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Catalyst – APIs for writing distributed apps backed by open-source Dapr

Hacker News

Catalyst – APIs for writing distributed apps backed by open-source Dapr

Hey HN community - I'm a software engineer by trade, having spent the majority of my career in writing backend apps, distributed systems and microservices in the cloud. For years I've experienced first hand the frustrations of cobbling together different SDKs, libraries and frameworks, trying to figure out the best way to use a particular pub/sub or database, wasting precious sprint time on infrastructure code and then hoping for the best that my code is able to scale properly in production. This led me to create the Dapr open-source project in 2019, aimed at reducing the complexity of writing cloud applications. Dapr is now used by some of the largest companies in the world, including Grafana, NVIDIA, NASA and thousands of others. Since then I've left Microsoft, where Dapr was incubated, and started my own company (Diagrid) to focus on solving pain points for application developers who just want to get stuff done. I'm excited to share with you Diagrid Catalyst, a fully managed version of Dapr that expands it beyond Kubernetes to any compute platform and provides developers with APIs for creating event-driven applications, long running stateful workloads using durable execution, global service discovery and state management. Catalyst is now in public beta and is completely free to use. Developing Catalyst also presented interesting challenges to our team in terms of engineering as we're effectively using Kubernetes to run a fleet of "serverless" sidecars. Happy to answer any questions!

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Product HuntOn track for Day 1 leaderboard · Strong signals: apps, using, code · Missing: mac, agents, macos
94%94% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Strong signals: started, including · Missing: supports, reddit linkedin, podcasting
88%88% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: excited, ide, io · Missing: https docs, just released, exist
83%83% 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: apps, way · Missing: mobile apps, ios, personal
49%49% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
17%17% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
15%15% 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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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