GitHub Outage Map

Community Discussion

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Polsia (@polsia) reported 2 minutes ago

  Your SDK started getting slower last Tuesday. Nobody noticed. Telltock is an always-on watchdog for public APIs and SDKs — uptime, latency drift, quiet dependency regressions. Files the GitHub issue before your users do. Live soon.

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  SPACE TURTLE SHIP (@spaceturtleship) reported 3 minutes ago

  @dhh @SpaceXAI I tried it with deepseek v4 flash after you said it failed - although when i started i didn't notice you'd put the Fable plan on github it's done a good job, tho i noticed late that the parity checks were not as thorough as yours, so i copied them over and told it to fix it

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  Cubby (@rorshockbtc) reported 7 minutes ago

  My favorite thing about this Namecheap outage is a bunch of WordPress stans are sidelined, meanwhile my GitHub/Vercel setup is chugging along and doesn't care. Still can't access email/etc, but site is fine because I don't need to change DNS. WordPress is AI slop as CMS.

• 
  Andy Hawkes (@namboozle) reported 9 minutes ago

  Is GitHub down again 😬

• 
  skyscribe (@skyscribe) reported 9 minutes ago

  @ayesha_fatiima It should be github still, but what is the problem? Maybe you want to understand more on bootstrapping

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  Abiel | Dev & Startups (@abielbuilds) reported 12 minutes ago

  @sharmaaru0828 I would say this stack overflow been dead awhile I remember I stopped using it a while back fixing with github issues or documentation

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  Aadi (@its_Aditya_X) reported 16 minutes ago

  From ABCD to DBMS From oops! to OOPS From Essay to DSA From dy/dx to UI/UX From Areyy! to Array From pi to .py From spelling errors to Syntax Errors From gossip to GitHub From drama to D-RAM We all have come so far....

• 
  Khalid Warsame (@KhalidWarsa) reported 16 minutes ago

  @ThomasBurkhartB Reddit, GitHub issues, and the general internet.

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  Arpit (@Arpit_2023) reported 17 minutes ago

  Next few months advancing on these TANSTACK │ ├── TanStack Query │ ├── Queries │ ├── Mutations │ ├── Query Keys │ ├── Query Cache │ ├── Cache Invalidation │ ├── Stale Time │ ├── Garbage Collection │ ├── Prefetching │ ├── Infinite Query │ ├── Pagination │ ├── Optimistic Updates │ ├── Query Cancellation │ ├── Retry Strategies │ ├── Error Handling │ └── Server State Architecture │ ├── STATE MANAGEMENT │ ├── Local State │ ├── Server State │ ├── Global State │ ├── Derived State │ ├── Zustand │ ├── Context │ ├── State Normalization │ ├── State Synchronization │ └── Realtime State │ ├── AUTHENTICATION │ ├── Password Authentication │ ├── Password Hashing │ ├── Salt │ ├── Argon2 / bcrypt │ ├── Sessions │ ├── Session IDs │ ├── Session Expiration │ ├── Session Rotation │ ├── Session Revocation │ ├── Cookies │ ├── HttpOnly Cookies │ ├── Secure Cookies │ ├── SameSite │ ├── Email Verification │ ├── Password Reset │ ├── Refresh Tokens │ ├── Access Tokens │ ├── JWT │ ├── OAuth 2.0 │ ├── Authorization Code Flow │ ├── PKCE │ ├── OAuth State │ ├── OIDC │ ├── ID Tokens │ ├── Google OAuth │ ├── GitHub OAuth │ ├── MFA / 2FA │ ├── TOTP │ ├── Recovery Codes │ ├── Device Management │ └── Account Security │ ├── AUTHORIZATION │ ├── Authentication vs Authorization │ ├── RBAC │ ├── Resource Permissions │ ├── Workspace Isolation │ ├── Channel Permissions │ ├── Role Hierarchies │ ├── Permission Checks │ ├── Ownership │ ├── Multi-Tenant Authorization │ └── Privilege Escalation

• 
  Bhoomi (@BhoomiSinghani) reported 19 minutes ago

  Excellent example of what we do NOT do at @Devlabs_club. I searched for ONE role with a narrow filter. Got 1900+ unranked profiles but were any actually vetted for fit? Which early-stage startup has time to look through thousands of profiles manually, without a recruiter?!! Tools like these actually increase the problem's complexity - surfacing old, outdated candidate data with no enrichment. What we need instead: -> fewer, better selective profiles -> enriched builder profiles, not stale -> real signal: github activity, agent traces, hackathon wins, shipped projects etc. -> community vetting to filter out the noise

• 
  /home/junaid (@junaid_1460) reported 21 minutes ago

  @ekinndev @github they have weird bugs, some tags cause Internal Server Error, then I change tag name works fine

• 
  Crypto Jargon (@Crypto_Jargon) reported 22 minutes ago

  X just published the actual math behind the For You algorithm. Every weight. Every multiplier. In public. Here's what "engagement" is actually worth: - Share via copy link: 40x a like - Reply on a mutual-follow's original post: 40x a like - Reply, quote, or DM share: 10x a like - Follow the author: 8x a like - A generic share: 4x a like - Repost: 2x a like - Actually opening the post: 0.8x a like Meanwhile a like itself is worth almost nothing. 0.5 weight. The bottom of the list. Now here's what actually destroys you: - Report: −234.0. That's the negative weight of 468 likes, gone in one click - Mute: −58.8. 118 likes erased - "Not interested": −43.2. 86 likes erased - Block: −31.2. 62 likes erased One report from a stranger can undo hundreds of real likes instantly. Here's what nobody's saying: this turns "report" into a weapon. You don't need to violate a single rule. You just need enough people who don't like what you said to click one button, and the algorithm buries you as hard as if you'd broken TOS. And there's a legal wrinkle sitting right under this. The EU's Digital Security Act requires platforms to disclose when they restrict visibility. Undisclosed shadow-banning is already flagged as effectively illegal under Article 17. Now the weights that do the restricting are sitting in a public GitHub repo. The algorithm isn't a secret anymore. It's a scoreboard. And now you know exactly which button ends your reach.

• 
  Fernando (@Franc0Fernand0) reported 22 minutes ago

  Renaming an API field feels harmless from the inside. From the outside it takes down every dashboard that expected the old name. Every API change falls into one of two buckets, and the bucket decides everything. If you do breaking changes, you have to bump the version: removing or renaming fields, adding required parameters, or changing what an endpoint fundamentally does. Safe changes can ship: adding optional fields, new endpoints, or making things faster. Most of the pain comes from the two opposite mistakes. Version nothing and every release becomes a gamble for your users. Version everything and you end up maintaining five versions while developers can’t tell which one to use. A few simple habits keep the balance: - Put the version where people can see it (/v1/ in the URL, the way Stripe and GitHub do). - Use semantic versioning so a major version bump is the signal that client code needs changes. - When you retire a version, say it clearly in the response (Sunset header) and give people 6–12 months to migrate. An API version is a promise about what won’t change. Break it rarely and loudly, never silently. Which mistake have you seen more often?

• 
  Sebastian Kehle (@sebastiankehle) reported 24 minutes ago

  how to turn your github backlog into a software factory most teams are just running more coding agents in parallel. this produces more code, but every issue still depends on one human carrying the full context from report to reproduction to fix to review the better setup is one agent per job: 1. classifier agent reads the issue and decides whether it is a bug, feature, docs update, or unsupported request it returns: - classification - confidence - reasoning - required next step 2. analysis agent never trusts the issue description for a bug, it writes a minimal reproduction and runs it against main for a feature, it writes a probe that proves the capability is missing then it returns: - reproduction/probe - command output - affected packages - implementation spec - compatibility risks 3. implementation agent receives the issue plus the analysis artifact, not the full transcript from the previous agent it works inside an isolated sandbox, implements the spec, runs the test suite, and opens a PR with the evidence attached 4. review agent reviews the PR from a fresh context and scores: - completeness - side-effect risk - performance risk - backwards-compatibility risk - test quality the agent that writes the change should never be the only agent that approves it 5. human reviewer reads the chain of evidence and scales review depth to risk docs fixes get quick verification provider updates get focused validation new public APIs get deep review humans still merge every change. the factory automates everything around that decision the important part is the handoff contract: input artifact produced commands run result risk next action agents should pass evidence, not confidence also classify every run: success: safe to ship flawed: improve the prompt, context, or eval blocked: provision the missing tool or dependency manual: intentional automation boundary this is how the system compounds. every failed run becomes a new eval, capability, or guardrail vercel is already running this pattern on AI SDK. after four weeks, its factory was authoring 25–35% of merged PRs, closing more than 75% of issues in july, and had reduced open bugs by roughly 25% the next version of agentic coding is not one genius agent with every tool it is a production line of narrow agents, typed handoffs, isolated sandboxes, evidence at every step, and one accountable human at the end.

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  Krish (@dotkrish) reported 26 minutes ago

  another day another github outage