Microsoft Ignite OAM, dapr, and rudr The future of cloud native applications Mark Russinovich @markrussinovich Open Application Model dapr: Distributed Application Platform Building Cloud Scale,

The Future of Cloud Native Applications with Open Application Model (OAM) and Dapr @markrussinovich Application models Describes the topology of your application and its components The way developers

Shaping its Future Dan Romlein UX Designer, Google Spencer Sugarman UX Researcher, Google Talk Goals 1. What Dashboard is and why you should be using it 2. Research findings and the future of Dashboard Migrating metrics from Heapster to Kubernetes Metrics API (#2986) ● Apps list page (#2980) Demo Future of Dashboard How do people use Dashboard today, and want to use it tomorrow? https://unsplash

arithmetic. APEX AMP is included to support models that currently rely on it, but torch.cuda.amp is the future-proof alternative and offers a number of advantages over APEX AMP. ‣ Guidance and examples demonstrating arithmetic. APEX AMP is included to support models that currently rely on it, but torch.cuda.amp is the future-proof alternative and offers a number of advantages over APEX AMP. ‣ Guidance and examples demonstrating arithmetic. APEX AMP is included to support models that currently rely on it, but torch.cuda.amp is the future-proof alternative and offers a number of advantages over APEX AMP. ‣ Guidance and examples demonstrating

be aggregated and silently dropping them from the results is deprecated and will be removed in a future version. If any porition of the columns or operations provided fail, the call to .agg will raise a warning is issued and the column takes precedence. This will result in an ambiguity error in a future version. searchsorted Series has the searchsorted() method, which works similarly to numpy.ndarray to_latex() due to the former’s greater flexibility with conditional styling, and the latter’s pos- sible future deprecation. Review the documentation for Styler.to_latex, which gives examples of conditional styling

be aggregated and silently dropping them from the results is deprecated and will be removed in a future version. If any porition of the columns or operations provided fail, the call to .agg will raise a warning is issued and the column takes precedence. This will result in an ambiguity error in a future version. searchsorted Series has the searchsorted() method, which works similarly to numpy.ndarray to_latex() due to the former’s greater flexibility with conditional styling, and the latter’s pos- sible future deprecation. Review the documentation for Styler.to_latex, which gives examples of conditional styling

be aggregated and silently dropping them from the results is deprecated and will be removed in a future version. If any porition of the columns or operations provided fail, the call to .agg will raise a warning is issued and the column takes precedence. This will result in an ambiguity error in a future version. searchsorted Series has the searchsorted() method, which works similarly to numpy.ndarray to_latex() due to the former’s greater flexibility with conditional styling, and the latter’s pos- sible future deprecation. Review the documentation for Styler.to_latex, which gives examples of conditional styling

Python data analysis toolkit, Release 1.3.2 precedence. This will result in an ambiguity error in a future version. searchsorted Series has the searchsorted() method, which works similarly to numpy.ndarray to_latex() due to the former’s greater flexibility with conditional styling, and the latter’s possible future deprecation. Review the documentation for Styler.to_latex, which gives examples of conditional styling version 1.2.0: As the xlwt package is no longer maintained, the xlwt engine will be removed from a future version of pandas. This is the only engine in pandas that supports writing to .xls files. pandas

a warning is issued and the column takes precedence. This will result in an ambiguity error in a future version. 2.3. Essential basic functionality 255 pandas: powerful Python data analysis toolkit, to_latex() due to the former’s greater flexibility with conditional styling, and the latter’s pos- sible future deprecation. Review the documentation for Styler.to_latex, which gives examples of conditional styling version 1.2.0: As the xlwt package is no longer maintained, the xlwt engine will be removed from a future version of pandas. This is the only engine in pandas that supports writing to .xls files. pandas

a warning is issued and the column takes precedence. This will result in an ambiguity error in a future version. 2.3. Essential basic functionality 255 pandas: powerful Python data analysis toolkit, to_latex() due to the former’s greater flexibility with conditional styling, and the latter’s pos- sible future deprecation. Review the documentation for Styler.to_latex, which gives examples of conditional styling version 1.2.0: As the xlwt package is no longer maintained, the xlwt engine will be removed from a future version of pandas. This is the only engine in pandas that supports writing to .xls files. pandas