Spot Instances
Spot instances are a pricing model offered by cloud providers such as AWS, Google Cloud, and Microsoft Azure. They allow users to rent unused cloud capacity at a significantly lower
Stateful Workloads
In modern DevOps, managing workloads efficiently is critical for ensuring application stability, scalability, and reliability. Workloads are generally classified into two types: stateless and stateful. While stateless workloads do not
Supervised Learning
What Is Supervised Learning? Supervised learning is a fundamental approach in machine learning where a model learns from labeled data. In this method, the algorithm receives a dataset that includes
Synthetic Data
Synthetic data is artificially generated data that is created using algorithms instead of being collected from real-world events. It mimics the structure, patterns, and characteristics of real data without containing
Test-Driven Development (TDD)
In DevOps and modern software development, ensuring code reliability, maintainability, and efficiency is a top priority. Test-driven development (TDD) is one of the most effective methodologies for achieving these goals.
Text Embeddings
What Are Text Embeddings? Text embeddings convert words, phrases, sentences, or entire documents into numerical representations, making it easier for machines to process language. Unlike traditional text-processing methods that rely
Text-to-Image Models
Text-to-image models are a generative artificial intelligence (AI) system that can create images from written descriptions. These models take a text, often called a prompt, and produce a visual representation
Text-to-Speech (TTS)
Text-to-speech (TTS) is an assistive and generative technology that converts written text into spoken voice output. It uses artificial intelligence (AI) and speech synthesis techniques to produce natural-sounding audio from
Text-to-Video Models
Text-to-video models are AI systems that help to generate video content directly from text descriptions. These models analyze the meaning and context of the input text and produce sequences of
Token Limit
What is a Token Limit? A token limit refers to the maximum number of tokens a language model can process in a single interaction. In natural language processing (NLP) and
Tokenization
Tokenization converts something into smaller, manageable, and standardized units called tokens. The term has two primary meanings in modern technology: In Natural Language Processing (NLP): Tokenization breaks down text into
Total Cost of Ownership (TCO)
Total Cost of Ownership (TCO) in cloud computing refers to the complete cost of owning and operating a cloud environment over a specified period. Unlike direct costs, such as subscription
Traffic Splitting
In modern DevOps practices, ensuring seamless deployments, feature rollouts, and application stability is crucial for delivering high-quality software. Traffic splitting is a technique that enables teams to control how user
Transaction Monitoring
In modern software systems, ensuring transactions execute smoothly, securely, and efficiently is critical to maintaining application performance and user satisfaction. Transaction monitoring is essential in tracking, analyzing, and optimizing these
Transfer Learning
Transfer learning is a machine learning technique where a model trained on one task is reused or adapted to perform a different but related task. Instead of starting from scratch,
Transformer Models
A transformer model is a type of deep learning architecture primarily used for natural language processing (NLP) tasks such as text generation, translation, summarization, and language understanding. The Transformer architecture
Unsupervised Learning
What Is Unsupervised Learning? Unsupervised learning is a branch of machine learning in which algorithms analyze and interpret data without labeled outputs or predefined categories. The goal is to uncover
Update Rollback
In modern software development, frequent updates and deployments are a necessity. However, not every update goes as planned. Sometimes, new deployments introduce bugs, performance issues, or security vulnerabilities, requiring a
Usage Analytics
Usage analytics is crucial for understanding user behavior, improving product performance, and optimizing system efficiency. DevOps teams can make informed decisions about feature enhancements, system optimizations, and infrastructure scaling by
User Acceptance Testing (UAT)
Software development before release requires ensuring an application meets business requirements and user expectations. User Acceptance Testing (UAT) is the final phase of testing, during which end-users test the system
