Google Kubernetes Engine Reviews

Google Cloud Functions Reviews

Google Kubernetes Engine mentions (45)

• 26 Top Kubernetes Tools

  Google Kubernetes Engine (GKE) is another managed Kubernetes service that lets you spin up new cloud clusters on demand. It's specifically designed to help you run Kubernetes workloads without specialist Kubernetes expertise, and it includes a range of optional features that provide more automation for admin tasks. These include powerful capabilities around governance, compliance, security, and configuration... - Source: dev.to / 17 days ago

• Kubernetes: Hello World

  Cloud Clusters: If you'd rather work in a cloud environment, consider platforms like Google Kubernetes Engine (GKE) or Amazon EKS for managed Kubernetes clusters. - Source: dev.to / 20 days ago

• Using Cloud Monitoring to Monitor IRIS-Based Applications Deployed in GKE

  In this article, we’ll look at one of the ways to monitor the InterSystems IRIS data platform (IRIS) deployed in the Google Kubernetes Engine (GKE). The GKE integrates easily with Cloud Monitoring, simplifying our task. As a bonus, the article shows how to display metrics from Cloud Monitoring in Grafana. - Source: dev.to / about 1 month ago

• Using NetBird for Kubernetes Access

  Set up a remote Kubernetes cluster. For this tutorial, Google Kubernetes Engine (GKE) was chosen; however, feel free to use any remote Kubernetes cluster. - Source: dev.to / 2 months ago

• The 2024 Web Hosting Report

  Docker swarm still exists, it still works, and some of these other container orchestrators are still hanging on, but for the most part, you’re using Kubernetes if you’re doing this stuff at work. Generally it's well-understood that kubernetes is hard to get right, and so most people use it via a managed provider like Elastic Kubernetes Service from AWS, Azure Kubernetes Service from MSFT, or Google Kubernetes... - Source: dev.to / 4 months 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 2 months 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