Testing
The .NET ecosystem has two mature approval/snapshot testing libraries: ApprovalTests.Net (the original) and Verify (the modern alternative with better async support and scrubbing). Both capture output to files and compare on subsequent runs. This guide covers both libraries with practical C# examples for NUnit and xUnit. Key Takeaways
Testing
Rate limiting in multi-tenant SaaS serves two goals: protecting infrastructure and enforcing plan limits. Both can break in ways that are hard to catch without explicit tests. The failure modes are distinct. Infrastructure protection fails when one tenant can starve other tenants — their traffic exhausts rate limit headroom that should
Testing
Billing bugs are the most expensive bugs in SaaS. A customer who gets charged incorrectly after a downgrade files a chargeback. A cancelled account that keeps getting charged generates legal exposure. A failed upgrade that doesn't grant access creates a support crisis. Unlike UI bugs, billing bugs often
Testing
White-label SaaS is a forcing function for good multi-tenancy. When a customer runs your product under their own brand, on their own domain, with their own colors and logo, any configuration leak becomes immediately visible. Their customers see a broken experience with the wrong logo, wrong colors, or the wrong
Testing
Onboarding is where SaaS companies win or lose customers before the product has a chance to prove its value. A broken signup flow, an email verification link that doesn't work, a workspace setup that fails silently — any of these ends the relationship before it begins. The problem with
Testing
Feature flags in single-user apps are already tricky. In multi-tenant SaaS, they're an order of magnitude harder. You're not just controlling whether a feature is on or off — you're controlling which tenants see which features, often with different rollout percentages, different target rules, and
Testing
Data isolation bugs in multi-tenant SaaS are catastrophic. When tenant A can see tenant B's data, you don't get a bug report — you get a breach notification, a legal team, and customer churn. The failure mode is silent: everything looks fine until someone notices records they
Testing
WeasyPrint converts HTML/CSS to PDF in Python, making it popular for invoice generation, report rendering, and document exports in Django/Flask apps. Testing WeasyPrint output involves extracting text from the generated PDF bytes, comparing page structure, and doing visual regression checks against PNG renderings. This guide covers the full
Testing
LLM regressions are silent killers: the app still returns a response, but the quality degraded after a prompt change, model upgrade, or context window modification. Traditional regression tests that assert exact string equality fail immediately with LLMs. This guide covers behavioral regression testing, prompt versioning, LLM-as-judge evaluation, and CI gates
Testing
Apache PDFBox is an open-source Java library for reading and writing PDFs. Unlike iText (commercial license for production use), PDFBox is Apache-licensed. It's ideal for testing PDFs regardless of how they were generated — iText, wkhtmltopdf, Puppeteer, or any other tool. This guide shows how to parse, compare, and
Testing
AI agents call external APIs — search engines, databases, Slack, GitHub, payment processors. Mocking these in tests is essential: real APIs are slow, rate-limited, non-deterministic, and sometimes irreversible. This guide covers four mocking strategies for agentic systems: HTTP interception, tool-level mocking, record/replay, and in-process fakes. An AI agent that manages
Testing
Golden master testing (also called characterization testing) captures what your code currently does and stores it as a baseline. You then refactor with confidence — if the output changes, the test fails. It's not about proving your code is correct; it's about proving a refactor didn'