Remove Azure Remove Load Balancer Remove Serverless Remove Testing
article thumbnail

AWS vs. Azure vs. Google Cloud: Comparing Cloud Platforms

Kaseya

In addition, you can also take advantage of the reliability of multiple cloud data centers as well as responsive and customizable load balancing that evolves with your changing demands. In this blog, we’ll compare the three leading public cloud providers, namely Amazon Web Services (AWS), Microsoft Azure and Google Cloud.

article thumbnail

Building Resilient Public Networking on AWS: Part 2

Xebia

Fargate Cluster: Establishes the Elastic Container Service (ECS) in AWS, providing a scalable and serverless container execution environment. Public Application Load Balancer (ALB): Establishes an ALB, integrating the previous SSL/TLS certificate for enhanced security. The ALB serves as the entry point for our web container.

AWS 147
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Deploy a serverless workload on Kubernetes using Knative and ArgoCD

CircleCI

Creating a pipeline to continuously deploy your serverless workload on a Kubernetes cluster. The serverless approach to computing can be an effective way to solve this problem. Serverless allows running event-driven functions by abstracting the underlying infrastructure. Microsoft Azure account. Prerequisites.

article thumbnail

Hack day experiments with the cloud and orchestration of serverless functions

Bernd Rucker

The latter might need computing power for the PDF creation, so a scalable serverless function might make sense here. The plan was quickly drawn in my sketch book: And we prepared logins for some of the well known cloud providers: AWS, Microsoft Azure, Google Cloud, IBM Bluemix, Pivotal, Heroku and OpenShift.

article thumbnail

Cloudera DataFlow Designer: The Key to Agile Data Pipeline Development

Cloudera

Allows them to iteratively develop processing logic and test with as little overhead as possible. With the general availability of DataFlow Designer, developers can now implement their data pipelines by building, testing, deploying, and monitoring data flows in one unified user interface that meets all their requirements.

Agile 82
article thumbnail

The Good and the Bad of Kubernetes Container Orchestration

Altexsoft

For testing purposes, a cluster may have a single node but on average it uses five nodes with 16 to 32 GB of memory each in the public clouds and nine nodes with 32 to 64 GB when deployed on-premises Components of a Kubernetes cluster. Kubernetes Certified Application Developer (KSAD) with Tests on Udemy.

article thumbnail

Understanding API Gateway: When You Need It and How to Implement

Altexsoft

A tool called load balancer (which in old days was a separate hardware device) would then route all the traffic it got between different instances of an application and return the response to the client. Load balancing. For serverless development. API gateways are becoming a go-to way for serverless computing.