🔍 Key Topics Covered 1️⃣ The Python Problem in Power Platform
- Why “Python runs natively” doesn’t mean “Python runs anywhere.”
- The rise of Code Interpreter inside Copilot Studio—and the chaos that followed.
- The real reason flows time out and files hit 512 MB limits.
- Why using Azure Functions for everything—or nothing—is equally misguided.
- How Code Interpreter works inside Copilot Studio (the “glass terrarium” analogy).
- Admin controls: why Python execution is disabled by default.
- What it can actually do: CSV transformations, data cleanup, basic analytics.
- Key limitations: no internet calls, no pip installs, and strict timeouts.
- Why Microsoft made it intentionally safe and limited for business users.
- Real-world examples of using it correctly for ad-hoc data prep and reporting.
- What makes Azure Functions the true enterprise-grade Python runtime.
- The difference between sandbox snippets and event-driven microservices.
- How Azure Functions scales automatically, handles dependencies, and logs everything.
- Integration with Power Automate and Power Apps for secure, versioned automation.
- Governance, observability, and why IT actually loves this model.
- Example: processing gigabytes of sales data without breaking a sweat.
- Why teams keep mistaking Code Interpreter for production infrastructure.
- How “sandbox convenience” turns into “production chaos.”
- The cost illusion: why “free inside Power Platform” still burns your capacity.
- The hidden governance risks of unmonitored Copilot scripts.
- How Azure Functions delivers professional reliability vs. chat-prompt volatility.
- A practical rulebook for choosing the right tool:
- Code Interpreter = immediate, disposable, interactive.
- Azure Functions = recurring, scalable, governed.
- Governance and compliance boundaries between Power Platform and Azure.
- Security contrasts: sandbox vs. managed identities and VNET isolation.
- Maintenance and version control differences—why prompts don’t scale.
- The “Prototype-to-Production Loop”: start ideas in Code Interpreter, deploy in Functions.
- How to align analysts and architects in one workflow.
- How quotas, throttles, and limits affect Python inside Power Platform.
- Understanding compute capacity and why Code Interpreter isn’t truly “free.”
- Security posture: sandbox isolation vs. Azure-grade governance.
- Cost models: prepaid licensing vs. consumption billing.
- Audit readiness: why Functions produce evidence and prompts produce panic.
- Real-world governance failure stories—and how to prevent them.
- Code Interpreter is for experiments, not enterprise pipelines.
- Azure Functions is for scalable, auditable, production-ready automation.
- Mixing them up doesn’t make you clever—it makes you a liability.
- Prototype fast in Copilot, deploy properly in Azure.
- Because “responsible architecture” isn’t a buzzword—it’s how you keep your job.
- Code Interpreter = sandbox: great for small data prep, visualizations, or lightweight automations inside Copilot Studio.
- Azure Functions = infrastructure: perfect for production workloads, scalable automation, and secure integration across systems.
- Don’t confuse ease for capability. The sandbox is for testing; the Function is for delivering.
- Prototype → Promote → Deploy: the golden loop that balances agility with governance.
- Governance, monitoring, and cost management matter as much as performance.
- Microsoft Docs: Python in Power Platform (Code Interpreter)
- Azure Functions Overview
- Power Platform Admin Center — Enable Code Execution
- Copilot Studio for Power Platform
- Copilot in the enterprise
- AI governance frameworks
- Low-code meets pro-code: the future of automation
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信息
- 节目
- 频率一日一更
- 发布时间2025年11月12日 UTC 05:00
- 长度21 分钟
- 分级儿童适宜
