I initiated an upgrade from a free (M0) cluster to a dedicated M10 cluster in AWS eu-west-3 (Paris). The Activity Feed shows the old cluster was deleted and a new cluster was created within seconds of each other:

• 695283b63d0d645020bfc79a — old M0 cluster, deleted 2026-07-21 10:29:58–10:30:26 GMT+1
• 6a5f3bc185cf74c924565a52 — new M10 cluster, created 2026-07-21 10:30:32 GMT+1

It's now been roughly 3 hours and:

• The UI still shows "Separately, we are deploying your changes (current action: migrating data to a new cluster)"
• There's also a persistent banner saying the cloud provider is out of capacity for the selected configuration, though the cluster itself shows as created
• The Connect flow fails with "Problem generating your connection string — your connection string is not available"
• I cannot reach the cluster at all, and Edit Configuration is greyed out

Questions:

1. Is the data restore into the new M10 cluster actually still in progress, or is this job stuck/failed silently?
2. Given the source M0 cluster has already been deleted, is my data safe and fully captured in this migration, or is there any risk of partial/incomplete restore?
3. Can someone on the Atlas team manually inspect or restart cluster 6a5f3bc185cf74c924565a52's migration job?
4. Is there a way for a free-tier project (no Commercial Support entitlement) to escalate a stuck deployment like this beyond the in-app chat widget, which has also been unresponsive?

Project: The PowerPointTribe / Project 0, cluster name: PPT

I have issues with accessing a field of a document returned by a find query.

I'm new to MongoDB and I'm trying to do some login logic but cannot get the field "password" of a document. (I'm using the C# driver.)

I first fetch the document from the database with the username that's been put in by the user, and that works fine, but when I try to get the password field of that document, it gives me an exception (Keynotfound).

BsonDocument loginDoc = libDB.GetCollection<User>("User").Find(filter).ToBsonDocument(); Console.WriteLine(loginDoc.GetElement("password").Value);

The last line is where I get the KeyNotFoundException: Element name not found, while running the program.

The only thing I found online that might help was to use SetFields for the BsonDocument but the compiler says that method doesn't exist and so does the Documentation.

I'm at a loss here, I don't even know if my approach of doing this is all that good. I' appreciate any help!

PS E:\task-manager-api> npm start

> [email protected] start

> node src/server.js

◇ injected env (3) from .env // tip: ⌘ multiple files { path: ['.env.local', '.env'] }

MongooseServerSelectionError: Could not connect to any servers in your MongoDB Atlas cluster. One common reason is that you're trying to access the database from an IP that isn't whitelisted. Make sure your current IP address is on your Atlas cluster's IP whitelist: https://www.mongodb.com/docs/atlas/security-whitelist/

at _handleConnectionErrors (E:\task-manager-api\node_modules\mongoose\lib\connection.js:1180:11)

at NativeConnection.openUri (E:\task-manager-api\node_modules\mongoose\lib\connection.js:1111:11)

at async connectDB (file:///E:/task-manager-api/src/config/db.js:8:9)

at async file:///E:/task-manager-api/src/server.js:7:1 {

errorLabelSet: Set(0) {},

reason: TopologyDescription {

type: 'Unknown',

servers: Map(1) {

'cluster0.gioaaxk.mongodb.net:27017' => [ServerDescription]

},

stale: false,

compatible: true,

heartbeatFrequencyMS: 10000,

localThresholdMS: 15,

setName: null,

maxElectionId: null,

maxSetVersion: null,

commonWireVersion: 0,

logicalSessionTimeoutMinutes: null

},

code: undefined,

cause: TopologyDescription {

type: 'Unknown',

servers: Map(1) {

'cluster0.gioaaxk.mongodb.net:27017' => [ServerDescription]

},

stale: false,

compatible: true,

heartbeatFrequencyMS: 10000,

localThresholdMS: 15,

setName: null,

maxElectionId: null,

maxSetVersion: null,

commonWireVersion: 0,

logicalSessionTimeoutMinutes: null

}

}

Server running on 5000

Hi everyone,

I struggle with a few quirks of compass as the primary data visualisation app for my DB. The biggest problem being slowly going through queries and not being able to follow up with my claude setup. MCP requires me to pass connection string every time and that's too much of a hassle when I already have everything saved in compass.

Therefore I built this alternative, it's fully opensource and allows you to simply query your collections with AI while letting you choose between read only connection or read/write connection.

You can also create visualisations for your data with simple prompt.

Check out - https://github.com/Vikings-Studio/mongopilot

Consider giving it a star if you like it.

My production environment was down, I dig into things and find out that yesterday (July 15th 2026) “System” wiped the addresses in my IP Access List for my Atlas database (noted “Network permission entry removed” in the Activity Feed).

Added the appropriate IP range needed for my GCP <-> Atlas Cloud peering to work and it was fine again.

Anyone experience this before or know how it could have happened?

Hi everyone,

I'm preparing for the MongoDB Certified DBA Associate exam. Can anyone recommend good practice resources, mock tests, or study strategies that helped you pass?

I’m deciding whether to use MongoDB Atlas for an application that will otherwise run primarily on Google Cloud.

For those using MongoDB with GCP, which services are you pairing it with, and how well does the setup work in practice? I’m especially curious about Cloud Run, Pub/Sub, BigQuery, Vertex AI, and Google Cloud networking or IAM.

Have you run into any friction around latency, data movement, authentication, observability, or cost?

Also, did anyone seriously evaluate Firestore and choose it over MongoDB, or move from MongoDB to Firestore? What drove that decision?

If I try to import and initialize my client in a CF worker like this:

import { MongoClient } from 'mongodb';

I get an error

Uncaught Error: Disallowed operation called within global scope.
Asynchronous I/O (ex: fetch() or connect()), setting a timeout, and generating random values are not allowed within global scope.

Workers intentionally disallow generating random values during module evaluation. The crash happens before any request runs.

This wasn't an issue with v6, it started in v7.

The workaround is to do a dynamic import of the 'mongodb' library, but I have other packages that do top-level imports so this isn't really viable.

i.e.

    const { MongoClient } = await import('mongodb');

Repro: https://github.com/ozzyonfire/mongodb-worker-example
([email protected] → [email protected])

Cause: In bson, ObjectId calls ByteUtils.randomBytes(5) in a static {} block during module load (process-unique bytes / startup-snapshot reset). Workers forbid random at global scope, so any package with a top-level mongodb import is blocked.

Would the bson team consider lazy-init of that state on first use instead? Not sure how it worked in v6...

P.S.

This feels strange to post on reddit, but I couldn't find a recommended way to submit these types of requests? The official community forums pointed me here. And there was no way to log an issue on mongodb/js-bson

Storing birthDate as a Mongo Date, with a unique index on (firstName, lastName, birthDate) to catch duplicate records.

Frontend builds the ISO string by taking "now," overriding just the year/month/day, then calling .toISOString(). Problem: the time-of-day at submission carries through, so depending on the user's timezone and what time they submit, the date can shift by a day after UTC conversion. Same birth date can end up stored as two different days, and in some cases two different real birth dates collide onto the same stored day - which breaks the unique index outright.

Can't change how the frontend serializes the date.

Anyone hit this before, or know a better fix?

I have taken C100DBA exam on July 8, 2026 (2026-07-08) and was using my student voucher(obtained through completing the learning path) for this attempt, and my session was terminated by ProctorUstaff based on a misreading of normal test-takingbehavior.

I complied fully, instantly and promptly with every instruction given throughout the session, including multiple full room scans, and I submitted a detailed account of these events in the feedback form I was automatically redirectedto at the end of the session.

I have sent a mail to [email protected] with a formal appeal including all time stamps (as far as I remember) with screenshots of me (which were automatically copied to my clipboard during the session through a software I installed which was told by my proctor) and justifying those exact moments.

- they replied :

"After a thorough review of the video footage, we have concluded that your actions during your exam were not in compliance with our testing protocols. Despite warnings from the proctor and intervention specialist, the behavior continued, leading to the termination of your exam.

As a result of these violations, we have inactivated your ProctorU account. It is essential for us to uphold the integrity of our examination process, and adherence to our policies is necessary to ensure fairness for all test takers.

We understand this may be disappointing, but our decision is final. "

What can I do now, as a student with no income, I cannot afford another exam which costs $150.

Anyone who have any knowledge (even a little) in this regarding, pls drop a comment.

Edit : They have sent a mail that my exam suspension was not necessary, and have issued a new voucher. Thanks to mongoDB team. But does anyone know what will be the expiry date of the voucher (as my summer vacation is getting over, I am heading back to my university, and need to plan accordingly). Will it be same as 6 Months as a student voucher or different ?

I built Argon, an open-source (MIT) versioning layer for MongoDB: branch, diff, and merge your data the way you manage code. Postgres has Neon and MySQL has PlanetScale; MongoDB had no equivalent — no way to spin off an isolated branch, let something change it, and merge the good work back. That gap is the whole reason Argon exists, and AI agents are what make it urgent.

How it works, in one paragraph. Every write is recorded in an append-only log with full before/after document images and a global sequence number. A branch is just a pointer into that log — creating one writes a single metadata document (0.86ms p50 on a 50k-entry project, 479 bytes of storage per branch [1]). "argon checkout" materializes a branch into a real MongoDB database and prints a connection string, so every driver, index, aggregation, and transaction just works — I didn't reimplement MongoDB. Direct writes flow back into the log via change streams, attributed to whoever made them. Replay is deterministic and property-tested in CI: the same history always reconstructs the same state, byte for byte.

What you can do with it:

- Give an AI agent its own branch. "argon sandbox create -p prod --ttl 1h" forks production into an isolated real database and hands you a URI. Point any agent at it — production is never in the blast radius, and every write is captured with the agent as actor. Then "argon diff" to review exactly what it did, and "argon merge preview/apply" to adopt the good work — persisted, reviewable plans, applied exactly once: a pull request for data. Don't like it? Discard the branch, or "argon undo --actor agent:x" to revert just that agent's writes (conflicts reported, never silently clobbered). There's an MCP server ("argon mcp", 13 tools, now in the official MCP Registry) so Claude/Cursor agents open their own branches before touching real data.

- Test the scary migration. Branch, run it against production-shaped data, "argon diff" the result, merge it back through a reviewed plan — or just delete the branch.

- Reproducible evals. "argon pin create" freezes a named dataset state that GC and reset can never touch; every eval run forks a sandbox from the pin and sees identical input while the live corpus keeps moving.

- LangGraph memory you can branch. "pip install argon-agents[langgraph]" gives you a checkpointer that forks and rewinds conversation state, plus a Mem0 factory, on the same engine.

- Un-break production, when it comes to that. "argon restore preview --time '10 minutes ago'" shows what would change, then reset — and the restore is itself logged, so you can even undo the undo.

Sixty seconds to try it:

brew install argon-lab/tap/argonctl # or: npm install -g argonctl

argon import database --uri mongodb://localhost:27017 --database myapp --project myapp

argon branches create experiment -p myapp

argon checkout -p myapp -b experiment

Honest limitations: change-stream capture needs a replica set or Atlas (standalone won't do); reads on non-checked-out branches materialize in memory; a GCS chunk-store backend and synchronous capture in the wire proxy are still on the roadmap; and the hosted console is a demo — the product is the open-source engine. It's a young project and I'd genuinely love to be told what breaks.

Every performance number links to a benchmark suite you can run yourself with docker compose up [1].

Site: https://argonlabs.tech · Code: https://github.com/argon-lab/argon · Demo: https://argonlabs.tech/demo

[1] https://github.com/argon-lab/benchmarks (RESULTS.md has the pinned engine ref and environment for every published run)

Hi! I'm looking for feedback on a tool I created that connects to MongoDB and creates live dashboards that you can publish and share with a link.

Normal Claude Code can generally only create static dashboards, and sharing them is difficult, usually passing around an html file or pdf.

Would love to get feedback if anyone is interested.

Hi everyone, I’m currently interviewing for senior PM role at MongoDB and would love to hear your experience and what should I prepare for as there is not much available on the internet.
Specifically, I would like to know:
- do they have coding interview questions? (As it is on exponent)
- how in depth can one expect database design and system design questions?
- any other advice.

Thanks in advance.

Hi Team,

We had requirement to move data from one mongo cluster to another. So before starting in production while trying lab (VM with minimal configuration(1 cpu and 2 GB RAM)) we are getting message continuously as "INITIALIZING" from last 4-5 hrs. Do you think is it due to configuration issue of vms.

Thanks,

Debasis

Greetings all, looking for some advice on an offer I just received from MongoDB Gurgaon.

Just wanted to understand the work culture at mongoDB, how's the wlb, how easy it is to get promoted, is there pip culture? do they do layoffs?

If people have insight regarding thr agentic AI team work culture that would be great as well.

Thanks

Basically the title.
We all know IPv4 is getting expensive and AWS has been charging for it quite a while now.
Currently i can migrate to using an IPv6 only EC2 instance but MongoDB Atlas does not support IPv6 connections (as far as i know, tell me if i am wrong).

It could reduce their costs, but most importantly allow services to communicate over IPv6, think about those serverless functions, why do they need IPv4, many low traffic EC2 instances which could work without IPv4. Many times these EC2 instances are cheaper than the IPv4 costs.

I'm curious whether this is a technical limitation, a cloud-provider limitation, a product-priority issue, or simply low customer demand.

For real, working with mongodb gives me so much frustrations. Everytime i want to go on the dashboard, it keeps spinning and does not do anything. U must click on the logo and it will finally redirects you to the signin page. It automatically sign you out after a while, super annoying. And it does not let you know when it does... Also if u have changing ip, its super annoying to always allow the ip... COMON MAN, WE ARE DEVELOPERS WE ARE LAZY. NOBODY WANTS TO DO THIS. DO THIS ONLY FOR PRODUCTION OR SO, NOT WHEN UR DEVELOPING. WHO DECIDES THESE THINGS INTERNALLY? PROBABLY SOMEONE WHO DOES NOT TOUCH A SINGLE CODE. FIRE HIM / HER / IT. This flow is probably the reason why mongodb is in decline. The only reason that makes it survives is probably ai recommendations and the amount of vibe coders using it. But for real... this sucks.