Putting an Invisible Shield on Kubernetes SecretsKailun 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 responsible0 码力 | 33 页 | 20.81 MB | 1 年前3
Oracle VM VirtualBox UserManual_fr_FR.pdfversion 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 . . . . . . . . . . . . . . . etc.). Ces paramètres apparaissent dans la fenêtre du gestionnaire de VirtualBox ainsi que par le pro- gramme en ligne de commande VBoxManage ; voir le chapitre 8, VBoxManage, page 121. Autrement dit, 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“0 码力 | 386 页 | 5.61 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 1.2.3tables can be concatenated both column wise as row wise and database-like join/merge operations are pro- vided to combine multiple tables of data. To introduction tutorial To user guide Straight to tutorial 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 strategies0 码力 | 3323 页 | 12.74 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 1.2.0tables can be concatenated both column wise as row wise and database-like join/merge operations are pro- vided to combine multiple tables of data. To introduction tutorial To user guide Straight to tutorial 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 strategies0 码力 | 3313 页 | 10.91 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 1.1.1tables can be concatenated both column wise as row wise and database-like join/merge operations are pro- vided to combine multiple tables of data. To introduction tutorial To user guide Straight to tutorial 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 strategies0 码力 | 3231 页 | 10.87 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 1.1.0tables can be concatenated both column wise as row wise and database-like join/merge operations are pro- vided to combine multiple tables of data. To introduction tutorial To user guide Straight to tutorial 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 strategies0 码力 | 3229 页 | 10.87 MB | 1 年前3
Oracle VM VirtualBox 7.0.0_BETA2 User ManualClean architecture and unprecedented modularity. Oracle VM VirtualBox has an ex- tremely modular design with well-defined internal programming interfaces and a clean separation of client and server code Oracle provides a single extension pack, available from: http://www.virtualbox.org. The extension pack pro- vides the following added functionality: – The virtual USB 2.0 (EHCI) device. See chapter 3.11.1 mentioned in chapter 1.3, Features Overview, page 3, Oracle VM VirtualBox has a very flexible internal design that enables you to use multiple interfaces to control the same virtual machines. For example, you0 码力 | 519 页 | 4.49 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 1.0.0(GH27283) • MultiIndex.from_arrays() will no longer infer names from arrays if names=None is explicitly pro- vided (GH27292) • In order to improve tab-completion, Pandas does not include most deprecated attributes 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 [236]: s.loc['c':'e'] Out[236]: 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 strategies0 码力 | 3015 页 | 10.78 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 1.0tables can be concatenated both column wise as row wise and database-like join/merge operations are pro- vided to combine multiple tables of data. To introduction tutorial To user guide Straight to tutorial 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 [236]: s.loc['c':'e'] Out[236]: 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 strategies0 码力 | 3091 页 | 10.16 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 1.0.4tables can be concatenated both column wise as row wise and database-like join/merge operations are pro- vided to combine multiple tables of data. To introduction tutorial To user guide Straight to tutorial 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 [236]: s.loc['c':'e'] Out[236]: 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 strategies0 码力 | 3081 页 | 10.24 MB | 1 年前3
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