My

MyADMonitor, open-source tool to track live Active Directory changes

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MyADMonitor, open-source tool to track live Active Directory changes

myADMonitor is an open-source tool I created to provide real-time visibility into Active Directory changes. It's particularly useful when executing bulk updates or running operations where you need to analyze AD modifications as they occur. Key features: Real-time tracking of Active Directory changes Portable tool for easy deployment .NET backend using ASP.NET Core 8.0 Web API. Runs on localhost or mounted on a particular IP. React 18 frontend capable of handling thousands of DOM updates Designed for personal use but scalable for larger environments Changes are served via web API so they can be consumed from other sources, such as Excel, Power BI, Powershell, etc... Custom settings such as custom LDAP query to define the scope, real-time filtering, custom port, custom Domain Controller to connect, etc... I built this to solve the problem of lacking visibility during AD operations. I use it when executing complex scripts, bulk changing AD, troubleshooting replication or Azure AD sync, etc... It is not intended, yet, to be running as a service, but it is something I am considering. If you use or test it, please give me your feedback so I can fix any bug or add new features. https://github.com/mihemihe/myADMonitor

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting
95%95% 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.
Product HuntOn track for Day 1 leaderboard · Strong signals: new, using, open · Missing: mac, agents, macos
77%77% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: host · Missing: plus, platform, intuitive
43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
40%40% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs
37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · 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 · Strong signals: time tracking · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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