The content discusses the transition from a monolithic to a microservices architecture for a growing online retail company. It explains challenges of monolithic systems under increased demand, benefits of microservices such as independent deployment and service autonomy, and suggests a microservices redesign to enhance scalability, fault isolation, and maintainability.
The post discusses the evolution of a data pipeline, highlighting the integration of an API-driven layer for enhanced observability. This new functionality allows authorized users to access real-time operational status without manual checks across AWS services. The approach improves transparency, accountability, and agility while enabling proactive monitoring and automated responses in future enhancements.
This post details the development of a Machine Learning Pipeline for demand forecasting. Utilizing AWS Glue and PySpark, it covers training and evaluating Linear Regression and Random Forest models using an engineered feature dataset. Results show Random Forest slightly outperforms Linear Regression, demonstrating effective model stability and reliability for deployment.
The Feature Engineering stage follows Exploratory Data Analysis, preparing the dataset for machine learning. It generates temporal and statistical features, encodes categorical identifiers, and ensures schema consistency. Implemented in AWS Glue, it enables reproducibility and scalability for model training, enhancing forecasting accuracy by incorporating lag and rolling average features.
The post details enhancements made to a serverless ETL pipeline using AWS Glue and PySpark for retail sales data. Improvements include explicit column type conversions, missing value imputation, normalization of sales data, and integration of logging for observability. These changes aim to create a production-ready, machine-learning-friendly preprocessing layer for effective data analysis.
This project aims to develop a demand forecasting solution for retail using historical sales data from Kaggle. A data pipeline employing AWS Glue and PySpark will preprocess the data by cleaning and splitting it into training and testing sets. The objective is to maximize inventory management and customer satisfaction.
Last weekend, I explored GPU CUDA programming using AWS. Despite initial service quota issues, I successfully launched an EC2 instance equipped with an NVIDIA GPU. After setting up the environment, I compiled and ran a CUDA program, achieving a remarkable speedup of 151 times faster on the GPU compared to the CPU.
The author explores CUDA programming on AWS using an NVIDIA GPU, facing vCPU quota limitations that prevent launching an EC2 instance. After diagnosing the issue, they submitted a request for a quota increase through the Service Quotas console. The experience highlights the importance of checking AWS service limits when setting up GPU instances.
In this blog, we’ll build a simple distributed file service on AWS. The setup will have two file servers — Server 1 and Server 2.…
Continue reading → Setting Up a Simple Distributed File Service on AWS
Aviation data has always been fascinating. Planes crisscross the globe. Each one sends out tiny bursts of information as it soars through the sky. Thanks…
In today's interconnected world, real-time location tracking plays a crucial role in many industries. These include logistics and fleet management. It is also vital to…
Continue reading → Building a Real-Time GPS Data Processing System on AWS: A Step-by-Step Guide
Hadoop is a powerful framework that enables distributed processing of large datasets. It follows the MapReduce paradigm. Computation is broken down into independent map and…
Continue reading → Set Up a Hadoop Cluster on AWS EMR: A Step-by-Step Guide
The "SignatureDoesNotMatch" error often occurs when uploading files to AWS S3 due to signature mismatches related to secret keys. The author shares a step-by-step guide to troubleshoot this issue, which includes verifying IAM user credentials, configuring access keys, and successfully retrying the upload operation after resolving permissions.
Recently I have been involved in doing to some source code compilation on an AWS EC2 instance. However, after the compilation I encountered a problem.…
Continue reading → Step-by-Step Guide: Filezilla Setup for AWS EC2
I am using an AWS EC2 instance for all my development works right now. And I am trying to figure out various ways to log…
Once you have created an AWS account it has to be configured. The first thing you need to setup is the second level security called the MFA. This blog takes you through the step by step process of setting up MFA for your root user account.
A step by step guide for AWS beginners to setup their first AWS account to kick start with AWS cloud technology. It's free!