Luís Ventura
Answering the Million Dollar Question: Why did I Break Production?
#1about 4 minutes
Understanding the complexity of modern software development
Modern software is complex due to large codebases, external dependencies, changing requirements, and distributed teams.
#2about 6 minutes
How human error and assumptions lead to outages
Real-world examples show how simple mistakes, phishing attacks, and incorrect assumptions can cause major system failures.
#3about 5 minutes
Managing infrastructure complexity and planning for scale
Over-provisioning, under-provisioning, and failing to anticipate user load can lead to costly outages and poor performance.
#4about 1 minute
How to anticipate future-proofing issues in code
The "Gangnam Style" integer overflow illustrates why developers must consider data type limits and long-term system behavior.
#5about 5 minutes
Finding leaked secrets with static analysis tools
A live demo shows how to use a tool like Trivy to automatically scan infrastructure-as-code files for exposed credentials.
#6about 4 minutes
Scanning for vulnerable dependencies and IaC misconfigurations
Tools like Trivy and Checkov can automatically scan package manifests and configuration files for known vulnerabilities and security issues.
#7about 2 minutes
Using linters to catch common code-level bugs
A demonstration of ESLint shows how linters can identify common programming mistakes like scope errors or missing break statements.
#8about 1 minute
Recognizing the limitations of automated security tools
Automated tools are helpful but cannot replace the critical thinking and context provided by manual code reviews and comprehensive testing.
#9about 1 minute
The critical role of human observation in security
The discovery of the XZ Utils backdoor highlights that human intuition and detailed investigation remain essential for finding sophisticated threats.
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Matching moments
24:07 MIN
Q&A on customer impact and worst production breaks
I broke the production
40:25 MIN
Q&A on production code analysis and performance bottlenecks
Data Science on Software Data
00:48 MIN
A personal story of breaking production at scale
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51:53 MIN
Q&A on shared systems and scaling productivity
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29:58 MIN
How engineers handle production errors and monitoring
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25:59 MIN
Securing applications in the production environment
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29:56 MIN
Q&A on speed, team adoption, and common mistakes
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1:13:07 MIN
Q&A on low-code, production readiness, and career
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