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ExternalSoftware Engineering
DZone

Bridging Gaps in SOC Maturity Using Detection Engineering and Automation

Security operations centers often mature in uneven increments: telemetry expands faster than normalization, alerting grows faster than triage capacity, and response playbooks exist without reliable signals to trigger them. SOC maturity is best treated as the ability to operate a stable feedback loop in which detection and response are governed, measured, and improved continuously as infrastructure and adversary behavior evolve. This loop becomes easier to sustain when detections are engineered a

ExternalCloud
Google Cloud Blog

Beyond the Query: 5 Scenarios Laying the Foundation for the Agentic Era

Accessing enterprise data is shifting from static reports to dynamic use by autonomous systems. To keep up, organizations must route fragmented data from SaaS, IoT, and legacy sources into secure, scalable endpoints. However, moving to AI-driven exposure requires more than just connecting an LLM to a database, it requires a fundamental architectural shift to manage security, costs, and semantic accuracy. What we’ll cover This article explores the technical evolution of data exposure through five

Data Analytics
Google Cloud BlogRead original
ExternalCloud
Google Cloud Blog

How Google Does It: Fleet-wide, large-scale A/B experimentation

When most people think of A/B experimentation, they think of button colors, landing page layouts, or checkout flows. At Google, many fundamental infrastructure improvements also need the rigor of A/B experimentation. Optimizing a memory allocator or a kernel scheduler can unlock massive savings in compute resources and slash latency for millions of users. But experimenting with such critical changes is inherently risky; a buggy kernel update doesn't just result in an unhappy user, it can take do

InfrastructureSystems
Google Cloud BlogRead original
ExternalCloud
Google Cloud Blog

What we announced in streaming AI at Next ‘26

Every device, user, and microservice generates data. Ingesting this data, extracting meaning and insights, and driving business decisions in real time has the potential to deliver transformational business value.The rise of agentic AI represents an opportunity for users to overcome the challenges inherent in real-time analytics. But while agentic AI has the potential to accelerate adoption, users face a new set of challenges with effectively leveraging real-time data: Real-time context is hard t

StreamingGoogle Cloud NextData Analytics
Google Cloud BlogRead original

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