Artifactory Reviews

Google Cloud Functions Reviews

Artifactory mentions (20)

• Where to store executables shared by a team/project

  I kind of hate it, but Artifactory seems popular at companies: https://jfrog.com/artifactory/. Source: 12 months ago

• Adding Virtual Environments to Git Repo

  When not providing all dependencies yourself, you might suffer from people deleting the packages you depend on (IMHO a very rare scenario). If it is really that critical (hint: usually it isn't), create a local mirror of Pypi (full or only the packages you need). Devpi, Artifactory, etc. Can do that or you just dump the necessary files into Cloud storage, so you have a backup. Source: about 1 year ago

• Authenticated Docker Hub image pulls in Kubernetes

  Operate a pull-through cache registry, like Artifactory or the open source reference Docker registry. This will allow you to pull images from Docker Hub less frequently, improving your chances of staying under the anonymous usage limit. - Source: dev.to / about 1 year ago

• Concretely, how do you trust the experts? That is, how do you a) identify experts relevant to something and b) determine if they have a consensus (and if so, what it is) on a given topic?

  Like suppose for a second that . . . Idk . . . a product team wants our ci workflows to start using Artifactory. Okay great, I don't know Artifactory integration but I'm going to tell them "Sure, I'll get right on that.". Source: over 1 year ago

• What do I do with large "asset" files?

  If these "assets" have an independent release schedule I would treat them separately (especially if they are externally provided). If they are not built from source then treat them as artefacts, they don't belong in git. You can store the in an artefact repository (like Artifactory of Nexus) or (as u/nekokattt points out) in something like S3. Source: over 1 year ago

Google Cloud Functions mentions (43)

• Is Serverless Architecture Right For You?

  The first reason is that serverless architectures are inherently scalable and elastic. They automatically scale up or down based on the incoming workload without requiring manual intervention through serverless compute services like AWS Lambda, Azure Functions, or Google Cloud Functions. - Source: dev.to / about 1 month ago

• A Brief History Of Serverless

  The FaaS platform gained a lot of popularity which resulted in many competitors. There was OSS providers like OpenFaaS or Fission. There were of course the commercial versions to like Azure Functions and Google Cloud Functions. - Source: dev.to / about 1 month ago

• Increasing Your Cloud Function Development Velocity Using Dynamically Loading Python Classes

  One of the issues developers can encounter when developing in Cloud Functions is the time taken to deploy changes. You can help reduce this time by dynamically loading some of your Python classes. This allows you to make iterative changes to just the area of your application that you’re working on. - Source: dev.to / 7 months ago

• Need some advice on API key storage

  I've been looking at Google Secret Manager which sounds promising but I've not been able to find any examples or tutorials that help with the actual practical details of best practice or getting this working. I'm currently reading about Cloud Functions which also sound promising but again, I'm just going deeper and deeper into GCP without feeling like I'm gaining any useful insights. Source: 8 months ago

• Golden Ticket To Explore Google Cloud

  Serverless computing was also introduced, where the developers focus on their code instead of server configuration.Google offers serverless technologies that include Cloud Functions and Cloud Run.Cloud Functions manages event-driven code and offers a pay-as-you-go service, while Cloud Run allows clients to deploy their containerized microservice applications in a managed environment. - Source: dev.to / 11 months ago