No Google Cloud Load Balancing videos yet. You could help us improve this page by suggesting one.
Based on our record, Google Cloud Functions should be more popular than Google Cloud Load Balancing. It has been mentiond 41 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
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 / 5 months ago
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: 7 months ago
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 / 9 months ago
Lambda is made for your use case :). It doesn’t have to be AWS there are plenty of other serverless computing services like: - Google cloud functions - Azure functions Etc. Source: 11 months ago
Once you have some basic familiarity with programming, try deploying one of your Python programs to the cloud. Start with Cloud Functions, because that doesn't require any knowledge of Linux server administration. Source: 11 months ago
Unfortunately, the API we created is not suitable for anything but the most basic prototyping. For a real API, we will likely want to use our own domain. This appears to be quite complicated in GCP. We will need a Load Balancer, a serverless NEG and an API Gateway among some other components. See Getting started with HTTP(S) Load Balancing for API Gateway and HTTP(S) Load Balancing for API Gateway. - Source: dev.to / about 1 year ago
Set up a Load Balancer and Cloud Armor in front of your function, or. Source: over 1 year ago
In this article, I’ll show you how to configure a global cloud load balancer that serves as both a proxy and a load balancer. This type of load balancer comes with a single IP address that can be accessed from any location on earth and can route a request to the nearest (active!) application instance. - Source: dev.to / over 1 year ago
Cloud Load Balancing for distribution. - Source: dev.to / almost 2 years ago
While the precise features of the application are immaterial, the architecture is of primary importance. A lot of tools (and buzzwords) come to mind when trying to architect a modern web application. Assets can be served from a CDN to improve page load speed. A global load balancer can front all traffic, sending requests to the nearest server. Serverless functions and edge functions can be used to handle requests,... - Source: dev.to / almost 2 years ago
Google App Engine - A powerful platform to build web and mobile apps that scale automatically.
nginx - A high performance free open source web server powering busiest sites on the Internet.
Salesforce Platform - Salesforce Platform is a comprehensive PaaS solution that paves the way for the developers to test, build, and mitigate the issues in the cloud application before the final deployment.
AWS Elastic Load Balancing - Amazon ELB automatically distributes incoming application traffic across multiple Amazon EC2 instances in the cloud.
Dokku - Docker powered mini-Heroku in around 100 lines of Bash
Azure Traffic Manager - Microsoft Azure Traffic Manager allows you to control the distribution of user traffic for service endpoints in different datacenters.