A small percentage of the kids were ahead in their thought process, and understanding of building things. One of them even had a registered company and plans to get revenues of crores in the next few years. Some had built drones, the likes of which you see in at engineering level. The majority though were still working on school level projects.

Deleting S3 buckets can be a painful multistep process. Buckets need to be emptied out before they can be removed with several captchas in place to avoid accidental deletes. aws-cli can be used to do this quickly.

aws s3 ls | awk '{print $3}' | xargs -n1 -I{} aws s3 rb s3://{} --force

Introduction

I’ve been working with large NGOs to architect their multi-faceted systems. These systems are responsible for information dissemination, data collection, analysis, and sources & sinks to other systems. Our near term goal was to build an information platform (IP). The MDP was narrowed down to the following feature set.

Target persona

The IP was intended for 3 main personas.

• Villagers
  • Direct consumers
  • Low tech capability
  • Language barriers
  • Varied devices - sizes and capabilities
  • Irregular bandwidth
• Ops team
  • Responsible for training using the content
  • Submitting feedback for content from users
  • Updates to content (limited)
• Content team
  • Primarily responsible for content
  • Regular content updates

Requirements

Media support

The portal has to support different media types which includes but not limited to; video, digital books, images, audio (podcast). The content is generated by a marketing and education team which is then uploaded to a public repository for downloads. All content is in the public domain.

Introduction

I recently passed my AWS Solutions Architect Professional Certification on the first attempt. I wanted to share my experience of preparing for the exam as well as the actual exam day tips and tricks I learnt. I’ll also talk about what to expect and approaches to navigate the challenges.

Getting an AWS certification is important for your cloud ecosystem career. Any role including DevOps, Data Engineer, Software Engineer, Architect would immensely benefit from this certification. This certificate demonstrates your ability to analyze and evaluate architectures.

During the start of a product, the database is quite small, mostly empty or populated with dummy data. Developers prefer having a local database instance running their favorite database like PostgreSQL or MySQL. This frees them from dependencies, and has the added advantage of having near zero latency.

As the product grows, inevitably the database also increases in size. In some cases, replicating production issues also requires that the code be run on a copy of the production database. Which eventually leads to often databases for development environments being created by copying a database dump from production and then importing that database dump. And since database dumps are text, they can be highly compressed, which can result in a relatively small file to copy over. But the import of the dump can still take lots of time and cause high load on the dev computer as it rebuilds tables and indexes. As long as your data is relatively small, this process may be perfectly acceptable.

Github is a great place to contribute and create amazing projects. As the project scales, so does the team and the issues from users. Most are clear, concise and contructive to the project. Developers leave comments and answer these questions. For a large team, maintaining a positive sentiment around the project needs to be tracked. The goal of this project was to provide a fast way to keep a signboard about the overall project sentiment.

I’ve had a Raspberry Pi 4B sitting in my cabinet for a few months now. I dusted it off and realized that the SD card was busted. Got a replacement 64GB U3 A2 card and got it up and running with Ubuntu server. The primary intended use was to run docker with DB containers that I use for my side projects such as Postgres/MySQL/MongoDB.

My current home network consists of several routers for WiFi reachability. I try to ensure 5Ghz coverage to all my devices. Due to the concrete walls a single router does not suffice, hence a home made mesh.

Design systems give your budding project a jump start and more importantly a structure when the project continues to grow. These systems bring in a level of sophistication of thinking and uniformity. Their value lies beyond pre-made CSS/JS assets. Identifying the right design system in the initial phases is crucial for progress. I employ various metrics to pick one such as:

• Community support & acceptance
• Documentation
• a11y/i18n/l10n
• Component library
• Commit rate
• Backers

However when it is time to play aka. a throwaway project for ML/AI or Raspberry Pi, you should experiment with the budding ones. Below are 5 of my current experimental design systems; known and unknown. They may not check all the boxes above however have potential and are super fun. They are not Bootstrap, Ant Design, or Material.

Introduction

Moving to or starting with AWS (or any cloud provider) comes with an implicit assumption that your business will pay what it uses. Although technically true, most businesses ignore the human aspect. More often than not, developers will make assumptions while allocating resources and end up with:

• Overprovisioned resources
• Unused resources

In this article, based on our experiences and AWS events/whitepapers¹, we will outline a few approaches to combat the ramifications of these decisions at any stage of product growth. The earlier we recognize how to manage them constantly, the more cost savings we can achieve.

General progression is from a monolith to handful of homogenous microservices. As the product gets diverse and team size grows, these microservices become heterogeneous. They can use different languages, servers, API end points, etc.