This post is part of our Cloud Exit series. Over more than a decade we paid AWS about $244K, net of credits. Then we rebuilt on servers we own. Earlier posts cover the full cost story and how we swapped Lambda for cron. This one is about the database, and why moving it was the easy part.
Everything our 97 Lambda functions used to do now runs as a handful of Python scripts on a schedule, on servers we own. The SQS queues are gone and so are the SNS topics. When something breaks, there's one log file to read, not a chain of request IDs across five services. And the bill dropped fro...
Buzzwords worked. It read the news from dozens of sources, pulled out the words everyone was repeating, scored the mood of each channel, and told you what the world was talking about today. It started as one cloud function in August 2016 and grew into a real event-driven platform: 32 Lambda funct...
In 2019 we paid Amazon Web Services an average of about $4,500 a month. Today our infrastructure runs for about $100 a month, on hardware we own.
Our infrastructure now costs about $100 a month to run, on hardware we own. A few years ago, the same company was paying Amazon Web Services an average of about $4,500 a month. In 2025, with most of the move behind us, the cloud bill was still a few hundred dollars a month. Today the cloud is a s...
In the following series, we will explore how to setup a well architected cloud software project in the AWS cloud, from beginner to advanced,
In this article, we will learn about AWS CodeStar - arguably one of the most important aws cloud developer tools that most Cloud DevOps engineers are not even familiar with.We will get started with some example AWS CodeStar code & architecture patterns.We will provide links to examples throughout the article.Let's begin! View Our Ai Explainer Video about this post!!Like, Comment, Subscribe to our YouTube Channel, for more Ai explainer videos!What is AWS CodeStar?Think of CodeStar as a wrapper se
Introducing the new shiny :: * https://buzzwords.newsNew Features:* More Speed!* More Precision!* Visualization! Motivation:* To measure every word mentioned in todays digital media* Based on this, to calculate the positive / negative sentiment at scale* To hold the media accountable* To gain back wasted time reading through infinite feeds of duplicate / recycled news content Goals:* Precision calculation at scale* Perfecting AutoScaling & ServerLess* Maintaining maximum compute cost efficiency*
Today is an exciting day for me....after years of hard work, i have reached a milestone......i have finally reached "The Coupling Point" ™ The Coupling Point, is the point in your application integration, where you can merge 2 different technologies together, for the purpose of creating a better experience for your application users, and for me, most importantly, how to make your application more efficient for the purpose of cost savings on your application architecture to reduce cloud infrastru
Super App:* WixUI* pureJS fe libs with Serverless backend* d8 rest api or json api
These cookies enable core functionality such as security, verification of identity and network management. These cookies can’t be disabled.
These cookies are used to track advertising effectiveness to provide a more relevant service and deliver better ads to suit your interests.
These cookies collect data to remember choices users make to improve and give a more personalised experience.
These cookies help us to understand how visitors interact with our website, discover errors and provide a better overall analytics.
