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Securing Machine Learning Pipelines: Best Practices in Amazon SageMaker
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Securing Machine Learning Pipelines: Best Practices in Amazon SageMaker

John Patrick Laurel2024-01-17T00:45:41+00:00

Introduction In today's digital era, the importance of security in machine learning (ML) pipelines cannot be overstated. As ML systems increasingly become integral to business operations and decision-making, ensuring the integrity and security of these systems is paramount. A breach or a flaw in an ML pipeline can lead to compromised data, erroneous decision-making, and potentially catastrophic consequences for businesses and individuals alike. This section will delve into why securing ML pipelines is crucial, highlighting the potential risks and impacts of security lapses. Short Introduction to Amazon SageMaker Amazon SageMaker is a fully managed service that provides every developer and [...]

Securing Machine Learning Pipelines: Best Practices in Amazon SageMakerJohn Patrick Laurel2024-01-17T00:45:41+00:00

HTTP Flood Attack Notification using AWS Lambda, Amazon EventBridge and CloudWatch Logs Insights
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HTTP Flood Attack Notification using AWS Lambda, Amazon EventBridge and CloudWatch Logs Insights

Neil Rico2024-01-25T05:04:59+00:00

We can almost do everything now on the website. Selling clothes, ordering food, video posting, doing business meetings, online classes, and others, you name it. Running a website is very awesome and at the same time hard, especially when bad actors want to mess with it. One sneaky way is an "HTTP Flood Attack," where your website gets bombarded with too many requests. This can slow down or even break your site. Detecting and responding to such attacks promptly is crucial for maintaining the availability and performance of your applications. In this blog post, we'll explore how to implement a simple [...]

HTTP Flood Attack Notification using AWS Lambda, Amazon EventBridge and CloudWatch Logs InsightsNeil Rico2024-01-25T05:04:59+00:00

Training an Image Classification Model with TensorFlow in Amazon SageMaker
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Training an Image Classification Model with TensorFlow in Amazon SageMaker

John Patrick Laurel2024-01-15T12:39:38+00:00

Introduction In today's digital age, where data is as vital as currency, the power of Machine Learning (ML) in transforming industries is undeniable. From self-driving cars to personalized medicine, ML models are at the heart of many technological breakthroughs. Among the various tools and frameworks available for ML, TensorFlow has emerged as a leader, renowned for its versatility and scalability. This article aims to demystify the process of training an Image Classification model using TensorFlow, specifically within the Amazon SageMaker environment. For beginners and intermediate enthusiasts alike, navigating through TensorFlow's complexities and harnessing the power of SageMaker can seem daunting. [...]

Training an Image Classification Model with TensorFlow in Amazon SageMakerJohn Patrick Laurel2024-01-15T12:39:38+00:00

NEW Product Release: All-in-Access: Courses + PlayCloud Sandbox (AWS) & Play Sandbox (AWS)
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NEW Product Release: All-in-Access: Courses + PlayCloud Sandbox (AWS) & Play Sandbox (AWS)

Nikee Tomas2024-03-26T01:17:06+00:00

Brace yourselves for a journey into the cutting-edge realms of tech and education! We're thrilled to announce not one but two incredible products designed to supercharge your learning experience and bring your skills to new heights! 🚀 Get ready to dive into innovation with our super-focused PlayCloud Sandbox (AWS) and All-in-Access: Courses + PlayCloud Sandbox (AWS). Let's explore why these releases are set to revolutionize your learning journey. PlayCloud Sandbox (AWS) The PlayCloud Sandbox is a secure, isolated AWS environment where you can confidently experiment and run applications at your own pace. With this Playcloud Sandbox product subscription, you get two (2) [...]

NEW Product Release: All-in-Access: Courses + PlayCloud Sandbox (AWS) & Play Sandbox (AWS)Nikee Tomas2024-03-26T01:17:06+00:00

Building a Deployment Pipeline for a React Application with AWS CodePipeline
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Building a Deployment Pipeline for a React Application with AWS CodePipeline

Kaye Alvarado2024-01-07T02:48:10+00:00

This is the second part of a series of blogs about the platform management of a React Application infrastructure by adding a continuous deployment component to the earlier infrastructure. In an earlier article, I wrote about how a private react application infrastructure can be deployed with Terraform code. Now, we will explore this further by building a deployment pipeline using AWS CodePipeline. Let's assume that the source code of the React web application is hosted on GitHub. Using the GitHub connections feature of AWS CodePipeline, we can authorize the third-party provider to work with AWS resources to establish integration between [...]

Building a Deployment Pipeline for a React Application with AWS CodePipelineKaye Alvarado2024-01-07T02:48:10+00:00

Train and Deploy a Scikit-Learn Model in Amazon SageMaker
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Train and Deploy a Scikit-Learn Model in Amazon SageMaker

John Patrick Laurel2024-01-05T10:10:06+00:00

Introduction In the ever-evolving world of machine learning (ML), the ability to efficiently train and deploy models is crucial for turning innovative ideas into real-world applications. This is where Amazon SageMaker, a fully managed service that provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly, stands out. Amazon SageMaker streamlines the machine learning workflow, offering a broad set of capabilities that are designed to enable users to focus more on the problem at hand and less on the underlying infrastructure. While SageMaker comes equipped with built-in algorithms and support for various [...]

Train and Deploy a Scikit-Learn Model in Amazon SageMakerJohn Patrick Laurel2024-01-05T10:10:06+00:00

Securing LLMs with Guardrails for Amazon Bedrock
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Securing LLMs with Guardrails for Amazon Bedrock

Kaye Alvarado2024-01-03T00:32:13+00:00

One of the pillars of the AWS Well-Architected Framework is security. It is a foundational concept when running your workloads in the cloud to think about privacy, access limits, compliance with regulatory requirements, and data protection; and this includes Amazon Bedrock. Along with several AI announcements during the keynote of AWS CEO, Adam Selipsky during AWS re:Invent 2023 was Guardrails for Amazon Bedrock. As AI technology evolves and becomes more mature, it makes sense to also reinvent the way usage is handled by security safeguards. Guardrails for Amazon Bedrock allow security policies to be applied across foundational models, to fulfill [...]

Securing LLMs with Guardrails for Amazon BedrockKaye Alvarado2024-01-03T00:32:13+00:00

Building a Private React Application Infrastructure with Terraform
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Building a Private React Application Infrastructure with Terraform

Kaye Alvarado2024-01-02T03:12:00+00:00

This is the first part of a series of blogs about the platform management of a React Application infrastructure using Terraform. In the early phases of a software development project, it is mandatory to have the application reviewed by security way before the Beta release to ensure that the app adheres to the standards of a secure web application and is able to protect the sensitive data it handles. Most of the time, DevOps Engineers are tasked to deploy the web application in a private domain to allow the initial load testing, penetration testing, and other security-related testing while keeping [...]

Building a Private React Application Infrastructure with TerraformKaye Alvarado2024-01-02T03:12:00+00:00

How to Install and Configure PHP OpCache with Web Viewer on Ubuntu 20.04
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How to Install and Configure PHP OpCache with Web Viewer on Ubuntu 20.04

Nestor Mayagma Jr.2024-01-02T01:18:27+00:00

The performance of your PHP applications can be significantly enhanced by using OpCache, a PHP opcode cache. OpCache reduces the need to recompile your PHP scripts on each request by storing the generated bytecode in memory, resulting in quicker execution rates and lessened server load. Image retrieved from https://www.pinterest.ph/pin/flash-running-poster-custom-posters-design-your-own-wall-art-create-personalized-prints--792281759458556733/ This article will walk you through installing and configuring PHP OpCache with Web Viewer on Ubuntu 20.04. Install OpCache Install the Nginx, PHP, and additional PHP extensions with the following command: sudo -i apt-get install nginx php php-fpm php-cli php-OpCache php-mysql php-zip php-gd php-mbstring php-curl php-xml -y After installing, use [...]

How to Install and Configure PHP OpCache with Web Viewer on Ubuntu 20.04Nestor Mayagma Jr.2024-01-02T01:18:27+00:00

Deploying a Serverless Inference Endpoint with Amazon SageMaker
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Deploying a Serverless Inference Endpoint with Amazon SageMaker

John Patrick Laurel2023-12-27T11:56:32+00:00

Introduction Welcome to our deep dive into the world of serverless machine learning (ML) inference using Amazon SageMaker. In this blog post, we will explore the innovative and efficient approach of deploying ML models without the need for managing servers, a method known as serverless inference. What is Serverless Inference? Serverless inference is a cloud computing execution model where the cloud provider dynamically manages the allocation of machine resources. The key advantage here is that it abstracts the underlying infrastructure, allowing developers and data scientists to focus solely on their application logic. This approach offers several benefits: Cost-Effectiveness: You pay [...]

Deploying a Serverless Inference Endpoint with Amazon SageMakerJohn Patrick Laurel2023-12-27T11:56:32+00:00