Systems | Development | Analytics | API | Testing

Introducing ARIA

What if you could build a data pipeline by just describing it in plain English? Sudais sits down with Maha, Astera's AI evangelist and one of the thought leaders behind ARIA, to talk about Astera's helper agents: what they are, why we built them, and where they're heading. ARIA is a set of specialized agents for Astera products like Centerprise and ReportMiner. Describe what you want, like migrating data from a SQL database to Snowflake, and the agent configures the pipeline for you.

AI Workspace + Playwright: Deploy Playwright tests from Jira requirements

Connect AI Workspace, the Tricentis Quality Agent, and Playwright so a Jira requirement generates test cases and runs them as an unattended web test. In this walkthrough, you will see how a ticket drives test case generation, triggers a Playwright run over MCP, and returns a pass/fail report to Jira. Key highlights.

8 Leading Platforms for Automated Software Delivery With AI Agents

Software delivery automation is moving beyond pipelines. CI/CD can compile code, run tests, build artifacts, and execute predefined deployment steps. AI agents add something different: the ability to interpret engineering work, gather context, choose what should happen next, respond to failed checks, coordinate tools, and continue working toward an outcome.

8 Best AI SRE Tools for Platform Engineers

A Kubernetes deployment succeeds, but the application starts returning errors. CPU utilization looks normal, yet response times climb. An autoscaler adds capacity without improving performance, and the on-call engineer spends the next hour moving between dashboards, deployment histories, logs, and configuration files. The difficulty is rarely a lack of monitoring data. It is determining which signals matter, how they relate, and what action will restore service without introducing another failure.

Agentic AI Security and Governance: Risks, Controls, and a Practical Checklist

Agentic AI security is the set of controls that keep AI agents from accessing, changing, or sharing more than they should. It covers who an agent acts for, which data and tools it can use, which actions need approval, and how its activity is recorded and reviewed. AI agents are moving from pilots into daily operations. They read invoices, update records, answer customers, and trigger workflows across business systems.

LLM and AI Agent Observability: What to Monitor, Evaluate, and Test

LLM observability is the practice of collecting and analyzing data about how a language model application or AI agent behaves, including prompts, responses, tool calls, cost, speed, and errors, so teams can find problems, measure quality, and improve results. AI agents can now plan tasks, call tools, and work across business systems. That makes them powerful, and it also means a single request can involve many steps that no one sees directly.

How to Install Claude Code on Mac (Official Installer, Step by Step) #shorts #coding #claudecode

How to install Claude Code on Mac in under one minute using the official native installer. Claude Code is Anthropic’s AI coding assistant for Terminal. This tutorial follows the official setup process step by step: find the installer, open Terminal, complete the installation, verify the version and sign in.

AI-Powered Performance Testing: Why Modern Systems Need Intelligent Engineering

Digital platforms move faster than ever today. In complicated systems, engineering teams upload code modifications numerous times a day. These apps are powered by distributed microservices, third-party APIs, and cloud resources. But many teams still validate speed with legacy workflows. Traditional load tests run solely static scripts against pre-planned scenarios. After the developers complete constructing the feature, they model historical traffic.

Connect AI Studio to On-Prem SQL Server (No Open Ports)

Connect Google AI Studio to an on-prem SQL Server database without opening a single firewall port or handing over a database password. In this video I put DreamFactory in front of a SQL Server database on my local network, generate a REST API from it, lock that API down with a read-only role and a scoped API key, then I have AI Studio build a live delivery operations dashboard on top of it. AI Studio calls the API from its own Node server, so the key never reaches the browser.