Dropbox Outage Map

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Dropbox Issues Reports

Latest outage, problems and issue reports in social media:

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  Ryan Zygar (@zygar) reported 5 minutes ago

  I am beginning to have issues with Dropbox hanging and my @NousResearch Hermes agent not being able to file @grok build confirmed. This is a new issue for months no issue now my agent filing and following up is hanging up. What’s everyone recommend for data management Mac Mini. This is new. No changes made by me.

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  prodbysvrge (@prodbysvrge) reported 10 minutes ago

  I wish I knew this starting out Stay ready Every day, make a small list of relationships to nurture Keep Dropbox iCloud open at all Times | Load Directly after cooking up After making beats, write down the labs you need to send Make a list of discord servers to send in

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  Harman (@itsharmanjot) reported 15 minutes ago

  Open source NotebookLM alternative with no data limits and AI agents. Same idea as Google's NotebookLM. Same chat-with-your-docs. Same podcast generator. Same cited answers. Except this one has no source limit, no notebook limit, no 200MB file cap, and no Google login. It's called SurfSense. Google NotebookLM vs SurfSense: - Sources per notebook: 50 to 600 → Unlimited - File size cap: 200MB and 500K words → No limit - LLM choice: Gemini only → 100+ models via LiteLLM - Local LLMs: Not allowed → Full Ollama and vLLM support - Self-host: No → Yes, one Docker command - Price: $0, $19.99/mo Pro, or $249.99/mo Ultra → $0 forever Here's the wildest part: It connects to 27+ sources Google can't touch. Notion. Slack. Linear. Jira. GitHub. Discord. Dropbox. OneDrive. Gmail. Confluence. Obsidian. ClickUp. Microsoft Teams. Airtable. Your entire work life, indexed once, searchable from one chat box. 14.4K GitHub stars. 1.4K forks. 6,232 commits. Apache-2.0 license. One honest note: the README says it's not yet production-ready and still being actively developed. But it already does more than NotebookLM does, and the gap is widening every release. This is what NotebookLM should have been from the start. Repo in the first comment.

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  StarHaze (@ST4RHaze) reported 19 minutes ago

  @neil_xbt Drew Houston started Dropbox because he forgot a USB stick on a bus in 2007. Nineteen years later the fix is still a 15 second demo

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  hiverot (@amusudan) reported 19 minutes ago

  @cowboyshibuya Thanks for the reply! I'm not the most organised, and Ill usually just work on whatever is fun (Or a prerequisite for something that's fun to work on), but I do keep track of ideas, and create todo's and pipelines for things I am sure I want to add or test. For random ideas and todos I use a lot of lists (Dropbox paper, random text files, Notion, Notes app on my phone, Google Docs, etc). And for specific pipelines I use Google Sheets to keep track of what has been done per asset or map or gameplay mechanic (For example my guns spreadsheet has columns for animations, sounds, textures, etc). Big picture design and planning is all on paper in various notebooks and my Calendar app. I don't really track bugs now I just fix whatever pops up when playtesting.

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  Eric S (@Lazy_Bari_Sax) reported 23 minutes ago

  @retrobike_c16 @themiasandrist Why doesn't the mobile version allow you to upload or download files, though? And why is it so damn slow to update? I'm thinking about changing back to Dropbox, despite it's many issues.

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  Abhishek Singh (@0xlelouch_) reported 25 minutes ago

  Design Dropbox file sync (typical system design prompt). 1) Clarify requirements - Devices: desktop + mobile, many devices/user - Semantics: eventual vs strong; last-writer-wins vs conflict files - Granularity: whole file vs block/chunk diff (large files) - Offline edits, resumable uploads, deletes/renames, shared folders - Targets: sync delay (ex: <2s LAN, <10s WAN), max file size, storage limits 2) APIs + data model - POST /changes (client reports local ops: create/modify/delete/rename) - GET /changes?cursor=… (server streams remote ops since cursor) - PUT /upload_session (init), PUT /upload_session/{id}/chunk, POST /commit Tables: - users, devices, folders - files(file_id, folder_id, name, latest_version_id, tombstone) - versions(version_id, file_id, hash, size, mtime, author_device, parent_version) - blocks(block_hash, size, refcount, storage_ptr) - version_blocks(version_id, block_hash, idx) - change_log(user_id/folder_id, seq, op, file_id, version_id) 3) Architecture - Client watcher + local metadata DB; compute chunk hashes; upload missing blocks - Metadata service (txn + authz) + object store for blocks (S3/GCS style) - Change propagation: long-poll/WebSocket for online devices; push notifications - Dedup: content-addressed blocks by hash; refcount GC 4) Scaling choices - Shard metadata by user_id/folder_id; keep change_log append-only - Cache hot metadata (latest_version, cursors) in Redis; rate limit clients - CDN/object store for block download; multipart for big files - Background workers: GC, compaction, conflict detection, virus scan (optional) 5) Tradeoffs to discuss - Chunk size: 4MB lowers metadata; 256KB improves delta sync but higher overhead - Strong ordering per folder via monotonic seq vs global ordering (hard) - Conflict model: last-writer-wins is simple; conflict copies preserve data but noisy - Encryption: TLS always; client-side E2E complicates server-side dedup/search 6) Failure cases - Network *****: idempotent commits via upload_session + version_id; retries with backoff - Duplicate uploads: hash-based existence check; commit is atomic in metadata store - Clock skew: don’t trust mtime for ordering; use server seq + parent_version - Retry storms after outage: jitter + per-device budgets; push minimal deltas - Corrupt blocks: hash verification on download; re-fetch; quarantine bad replicas

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  Dodz4allai (@DrGhattasMD) reported 28 minutes ago

  nstead of waiting for an API integration with Epic (which is costly and slow), OmniMed Pro deploys as a Chrome/Edge Browser Extension.3 Mechanism: Most hospital EHRs (Epic Hyperdrive, Cerner Millennium, AthenaHealth) are now accessed via web browsers (Citrix/VDI or native web interfaces). The OmniMed extension "sits on top" of the EHR window as a persistent sidebar. Data Ingestion (The "Read"): The extension uses the DOM (Document Object Model) to "read" the patient notes, labs, and vitals currently displayed on the doctor's screen. It does not need a backend integration; it reads what the doctor sees, acting as a "visual reader" similar to a human assistant. Intelligence Injection (The "Write"): The extension injects its "Co-Pilot" interface into the side of the screen. It offers "One-Click Transfer" buttons to paste generated notes, codes, or orders directly into the EHR's text fields.3 Value Proposition: This "Zero-Integration" approach allows individual doctors or departments to adopt OmniMed Pro today, bypassing the multi-year IT integration queue. This creates a Bottom-Up Adoption loop similar to how Slack or Dropbox entered the enterprise—employees brought it in because it solved their immediate problems. 5.2 Viral Loops & Community Growth To fuel this bottom-up growth, OmniMed Pro leverages the Medical Creator Economy 16: MedTwitter & Reddit: Solo founders and small teams are winning by "building in public." OmniMed Pro should release "light" versions of its tools (e.g., a "Scientific Paper Summarizer" or "Anki Card Generator" for med students) to gain viral traction. These free tools serve as a "Trojan Horse" for the OmniMed brand.18 The "Secret Cyborg" Phenomenon: Many doctors already use GPT-4 on their phones ("Shadow AI") to help with drafting notes or looking up conditions. OmniMed Pro legitimizes this behavior by offering a HIPAA-compliant, secure wrapper. By solving the "compliance headache" for the individual doctor, it wins the user first, then the enterprise.20 Anki Integration: For the student/resident market, integrating with Anki (spaced repetition flashcards) creates a lock-in effect early in a clinician's career. Tools that automatically generate Anki cards from clinical guidelines or textbooks are highly viral among medical trainees. Capture the medical student today, and you have the Attending Physician of tomorrow.19 5.3 Risks and Mitigation: The "Shadow" Dilemma This strategy carries significant risk. "Shadow AI" creates governance gaps and potential security liabilities.4 To mitigate this and eventually convert to enterprise contracts, OmniMed Pro employs a specific conversion strategy: Enterprise-Grade Security by Default: Even the individual version must be HIPAA-compliant (BAA signed on sign-up). Data processing should happen locally or in compliant cloud enclaves. The "IT Trojan Horse": Once adoption reaches a critical mass (e.g., 30% of doctors in a hospital), OmniMed Pro approaches the CIO with usage data. "Your doctors are already using this tool 5,000 times a week. Let's sign an enterprise deal to give you visibility, control, and single sign-on (SSO)." This flips the sales conversation from "Please try our product" to "Please secure and manage your existing usage".4 This is the exact playbook used by companies like Yammer and Slack to penetrate the enterprise. 6. User Experience: Visualizing Uncertainty and Generative UI The final barrier to adoption is Trust. Clinicians do not trust "Black Box" AI that spits out confident answers without rationale. OmniMed Pro employs a "Glass Box" UX philosophy that prioritizes transparency and interactivity. 6.1 Explainability via Visualization Sankey Diagrams for Reasoning: To visualize the "Chain of Thought," the UI uses Sankey diagrams that show how data flowed from "Lab Result" -> "Intermediate Reasoning" -> "Final Diagnosis".12 This allows the clinician to trace the logic visually. Interactive Debate Logs: The UI allows the doctor to "replay" the debate between the AI agents. "See why the AI ruled out Lupus." This turns the AI into a teaching tool rather than just an oracle, fostering trust and verifying the reasoning process. 6.2 Agentic Generative UI Instead of static dashboards or simple chat bubbles, the OS uses Generative UI.22 The interface adapts to the context of the conversation. Dynamic Charts: If a doctor asks about "Cardiology Trends," the system doesn't just write text; it generates a live, interactive chart of the patient's troponin levels over time. Actionable Forms: If the doctor asks for a "Referral," it generates the referral form, pre-filled with patient data, ready for signature. Contextual Cards: The UI presents "cards" for different data types (medications, allergies, labs) that can be manipulated, reordered, or expanded, creating a fluid workspace that replaces the rigid, click-heavy menus of the EHR.23 7. Regulatory & Ethical Moats: Defending the OS To operate at this scale and depth, OmniMed Pro must build defensible moats around regulation and safety. 7.1 MedHELM Evaluation Framework To prove superiority and safety, OmniMed Pro adopts the MedHELM (Holistic Evaluation of Large Language Models for Medical Applications) framework.1 Unlike static benchmarks (USMLE), MedHELM evaluates models on: Clinical Utility: Is the answer helpful and actionable? Safety/Harm: Did it suggest a fatal dosage or miss a critical red flag? Bias: Does it perform equally well for all demographics? Alignment: Does it follow the specific hospital's protocols? By continuously running MedHELM evaluations on its hybrid outputs, OmniMed Pro provides a "Quality Seal" that single-model providers cannot match without deep integration into the hospital's data. 7.2 Liability Frameworks In a multi-model world, liability is complex. OmniMed Pro positions itself as a Clinical Decision Support (CDS) tool, not a diagnostic device. The "Human-in-the-Loop" is mandatory. By visualizing the debate and uncertainty, the OS places the final decision firmly in the hands of the clinician, mitigating liability risks associated with "autonomous" diagnosis. 8. Conclusion: The Strategic Imperative The OmniMed Pro 'Medical AI Operating System' represents the inevitable evolution of healthcare artificial intelligence. By moving beyond the "Model-as-Product" mindset and embracing an Architecture of Aggregation, it solves the fundamental trilemma of medical AI: Accuracy, Cost, and Trust. Leverage the Router to commoditize the giants (OpenAI, Anthropic) and extract the best capabilities of each.1 Deploy the Consensus Engine (MCC) to achieve "Super-Human" reliability through adversarial debate.2 Unleash the Swarms to automate the physical and administrative burdens of healthcare.7 Infiltrate via Shadow AI to bypass bureaucratic inertia and win the hearts and minds of clinicians directly.3 In doing so, OmniMed Pro does not just "outperform" OpenAI; it contains them, turning their powerful models into mere components of a higher-order medical intelligence. This is the path to disrupting the global medical industry. Technical Appendix: Implementation Roadmap A.1 Deploying the MCC Debate Engine To implement the Model Confrontation and Collaboration (MCC) engine 2: Select Models: Integrate API endpoints for GPT-o1 (Moderator), Claude 3.7 (Reasoning), and DeepSeek-R1 (Critic). Define Prompts: Moderator: "Compare the following diagnoses. If semantically identical, output FINAL. If divergent, initiate DEBATE_ROUND_1." Critic: "Review the diagnosis provided by Model A. Identify any inconsistencies with the provided lab values. Cite clinical guidelines." Set Thresholds: If consensus > 0.8 similarity score, output. Else, iterate max 3 rounds. Fallback: If no consensus, route to "Human-in-the-Loop" queue. A.2 Building the "Sidecar" Extension To build the "Shadow AI" browser extension 3: Manifest V3: Develop using Chrome Manifest V3 for security compliance. DOM Observer: Use a MutationObserver to detect when the EHR (e.g., Epic Hyperdrive web) loads a patient note field. Context Extraction: Scrape relevant DOM elements (vitals, meds) locally in the browser (client-side) to minimize data egress risks. Injection: Inject a floating "FAB" (Floating Action Button) or sidebar IFrame that contains the OmniMed chat interface. Clipboard Actions: Use the Clipboard API to paste generated text back into the EHR's focused input field. A.3 Setting up the Swarm Architecture To orchestrate the Swarm 13: Orchestrator: Use a Python-based orchestrator (like Swarms API or LangGraph). State Management: Maintain a shared "Case State" object (JSON) that all agents can read/write to. Handoffs: Define explicit state transitions. if (labs_missing) -> route_to(Intake_Agent). if (diagnosis_ready) -> route_to(Synthesizer). Standardization: Ensure all agents output in structured JSON (FHIR format) to maintain data integrity across the swarm. Works cited

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  Ricker (@0xRicker) reported 28 minutes ago

  Senior engineer just dropped a GPT-5.6 stress test after burning around $200K on API usage: 00:00 - $180K–$240K spent testing GPT-5.6 in Fast Mode 02:43 - The model using browsers, dashboards and settings like a remote operator 05:32 - 67 projects and 20+ hour autonomous sessions 07:07 - Lakebed, T3 Code and native app rewrites in 2–4 hours 15:08 - Rust compiler experiments, 18x speedup and a $91K Dropbox-style build 17:46 - GPT-5.6 fixing a broken Linux GRUB boot through KVM 22:56 - 3D games, weird assets and the remaining frontend taste problem It is a field test for agent loops The future edge is not the prompt It is the loop that can keep working after the prompt stops being useful

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  Mark van Eijk (@markvaneijk) reported 29 minutes ago

  @freekmurze It's the most stable beta in last 15 years. These apps I also use still work: Dropbox, PHP, Conductor. I did not encounter any issues, besides sometimes a lag here and there (regular beta stuff).

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  Dan Holzrichter (@dholzric) reported 34 minutes ago

  @JoshuaKhane This is why i have primary copy on my home system, backup on local server (raid array of old hd's), and copies on google drive and dropbox for anything important.

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  Windows Latest (@WindowsLatest) reported 36 minutes ago

  Windows 11 June 2026 update, which was supposed to make PCs faster, is crashing some PCs with BSODs, breaking OneDrive integration in File Explorer and custom folder icons, and causing other problems. We're seeing reports that Windows 11 KB5094126 is causing boot failures on some PCs, mostly HP enterprise hardware. The worst reports involve BitLocker recovery loops, Black Screen of Death/BSOD failures, Secure Boot signature errors, and error 0xc0430001. Affected models appear to include HP EliteBook 840 G10, HP ProBook 460 G11, HP Engage One Pro G2 AiO POS, HP ZBook, and some Dell Precision systems. The likely trigger is Secure Boot certificate handling + EFI partition space. On older images with a 100MB EFI partition, Windows may fail to update Boot Manager because there isn’t enough space, especially on HP systems where firmware recovery files can bloat EFI. There are also File Explorer cloud integration issues. OneDrive, and in some cases Dropbox or iCloud Drive, may stop opening from the sidebar/tray shortcut after KB5094126. Microsoft also confirms desktop.ini hardening can break custom folder icons or localized folder names from untrusted sources. KB5094126 is important, as it fixes 200+ security bugs, but be careful, as it could cause havoc on some PCs.

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  Teja Punna (@punna_teja) reported 36 minutes ago

  Indian Government: "We've blocked Telegram to protect the NEET exam." The Internet: So the problem was... Telegram? Not the people selling fake papers? Not the organised scam networks? Not the thousands of mule bank accounts? Not the hundreds of disposable SIM cards? Not the fake payment gateways? Not the people exploiting students' panic and desperation? Solution: Block Telegram. Meanwhile: ✅ Discord still exists. ✅ WhatsApp still exists. ✅ Signal still exists. ✅ Slack still exists. ✅ Email still exists. ✅ Google Drive still exists. ✅ Dropbox still exists. ✅ OneDrive still exists. ✅ iMessage still exists. ✅ Bluetooth still exists. ✅ AirDrop still exists. ✅ The entire web still exists. Scammers: "No problem. See you tomorrow on another platform." Meanwhile, millions of legitimate users who rely on Telegram for: College and study groups Open-source communities Cybersecurity research Software development Startups and businesses Education and learning News and information sharing are left wondering what they did wrong. The platform changes. The abuse doesn't. Target the criminals. Not the communication tools.

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  Abhishek Singh (@0xlelouch_) reported 36 minutes ago

  System design question. How would you design Dropbox file sync with conflict handling? Constraints to make it real: 1) Same file edited on 2 devices while offline for 3 days, then both reconnect 2) Large files (2GB). Need chunking, resume, and content-hash dedupe 3) Renames/moves vs edits should not explode into full re-uploads 4) At-least-once change events from clients, out of order, with retries 5) Server must support 10M files per user without scanning the whole tree 6) Conflict UX: when do you auto-merge (text) vs create conflicted copies (binary)? 7) Cross-region sync, eventual consistency, and p95 sync latency < 5s for small edits [generated using my AI agent, hope this was useful]

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  Santiago Bustelo (@sbustelo) reported 37 minutes ago

  @DropboxSupport THEY ARE GIVING ME CANNED REPLIES. YOU SCREWED MY WORK AND BURIED ME FOR THE FOLLOWING MONTHS TO FIX UP THE MESS YOU MADE UP WITH MY FILES. I DEMAND A REFUND.