OpenZiti (Apache 2.0, P2P, E2E encrypted, full mesh overlay) is now 1.0

Hacker News

>$ ziti – version v1.0.0 Following a few years of early adopter use, OpenZiti (Apache 2.0) graduated to 1.0 a couple weeks ago. OpenZiti enables you to spin up overlay networks, and embed them in your software. Embedding via the SDKs means your overlay network extends into the process space of your application. The network goes anywhere your software goes. What’s in the box + Overlay network endpoints, including the SDKs to integrate the overlay network endpoints into your software; customized agents for OT, IoT, edge and IT; as well as browsers, reverse proxies, modems and firewalls. + Identity, authN, authZ, policy, private DNS…integrated between app and network overlay. Includes built-in PKI, MFA and posture checks. You can use external CAs and IdPs, but aren't forced to. + The overlay network controllers and routers. Includes e2e encryption, performance optimization, HA, load balancing, mTLS. The overlay network can be operated by you or by NetFoundry (initiator and maintainer of the OpenZiti platform). We’d love to hear your feedback . I am a cofounder and a few of us will be around to discuss.

Visit product View on Hacker NewsApr 23, 2024

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Indie HackersFits the IH revenue-focused audience · Strong signals: including · Missing: supports, reddit linkedin, podcasting

72%72% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io, including · Missing: https docs, excited, just released

55%55% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, open · Missing: mac, macos, cursor

54%54% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews

36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

30%30% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

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