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Docker rollout – Zero Downtime Deployment for Docker-compose

Hacker News

Docker rollout – Zero Downtime Deployment for Docker-compose

docker-compose is great for single node docker deployments, but it doesn't have a feature that would allow zero downtime deployments. It's not possible to deploy often if your app goes down every time, and using Kubernetes/Nomad/Swarm on a single node is an overkill. I created this Docker plugin to be a drop-in replacement for the restart command in usual docker-compose deployment scripts. It performs a simple rolling deployment of a single service.

Visit productView on Hacker NewsFeb 7, 2023
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Product HuntOn track for Day 1 leaderboard · Strong signals: dock, single, using · Missing: mac, agents, macos
73%73% 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: created · Missing: supports, reddit linkedin, podcasting
50%50% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released
34%34% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
30%30% 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
28%28% 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
20%20% 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
8%8% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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