we have a Google cloudbuild pipeline that does the following:
Create a temp function
Run some tests
Deploy the production function
However, the second step often fails due to the first container not being ready yet:
Step #3: Unexpected token '<' at 2:1
Step #3: <html><head>
Step #3: site unreachable
looks like it is returning some placeholder html from nginx.
How can we fix that?
Currently, we just put an ugly sleep between steps
You probably want to have a look to the Cloud Functions API, there you can find the operations endpoint that will tell you if the operation is finished or not (assuming v1, otherwise look below): https://cloud.google.com/functions/docs/reference/rest/v1/operations/get
The operation is the same Id that is returned in the creation operation. Also you can list them with the list endpoint (in the same doc).
Related
I have the following lines of python code
import os
def hello_world():
r=os.system("curl ipinfo.io/ip")
print (r)
hello_world()
Shows the desired output when executed from command line in Google Cloud Shell but seems there is a 0 at the end of IP Address output
$ python3 main2.py
34.X.X.2490
When I deployed the same code in Google CLoud function it is showing OK as output
I have to replace the first line of code in GCF as follows to make it deploy.
def hello_world(self):
Any suggestion so that GCF displays the desired output which is the output of curl command?
Your function won't work for 2 reasons:
Firstly, you don't respect the HTTP Cloud Function Python function signature:
def hello_world(request):
....
Secondly, you can't use system call. In fact not exactly, you can perform system call, but, because you don't know which package/binaries are installed, you can't rely on this. It's serverless, you don't manage the underlying infrastructure and runtime environment.
Here you made the assumption that CURL is installed on the runtime image. Maybe yes, maybe not, maybe it was, maybe it will be remove in future!! You can't rely on that!!
If you want to manage you runtime environment, you can use Cloud Run. You will manage your runtime environment, and you can install what you want on it and then you are sure of what you can do.
Last remarks:
note: instead of performing a CURL, you can perform a http get request to the same URL to get the IP
Why do you want to know the outgoing IP? It's serverless, you also don't manage the network. You will reach the internet through a Google IPs. It can change everytime, and other cloud functions (or cloud run), from your projects or project from others (like me), are able to use the same IPs. It's Google IPs, not yours! If it's your requirement, let me know, there are solutions for that!
In using realbrowserlocusts class it appears that I'm limited in any exception handling.
The only reference that partially works is: self.client.wait.until(EC.visibility_of_element_located ....
In a failed condition where the element is not found the script simply starts over again. With the script I'm working with I need to maintain a solid session state; I need to throw and exception(report an error), log the user out and then let the script start over again. I've been testing out the behavior with the locust.py script that Nick B. created with several approaches to "try, except" and they work running without realbrowserlocusts (selenium only) but with it the execution just stops.
Any examples would be greatly appreciated.
In its current format I've been able to run 3x the amount of a browser-based load per/agent/slave than our commercial tool. My goal is to replace it with a locust/selenium approach.
locust-plugins's WebdriverUser has a little bit better exception handling I think. A failure to find an element will log a failed request and if you use RescheduleTaskOnFail (as in the the example) it will restart the task when that happens.
https://github.com/SvenskaSpel/locust-plugins/blob/master/examples/webdriver_ex.py
I am doing a lookup operation Couchbase Java SDK 3.0.9 which looks like this:
// Set up
bucket = cluster.bucket("my_bucket")
collection = bucket.defaultCollection()
// Look up operation
val specs = listOf(LookupInSpecStandard.get("hash"))
collection.lookupIn(id, specs)
The error I get is BUCKET_NOT_AVAILABLE. Here are is the full message:
com.couchbase.client.core.error.UnambiguousTimeoutException: SubdocGetRequest, Reason: TIMEOUT {"cancelled":true,"completed":true,"coreId":"0xdb7f8e4800000003","idempotent":true,"reason":"TIMEOUT","requestId":608806,"requestType":"SubdocGetRequest","retried":39,"retryReasons":["BUCKET_NOT_AVAILABLE"],"service":{"bucket":"export","collection":"_default","documentId":"export:main","opaque":"0xcfefb","scope":"_default","type":"kv"},"timeoutMs":15000,"timings":{"totalMicros":15008977}}
The strange part is that this code hasn't been touched for months and the lookup broke out of a sudden. The CB cluster is working fine. Its version is
Enterprise Edition 6.5.1 build 6299.
Do you have any ideas what might have gone wrong?
Note that in Couchbase Java SDK 3.x, the Cluster::bucket method returns instantly, and continues opening a bucket in the background. So the first operation you perform - a lookupIn here - needs to wait for that resource opening to complete before it can proceed. It looks like it took a little longer to access the Couchbase bucket than usual and you got a timeout.
I recommend using the Bucket::waitUntilReady method after opening a bucket, to block until the resource opening is complete:
bucket = cluster.bucket("my_bucket")
bucket.waitUntilReady(Duration.ofMinutes(1));
This problem can occur because of firewall. You need to allow these ports.
Client-to-node
Unencrypted: 8091-8097, 9140 [3], 11210
Encrypted: 11207, 18091-18095, 18096, 18097
You can check more from below
https://docs.couchbase.com/server/current/install/install-ports.html#_footnotedef_2
In developing in Fi-Cloud's CEP I've been having an issue that has been happening repeatedly. As I'm trying to develop a definition to perform a task, CEP's server and Authoring Tool stop responding, although ssh is still responsive.
This issue happens as I develop. I'm using the AuthoringTool to alter the definition bit by bit and then I re-upload it to the server through the authoring tool's export feature.
To reinitiate the proton with the new definition each time I alter it, I use Google's Postman with this single operation:
-PUT (url:http://{ip}:8080/ProtonOnWebServerAdmin/resources/instances/ProtonOnWebServer)
header: 'Content-Type' : 'application/json'; body : {"action": "ChangeDefinitions","definitions-url" : "/ProtonOnWebServerAdmin/resources/definitions/Definition_Name"}
At the same time, I'm logged in with three ssh intances, one to monitor the files being created on /opt/tomcat10/sample/ and other things, and the other two to 'tail -f ' log files the definition writes to, as events are processed: one log for events recieved and another log for events detected by the EPAgent.
I'm iterating through these procedures over and over as I'm developing and eventualy CEP server and the Authoring Tool stop responding.
By "tailing" tomcat's log file (# tail -f /opt/tomcat10/logs/catalina.out) I can see that, when under these circumstances, if I attemp a:
-GET (url: http://{ip}:8080/ProtonOnWebServerAdmin/resources/instances/ProtonOnWebServer)
I get no response back and tomcat logs the following response:
11452100 [http-bio-8080-exec-167] ERROR org.apache.wink.server.internal.RequestProcessor - An unhandled exception occurred which will be propagated to the container.
java.lang.OutOfMemoryError: PermGen space
Exception in thread "http-bio-8080-exec-167" java.lang.OutOfMemoryError: PermGen space
Ssh is still responsive and I can look at tomcat's log this way.
To get over this and continue, I exit ssh connections and restart CEP's instance in the Fi-Cloud.
Is the procedure I'm using to re-upload and re-run the definition inapropriate? Should I take a different approach to developing?
When you update a definition that the CEP is already working with, and you want the CEP engine to work with the updated definition, you need to:
Export the definition using the authoring tool export (as you did)
Stop the engine run, using REST PUT
PUT //host:8080/ProtonOnWebServerAdmin/resources/instances/ProtonOnWebServer
{"action":"ChangeState","state":"stop"}
Start the engine, using REST PUT
PUT //host:8080/ProtonOnWebServerAdmin/resources/instances/ProtonOnWebServer
{"action":"ChangeState","state":"start"}
You don't need to activate the "ChangeDefinitions" action, since it is the same definition name that the engine is already working with.
Activating "ChangeDefinitions" action, only influences the next run of the CEP, and has no influence on the current run.
This answer your question about how you should update a CEP definition.
Hope it will solve your issue.
I have written a script to update my db table after reading data from db tables and solr. I am using asyn.waterfall module. The problem is that the script is not getting exited after successful completion of all operations. I have used db connection pool also thinking that may be creating the script to wait infinitly.
I want to put this script in crontab and if it will not exit properly it would be creating a hell lot of instances unnecessarily.
I just went through this issue.
The problem with just using process.exit() is that the program I am working on was creating handles, but never destroying them.
It was processing a directory and putting data into orientdb.
so some of the things that I have come to learn is that database connections need to be closed before getting rid of the reference. And that process.exit() does not solve all cases.
When my project processed 2,000 files. It would get down to about 500 left, and the extra handles would have filled up the available working memory. Which means it would not be able to continue. Therefore never reaching the process.exit at the end.
On the other hand, if you close the items that are requesting the app to stay open, you can solve the problem at its source.
The two "Undocumented Functions" that I was able to use, were
process._getActiveHandles();
process._getActiveRequests();
I am not sure what other functions will help with debugging these types of issues, but these ones were amazing.
They return an array, and you can determine a lot about what is going on in your process by using these methods.
You have to tell it when you're done, by calling
process.exit();
More specifically, you'll want to call this in the callback from async.waterfall() (the second argument to that function). At that point, all your asynchronous code has executed, and your script should be ready to exit.
EDIT: As pointed out by #Aaron below, this likely has to do with something like a database connection being active, and not allowing the node process to end.
You can use the node module why-is-node-running:
Run npm install -D why-is-node-running
Add import * as log from 'why-is-node-running'; in your code
When you expect your program to exit, add a log statement:
afterAll(async () => {
await app.close();
log();
})
This will print a list of open handles with a stacktrace to find out where they originated:
There are 5 handle(s) keeping the process running
# Timeout
/home/maf/dev/node_modules/why-is-node-running/example.js:6 - setInterval(function () {}, 1000)
/home/maf/dev/node_modules/why-is-node-running/example.js:10 - createServer()
# TCPSERVERWRAP
/home/maf/dev/node_modules/why-is-node-running/example.js:7 - server.listen(0)
/home/maf/dev/node_modules/why-is-node-running/example.js:10 - createServer()
We can quit the execution by using:
connection.destroy();
If you use Visual Studio code, you can attach to an already running Node script directly from it.
First, run the Debug: Attached to Node Process command:
When you invoke the command, VS Code will prompt you which Node.js process to attach to:
Your terminal should display this message:
Debugger listening on ws://127.0.0.1:9229/<...>
For help, see: https://nodejs.org/en/docs/inspector
Debugger attached.
Then, inside your debug console, you can use the code from The Lazy Coder’s answer:
process._getActiveHandles();
process._getActiveRequests();