#IstioCon Set Sail for a Ship-Shape Istio Release Brian Avery / twitter: @briansvgs / Red Hat Senior Software Engineer Eric Van Norman / twitter: @kf0s / IBM Senior Software Engineer #IstioCon First

#IstioCon How HP set up secure and wise platform with Istio John Zheng/ john.zheng@hp.com #IstioCon Agenda ➢ HP Horizon platform design with Istio ➢ Secure Platform ➢ Wise Platform ➢ Excellent • Project runs as tenant, need control rights Solution cluster connect core cluster with Istio multi-cluster - Replicated control planes Some standalone cluster without Istio can access core cluster level, reduces application workload. Intelligence Platform for Multiple Tenant Support • Support multi-tenants (Add extra http header/ logs wisely) • Verify whether JWT token in blacklist or not • Different

Kubernetes VM Solutions for Multi-Tenant Applications Guangxu Li, Senior Software Engineer, ZTE li.guangxu@zte.com.cn Container and VM Ecosystem Kubernetes Docker Swarm Marathon Nomad Container

2.1 Possible incompatibility for HDF5 formats created with pandas < 0.13.0 . . . . . . 51 1.5.2.2 Map on Index types now return other Index types . . . . . . . . . . . . . . . . . . 52 1.5.2.3 Accessing . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 1.8.2.8 Index + / - no longer used for set operations . . . . . . . . . . . . . . . . . . . . . 105 1.8.2.9 Index.difference and .symmetric_difference returns Index . . . . . . . . . . . . . . . . . . . . 106 1.8.2.11 MultiIndex constructors, groupby and set_index preserve categorical dtypes106 1.8.2.12 read_csv will progressively enumerate chunks . . .

Possible incompatibility for HDF5 formats created with pandas < 0.13.0 . . . . . . 22 i 1.3.2.2 Map on Index types now return other Index types . . . . . . . . . . . . . . . . . . 23 1.3.2.3 Accessing . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 1.6.2.8 Index + / - no longer used for set operations . . . . . . . . . . . . . . . . . . . . . 76 1.6.2.9 Index.difference and .symmetric_difference returns Index . . . . . . . . . . . . . . . . . . . . 77 1.6.2.11 MultiIndex constructors, groupby and set_index preserve categorical dtypes 77 1.6.2.12 read_csv will progressively enumerate chunks . . .

joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 386 14.3 Merging with Multi-indexes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 395 15 Reshaping dimensional objects • Automatic and explicit data alignment: objects can be explicitly aligned to a set of labels, or the user can simply ignore the labels and let Series, DataFrame, etc. automatically align Here – MultiIndexing Using Slicers, See Here. – Ability to join a singly-indexed DataFrame with a multi-indexed DataFrame, see Here – More consistency in groupby results and more flexible groupby specifications

2.1 Possible incompatibility for HDF5 formats created with pandas < 0.13.0 . . . . . . 21 1.2.2.2 Map on Index types now return other Index types . . . . . . . . . . . . . . . . . . 21 1.2.2.3 Accessing . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 1.5.2.8 Index + / - no longer used for set operations . . . . . . . . . . . . . . . . . . . . . 74 1.5.2.9 Index.difference and .symmetric_difference returns Index . . . . . . . . . . . . . . . . . . . . 75 1.5.2.11 MultiIndex constructors, groupby and set_index preserve categorical dtypes 75 1.5.2.12 read_csv will progressively enumerate chunks . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 368 12.19 Set / Reset Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 472 17.3 Merging with Multi-indexes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 481 18 Reshaping dimensional objects • Automatic and explicit data alignment: objects can be explicitly aligned to a set of labels, or the user can simply ignore the labels and let Series, DataFrame, etc. automatically align

dimensional objects • Automatic and explicit data alignment: objects can be explicitly aligned to a set of labels, or the user can simply ignore the labels and let Series, DataFrame, etc. automatically align of bug fixes. Highlites include a consistent I/O API naming scheme, routines to read html, write multi-indexes to csv files, read & write STATA data files, read & write JSON format files, Python 3 support accepts regular expressions. 1.1.1 API changes • The I/O API is now much more consistent with a set of top level reader functions accessed like pd.read_csv() that generally return a pandas object. –

dimensional objects • Automatic and explicit data alignment: objects can be explicitly aligned to a set of labels, or the user can simply ignore the labels and let Series, DataFrame, etc. automatically align date_range(’20130101’,periods=10))) ...: In [9]: df.iloc[3:6,[0,2]] = np.nan # set to not display the null counts In [10]: pd.set_option(’max_info_rows’,0) In [11]: df.info() 4 Chapter 1. What’s New pandas: datetime64[ns] dtypes: datetime64[ns](1), float64(2) # this is the default (same as in 0.13.0) In [12]: pd.set_option(’max_info_rows’,max_info_rows) In [13]: df.info() Int64Index: