug/geth-linux-amd64-1.8.22-7fa3509e$ ./geth --datadir ../opt/ethereum/data/ --networkid 1515 --unlock 0xd6ee38421e1713dd50e888c6d689b82953946bc3 --password ../opt/ethereum/unlock_password --port 30306 --mine
INFO [11-21|17:06:25.374] Maximum peer count ETH=25 LES=0 total=25
INFO [11-21|17:06:25.374] Starting peer-to-peer node instance=Geth/v1.8.22-stable-7fa3509e/linux-amd64/go1.11.5
INFO [11-21|17:06:25.374] Allocated cache and file handles database=/home/vladimir/Public/projects/ethereum/repro-geth-bug/opt/ethereum/data/geth/chaindata cache=512 handles=2048
INFO [11-21|17:06:26.550] Initialised chain configuration config="{ChainID: 1515 Homestead: 1 DAO: <nil> DAOSupport: false EIP150: 2 EIP155: 3 EIP158: 3 Byzantium: 4 Constantinople: 5 ConstantinopleFix: <nil> Engine: clique}"
INFO [11-21|17:06:26.550] Initialising Ethereum protocol versions="[63 62]" network=1515
WARN [11-21|17:06:26.579] Head state missing, repairing chain number=4073749 hash=9bfb53…56d503
INFO [11-21|17:07:45.179] Rewound blockchain to past state number=371 hash=102018…d91947
INFO [11-21|17:07:45.180] Loaded most recent local header number=4073749 hash=9bfb53…56d503 td=8147499 age=2d5h43m
INFO [11-21|17:07:45.180] Loaded most recent local full block number=371 hash=102018…d91947 td=743 age=7mo3w6d
INFO [11-21|17:07:45.180] Loaded most recent local fast block number=4073749 hash=9bfb53…56d503 td=8147499 age=2d5h43m
INFO [11-21|17:07:45.180] Loaded local transaction journal transactions=3 dropped=3
INFO [11-21|17:07:45.180] Regenerated local transaction journal transactions=0 accounts=0
WARN [11-21|17:07:45.180] Blockchain not empty, fast sync disabled
INFO [11-21|17:07:45.623] New local node record seq=6 id=e8c5a9e8848d4e30 ip=127.0.0.1 udp=30306 tcp=30306
INFO [11-21|17:07:45.623] Started P2P networking self=enode://9647000ba2579dd529574b49f472f029839a09257c1bc3ade5135cbbb5f3ceaf1237aff5b6b947d2fa4f218fa24858dc2767bd4b78e082b04c9d013c1482cfa6#127.0.0.1:30306
INFO [11-21|17:07:45.624] IPC endpoint opened url=/home/vladimir/Public/projects/ethereum/repro-geth-bug/opt/ethereum/data/geth.ipc
INFO [11-21|17:07:46.192] Unlocked account address=0xd6ee38421e1713dD50E888c6D689B82953946bC3
INFO [11-21|17:07:46.192] Transaction pool price threshold updated price=1000000000
INFO [11-21|17:07:46.192] Transaction pool price threshold updated price=1000000000
INFO [11-21|17:07:46.192] Etherbase automatically configured address=0xd6ee38421e1713dD50E888c6D689B82953946bC3
INFO [11-21|17:07:46.192] Commit new mining work number=372 sealhash=685e15…2c52df uncles=0 txs=0 gas=0 fees=0 elapsed=75.951µs
INFO [11-21|17:07:46.192] Successfully sealed new block number=372 sealhash=685e15…2c52df hash=0c60ef…f29e6b elapsed=385.27µs
INFO [11-21|17:07:46.192] 🔨 mined potential block number=372 hash=0c60ef…f29e6b
INFO [11-21|17:07:46.193] Commit new mining work number=373 sealhash=337ae5…2b4704 uncles=0 txs=0 gas=0 fees=0 elapsed=222.362µs
INFO [11-21|17:07:47.962] Mapped network port proto=tcp extport=30306 intport=30306 interface="UPNP IGDv1-IP1"
INFO [11-21|17:07:48.391] Mapped network port proto=udp extport=30306 intport=30306 interface="UPNP IGDv1-IP1"
INFO [11-21|17:07:49.625] New local node record seq=7 id=e8c5a9e8848d4e30 ip=128.71.103.50 udp=30306 tcp=30306
INFO [11-21|17:07:51.001] Successfully sealed new block number=373 sealhash=337ae5…2b4704 hash=b67668…81f164 elapsed=4.807s
INFO [11-21|17:07:51.001] 🔨 mined potential block number=373 hash=b67668…81f164
INFO [11-21|17:07:51.002] Commit new mining work number=374 sealhash=c0e9f6…628d51 uncles=0 txs=0 gas=0 fees=0 elapsed=1.434ms
INFO [11-21|17:07:56.001] Successfully sealed new block number=374 sealhash=c0e9f6…628d51 hash=77aae2…9c44e8 elapsed=4.998s
INFO [11-21|17:07:56.001] 🔨 mined potential block number=374 hash=77aae2…9c44e8
INFO [11-21|17:07:56.003] Commit new mining work number=375 sealhash=6f7db7…adca12 uncles=0 txs=0 gas=0 fees=0 elapsed=1.305ms
^CINFO [11-21|17:07:58.483] Got interrupt, shutting down...
INFO [11-21|17:07:58.483] IPC endpoint closed url=/home/vladimir/Public/projects/ethereum/repro-geth-bug/opt/ethereum/data/geth.ipc
INFO [11-21|17:07:58.483] Writing cached state to disk block=374 hash=77aae2…9c44e8 root=e16e04…e93be1
INFO [11-21|17:07:58.483] Persisted trie from memory database nodes=0 size=0.00B time=7.185µs gcnodes=0 gcsize=0.00B gctime=0s livenodes=1 livesize=0.00B
INFO [11-21|17:07:58.483] Writing cached state to disk block=373 hash=b67668…81f164 root=e16e04…e93be1
INFO [11-21|17:07:58.483] Persisted trie from memory database nodes=0 size=0.00B time=2.571µs gcnodes=0 gcsize=0.00B gctime=0s livenodes=1 livesize=0.00B
INFO [11-21|17:07:58.484] Writing cached state to disk block=247 hash=7b422a…5f9a62 root=e16e04…e93be1
INFO [11-21|17:07:58.484] Persisted trie from memory database nodes=0 size=0.00B time=2.784µs gcnodes=0 gcsize=0.00B gctime=0s livenodes=1 livesize=0.00B
INFO [11-21|17:07:58.484] Blockchain manager stopped
INFO [11-21|17:07:58.484] Stopping Ethereum protocol
INFO [11-21|17:07:58.484] Ethereum protocol stopped
INFO [11-21|17:07:58.484] Transaction pool stopped
INFO [11-21|17:07:58.497] Database closed database=/home/vladimir/Public/projects/ethereum/repro-geth-bug/opt/ethereum/data/geth/chaindata
How to fix
The 1st thing that comes to mind is to restart geth nodes(gracefully) via cron everyday so that nodes persist trie node data on the disk.
How to handle UNgraceful system shutdown so that geth node persists data and keeps mining from the latest block on restart?
Please check the full answer: https://github.com/ethereum/go-ethereum/issues/20383#issuecomment-558107815
In short:
geth persists data after 1 hour worth of block processing
if your network is super light (i.e. mostly empty blocks), it takes a very very long time until blocks are flushed from memory to hard drive
currently there is no way to configure the period of persistency rounds in geth
Solution: restart geth periodically so it saves data from RAM to hard drive
I have a Google compute engine instance(Cent-Os) which I could access using its external IP address till recently.
Now suddenly the instance cannot be accessed using its using its external IP address.
I logged in to the developer console and tried rebooting the instance but that did not help.
I also noticed that the CPU usage is almost at 100% continuously.
On further analysis of the Serial port output it appears the init module is not loading properly.
I am pasting below the last few lines from the serial port output of the virtual machine.
rtc_cmos 00:01: RTC can wake from S4
rtc_cmos 00:01: rtc core: registered rtc_cmos as rtc0
rtc0: alarms up to one day, 114 bytes nvram
cpuidle: using governor ladder
cpuidle: using governor menu
EFI Variables Facility v0.08 2004-May-17
usbcore: registered new interface driver hiddev
usbcore: registered new interface driver usbhid
usbhid: v2.6:USB HID core driver
GRE over IPv4 demultiplexor driver
TCP cubic registered
Initializing XFRM netlink socket
NET: Registered protocol family 17
registered taskstats version 1
rtc_cmos 00:01: setting system clock to 2014-07-04 07:40:53 UTC (1404459653)
Initalizing network drop monitor service
Freeing unused kernel memory: 1280k freed
Write protecting the kernel read-only data: 10240k
Freeing unused kernel memory: 800k freed
Freeing unused kernel memory: 1584k freed
Failed to execute /init
Kernel panic - not syncing: No init found. Try passing init= option to kernel.
Pid: 1, comm: swapper Not tainted 2.6.32-431.17.1.el6.x86_64 #1
Call Trace:
[] ? panic+0xa7/0x16f
[] ? init_post+0xa8/0x100
[] ? kernel_init+0x2e6/0x2f7
[] ? child_rip+0xa/0x20
[] ? kernel_init+0x0/0x2f7
[] ? child_rip+0x0/0x20
Thanks in advance for any tips to resolve this issue.
Mathew
It looks like you might have an script or other program that is causing you to run out of Inodes.
You can delete the instance without deleting the persistent disk (PD) and create a new vm with a higher capacity using your PD, however if it's an script causing this, you will end up with the same issue. It's always recommended to backup your PD before making any changes.
Run this command to find more info about your instance:
gcutil --project= getserialportoutput
If the issue still continue, you can either
- Make a snapshot of your PD and make a PD's copy or
- Delete the instance without deleting the PD
Attach and mount the PD to another vm as a second disk, so you can access it to find what is causing this issue. Visit this link https://developers.google.com/compute/docs/disks#attach_disk for more information on how to do this.
Visit this page http://www.ivankuznetsov.com/2010/02/no-space-left-on-device-running-out-of-inodes.html for more information about inodes troubleshooting.
Make sure the Allow HTTP traffic setting on the vm is still enabled.
Then see which network firewall you are using and it's rules.
If your network is set up to use an ephemral IP, it will be periodically released back. This will cause your IP to change over time. Set it to static/reserved then (on networks page).
https://developers.google.com/compute/docs/instances-and-network#externaladdresses
I have an application (Node.JS) deployed on OpenShift (bronze plan) with the Web Load Balancer activated, the minimum gears active are 3 and the max are 16.
Sometimes in the main gear I can see more than one HAProxy instance running, for example now I have:
> ps -ef|grep /usr/sbin/haproxy
3505 37488 1 1 08:46 ? 00:00:01 /usr/sbin/haproxy -f /var/lib/openshift/<APP_ID>/haproxy//conf/haproxy.cfg -sf 37237
3505 149643 1 1 May28 ? 00:09:08 /usr/sbin/haproxy -f /var/lib/openshift/<APP_ID>/haproxy//conf/haproxy.cfg -sf 114873
looking the logs I can't any error. Any explanation about this?
Thanks!
This could be a consequence of executing Haproxy reload script (/etc/init.d/haproxy). This will usually create a new haproxy process to accept new connections. It will also keep the old process alive until there are still open connections to it. Once they are closed, old haproxy process will be terminated.
I found there are still failed request when the traffic is high using command like this
haproxy -f /etc/haproxy.cfg -p /var/run/haproxy.pid -sf $(cat /var/run/haproxy.pid)
to hot reload the updated config file.
Here below is the presure testing result using webbench :
/usr/local/bin/webbench -c 10 -t 30 targetHProxyIP:1080
Webbench – Simple Web Benchmark 1.5
Copyright (c) Radim Kolar 1997-2004, GPL Open Source Software.
Benchmarking: GET targetHProxyIP:1080
10 clients, running 30 sec.
Speed=70586 pages/min, 13372974 bytes/sec.
**Requests: 35289 susceed, 4 failed.**
I run command
haproxy -f /etc/haproxy.cfg -p /var/run/haproxy.pid -sf $(cat /var/run/haproxy.pid)
several times during the pressure testing.
In the haproxy documentation, it mentioned
They will receive the SIGTTOU
611 signal to ask them to temporarily stop listening to the ports so that the new
612 process can grab them
so there is a time period that the old process is not listening on the PORT(say 80) and the new process haven’t start to listen to the PORT (say 80), and during this specific time period, it will cause the NEW connections failed, make sense?
So is there any approach that makes the configuration reload of haproxy that will not impact both existing connections and new connections?
On recent kernels where SO_REUSEPORT is finally implemented (3.9+), this dead period does not exist anymore. While a patch has been available for older kernels for something like 10 years, it's obvious that many users cannot patch their kernels. If your system is more recent, then the new process will succeed its attempt to bind() before asking the previous one to release the port, then there's a period where both processes are bound to the port instead of no process.
There is still a very tiny possibility that a connection arrived in the leaving process' queue at the moment it closes it. There is no reliable way to stop this from happening though.
I have setup gunicorn with 3 workers, 30 worker connections and using eventlet worker class. It is set up behind Nginx. After every few requests, I see this in the logs.
[ERROR] gunicorn.error: WORKER TIMEOUT (pid:23475)
None
[INFO] gunicorn.error: Booting worker with pid: 23514
Why is this happening? How can I figure out what's going wrong?
We had the same problem using Django+nginx+gunicorn. From Gunicorn documentation we have configured the graceful-timeout that made almost no difference.
After some testings, we found the solution, the parameter to configure is: timeout (And not graceful timeout). It works like a clock..
So, Do:
1) open the gunicorn configuration file
2) set the TIMEOUT to what ever you need - the value is in seconds
NUM_WORKERS=3
TIMEOUT=120
exec gunicorn ${DJANGO_WSGI_MODULE}:application \
--name $NAME \
--workers $NUM_WORKERS \
--timeout $TIMEOUT \
--log-level=debug \
--bind=127.0.0.1:9000 \
--pid=$PIDFILE
On Google Cloud
Just add --timeout 90 to entrypoint in app.yaml
entrypoint: gunicorn -b :$PORT main:app --timeout 90
Run Gunicorn with --log-level debug.
It should give you an app stack trace.
Is this endpoint taking too many time?
Maybe you are using flask without asynchronous support, so every request will block the call. To create async support without make difficult, add the gevent worker.
With gevent, a new call will spawn a new thread, and you app will be able to receive more requests
pip install gevent
gunicon .... --worker-class gevent
The Microsoft Azure official documentation for running Flask Apps on Azure App Services (Linux App) states the use of timeout as 600
gunicorn --bind=0.0.0.0 --timeout 600 application:app
https://learn.microsoft.com/en-us/azure/app-service/configure-language-python#flask-app
WORKER TIMEOUT means your application cannot response to the request in a defined amount of time. You can set this using gunicorn timeout settings. Some application need more time to response than another.
Another thing that may affect this is choosing the worker type
The default synchronous workers assume that your application is resource-bound in terms of CPU and network bandwidth. Generally this means that your application shouldn’t do anything that takes an undefined amount of time. An example of something that takes an undefined amount of time is a request to the internet. At some point the external network will fail in such a way that clients will pile up on your servers. So, in this sense, any web application which makes outgoing requests to APIs will benefit from an asynchronous worker.
When I got the same problem as yours (I was trying to deploy my application using Docker Swarm), I've tried to increase the timeout and using another type of worker class. But all failed.
And then I suddenly realised I was limitting my resource too low for the service inside my compose file. This is the thing slowed down the application in my case
deploy:
replicas: 5
resources:
limits:
cpus: "0.1"
memory: 50M
restart_policy:
condition: on-failure
So I suggest you to check what thing slowing down your application in the first place
Could it be this?
http://docs.gunicorn.org/en/latest/settings.html#timeout
Other possibilities could be your response is taking too long or is stuck waiting.
This worked for me:
gunicorn app:app -b :8080 --timeout 120 --workers=3 --threads=3 --worker-connections=1000
If you have eventlet add:
--worker-class=eventlet
If you have gevent add:
--worker-class=gevent
I've got the same problem in Docker.
In Docker I keep trained LightGBM model + Flask serving requests. As HTTP server I used gunicorn 19.9.0. When I run my code locally on my Mac laptop everything worked just perfect, but when I ran the app in Docker my POST JSON requests were freezing for some time, then gunicorn worker had been failing with [CRITICAL] WORKER TIMEOUT exception.
I tried tons of different approaches, but the only one solved my issue was adding worker_class=gthread.
Here is my complete config:
import multiprocessing
workers = multiprocessing.cpu_count() * 2 + 1
accesslog = "-" # STDOUT
access_log_format = '%(h)s %(l)s %(u)s %(t)s "%(r)s" %(s)s %(b)s "%(q)s" "%(D)s"'
bind = "0.0.0.0:5000"
keepalive = 120
timeout = 120
worker_class = "gthread"
threads = 3
I had very similar problem, I also tried using "runserver" to see if I could find anything but all I had was a message Killed
So I thought it could be resource problem, and I went ahead to give more RAM to the instance, and it worked.
You need to used an other worker type class an async one like gevent or tornado see this for more explanation :
First explantion :
You may also want to install Eventlet or Gevent if you expect that your application code may need to pause for extended periods of time during request processing
Second one :
The default synchronous workers assume that your application is resource bound in terms of CPU and network bandwidth. Generally this means that your application shouldn’t do anything that takes an undefined amount of time. For instance, a request to the internet meets this criteria. At some point the external network will fail in such a way that clients will pile up on your servers.
If you are using GCP then you have to set workers per instance type.
Link to GCP best practices https://cloud.google.com/appengine/docs/standard/python3/runtime
timeout is a key parameter to this problem.
however it's not suit for me.
i found there is not gunicorn timeout error when i set workers=1.
when i look though my code, i found some socket connect (socket.send & socket.recv) in server init.
socket.recv will block my code and that's why it always timeout when workers>1
hope to give some ideas to the people who have some problem with me
For me, the solution was to add --timeout 90 to my entrypoint, but it wasn't working because I had TWO entrypoints defined, one in app.yaml, and another in my Dockerfile. I deleted the unused entrypoint and added --timeout 90 in the other.
For me, it was because I forgot to setup firewall rule on database server for my Django.
Frank's answer pointed me in the right direction. I have a Digital Ocean droplet accessing a managed Digital Ocean Postgresql database. All I needed to do was add my droplet to the database's "Trusted Sources".
(click on database in DO console, then click on settings. Edit Trusted Sources and select droplet name (click in editable area and it will be suggested to you)).
Check that your workers are not killed by a health check. A long request may block the health check request, and the worker gets killed by your platform because the platform thinks that the worker is unresponsive.
E.g. if you have a 25-second-long request, and a liveness check is configured to hit a different endpoint in the same service every 10 seconds, time out in 1 second, and retry 3 times, this gives 10+1*3 ~ 13 seconds, and you can see that it would trigger some times but not always.
The solution, if this is your case, is to reconfigure your liveness check (or whatever health check mechanism your platform uses) so it can wait until your typical request finishes. Or allow for more threads - something that makes sure that the health check is not blocked for long enough to trigger worker kill.
You can see that adding more workers may help with (or hide) the problem.
The easiest way that worked for me is to create a new config.py file in the same folder where your app.py exists and to put inside it the timeout and all your desired special configuration:
timeout = 999
Then just run the server while pointing to this configuration file
gunicorn -c config.py --bind 0.0.0.0:5000 wsgi:app
note that for this statement to work you need wsgi.py also in the same directory having the following
from myproject import app
if __name__ == "__main__":
app.run()
Cheers!
Apart from the gunicorn timeout settings which are already suggested, since you are using nginx in front, you can check if these 2 parameters works, proxy_connect_timeout and proxy_read_timeout which are by default 60 seconds. Can set them like this in your nginx configuration file as,
proxy_connect_timeout 120s;
proxy_read_timeout 120s;
In my case I came across this issue when sending larger(10MB) files to my server. My development server(app.run()) received them no problem but gunicorn could not handle them.
for people who come to the same problem I did. My solution was to send it in chunks like this:
ref / html example, separate large files ref
def upload_to_server():
upload_file_path = location
def read_in_chunks(file_object, chunk_size=524288):
"""Lazy function (generator) to read a file piece by piece.
Default chunk size: 1k."""
while True:
data = file_object.read(chunk_size)
if not data:
break
yield data
with open(upload_file_path, 'rb') as f:
for piece in read_in_chunks(f):
r = requests.post(
url + '/api/set-doc/stream' + '/' + server_file_name,
files={name: piece},
headers={'key': key, 'allow_all': 'true'})
my flask server:
#app.route('/api/set-doc/stream/<name>', methods=['GET', 'POST'])
def api_set_file_streamed(name):
folder = escape(name) # secure_filename(escape(name))
if 'key' in request.headers:
if request.headers['key'] != key:
return 404
else:
return 404
for fn in request.files:
file = request.files[fn]
if fn == '':
print('no file name')
flash('No selected file')
return 'fail'
if file and allowed_file(file.filename):
file_dir_path = os.path.join(app.config['UPLOAD_FOLDER'], folder)
if not os.path.exists(file_dir_path):
os.makedirs(file_dir_path)
file_path = os.path.join(file_dir_path, secure_filename(file.filename))
with open(file_path, 'ab') as f:
f.write(file.read())
return 'sucess'
return 404
in case you have changed the name of the django project you should also go to
cd /etc/systemd/system/
then
sudo nano gunicorn.service
then verify that at the end of the bind line the application name has been changed to the new application name