• LLM-as-a-judge-amazon-nova-and-claude

    Amazon Bedrock’s LLM-as-a-Judge: Automate AI Evaluation with Nova Lite + Claude

      Evaluating your LLM’s quality should not cost you too much money or even weeks of your time.  You’re probably  stuck in a limbo of choosing between two options that have their own drawbacks: Automated metrics like BLEU, ROUGE and accuracy scores? Sure, they are quite fast and cheap, [...]

  • a-beginners-guide-to-the-machine-learning-pipeline-on-gcp

    A Beginner’s Guide to the Machine Learning Pipeline on GCP

    When people hear the term "machine learning," they often imagine complex math, advanced algorithms, or mysterious "AI magic" happening behind the scenes. In reality, machine learning on the cloud is far more practical and structured than it may sound. At its core, an ML pipeline is a series of [...]

  • Building a Cost-Aware RAG Application with Amazon Bedrock

    What if your Client can have a Chatbot that throws a highly accurate responses based on your documents? Without having a guilt of the monthly expenses. Without even subscribing to any costly,  AI-support subscriptions. Only pay per inquiry requests to your model provider,  and of course only costs you [...]

  • IAM Policy Autopilot Feature Image

    Zero-Sweat: A Comprehensive Guide to IAM Policy Autopilot

    Picture this: your application works perfectly on your local machine. You deploy it to AWS, then immediately hit an “Access Denied” error. If you’ve worked with AWS for any length of time, you’ve experienced this. What follows is usually a frustrating dive into IAM documentation, trial-and-error permission updates, and [...]

  • Claude code visuals

    The Year of the Agent: Anthropic’s Claude AI Models and Agents

      Looking back on the past year of 2025 coding with the help of artificial intelligence, we can safely say that it was the year of agents, especially pioneered by Anthropic with Claude Code. AI products have matured to offer highly reliable agents that can understand, navigate, and work [...]

  • Shifting Left with AI Key AWS Security Launches from reInvent 2025

    AI-Driven Cloud Security at AWS re:Invent 2025

    Cloud computing continues to accelerate at a pace that traditional security models were never designed to support. Development teams now provision infrastructure in minutes, deploy services continuously, and scale applications automatically. However, security processes often lag behind this speed. In many organizations, security still enters the workflow after key [...]

  • Amazon Q in Practice: How AWS’s AI Assistant Actually Works for Businesses and Developers

    Amazon Q is often introduced as AWS's generative AI assistant, but that description doesn't really explain why it exists or how it behaves once you start using it. If you treat Amazon Q like a general chatbot, it can feel restrictive or underwhelming. If you treat it as an [...]

  • AWS Security Agent Context Aware Application Security Featured Image

    AWS Security Agent: Context-Aware Application Security

    The Problem: Security Can't Keep Up In the current engineering landscape of our industry, modern software teams are supposed to be built to be able to move fast. Continuous integration, automated deployments, and agile workflows have seen the rise of weekly and even daily releases to be the norm. [...]

  • Detecting and Redacting PII with Amazon Comprehend

    Automating PII Detection and Redaction with Amazon Comprehend

    Organizations today are entrusted with enormous amounts of sensitive information. Customer support logs, healthcare records, financial transactions, and even training datasets often contain Personally Identifiable Information (PII) such as names, phone numbers, email addresses, or credit card numbers. Protecting this information is not just a matter of compliance with [...]

  • LLM Text Summarizer Extension Tutorial Article

    Build a Model-Agnostic AI Text Summarizer Web Extension

    Browser extensions are a great way to bring AI directly into your everyday workflows. Instead of copying text into external tools and websites to be summarized, you can do it right on the page. In this tutorial, we'll build a lightweight, model-agnostic Chrome extension that summarizes selected text using [...]

  • Calculating-Required-RCU-And-WCU-For-Your-DynamoDB-Table

Calculating the Required Read and Write Capacity Unit for your DynamoDB Table

Read Capacity Unit On-Demand Mode When you choose on-demand mode, DynamoDB instantly accommodates your workloads as they ramp up or down to any previously reached traffic level. If a workload’s traffic level hits a new peak, DynamoDB adapts rapidly to accommodate the workload. The request rate is only limited by the DynamoDB throughput default table limits, but it can be raised upon request. For on-demand mode tables, you don't need to specify how much [...]

  • Lambda-Integration-With-Amazon-DynamoDB-Streams

AWS Lambda Integration with Amazon DynamoDB Streams

Amazon DynamoDB is integrated with AWS Lambda so that you can create triggers, which are pieces of code that automatically respond to events in DynamoDB Streams. With triggers, you can build applications that react to data modifications in DynamoDB tables. After you enable DynamoDB Streams on a table, associate the DynamoDB table with a Lambda function. AWS Lambda polls the stream and invokes your Lambda function synchronously when it detects new stream records.  Configure [...]

  • Kinesis Scaling Resharding And Parallel Processing

Kinesis Scaling, Resharding and Parallel Processing

Kinesis Resharding enables you to increase or decrease the number of shards in a stream in order to adapt to changes in the rate of data flowing through the stream. Resharding is always pairwise. You cannot split into more than two shards in a single operation, and you cannot merge more than two shards in a single operation. The Kinesis Client Library (KCL) tracks the shards in the stream using an Amazon DynamoDB table, [...]

  • DynamoDB Scan vs Query

DynamoDB Scan vs Query

Scan The Scan operation returns one or more items and item attributes by accessing every item in a table or a secondary index. The total number of scanned items has a maximum size limit of 1 MB. Scan operations proceed sequentially; however, for faster performance on a large table or secondary index, applications can request a parallel Scan operation. Scan uses eventually consistent reads when accessing the data in a table; therefore, the result [...]

  • ECS Task Placement Strategies

ECS Task Placement Strategies

A task placement strategy is an algorithm for selecting instances for task placement or tasks for termination. When a task that uses the EC2 launch type is launched, Amazon ECS must determine where to place the task based on the requirements specified in the task definition, such as CPU and memory. Similarly, when you scale down the task count, Amazon ECS must determine which tasks to terminate.  A task placement constraint is a rule [...]

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