Ne

New version of AutoSpotting with lots of improvements

Hacker News

New version of AutoSpotting with lots of improvements

These are the main changes in this new stable release. Some were previously available in the Open Source trunk code, while others were built over the last couple of weeks: - Added support for recently launched EC2 instance types, including up to R6a, released in July 2022. - Significantly lower Spot interruption rates in the default configuration by 1.switching to the EC2 Fleet API in instant mode with the capacity-optimized-prioritized allocation strategy so that we now avoid instance types with a large likelihood of interruption. 2.increasing instance type diversification by relaxing the instance type selection logic. Previously we enforced instance types with at least as much EBS bandwidth, but this is now off by default. 3.Disabling the handling of Rebalancing recommendation events in the default configuration, which have been seen to significantly increase interruption rates. - Add support for biasing instance types selection to newer instance generations such as C7g, which offer significant performance improvements but with a slight cost increase. This is now turned on by default but can be turned off if lowest cost needs to be prioritised. The way this works is by penalising older generations when doing cost comparisons by 10% of the Spot price for each older generation, while the current generation isn't penalised at all. - Lower AutoSpotting costs, by considering the on demand price of the initial instance type configured on the group instead of the on-demand price of the Spot instance type that was launched to replace it. - Fixed handling of Allowed/Disallowed InstanceTypes in the default configuration, which was previously allowing all instance types and ignoring the list of Disallowed instance types. - Add support AutoScaling Group-based CodeDeploy deployment groups by triggering CodeDeploy deployments on new Spot instance launches so we no longer depends on tag-based deployment groups. This is a major release and I recommend anyone using AutoSpotting to give it a try. For now this is only available from the AWS Marketplace, but I plan to eventually release this functionality to the Open Source code.

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, using, code · Missing: mac, agents, macos
76%76% 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: including · Missing: supports, reddit linkedin, podcasting
76%76% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: open source, ide, io · 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.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
33%33% 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
17%17% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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