Amazon Bedrock simplifies AI app development with serverless APIs, offering Q&A, summarization, and image generation using top models like Claude and Stability AI.
Learn in this article how BDD, AI-powered Cursor, and Playwright MCP simplify test automation, enabling faster, smarter, and more collaborative workflows.
When you need a quick assessment of your service’s ability to handle a load of 100+ requests per second, there’s no need to involve multiple teams in complex processes.
Starting your first job in Agile? This article breaks down what junior IT professionals really face—and how to handle real-world team dynamics, tools, and expectations.
Data quality isn’t an afterthought anymore; it is real-time, embedded, and self-healing. Cloud ETL needs smart checks, not checklists. Trust your data before it lies.
Learn about key qualities for writing software requirements—documented, correct, testable, and more—tailored for both human developers and AI code generation.
Use distributed tracing—the key third pillar of observability—to track requests across microservices and turn debugging from guesswork into precise insights.
CI/CD pipelines—the backbone of any successful DevOps strategy—ensure code is tested, integrated, and deployed automatically, allowing teams to focus on innovation rather than manual processes.
This guide shows how to move from a monolith to containers: containerize the app, split services gradually, adopt Kubernetes, automate with CI/CD, and modernize.
Embedding security in the SDLC builds resilient apps against threats. Key practices include early integration, teamwork, automation, updates, and metric tracking.
Finding a better way to handle real-time data for my GenAI app pushed me to rethink the tools I use—and that decision paid off in ways I never expected.