I like AWS and work with its resources daily. Containerized applications are very popular these days. In AWS, you can use Lambda to run containers, ECS Fargate or even Kubernetes. I often use Fargate because it’s AWS-managed, easy to use, easy to configure, and good for long-running heavy applications with high traffic. However, I often…
Azure cost optimisation is the process of reducing the overall expenses of Azure cloud services without compromising on performance or, even better, improving performance. This involves adapting best practices such as turning off idle resources (resources not in use), using discounts and savings plans, setting up autoscaling etc. So you will stop paying too much and…
When choosing between EKS, AKS, and GKE, several key factors influence the overall Kubernetes cluster cost. These factors can be grouped into two broad categories: objective cloud costs and operational/manageability costs. 1. Objective Cloud Costs Workload Nature The nature of your workload significantly impacts costs across cloud providers. Consider the following factors: Cloud Provider Pricing…
Azure vs AWS: Overview The cloud computing industry is booming and expected to reach a $5,150.92 billion market size by 2034. The leading cloud service providers, Azure vs AWS remain ahead of the pack with a combined market share of 55%, more than half of the total cloud computing market (as of Q4 2024). Although AWS still…
Every modern data team has experienced it: A product manager asks for a quick metric, “total signups in Asia over the last quarter, broken down by device type,” and suddenly the analytics backlog grows. Somewhere deep in the data warehouse, an engineer is now tracing join paths across five tables, crafting a carefully optimized SQL…
Caching is an important technique for enhancing the performance and cost efficiency of diverse cloud native applications, including modern generative AI applications. By retaining frequently accessed data or the computationally expensive results of AI model inferences, AI applications can significantly reduce latency and also lower token consumption costs. This optimization allows systems to handle larger…
SQL queries can be intimidating, especially for non-technical users. What if we could bridge the gap between human language and structured SQL statements? Enter SQLGenie—a tool that translates natural language queries into SQL by understanding database schemas and user intent. To build SQLGenie, I explored multiple approaches—from state-of-the-art LLMs to efficient rule-based systems. Each method had…
Large language models (LLMs) like GPT-4 can produce fluent, grammatically accurate text; however, without access to external, updated knowledge, they frequently hallucinate or fabricate facts. This turns into a prime issue in high-stakes environments — like legal, medical, or business enterprise contexts — in which accuracy and accept as true with are non-negotiable. Retrieval-augmented generation (RAG)…
Transcribing handwriting to text is standard among businesses that need to scan handwritten documents or convert old records into something accessible and editable online or in searchable databases. Not only can transcribing handwritten documents make data extraction easy, but it is also a way to go paperless. With OCR’s expanding role across industries, from healthcare…
Artificial intelligence (AI) and machine Learning (ML) are transforming business operations by enabling systems to learn from data and make intelligent decisions for predictive and generative AI use cases. Two essential components of AI/ML are model training and inference. Models are developed and refined using historical data. Model inference is the process of using trained…