“Beautiful your code is not, improve it you must.” Yoda doesn’t hold back and he roasted my code again. 😅 At least I recorded the evidence. Frontend, backend, errors and all.

👀 You get a free 30 day trial of ALL features. Here’s how to get the most out of it: 1. Install the browser extension, SDK, or in-app widget. 2. Connect your backend services (we’re backend agnostic and OpenTelemetry-compatible). 3. Capture your first full stack session recording.

👀 We're on that list too

Session replays shouldn’t stop at the browser. That’s why Multiplayer records full stack sessions. Here’s how it works 🧵

Full stack session recordings: record. code. fix. repeat.

👀 Understand it. Debug it. Test it. Built on it. Improve it.

You can’t fix what you don’t understand… or can’t visualize. So here’s a map 😊

More data ≠ more answers

Smarter prompts start with better data. Full-stack context beats guesswork every time.

One session recording to rule them all.

Traditional session replay hits different after full-stack

👩‍⚕️🧑‍⚕️ How healthy are your API docs? Here are 6 questions to ask yourself (or your team) that reveal whether your docs are helping developers, or quietly draining their time.

Stop guessing. Stop stitching. Start replaying.

When an API breaks, are you just reacting or actually diagnosing? How many of these best practices are you following?

Context shouldn’t take hours to piece together. With full-stack session recordings, it’s all in one replay, frontend to backend. Excited to see our CTO highlight this at API World today 🔥

What will you do with all the time we help you save? 🧶 Take up knitting 🍅 Grow tomatoes 🐞 Fix all the bugs

Fast debugging isn’t about faster engineers. It’s about having the full picture, frontend to backend, without hunting for it.

[1/] Debugging *should* be simple: ✔️ Detect a bug ✔️ Find the root cause ✔️ Fix it ✔️ Test + ship But anyone who’s actually done it knows… the reality looks nothing like this. Let’s look at the common hurdles and how to solve them.

When we build something at @multiplayer.app, we aim for insanely great quality. For example: we’ve been building a sandbox so you can test Multiplayer without signing up for a free trial. Seems straightforward, right? But in practice, there’s a lot to think through 👇

Most API docs go stale the moment you write them. Multiplayer notebooks are your documentation: living, runnable, versioned alongside your system. Anyone on your team can see what’s wired up and how.

What’s the impact of this change on error rates? 👉Ask your observability tools What happened during this test that failed? 👉 Record a full-stack session recording

Every engineering team has *that* Confluence space.

Should we redefine unknown unknowns? It’s a classic term in engineering and distributed systems that’s even more relevant now when we talk about debugging and AI coding assistants.

Test coverage is great. But it doesn’t always catch weird inputs, slow responses, or flaky 3rd-party behavior. Multiplayer Notebooks let you test real integration flows.

How is my backend service behaving under load? ▷ Ask your observability tools How can I reproduce and fix this bug? ▷ Record a full-stack session recording

Distributed systems rarely die from a single failure. They die from many small, unpredictable, non-linear causes, no one caught until they compounded into an outage. That’s why you need the full play-by-play to actually fix it.

How it feels to have every piece of data from the frontend and backend automatically correlated in a single session.

Rewind any issue. Replay every action. Get to “ohhh” faster.

Your integration broke. Again. Was it you? Them? A network hiccup? With notebooks you can replay the full flow (headers, payloads, latency…) so you can *see* what went wrong and fix it fast.

Is the system healthy? ▷ Ask your observability tools What caused this user flow to break? ▷ Record a full-stack session recording

Full-stack bugs, but you only get half the stack’s data.

Stop coaxing your AI coding assistant. Give it the precise data it needs. Automatically correlated and enriched.

👀 How great would it be to push record and never ask “what happened?” again? But for real. With backend data, automatically correlated with frontend end screens.

What is self-healing code? It’s not a buzzword. It’s a real concept, one that’s been around for decades. But with AI now in the mix, it's evolving fast. Let’s break it down 🧵👇

What is vibe debugging? If you’ve used an AI coding assistant, you’ve probably done it, even if you didn’t call it that. Let’s unpack this very unofficial, very real debugging pattern 🧵👇

Every missing trace, every unlabeled log, every ‘unknown’ in a dashboard … these are debts that will compound during your next production incident.

99% of debugging time is just trying to get the system to confess.

Building an internal API integration? Here’s an example of how you can: ✔️ Chain internal API calls to model real workflows ✔️ Prototype code logic inline ✔️ Add interactive custom visualizations using HTML/CSS/JS

If your system goes down and the first step is 'open five dashboards,' you don’t have a debugging workflow. You have a scavenger hunt.

We’re not saying your system is the problem. But we’re also not not saying it.

😍

Missed our live session on faster debugging workflows? Check the recording to learn: 🧠 Why observability needs to move left 🐛 How to debug with full-stack context (and no guesswork) 🤖 What AI can actually do to fix bugs

🔴 We’re live! Tune in to see: ✔️ Full-stack debugging in action ✔️ How to feed real runtime context into your AI IDE ✔️ What it takes to go from symptom to fix, fast

Today’s the day! 🐞 Bug reports don’t have to mean Slack threads, log spelunking, and guesswork. Join us for a live walkthrough of how left-shifted observability + AI-assisted debugging can speed up your entire workflow. 📅 July 23 | 2PM ET | 11AM PT | 8PM CEST

Tomorrow we’re going live with a deep-dive into modern debugging workflows: ▸ What happens when you shift observability earlier ▸ How to debug faster with full-stack session data ▸ Where AI fits into all of this 📅 July 23 | 2PM ET | 11AM PT | 8PM CEST

Every. single. sprint. If only your debugger could tell you what really happened! (spoiler: it can.)

What exactly is end-to-end debugging? It’s a term that gets tossed around a lot, but in distributed systems, it has a very specific meaning. Let’s unpack it 🧵👇

Tired of bugs you can’t reproduce, logs that miss the point, and AI that’s great at writing code, but useless at fixing it? Join our live session on how left-shifted observability helps you debug what actually happened. 📅 July 23 | 2PM ET | 11AM PT | 8PM CEST

How to get a unit test written by the bug itself: ✔️ Record full-stack session recording ✔️ Convert it into a Notebook your team can run, edit, and verify In one click, and you’ve got an auto-generated, reproducible test script ✨

In distributed systems bugs are often systemic, emergent, and multi-layered. You might think you've found the root cause, only to hit another unexpected error while reproducing it.