Windows-Containers
workflows-samples
Windows-Containers | workflows-samples | |
---|---|---|
5 | 14 | |
348 | 67 | |
4.6% | - | |
6.6 | 6.0 | |
6 days ago | 5 days ago | |
PowerShell | Shell | |
MIT License | Apache License 2.0 |
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Windows-Containers
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Kubernetes Reinvented Virtual Machines (in a good sense)
You're trading one convenience for a world of hurt if you use Kubernetes with Windows. Just take a casual glance at the "Windows containers" issues list on GitHub: https://github.com/microsoft/Windows-Containers/issues
Some of the very recently closed issues were jaw-dropping, such as totally broken networking in common scenarios.
DNS resolution is very different in Windows compared to Linux, making much of the "neatness" of Kubernetes pod-to-pod communication not work.
There is no maximum memory limit in Windows kernel "job objects" (equivalent to cgroups), so one memory leak in one pod can kill an entire node or cluster. This is very hard to solve, and I've seen it take out Service Fabric clusters also.
Etc, etc...
- Anyone have any idea or solution with this?
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Unable to start critical Windows Services in Docker Windows Container
There is also a GitHub unresolved closed issue with similar issue: https://github.com/microsoft/Windows-Containers/issues/173
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Docker and Powershell/Cake Windows Compatibility Matrix/Script?
We keep checking for version compatibility with testing internally before releasing it externally. However, if something still breaks, you can expect a communication from Microsoft - most likely here: https://github.com/microsoft/Windows-Containers/issues
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Docker in windows
If you think this is a bug and want the Microsoft team to investigate, please file a an issue here: https://github.com/microsoft/Windows-Containers/issues (Please remember to post the resolution here so other Reddit users can also see that)
workflows-samples
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Event driven architects: how to handle event state through multiple services?
Have you seen this? https://cloud.google.com/workflows
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Job Scheduling on Google Cloud Platform
Cloud Workflows: A serverless workflow orchestration service
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Trigger Cloud Run job execution
Workflows can trigger actions, like Cloud Run Jobs, in a sequence of steps. The Workflows product waits for the job to complete, fail, or time out before it moves on to the next step. It uses polling to check on the job, so there may be a delay between the job finishing and the next step.
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GCP Workflows
Has anyone integrated firestore/realtime database together with GCP workflows? What was your use case? How was your experience with it? Why have you decided to go that way?
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Handy Yaml Tricks!
In the past few years, YAML (http://yaml.org) has become an essential part of software, particularly for infrastructure-as-code tools. Yaml at the heart of kubernetes configuration, kubernetes-inspired APIs like Google's config connector, and a number of workflow systems like Google Cloud Workflows and Github Actions.
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Newbie to Google Cloud, but I was wondering if there was a way to set up a routine to run a code snippet daily?
If your routine is just a bunch of API calls, you can also replace steps 1-2 with Workflows.
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Kubernetes Reinvented Virtual Machines (in a good sense)
I have come at this problem from a bit of a different angle by asking what is the closest I can possibly get to the hypothetical dream state of everything is automated, autoscaling blah blah blah as possible with the absolute smallest budget in terms of not only actual costs but time budget as well.
I only know the GCP ecosystem kind of well so I don't fully know to what extent these things exist in AWS and Azure but there I think there is a really nice path you can get on with the serverless route that skips K8s entirely but keeps you very well aligned in case you ever need to "upgrade" or get out of the GCP ecosystem.
I write very stock standard gRPC services and then put them onto Cloud Run (which has a very Heroku like workflow) and stick https://cloud.google.com/api-gateway in front of things and now my API is running on the exact same setup as any other service Google is running in production. Huge amounts of logic get moved out of my code base as a result.
If you are also willing to write your APIs a fairly particular way https://google.aip.dev/ it starts to become trivial to integrate other things like https://cloud.google.com/workflows, https://cloud.google.com/pubsub and https://cloud.google.com/tasks which is traditionally where a lot of the "state" and weirdly complicated logic previously lived in my code. I'm now not really writing any of that.
Now it's all declarative where I just say what I want to happen and I don't have to think about much else beyond that because it too is using that same internal GCP infrastructure to handle all the complicated parts around what to do when things go wrong.
But to me they are all extremely heavily aligned with the K8s path so the lock in certainly doesn't feel as scary.
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A Brief Comparison of Apache DolphinScheduler With Other Alternatives
Google Workflows combines Google’s cloud services and APIs to help developers build reliable large-scale applications, process automation, and deploy machine learning and data pipelines.
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Associate with parent Cloud Workflows logs and child APIs logs using structured logs
Lately, I build a system using Cloud Workflows which can combine Google Cloud Services such as Cloud Functions and Cloud Run. Sometimes, I was in a situation where I want to examine more efficiently using logs on Cloud Logging when debugging or daily monitoring.
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My GCP feature requests for 2022
Look at Cloud Workflows for simple workflows
What are some alternatives?
nodejs-pubsub - Node.js client for Google Cloud Pub/Sub: Ingest event streams from anywhere, at any scale, for simple, reliable, real-time stream analytics.
incubator-dolphinscheduler - Apache DolphinScheduler is the modern data orchestration platform. Agile to create high performance workflow with low-code
specification - Serverless Workflow Specification
professional-services - Common solutions and tools developed by Google Cloud's Professional Services team. This repository and its contents are not an officially supported Google product.
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows