I'm running Apache Openwhisk on k3s, installed using helm.
Below is the invoker logs, taken several hours after a fresh install, with several functions set to run periodically. This message appears every few seconds after the problem starts.
[2020-03-17T13:27:12.691Z] [ERROR] [#tid_sid_invokerHealth] [ContainerPool]
Rescheduling Run message, too many message in the pool, freePoolSize: 0 containers and 0 MB,
busyPoolSize: 8 containers and 4096 MB, maxContainersMemory 4096 MB, userNamespace: whisk.system,
action: ExecutableWhiskAction/whisk.system/invokerHealthTestAction0#0.0.1, needed memory: 128 MB,
waiting messages: 24
Here are the running pods. Notice all the function pods have an age of 11+ hours.
NAME READY STATUS RESTARTS AGE
openwhisk-gen-certs-n965b 0/1 Completed 0 14h
openwhisk-init-couchdb-4s9rh 0/1 Completed 0 14h
openwhisk-install-packages-pnvmq 0/1 Completed 0 14h
openwhisk-apigateway-78c64dd7c9-2gsw6 1/1 Running 2 14h
openwhisk-couchdb-844c6df68f-qrxq6 1/1 Running 2 14h
openwhisk-wskadmin 1/1 Running 2 14h
openwhisk-redis-77494b8d44-gkmlt 1/1 Running 2 14h
openwhisk-zookeeper-0 1/1 Running 2 14h
openwhisk-kafka-0 1/1 Running 2 14h
openwhisk-controller-0 1/1 Running 2 14h
openwhisk-nginx-5f795dd747-c228s 1/1 Running 4 14h
openwhisk-cloudantprovider-69fd94b6f6-x88f4 1/1 Running 2 14h
openwhisk-kafkaprovider-544fbfdcc7-kn29p 1/1 Running 2 14h
openwhisk-alarmprovider-58c5454cc8-q4wbw 1/1 Running 2 14h
openwhisk-invoker-0 1/1 Running 2 14h
wskopenwhisk-invoker-00-1-prewarm-nodejs10 1/1 Running 0 14h
wskopenwhisk-invoker-00-6-prewarm-nodejs10 1/1 Running 0 13h
wskopenwhisk-invoker-00-15-whisksystem-checkuserload 1/1 Running 0 13h
wskopenwhisk-invoker-00-31-whisksystem-guacscaleup 1/1 Running 0 12h
wskopenwhisk-invoker-00-30-whisksystem-guacscaledown 1/1 Running 0 12h
wskopenwhisk-invoker-00-37-whisksystem-functionelastalertcheckd 1/1 Running 0 11h
wskopenwhisk-invoker-00-39-whisksystem-checkuserload 1/1 Running 0 11h
wskopenwhisk-invoker-00-40-whisksystem-functionelastalertcheckd 1/1 Running 0 11h
wskopenwhisk-invoker-00-42-whisksystem-guacscaleup 1/1 Running 0 11h
wskopenwhisk-invoker-00-43-whisksystem-functionelastalertcheckd 1/1 Running 0 11h
Shouldn't Openwhisk be killing these pods after they reach the timeout? The functions all have a timeout of either 3 or 5 minutes, but Openwhisk doesn't seem to enforce this.
One other thing I noticed was "timeout" being set to "false" on the activations.
$ wsk activation get ...
{
"annotations": [
...
{
"key": "timeout",
"value": false
},
...
}
The timeout annotation is specific to an particular activation. If the value is true it means that particular activation of the corresponding function exceeded its set maximum duration which is a range of values from 100 ms to 5 minutes by default (per the docs) unless changed for the system deployment as a whole.
The pods are used to execute the functions - they will stick around for some duration while idle to facilitate future warm starts. The openwhisk invoker will terminate these warm pods eventually after an idle timeout, or when resource are required to run other pods.
Ok I fixed this by changing the invoker container factory implementation to docker. I'm not sure why the kubernetes implementation fails to kill pods (and release memory), but we are using docker as the container runtime for k3s.
To set this, change invoker.containerFactory.impl to docker in the helm chart values:
https://github.com/apache/openwhisk-deploy-kube/blob/master/helm/openwhisk/values.yaml#L261
I also increased the invoker memory (invoker.jvmHeapMB) to 1024:
https://github.com/apache/openwhisk-deploy-kube/blob/master/helm/openwhisk/values.yaml#L257
Here is a link that explains the container factory setting:
https://github.com/apache/openwhisk-deploy-kube/blob/master/docs/configurationChoices.md#invoker-container-factory
Related
I am using a containerized Spring boot application in Kubernetes. But the application automatically exits and restarts with exit code 143 and error message "Error".
I am not sure how to identify the reason for this error.
My first idea was that Kubernetes stopped the container due to too high resource usage, as described here, but I can't see the corresponding kubelet logs.
Is there any way to identify the cause/origin of the SIGTERM? Maybe from spring-boot itself, or from the JVM?
Exit Code 143
It denotes that the process was terminated by an external signal.
The number 143 is a sum of two numbers: 128+x, # where x is the signal number sent to the process that caused it to terminate.
In the example, x equals 15, which is the number of the SIGTERM signal, meaning the process was killed forcibly.
Hope this helps better.
I've just run into this exact same problem. I was able to track down the origin of the Exit Code 143 by looking at the logs on the Kubernetes nodes (note, the logs on the node not the pod). (I use Lens as an easy way to get a node shell but there are other ways)
Then if you look in /var/log/messages for terminated you'll see something like this:
Feb 2 11:52:27 np-26992252-3 kubelet[23125]: I0202 11:52:27.541751 23125 kubelet.go:2214] "SyncLoop (probe)" probe="liveness" status="unhealthy" pod="default/app-compute-deployment-56ccffd87f-8s78v"
Feb 2 11:52:27 np-26992252-3 kubelet[23125]: I0202 11:52:27.541920 23125 kubelet.go:2214] "SyncLoop (probe)" probe="readiness" status="" pod="default/app-compute-deployment-56ccffd87f-8s78v"
Feb 2 11:52:27 np-26992252-3 kubelet[23125]: I0202 11:52:27.543274 23125 kuberuntime_manager.go:707] "Message for Container of pod" containerName="app" containerStatusID={Type:containerd ID:c3426d6b07fe3bd60bcbe675bab73b6b4b3619ef4639e1c23bca82692633765e} pod="default/app-comp
ute-deployment-56ccffd87f-8s78v" containerMessage="Container app failed liveness probe, will be restarted"
Feb 2 11:52:27 np-26992252-3 kubelet[23125]: I0202 11:52:27.543374 23125 kuberuntime_container.go:723] "Killing container with a grace period" pod="default/app-compute-deployment-56ccffd87f-8s78v" podUID=89fdc1a2-3a3b-4d57-8a4d-ab115e52dc85 containerName="app" containerID="con
tainerd://c3426d6b07fe3bd60bcbe675bab73b6b4b3619ef4639e1c23bca82692633765e" gracePeriod=30
Feb 2 11:52:27 np-26992252-3 containerd[22741]: time="2023-02-02T11:52:27.543834687Z" level=info msg="StopContainer for \"c3426d6b07fe3bd60bcbe675bab73b6b4b3619ef4639e1c23bca82692633765e\" with timeout 30 (s)"
Feb 2 11:52:27 np-26992252-3 containerd[22741]: time="2023-02-02T11:52:27.544593294Z" level=info msg="Stop container \"c3426d6b07fe3bd60bcbe675bab73b6b4b3619ef4639e1c23bca82692633765e\" with signal terminated"
The bit to look out for is containerMessage="Container app failed liveness probe, will be restarted"
I have implemented ELK on k8s, however my data pod keep on getting into crashloopbackoff status.
[]$ kubectl get pod -n es
NAME READY STATUS RESTARTS AGE
logging-es-opendistro-es-client-76ff944d-rwjvz 1/1 Running 0 134m
logging-es-opendistro-es-data-0 0/1 CrashLoopBackOff 3 18m
logging-es-opendistro-es-data-1 0/1 Init:1/2 0 5m24s
logging-es-opendistro-es-kibana-5cfbd8dc49-g5rdl 1/1 Running 0 39m
logging-es-opendistro-es-master-0 1/1 Running 0 134m
logging-es-opendistro-es-master-1 1/1 Running 0 127m
Logs from data pod
[2021-02-15T08:02:46,683][INFO ][o.e.p.PluginsService ] [logging-es-opendistro-es-data-1] loaded plugin [opendistro_security]
[2021-02-15T08:02:46,683][INFO ][o.e.p.PluginsService ] [logging-es-opendistro-es-data-1] loaded plugin [opendistro_sql]
[2021-02-15T08:02:47,027][INFO ][o.e.e.NodeEnvironment ] [logging-es-opendistro-es-data-1] using [1] data paths, mounts [[/usr/share/elasticsearch/data (//fbeff48040de841b395c700.file.core.windows.net/kubernetes-dynamic-pvc-0f5e7e46-5138-0dfbe0aadff3)]], net usable_space [37.1gb], net total_space [50gb], types [cifs]
[2021-02-15T08:02:47,027][INFO ][o.e.e.NodeEnvironment ] [logging-es-opendistro-es-data-1] heap size [4gb], compressed ordinary object pointers [true]
Failed to pull image "/infrastructure/busybox:1.27.2". Your image name looks wrong. The image name is not supposed to start with a /.
You can check this doc if you need to fetch an image from a specific registry.
I started learn Kubernetes, so I follow this guide https://kubernetes.io/docs/setup/turnkey/gce/
I got an error after I run "cluster/kube-up.sh"
Waiting up to 300 seconds for cluster initialization.
This will continually check to see if the API for kubernetes is reachable.
This may time out if there was some uncaught error during start up.
.........................................................................................................................................Cluster failed to initialize within 300 seconds.
Last output from querying API server follows:
% Total % Received % Xferd Average Speed Time Time Time current
Dload Upload Total Spent Left speed
0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0curl: (7) Failed to connect to "[kubernetes-master (external IP)]"
So I tried to search about this error. And then found one solution. It said go to the "cluster/gce/config-default.sh"
secret: $(dd if=/dev/urandom iflag=fullblock bs=32 count=1 2>/dev/null | base64 | tr -d '\r\n')
And then change 'dd' to 'gdd'. So I modified config-default.sh, But it doesn't work.
I don't know how to fix it. Is there are any solution about this error ?̊̈ Also in the /var/logs there are no logs about Kubernetes. Where logs are saved ?̊̈
My Mac version: mas OS Mojave
version: 10.14.3
Looks like GDD is only available in MacOS, about the Kubernetes logs you can have a look at this other article. If you would have a Google Kubernetes Engine cluster it would be easier to check the log by looking at Stackdriver.
Trying to start an h2o cluster on (MapR) hadoop via python
# startup hadoop h2o cluster
import os
import subprocess
import h2o
import shlex
import re
from Queue import Queue, Empty
from threading import Thread
def enqueue_output(out, queue):
"""
Function for communicating streaming text lines from seperate thread.
see https://stackoverflow.com/questions/375427/non-blocking-read-on-a-subprocess-pipe-in-python
"""
for line in iter(out.readline, b''):
queue.put(line)
out.close()
# clear legacy temp. dir.
hdfs_legacy_dir = '/mapr/clustername/user/mapr/hdfsOutputDir'
if os.path.isdir(hdfs_legacy_dir ):
print subprocess.check_output(shlex.split('rm -r %s'%hdfs_legacy_dir ))
# start h2o service in background thread
local_h2o_start_path = '/home/mapr/h2o-3.18.0.2-mapr5.2/'
startup_p = subprocess.Popen(shlex.split('/bin/hadoop jar {}h2odriver.jar -nodes 4 -mapperXmx 6g -timeout 300 -output hdfsOutputDir'.format(local_h2o_start_path)),
shell=False,
stdout=subprocess.PIPE, stderr=subprocess.PIPE)
# setup message passing queue
q = Queue()
t = Thread(target=enqueue_output, args=(startup_p.stdout, q))
t.daemon = True # thread dies with the program
t.start()
# read line without blocking
h2o_url_out = ''
while True:
try: line = q.get_nowait() # or q.get(timeout=.1)
except Empty:
continue
else: # got line
print line
# check for first instance connection url output
if re.search('Open H2O Flow in your web browser', line) is not None:
h2o_url_out = line
break
if re.search('Error', line) is not None:
print 'Error generated: %s' % line
sys.exit()
print 'Connection url output line: %s' % h2o_url_out
h2o_cnxn_ip = re.search('(?<=Open H2O Flow in your web browser: http:\/\/)(.*?)(?=:)', h2o_url_out).group(1)
print 'H2O connection ip: %s' % h2o_cnxn_ip
frequently throws a timeout error
Waiting for H2O cluster to come up...
H2O node 172.18.4.66:54321 requested flatfile
H2O node 172.18.4.65:54321 requested flatfile
H2O node 172.18.4.67:54321 requested flatfile
ERROR: Timed out waiting for H2O cluster to come up (300 seconds)
Error generated: ERROR: Timed out waiting for H2O cluster to come up (300 seconds)
Shutting down h2o cluster
Looking at the docs (http://docs.h2o.ai/h2o/latest-stable/h2o-docs/faq/general-troubleshooting.html) (and just doing a wordfind for the word "timeout"), was unable to find anything that helped the problem (eg. extending the timeout time via hadoop jar h2odriver.jar -timeout <some time> did nothing but extend the time until the timeout error popped up).
Have noticed that this happens often when there is another instance of an h2o cluster already up and running (which I don't understand since I would think that YARN could support multiple instances), yet also sometimes when there is no other cluster initialized.
Anyone know anything else that can be tried to solve this problem or get more debugging info beyond the error message being thrown by h2o?
UPDATE:
Trying to recreate the problem from the commandline, getting
[me#mnode01 project]$ /bin/hadoop jar /home/me/h2o-3.20.0.5-mapr5.2/h2odriver.jar -nodes 4 -mapperXmx 6g -timeout 300 -output hdfsOutputDir
Determining driver host interface for mapper->driver callback...
[Possible callback IP address: 172.18.4.62]
[Possible callback IP address: 127.0.0.1]
Using mapper->driver callback IP address and port: 172.18.4.62:29388
(You can override these with -driverif and -driverport/-driverportrange.)
Memory Settings:
mapreduce.map.java.opts: -Xms6g -Xmx6g -XX:PermSize=256m -verbose:gc -XX:+PrintGCDetails -XX:+PrintGCTimeStamps -Dlog4j.defaultInitOverride=true
Extra memory percent: 10
mapreduce.map.memory.mb: 6758
18/08/15 09:18:46 INFO client.MapRZKBasedRMFailoverProxyProvider: Updated RM address to mnode03.cluster.local/172.18.4.64:8032
18/08/15 09:18:48 INFO mapreduce.JobSubmitter: number of splits:4
18/08/15 09:18:48 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1523404089784_7404
18/08/15 09:18:48 INFO security.ExternalTokenManagerFactory: Initialized external token manager class - com.mapr.hadoop.yarn.security.MapRTicketManager
18/08/15 09:18:48 INFO impl.YarnClientImpl: Submitted application application_1523404089784_7404
18/08/15 09:18:48 INFO mapreduce.Job: The url to track the job: https://mnode03.cluster.local:8090/proxy/application_1523404089784_7404/
Job name 'H2O_66888' submitted
JobTracker job ID is 'job_1523404089784_7404'
For YARN users, logs command is 'yarn logs -applicationId application_1523404089784_7404'
Waiting for H2O cluster to come up...
H2O node 172.18.4.65:54321 requested flatfile
H2O node 172.18.4.67:54321 requested flatfile
H2O node 172.18.4.66:54321 requested flatfile
ERROR: Timed out waiting for H2O cluster to come up (300 seconds)
ERROR: (Try specifying the -timeout option to increase the waiting time limit)
Attempting to clean up hadoop job...
Killed.
18/08/15 09:23:54 INFO client.MapRZKBasedRMFailoverProxyProvider: Updated RM address to mnode03.cluster.local/172.18.4.64:8032
----- YARN cluster metrics -----
Number of YARN worker nodes: 6
----- Nodes -----
Node: http://mnode03.cluster.local:8044 Rack: /default-rack, RUNNING, 0 containers used, 0.0 / 7.0 GB used, 0 / 2 vcores used
Node: http://mnode05.cluster.local:8044 Rack: /default-rack, RUNNING, 0 containers used, 0.0 / 10.4 GB used, 0 / 2 vcores used
Node: http://mnode06.cluster.local:8044 Rack: /default-rack, RUNNING, 0 containers used, 0.0 / 10.4 GB used, 0 / 2 vcores used
Node: http://mnode01.cluster.local:8044 Rack: /default-rack, RUNNING, 0 containers used, 0.0 / 5.0 GB used, 0 / 2 vcores used
Node: http://mnode04.cluster.local:8044 Rack: /default-rack, RUNNING, 1 containers used, 7.0 / 10.4 GB used, 1 / 2 vcores used
Node: http://mnode02.cluster.local:8044 Rack: /default-rack, RUNNING, 1 containers used, 2.0 / 8.7 GB used, 1 / 2 vcores used
----- Queues -----
Queue name: root.default
Queue state: RUNNING
Current capacity: 0.00
Capacity: 0.00
Maximum capacity: -1.00
Application count: 0
Queue 'root.default' approximate utilization: 0.0 / 0.0 GB used, 0 / 0 vcores used
----------------------------------------------------------------------
WARNING: Job memory request (26.4 GB) exceeds queue available memory capacity (0.0 GB)
WARNING: Job virtual cores request (4) exceeds queue available virtual cores capacity (0)
ERROR: Only 3 out of the requested 4 worker containers were started due to YARN cluster resource limitations
----------------------------------------------------------------------
For YARN users, logs command is 'yarn logs -applicationId application_1523404089784_7404'
and noticing the later outputs
WARNING: Job memory request (26.4 GB) exceeds queue available memory capacity (0.0 GB)
WARNING: Job virtual cores request (4) exceeds queue available virtual cores capacity (0)
ERROR: Only 3 out of the requested 4 worker containers were started due to YARN cluster
I am confused by the reported 0GB mem. and 0 vcores becuase there are no other applications running on the cluster and looking at the cluster details in the YARN RM web UI shows
(using image, since could not find unified place in log files for this info and why the mem. availability is so uneven despite having no other running applications, I do not know). At this point, should mention that don't have much experience tinkering with / examining YARN configs, so it's difficult for me to find relevant information at this point.
Could it be that I am starting h2o cluster with -mapperXmx=6g, but (as shown in the image) one of the nodes only has 5g mem. available, so if this node is randomly selected to contribute to the initialized h2o application, it does not have enough memory to support the requested mapper mem.? Changing the startup command to /bin/hadoop jar /home/me/h2o-3.20.0.5-mapr5.2/h2odriver.jar -nodes 4 -mapperXmx 5g -timeout 300 -output hdfsOutputDir and start/stopping multiple times without error seems to support this theory (though need to check further to determine if I'm interpreting things correctly).
This is most likely because your Hadoop cluster is busy, and there just isn't space to start new yarn containers.
If you ask for N nodes, then you either get all N nodes, or the launch process times out like you are seeing. You can optionally use the -timeout command line flag to increase the timeout.
We are unable to deploy our sample go web program to Bluemix. Server is trying to start and finally crashing without any error. Please let me know if any files needs modification.
View Our Code In GitHub
Build Log:-
Preparing to start the job...
Downloading build artifacts...
Target: https://api.ng.bluemix.net
Using manifest file /home/pipeline/4095d817-6887-4f7e-b317-c58c97c5afd7/manifest.yml
Creating app JoinSplit-20170529103009108 in org Subhadeep / space dev as subhadeep.bose#in.ibm.com...
OK
Creating route joinsplit-20170529103009108-anecdotal-menorah.mybluemix.net...
OK
Binding joinsplit-20170529103009108-anecdotal-menorah.mybluemix.net to JoinSplit-20170529103009108...
OK
Uploading JoinSplit-20170529103009108...
Uploading app files from: /home/pipeline/4095d817-6887-4f7e-b317-c58c97c5afd7
Uploading 165.2K, 34 files
Done uploading
OK
Starting app JoinSplit-20170529103009108 in org Subhadeep / space dev as subhadeep.bose#in.ibm.com...
Creating container
Successfully created container
Downloaded app package (437.8K)
-----> Download go 1.8.3
-----> Checking Godeps/Godeps.json file
-----> Installing godep v79
Download [https://buildpacks.cloudfoundry.org/dependencies/godep/godep-v79-linux-x64-9e37ce0f.tgz]
-----> Installing glide v0.12.3
Download [https://buildpacks.cloudfoundry.org/dependencies/glide/glide-v0.12.3-linux-x64-aa256363.tgz]
-----> Installing go 1.8.3
Download [https://buildpacks.cloudfoundry.org/dependencies/go/go1.8.3.linux-amd64-32ec5ac6.tar.gz]
-----> Running go build finalize
[31;1m**WARNING**[0m vendor/ directory does not exist.
[31;1m**WARNING**[0m Installing package '.' (default)
-----> Running: go install -tags cloudfoundry -buildmode pie .
Exit status 0
Staging complete
Uploading droplet, build artifacts cache...
Uploading build artifacts cache...
Uploading droplet...
Uploaded build artifacts cache (194B)
Uploaded droplet (2.7M)
Uploading complete
Successfully destroyed container
0 of 1 instances running, 1 starting
0 of 1 instances running, 1 starting
0 of 1 instances running, 1 starting
0 of 1 instances running, 1 starting
0 of 1 instances running, 1 starting
0 of 1 instances running, 1 starting
0 of 1 instances running, 1 starting
0 of 1 instances running, 1 starting
0 of 1 instances running, 1 starting
0 of 1 instances running, 1 starting
0 of 1 instances running, 1 starting
0 of 1 instances running, 1 starting
0 of 1 instances running, 1 starting
0 of 1 instances running, 1 starting
0 of 1 instances running, 1 starting
0 of 1 instances running, 1 starting
0 of 1 instances running, 1 starting
0 of 1 instances running, 1 starting
0 of 1 instances running, 1 starting
0 of 1 instances running, 1 starting
0 of 1 instances running, 1 starting
0 of 1 instances running, 1 starting
0 of 1 instances running, 1 starting
0 of 1 instances running, 1 starting
0 of 1 instances running, 1 starting
0 of 1 instances running, 1 starting
0 of 1 instances running, 1 starting
0 of 1 instances running, 1 starting
0 of 1 instances running, 1 crashed
FAILED
Error restarting application: Start unsuccessful
TIP: use 'cf logs JoinSplit-20170529103009108 --recent' for more information
Finished: FAILED
Your code is listening on the hardcoded port "8081", not on the one provided by the Bluemix/Cloud Foundry environment. Try something like the following in your Main function:
err := http.ListenAndServe(":"+os.Getenv("PORT"), nil)
May be this link can help you out there are some Q&A are available on using go with Bluemix
https://developer.ibm.com/answers/questions/13591/about-using-go-with-bluemix.html