Terraform Production Readiness Cheatsheet
Terraform working isn’t enough. Learn what it takes to make it production-ready — from backend design to security and automated pipelines.
Updates and recent posts about GPT-5.4.. Activity
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Director - Cloud Engineering, osttra
DevSecOps: Rapid & Secure Delivery
If security is your last step, you’re already too late. This guide shows how to build a DevSecOps pipeline where security is continuous, automated, and invisible to delivery speed.
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Email address obfuscation: What works in 2026?
The article catalogs obfuscation methods:HTML entities,SVG in an object,display:none, JavaScript decoders, custom encodings, andAES‑256. It coversmailtoobfuscation, redirects (302/301,.htaccess), interaction-gated reveals, accessibility caveats, and ahoneypot-based spam-statistics system... read more
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SQLite Features You Didn’t Know It Had: JSON, text search, CTE, STRICT, generated columns, WAL
SQLite packsJSONextraction, expression indexes,FTS5full-text search,CTEs, window functions, andWALinto a single file. It enforcesstrict tables, supportsgenerated columns, and indexes JSON expressions for fast semi-structured queries... read more
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GitHub backs down, kills Copilot PR ‘tips’ after backlash
GitHub revoked Copilot's ability to inject tips into other users' pull requests after reports that Copilot Review inserted aRaycastlink. They disabled agent tips in PR comments, blamed a programming-logic bug, and said they won't turn tips into ads... read more
One of the defining features of GPT-5.4 is its ability to operate as part of agent-style workflows. The model can interact with tools, APIs, and external systems to complete tasks that extend beyond simple text generation. It also introduces native computer-use capabilities, allowing AI agents to operate applications using keyboard and mouse commands, screenshots, and browser automation frameworks such as Playwright.
GPT-5.4 supports context windows of up to one million tokens, enabling it to process and reason over very large documents, long conversations, or complex project contexts. This makes it suitable for tasks such as analyzing codebases, generating technical documentation, working with large spreadsheets, or coordinating long-running workflows. The model also introduces a feature called tool search, which allows it to dynamically retrieve tool definitions only when needed. This reduces token usage and makes it more efficient to work with large ecosystems of tools, including environments with dozens of APIs or MCP servers.
In addition to improved reasoning and automation capabilities, GPT-5.4 focuses on real-world productivity tasks. It performs better at generating and editing spreadsheets, presentations, and documents, and it is designed to maintain stronger context across longer reasoning processes. The model also improves factual accuracy and reduces hallucinations compared with previous versions.
GPT-5.4 is available across OpenAI’s ecosystem, including ChatGPT, the OpenAI API, and Codex. A higher-performance variant, GPT-5.4 Pro, is also available for users and developers who require maximum performance for complex tasks such as advanced research, large-scale automation, and demanding engineering workflows. Together, these capabilities position GPT-5.4 as a model aimed not just at conversation, but at executing real work across software systems.
