This article discusses how to gain deeper insights into AWS Lambda function performance using remote instrumentation—observability tools that don't require code changes. By leverag…
The article explores using Large Language Models (LLMs) to reduce false positives generated by static code analysis tools. By feeding LLMs the code snippet *and* the analysis resul…
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The Microsoft Sensitive Data Scanner now utilizes machine learning to more accurately detect human names within log data. This improved detection goes beyond simple keyword matchin…
This Datadog article explains how annotating LLM traces—adding metadata about inputs, outputs, and context—is crucial for understanding and improving LLM performance. By enriching …
The article advocates for "shifting left" on compliance – integrating security and regulatory checks *earlier* in the Software Development Life Cycle (SDLC), rather than as an afte…
This article explores using Large Language Models (LLMs) to improve the accuracy of static code analysis tools by reducing false positives. Researchers found LLMs can effectively d…
This article highlights the increasing need for automated vulnerability management as software development scales and becomes more complex. It introduces AI-powered solutions that …
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This article highlights new features in Amazon ECS designed to improve container issue detection and resolution. Specifically, it introduces default monitors which automatically tr…
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This article details how to use remote instrumentation to gain deeper insights into the performance and behavior of AWS Lambda functions *without* modifying application code. By le…