|
✂️ Cut your QA cycles down to minutes with QA Wolf (Sponsored)
 |
If slow QA processes bottleneck you or your software engineering team and you’re releasing slower because of it — you need to check out QA Wolf.
QA Wolf’s AI-native service supports web and mobile apps, delivering 80% automated test coverage in weeks and helping teams ship 5x faster by reducing QA cycles to minutes.
QA Wolf takes testing off your plate. They can get you:
Unlimited parallel test runs for mobile and web apps
24-hour maintenance and on-demand test creation
Human-verified bug reports sent directly to your team
Zero flakes guaranteed
The benefit? No more manual E2E testing. No more slow QA cycles. No more bugs reaching production.
With QA Wolf, Drata’s team of 80+ engineers achieved 4x more test cases and 86% faster QA cycles.
This week’s system design refresher:
Evolution of HTTP
System Performance Metrics Every Engineer Should Know
Why Is Nginx So Popular?
Network Debugging Commands Every Engineer Should Know
Hub, Switch, & Router Explained
SPONSOR US
Evolution of HTTP
The Hypertext Transfer Protocol (HTTP) has evolved over the years to meet the needs of modern applications, from simple text delivery to high-performance, real-time experiences.
 |
Here is how HTTP has progressed:
HTTP/0.9: Built to fetch simple HTML documents with a single GET request.
HTTP/1.0: Added headers and status codes to support richer interactions, but every request still required a new connection.
HTTP/1.1: Introduced persistent connections and more methods, making the web faster and more efficient for everyday browsing.
HTTP/2: Solved performance bottlenecks with multiplexing, enabling multiple requests to share one connection.
HTTP/3 (QUIC): Shifted to UDP with QUIC to reduce latency and improve reliability, especially for mobile and real-time apps.
Over to you: Are you already taking advantage of HTTP/3 in your projects?
2026 OKR: Use AI to make MTTR 70% faster & optimize costs (Sponsored)
 |
Code from Claude is about to hit prod, but it doesn’t have to be painful.
Engineering teams at Coinbase, Toast, Gametime, MSCI, and Zscaler use Resolve AI to resolve incidents, optimize costs, and build with production context using AI that works across code, infra, and telemetry
The results mean 70% faster MTTR, 30% fewer engineers pulled in per incident, and thousands of saved engineering hours. Imagine what you could ship with that time in 2026
Learn more about AI for prod, workflow-autonomous multi-agent systems, and how you can cut orchestration tax, improve investigations, and shift engineering time from grunt work to great work.