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I am attempting to create an EC2 instance and get the following error message. How do I decode it ? Launch Failed You are not authorized to perform this operation. Encoded authorization failure message: KDmmJmkLKmQhatEqYt...MN3iUtfAa
I'm aware of NAT table. I just want to know what happens if two clients in a private local area network want to download exactly the same resource on the same port? In other words , When a packet comes from the server, how can the router decide which client is supposed to get this packet? If I'm not wrong, the incoming packet from the server has destination
I know the purpose of other Kubernetes default namespaces such as: kube-system , default & kube-public , but there is no official document about the kube-node-lease . The only official explanation I've found is: Heartbeats, sent by Kubernetes nodes, help determine the availability of a node. There are two forms of heartbeats: updates of NodeStatus and th
I am running a jenkins pipeline with the following command: kubectl exec -it kafkacat-5f8fcfcc57-2txhc -- kafkacat -b cord-kafka -C -t BBSim-OLT-0-Events -o s@1585031458 which is running fine on the terminal of the machine the pipeline is running on, but on the actual pipeline I get the following error: "Unable to use a TTY - input is not a terminal or the r
When hosting an Azure Function in an App Service Plan, are there any significant differences compared with using an App Service (EDIT: for a restful API) associated with the same App Service Plan? I assume the only difference is that the Function offers additional out of the box triggers. Any differences I'm missing that would lead to preferring one over the
After upgrading to Django 4.0, I get the following error when running python manage.py runserver ... File "/path/to/myproject/myproject/urls.py", line 16, in <module> from django.conf.urls import url ImportError: cannot import name 'url' from 'django.conf.urls' (/path/to/my/venv/lib/python3.9/site-packages/django/conf/urls/__init__.py) My urls.py is as
The same project needs to behave consistently on developer machines, in CI and after deployment. Which versions, dependencies and configuration should be recorded?
A performance change should improve the measured workload without sacrificing correctness or wasting capacity. Which measurements and bottlenecks should be considered first?
I am running a Flask application and hosting it on Kubernetes from a Docker container. Gunicorn is managing workers that reply to API requests. The following warning message is a regular occurrence, and it seems like requests are being canceled for some reason. On Kubernetes, the pod is showing no odd behavior or restarts and stays within 80% of its memory a
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