I am currently working with the EA on their check for flooding team. I have been tasked to look at the 5 day river level charts with a view to add more historical data. This meant increasing the amount of data showed on the chart so users could compare the current river levels with the previous week, month or year. In order to proceed with some user research I needed to create a prototype of the r
In March 2024, Google replaced First Input Delay with Interaction to Next Paint as an official Core Web Vital. FID is gone. INP is what matters now — and most React apps that were passing before are failing under the new standard without anyone realizing it. FID measured how long the browser took to respond to the very first user interaction on a page. Click a button, FID measures the delay before
A defaced website is a curious problem. It's loud — anyone visiting the page can see something is wrong. But it's also quiet from a server's perspective: HTTP returns 200, your uptime monitor is happy, your TLS cert hasn't moved, and the CMS logs show a "successful" content update from a legitimate-looking session. The signal is on the rendered page, not in the metrics. I run a site at hi3ris.blue
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You just ran a dependency scan and the report shows 133 vulnerabilities. 34 are Critical. 68 are High. The dashboard is red, the backlog is exploding, and every item looks urgent. The engineering team asks the obvious question: where do we start? This is where vulnerability remediation prioritization matters. Without a clear framework, teams either panic and chase the loudest CVE, or they ignore t
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We've been there. JSON Schema gets hard to write as soon as your payload is non-trivial. Conditional logic, cross-field rules, business invariants, and at some point we stop writing contracts at all. We go code-first, generate the schema from annotations, and end up with 200 lines very few understand, and error messages referencing paths like #/properties/items/allOf/0/then/Then that map to nothin
This article provides a step by step deployment guide for using Amazon Bedrock models with ADK Agents. This project aims to configure an ADK agent to use an Amazon Bedrock model. LiteLLM is an open-source AI gateway and Python SDK that provides a unified OpenAI-compatible interface to over 100 LLMs (Anthropic, Gemini, Azure, Bedrock, Ollama). It simplifies API management by allowing users to call