Azure Cache for Redis provides an in-memory data store based on the open-source software Redis.

As a part of the industry-wide push toward the exclusive use of Transport Layer Security (TLS) version 1.2 or later, Azure Cache for Redis will not support TLS versions 1.0 and 1.1 i.e. your application will be required to use TLS 1.2 or later to communicate with your cache

To read the details, please refer to this page from the product documentation

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In Kafka Connect on Kubernetes, the easy way!, I had demonstrated Kafka Connect on Kubernetes using Strimzi along with the File source and sink connector. This blog will showcase how to build a simple data pipeline with MongoDB and Kafka with the MongoDB Kafka connectors which will be deployed on Kubernetes with Strimzi.

I will be using the following Azure services:

Please note that there are no hard dependencies on these components and the solution should work with alternatives as well

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Hello, folks! Delighted to announce that I recently joined the Cloud Developer Advocacy team at Microsoft 😃 😃

I was fortunate to have worked on developer platforms (PaaS and Serverless) during my stint as a Product Manager at Oracle with a focus on developer experience and advocacy — so I decided to convert this into a full-time role and glad to have joined a company which lays a huge emphasis on developer outreach.

Very often, there is a need to expose Kubernetes apps running in minikube to the public internet. This post just provides a manual, yet quick and dirty hack for this using ngrok (it’s probably been done before, but here it goes anyway)

We’ll use a simple nginx app to test things out i.e. we’ll expose an nginx server (running as a single replica Kubernetes Deployment) as a publicly accessible URL.

Test app (nginx)

Start by creating the nginx Deployment

This talk covers a bunch of common Serverless use cases like Backend APIs, Real-Time systems, Integration and Automation (uses Fn and Oracle Functions as the serverless platform).

The GitHub repo for the talk contains the ppt and links to other demos (source code etc.) - https://github.com/abhirockzz/oraclecode2019

Cheers!

Image classification is a canonical example used to demonstrate machine learning techniques. This post shows you how to run a TensorFlow-based image classification application on the recently announced cloud service Oracle Functions.

Photo by Franck V. on Unsplash

Oracle Functions

Oracle Functions which is a fully managed, highly scalable, on-demand, function-as-a-service platform built on enterprise-grade Oracle Cloud Infrastructure. It’s a serverless offering that enables you to focus on writing code to meet business needs without worrying about the underlying infrastructure, and get billed only for the resources consumed during the execution. You can deploy your code and call it directly or in response to triggers — Oracle Functions does all the work required to ensure that your application is highly available, scalable, secure, and monitored.