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How AI Is Changing Cybersecurity and Exposing Decades of Bad Code

Was this the worst week in cybersecurity? AI-discovered PHP2Shell vulnerabilities, the LiteLLM supply chain attack, and reports of unauthorized AI agents accessing bank accounts are exposing serious weaknesses in software security. But is this really a cybersecurity problem, or has AI exposed decades of poor software engineering decisions? In this episode of ShipTalk, Martin Reynolds and Adam Arellano break down a remarkable week in AI security and debate whether engineering or security teams should be responsible for fixing what comes next.

Deploying Apache Airflow on Aiven Runtime

When we first introduced people to Aiven Runtime, before it even had that name, we kept getting asked: "Can we schedule things?" If you come from a Unix background, that tends to cause a reflexive reach for the cron tool, which provides basic scheduling at fixed intervals. But if you've spent more time with distributed software, you're more likely to think of Apache Airflow, which can do a lot more (although, yes, you can use Airflow to schedule tasks at fixed intervals if you want).

Can AI Do Your Software Testing? #softwaretesting #aitools #codingtips #devlife #tech #aiagents

Learn how AI handles different types of testing, from simple unit tests to complex end-to-end setups. Discover where AI succeeds in writing test code and where human strategy is still needed. Learn more: speedscale.com.

Application Chaos Testing using Traffic Replay #apitesting #devops #microservices #chaostesting

Learn how to test your application's fallback mechanisms by intentionally injecting chaos and simulated dependency failures into recorded API traffic. Easily configure scoped rules to inject status code errors or delays during mock runs to verify your app handles failure gracefully. Learn more: speedscale.com.

Evaluate AI models for observability: o11y-bench joins Fireworks' Specialized Intelligence Index and reaches v1.1

When evaluating AI models for observability, generating a plausible query or explanation isn't enough. Teams need to know whether an agent's conclusions are supported by telemetry, whether its changes to dashboards actually work, and whether it can deliver reliable results consistently. This is why we built o11y-bench, Grafana Labs' open benchmark for evaluating AI models on observability and SRE tasks. And today, we're excited to share two updates.

CloudZero in 3 Minutes: See What Your AI and Cloud Spend Actually Buys

Cloud and AI spend in one place, tied to the teams, products, and customers behind it. Your bill tells you what you spent. CloudZero tells you why, and whether it paid off. This quick tour shows how CloudZero pulls cost from AWS, Azure, GCP, Kubernetes, Snowflake, OpenAI, Anthropic, and more, then allocates it to what your business actually cares about. No perfect tagging required.

Seedance 2.5 API Integration: A Practical Guide for Developers

A Seedance 2.5 integration has two distinct operations: create a video task, then read that task until it reaches a terminal state. Treating generation as an ordinary request that immediately returns a finished file is the first design mistake to avoid. This guide uses SeedRouter's documented Seedance 2.5 contract. The request shapes were checked on October 22, 2026. The examples explain submission and polling; they do not claim a paid generation was executed for this article.

Machine Learning Applications That Revolutionize IOP Scottsdale Practices

In the realm of Intensive Outpatient Programs (IOP), machine learning is reshaping how facilities such as those in Scottsdale operate. By integrating advanced algorithms and data-driven techniques, these programs are enhancing patient care, optimizing operational efficiency, and improving treatment outcomes. This article explores the transformative applications of machine learning within Iop Scottsdale, highlighting its potential to revolutionize practices and benefit both patients and providers alike.

Commercial Fleet Wraps as an Operations Project: Planning, Proofing, and Rollout

A fleet manager once described her first wrap project like this: the design was approved on a Tuesday, and on Wednesday morning she discovered that three of the vans scheduled for installation were out on emergency calls. Nothing was wrong with the artwork. The trouble was that the project had been treated as a graphics task instead of a scheduling one, and the calendar caught up with it.