article thumbnail

Can we trust Google Cloud Load Balancing?

Xebia

With Cloud getting a more prominent place in the digital world and with that Cloud Service Providers (CSP), it triggered the question on how secure our data with Google Cloud actually is when looking at their Cloud Load Balancing offering. During threat modelling, the SSL Load Balancing offerings often come into the picture.

article thumbnail

Deploy an HTTPS Load Balancer using a Google-managed wildcard SSL certificate on Google Cloud Platform

Xebia

Recently I was wondering if I could deploy a Google-managed wildcard SSL certificate on my Global External HTTPS Load Balancer. In this blog, I will show you step by step how you can deploy a Global HTTPS Load Balancer using a Google-managed wildcard SSL certificate.

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

One Year of Load Balancing

Algolia

From the beginning at Algolia, we decided not to place any load balancing infrastructure between our users and our search API servers. This is the best situation to rely on round-robin DNS for load balancing: a large number of users request the DNS to access Algolia servers, and they perform a few searches.

article thumbnail

Building Resilient Public Networking on AWS: Part 4

Xebia

One of the key differences between the approach in this post and the previous one is that here, the Application Load Balancers (ALBs) are private, so the only element exposed directly to the Internet is the Global Accelerator and its Edge locations. These steps are clearly marked in the following diagram.

AWS 130
article thumbnail

Network topologies – A series: Part 1

Xebia

This triggered the idea to document a number of network topologies, starting with the most simple of the simple, working our way to more complex setups. It’s expected that the reader does have some knowledge about basic cloud concepts, such as VPC and firewall rules, or have the ability to find the documentation for this when needed.

article thumbnail

Use LangChain with PySpark to process documents at massive scale with Amazon SageMaker Studio and Amazon EMR Serverless

AWS Machine Learning - AI

collect() Next, you can visualize the size of each document to understand the volume of data you’re processing. Adjust the layout plt.tight_layout() # Show the plot plt.show() %matplot plt Every PDF document contains multiple pages to process, and this task can be run in parallel using Spark. latest USER root RUN dnf install python3.11

article thumbnail

Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning - AI

Load balancer – Another option is to use a load balancer that exposes an HTTPS endpoint and routes the request to the orchestrator. You can use AWS services such as Application Load Balancer to implement this approach. API Gateway also provides a WebSocket API. This logic sits in a hybrid search component.