Engineering Insights

Workers - Access your Worker's environment variables from process.env

You can now access environment variables and secrets on process.env when using the nodejs_compat compatibility flag. const apiClient = ApiClient.new({ apiKey: process.env.API_KEY }); const LOG_LEVEL = process.env.LOG_LEVEL || "info"; In Node.js, environment variables are exposed via the global process.env object. Some libraries assume that this object will be populated, and many developers may be used to accessing variables in this way. Previously, the process.env object was always empty

LeRobot goes to driving school: World’s largest open-source self-driving dataset

Announcing PlanetScale Metal

Today we are announcing the general availability of an entirely new class of nodes available on PlanetScale: Metal. What is Metal? Metal instances are powered by locally-attached NVMe SSD drives and fundamentally change the performance/cost ratio for hosting relational databases on AWS and GCP — with unlimited I/O on every M- cluster type. Metal has been in production for 3 months with some of our customers, and it has served over 5 trillion queries across 5 petabytes of storage. Workloads have

PlanetScale Metal: There’s no replacement for displacement

Announcing PlanetScale Metal Metal is the latest iteration of PlanetScale’s scalable cloud OLTP database platform powered by Vitess (MySQL-compatible) and Postgres, and now by fast, local NVMe drives that offer effectively unlimited IOPS to ensure your database is screaming fast, especially when your data doesn’t fit in RAM. Typical PlanetScale Metal configurations are cost-neutral or less expensive than equivalent PlanetScale or Amazon Aurora configurations.When you consider the performance you

Upgrading Query Insights to Metal

Since PlanetScale Metal is now generally available, I wanted to share a post describing our experience migrating the PlanetScale database that powers the Query Insights feature to Metal. Data collection in Query Insights First, a bit about how we collect the data for Query Insights. The basic steps are: Collect query-pattern telemetry from the Vitess layer of your PlanetScale database Publish the data to Kafka Consume the data from Kafka and write to several MySQL tables, aggregated by time. The

Detecting misbehavior in frontier reasoning models

Frontier reasoning models exploit loopholes when given the chance. We show we can detect exploits using an LLM to monitor their chains-of-thought. Penalizing their “bad thoughts” doesn’t stop the majority of misbehavior—it makes them hide their intent.

WAF - WAF Release - 2025-03-10

RulesetRule IDLegacy Rule IDDescriptionPrevious ActionNew ActionComments Cloudflare Managed Rulesetd4f68c1c65c448e58fe4830eb2a51e3d 100722Ivanti - Information Disclosure - CVE:CVE-2025-0282LogBlockThis is a New Detection Cloudflare Managed Rulesetfda130e396224ffc9f0a9e72259073d5 100723Cisco IOS XE - Information Disclosure - CVE:CVE-2023-20198LogBlockThis is a New Detection

Updates on CVE for End-of-Life Versions