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The latest News and Information on DevOps, CI/CD, Automation and related technologies.

Microsoft 365 Departed User Archiving: The Complete Guide for Enterprise IT

When an employee leaves your organisation, a clock starts ticking. Microsoft begins deleting their data — OneDrive files, Exchange Online emails, Teams conversations — within days of their account being disabled. For most large enterprises this is happening continuously, quietly, and without IT teams necessarily knowing until someone asks for data that no longer exists.

How Will We Hold AI Accountable For Risky Investments?

The word “Trillion” never fails to set the tech world on fire. Foundation Capital’s Jaya Gupta and Ashu Garg are two of the most recent firestarters. Late in December, they co-wrote “AI’s trillion-dollar opportunity: Context graphs,” outlining how AI will transition from organizational knowledge to organizational comprehension.

Why Cloud and DevOps Practices Matter to Prop Trading Firms

The financial industry has always been driven by speed, precision, and the ability to act on information faster than anyone else. In recent years, prop trading firms have found themselves at a crossroads where traditional infrastructure simply cannot keep up with the demands of modern markets. Cloud computing and DevOps practices have emerged as two of the most transformative forces reshaping how trading operations are built, managed, and scaled. Understanding why these technologies matter is not just useful for tech teams, it is essential knowledge for anyone involved in or curious about the future of high-performance trading.

That production incident cost more than downtime

Every developer knows the sudden, cold spike of adrenaline that comes with a P0 alert. The site is down, the Slack channel is overwhelmed with notifications, and the "war room" is officially open. In the immediate aftermath, leadership looks at one metric: downtime. They calculate the lost revenue per minute and the hit to brand reputation. But for the engineering team, the official resolution of the incident is only the beginning.

Debugging the black box: why LLM hallucinations require production-state branching

The most frustrating sentence in modern engineering is no longer "it works on my machine." It is: "It worked in the playground." When an LLM-powered feature, such as a RAG-based search, an autonomous agent, or a dynamic prompt engine, fails in production, it doesn’t throw a standard stack trace. It returns "slop," hallucinations, or silent retrieval failures. Standard debugging workflows fail during triage because LLM hallucinations cannot be reproduced using static mocks or clean seed data.