Cloud Security Lounge – Datadog video series on cloud security

Hacker News

Datadog is launching the Cloud Security Lounge [0], a video series focused on cloud security products! My co-worker Izar Tarandach[1], and myself [2] will invite security professionals and discuss how they solve specific security problems, illustrated by hands-on demos and visuals. The first episode, vulnerability management the SBOM Way, features Steve Springett [3], director of product security at ServiceNow and in the core working group of the CycloneDX SBOM format [4]. We discuss common use cases for SBOMs, vendor push back, how SBOM don’t solve anything just by themselves, and how SBOM formats and content will evolve security practices and capabilities in the near future. 2 years after the Sqreen (YC W18) acquisition by Datadog, our dream to democratize security and break silos between security and engineering teams is shaping up. Our vision now goes beyond application security, encompassing everything runtime related such as cloud infrastructures and workloads.

Visit product View on Hacker NewsApr 20, 2023

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Indie HackersFits the IH revenue-focused audience · 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.

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

67%67% predicted probability of success on Product Hunt, 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

47%47% 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: video, way · Missing: mobile apps, ios, personal

44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

42%42% 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

13%13% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

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