Kailun Qin, Ant Group Putting an Invisible Shield on Kubernetes Secrets Agenda • K8s Secrets: Overview • TEE-based K8s Secrets Protection: Solution • Production Experience @ Ant Group • Demo • Summary security [1] KubeCon China 2018: Node Operator: Kubernetes Node Management Made Simple - Joe Chen, Ant Financial TEE-based Secrets Protection: Solution Confidential Computing A Trusted Execution Environment Secrets • Introducing mutual (remote / local) attestations between entities Production Experience @ Ant Group KMS Plugin • Workflow • Encryption • Decryption • Engineering decisions • apiserver is responsible

version 4.0 ou supérieur . . . . . . . . 208 10.1.2 Machines créées par des versions de VirtualBox antérieures à 4.0 . . . . 209 10.1.3 Données globales de configuration . . . . . . . . . . . . . . . Avant cette version, il n’était possible que de revenir au tout dernier instantané pris – pas à ceux antérieurs, et l’opération s’appelait “Désactiver l’état actuel” et non “Restaurer le dernier instantané“ partir du menu contextuel de la liste des VMs du gestionnaire (en sélectionnant “Cloner”) ou de la vue “Dépôts” de la VM sélectionnée. Choisissez d’abord un @ouveau nom pour le clone. Quand vous sélectionnez

┌──────────▼──────────┐ Siwi, /ˈsɪwi/ │ │ │ Web_Speech_API │ A PoC of Dialog System │ │ │ Vue.JS │ With Graph Database │ │ │ │ Backed Knowledge Graph │ │ # Browser End │ ├── README.md │ ├── package.json │ └── src │ ├── App.vue # Listen to user and pass Qs to S │ └── main.js └── wsgi.py wey-gu/nebula-siwi The Function

nodes and attributes into a pandas DataFrame. Note: Since there is no standard XML structure where design types can vary in many ways, read_xml works best with flatter, shallow versions. If an XML document comments, and others. Only namespaces at the root level is supported. However, stylesheet allows design changes after initial output. Let’s look at a few examples. Write an XML without options: In [350]: case is to limit a time series to start and end at two specific dates. To enable this, we made the design choice to make label-based slicing include both endpoints: In [235]: s.loc["c":"e"] Out[235]: c

nodes and attributes into a pandas DataFrame. Note: Since there is no standard XML structure where design types can vary in many ways, read_xml works best with flatter, shallow versions. If an XML document comments, and others. Only namespaces at the root level is supported. However, stylesheet allows design changes after initial output. 342 Chapter 2. User Guide pandas: powerful Python data analysis toolkit case is to limit a time series to start and end at two specific dates. To enable this, we made the design choice to make label-based slicing include both endpoints: In [235]: s.loc["c":"e"] Out[235]: c

nodes and attributes into a pandas DataFrame. Note: Since there is no standard XML structure where design types can vary in many ways, read_xml works best with flatter, shallow versions. If an XML document comments, and others. Only namespaces at the root level is supported. However, stylesheet allows design changes after initial output. 342 Chapter 2. User Guide pandas: powerful Python data analysis toolkit case is to limit a time series to start and end at two specific dates. To enable this, we made the design choice to make label-based slicing include both endpoints: In [235]: s.loc["c":"e"] Out[235]: c

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case is to limit a time series to start and end at two specific dates. To enable this, we made the design choice to make label-based slicing include both endpoints: In [237]: s.loc['c':'e'] Out[237]: c source implementations (like base::merge.data.frame in R). The reason for this is careful algorithmic design and the internal layout of the data in DataFrame. See the cookbook for some advanced strategies same type is returned, containing booleans. >>> df = pd.DataFrame([['ant', 'bee', 'cat'], ['dog', None, 'fly']]) >>> df 0 1 2 0 ant bee cat 1 dog None fly >>> pd.isna(df) 0 1 2 0 False False False

case is to limit a time series to start and end at two specific dates. To enable this, we made the design choice to make label-based slicing include both endpoints: In [237]: s.loc['c':'e'] Out[237]: c source implementations (like base::merge.data.frame in R). The reason for this is careful algorithmic design and the internal layout of the data in DataFrame. See the cookbook for some advanced strategies same type is returned, containing booleans. >>> df = pd.DataFrame([['ant', 'bee', 'cat'], ['dog', None, 'fly']]) >>> df 0 1 2 0 ant bee cat 1 dog None fly >>> pd.isna(df) 0 1 2 0 False False False

nodes and attributes into a pandas DataFrame. Note: Since there is no standard XML structure where design types can vary in many ways, read_xml works best with flatter, shallow versions. If an XML document comments, and others. Only namespaces at the root level is supported. However, stylesheet allows design changes after initial output. Let’s look at a few examples. Write an XML without options: In [354]: case is to limit a time series to start and end at two specific dates. To enable this, we made the design choice to make label-based slicing include both endpoints: In [235]: s.loc["c":"e"] Out[235]: c