Real-Time Server Monitoring with Grafana, Prometheus, and AWS: A Step-by-Step Guide
 
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In modern DevOps, monitoring infrastructure health and performance is crucial. Real-time observability helps teams stay proactive, identify issues early, and ensure optimal performance. This podcast will walk you through setting up real-time server monitoring using Grafana and Prometheus on AWS — a powerful stack that provides customizable, high-performance visualization and alerting.

Building Intelligent Applications with Amazon Bedrock: A Capstone Project
 
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As artificial intelligence reshapes the digital world, developers and enterprises rapidly adopt tools that streamline intelligent application development. Amazon Bedrock stands out as a powerful service that enables developers to build and scale generative AI applications using foundational models (FMs) from leading AI providers without managing infrastructure. This podcast presents a comprehensive capstone project demonstrating how to build a real-world intelligent application using Amazon Bedrock.

Build, Customize, and Scale AI Apps Effortlessly with Amazon Bedrock
 
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Artificial intelligence (AI) has moved from experimentation to execution. Developers and businesses seek faster ways to build, customize, and deploy AI applications without managing infrastructure. Enter Amazon Bedrock—a fully managed service from AWS that enables you to construct generative AI apps quickly using foundation models (FMs) from top providers via a simple API, all without the complexity of setting up servers.

Unlock Cloud Automation: Terraform for Beginners Explained with Examples
 
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In the ever-evolving world of cloud computing, automation is not a luxury—it's a necessity. Terraform, an open-source Infrastructure as Code (IaC) tool by HashiCorp, has emerged as a leader in automating cloud infrastructure setup. This podcast will walk you through the fundamentals of Terraform and provide easy-to-follow examples to kickstart your cloud automation journey.

Managing AWS EC2 Instances with Python Boto3
 
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Amazon EC2 (Elastic Compute Cloud) provides scalable computing capacity in the AWS Cloud. With Python's Boto3 library, you can automate EC2 operations efficiently—launching, managing, and terminating instances with just a few lines of code. This podcast walks through essential EC2 management tasks using Boto3.

How to Configure AWS CLI and CDK CLI Credentials for Secure Cloud Access
 
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In today’s cloud-native development landscape, secure credential management is critical. Whether you're using the AWS Command Line Interface (CLI) or the AWS Cloud Development Kit (CDK), proper configuration ensures both security and efficiency in your workflows.
This podcast walks you through securely configuring credentials for both AWS CLI and CDK CLI, helping you manage cloud resources safely and effectively.

Integrating AWS Lambda with SQS: A Blueprint for Scalable Web Service Design
 
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Scalability, fault tolerance, and decoupled architectures are the cornerstones of robust design in cloud-native applications. AWS Lambda and Amazon Simple Queue Service (SQS) form a powerful duo that enables developers to build scalable, event-driven web services without managing infrastructure. This podcast outlines the architecture, use cases, setup, and optimization strategies for integrating Lambda with SQS.

AWS Lambda Data Masking Made Easy with Powertools for Python
 
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As businesses move towards serverless architectures to gain scalability, flexibility, and cost-efficiency, data privacy becomes an essential concern—especially in regulated industries. AWS Lambda, combined with AWS Powertools for Python, offers an elegant solution to implement data masking at the function level. This podcast walks you through how to simplify and scale data masking for sensitive information using Powertools utilities.

Beyond Big Data: The Rise of Universal Analytics for Small Data Sets
 
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For years, the analytics world has been enamored with Big Data — massive volumes of information harvested from web traffic, IoT devices, social media platforms, and more. But a quiet revolution is underway. Universal analytics tools — traditionally designed for big data processing — are now being adapted and optimized for small data sets, enabling small businesses, researchers, and lean startups to make informed decisions without the infrastructure of a data giant.

Testing Amazon Bedrock with Python: A Guide to Unit Testing GenAI Applications
 
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As generative AI (GenAI) applications become central to modern software stacks, ensuring their reliability through robust unit testing is more important than ever. Amazon Bedrock, AWS's managed service for foundation models (FMs) from providers like Anthropic, AI21, Cohere, Meta, and Stability AI, allows developers to build scalable GenAI applications without managing infrastructure. However, testing these applications presents unique challenges — such as handling non-deterministic outputs and API dependencies.
In this podcast, we’ll walk you through strategies and practical examples for unit testing GenAI-powered applications built with Amazon Bedrock and Python.