Christian Minich cnolanminich

name

run-website-performance-ab

description

Build, publish, and evaluate website performance changes with controlled browser A/B tests, representative-route discovery, rendered parity checks, and evidence-based keep-or-revert decisions. Supports matched Preview or staging deployments with no user traffic and production rollouts with field telemetry. Use for web performance experiments, bundle or module-graph changes, runtime variants, matched deployments, or requests to compare candidate and control websites without assuming a repository, framework, hosting provider, CMS, authentication system, or fixed route list.

Run Website Performance A/B

Use an exact control and one independently reversible candidate. Preserve unrelated work and never expose credentials, cookies, tokens, environment values, or protected deployment configuration.

1. Discover the website and representative routes

Dagster+ ECS Sizing Guide: Non-Isolated Runs

Overview

With non-isolated runs, each run executes as a thread inside the long-running code server process. Memory and CPU are shared across all concurrent runs. This guide covers how to profile your runs, size your ECS tasks, configure Dagster's gRPC settings, and decide when to split into multiple replicas.

The Core Sizing Equation

Dagster Asset Versioning & Staleness for ML Pipelines

1. `code_version`: Manually Set, Not Auto-Hashed

code_version is a manually assigned string on the @asset decorator or AssetSpec. Dagster does not automatically hash your function source code.

import dagster as dg

@dg.asset(code_version="1.0.0")

Step 1 — Understand the Two Starting Repos

Existing dbt Cloud Repo

dbt-cloud-repo/                        # github.com/myorg/dbt-cloud-repo
├── .github/
│   └── workflows/
│       └── dbt_cloud_deploy.yml       # dbt Cloud CI/CD

Dagster Demo Skill: Session Comparison

Comparison of five Claude Code sessions that received the same prompt, with varying skill configurations and prompt refinements.

The Prompt

All sessions received essentially the same base prompt: create a demo Dagster project with Fivetran → dbt → Snowflake → PowerBI, Alteryx, Domo (migrating off) → Census/Fivetran Activations, with event-driven sensors and observe/orchestrate modes.

skills-10 received an enhanced prompt with additional explicit instructions: "Make sure any component that connects to an external system is using a state-backed component, uses a local cache and writes a set of mock assets using that cache, and that when it executes it logs a sample message and metadata instead of connecting to the external system. When modifying a component that exists, ALWAYS subclass, do not create a custom component."

Project & Session Comparison

Project Comparison: testing-new-skills vs testing-new-skills-2

Structural Differences

Aspect	Project 1 (`testing-new-skills`)	Project 2 (`testing-new-skills-2`)
dbt project location	Inside `src/.../defs/dbt_project/`	Top-level `dbt_project/`
dbt mart models	`account_360`, `pipeline_summary`, `lead_conversion_funnel`	`fct_sales_pipeline`, `dim_account_health`, `fct_lead_conversion`

Dagster Documentation Analysis: 1.6 Release vs. Current (1.12)

Analysis Date: March 2, 2026

Executive Summary

Between Dagster 1.6 and the current release (1.12.17, as of February 27, 2026), the documentation has undergone a fundamental transformation — not just a cosmetic refresh, but a philosophical and structural overhaul that reflects Dagster's evolution from a flexible orchestration framework into a highly opinionated data platform with prescribed workflows, new abstractions (Components, dg CLI), and a dramatically narrower "happy path" for new users.

	"""CLI for managing Dagster+ saved selections (catalog views) and homepage pins.

	A saved selection is a ``CatalogView`` — a named, filterable view of the
	asset catalog (e.g. "all assets owned by alice", "assets tagged core_kpis").
	A pinned saved selection appears on a user's Dagster+ homepage and in the
	left-nav saved-selections list.

	Besides asset selections, the homepage can also pin jobs and asset
	groups. A pinned job is stored as a (public) ``CatalogView`` of type ``JOB``
	and surfaces as a ``JobPinnableItem``.

	from collections.abc import Iterator

	import dagster as dg
	from dagster_dbt import DbtCliResource, DbtProjectComponent


	class DbtProjectWithInsightsComponent(DbtProjectComponent):
	"""A DbtProjectComponent subclass that enables Dagster+ Insights.

	Chains `.with_insights()` onto the dbt event iterator so that warehouse

	SELECT
	customer_id,
	COUNT(*) AS order_count,
	SUM(amount) AS total_spent
	FROM orders
	GROUP BY customer_id