 Rancher Kubernetes Cryptographic Library
FIPS 140-2 Non-Proprietary Security PolicyRecommendation for the Triple Data Encryption Algorithm (TDEA) Block Cipher 11/17/2017 [SP 800-90A r1] NIST SP 800-90A Rev. 1, Recommendation for Random Number Generation Using Deterministic Random Bit r2] NIST SP 800-133 Rev. 2, Recommendation for Cryptographic Key Generation 6/4/2020 [SP 800-135 r1] NIST SP 800-135 Rev. 1, Recommendation for Existing Application-Specific Key Derivation Functions A865 CVL [SP 800-135 r1] TLS 1.0/1.1 and 1.2 KDF Key Derivation Vendor Affirmed CKG [SP 800-133 r2] Cryptographic Key Generation Key Generation A865 DRBG [SP 800-90A r1] AES-256 CTR_DRBG0 码力 | 16 页 | 551.69 KB | 1 年前3 Rancher Kubernetes Cryptographic Library
FIPS 140-2 Non-Proprietary Security PolicyRecommendation for the Triple Data Encryption Algorithm (TDEA) Block Cipher 11/17/2017 [SP 800-90A r1] NIST SP 800-90A Rev. 1, Recommendation for Random Number Generation Using Deterministic Random Bit r2] NIST SP 800-133 Rev. 2, Recommendation for Cryptographic Key Generation 6/4/2020 [SP 800-135 r1] NIST SP 800-135 Rev. 1, Recommendation for Existing Application-Specific Key Derivation Functions A865 CVL [SP 800-135 r1] TLS 1.0/1.1 and 1.2 KDF Key Derivation Vendor Affirmed CKG [SP 800-133 r2] Cryptographic Key Generation Key Generation A865 DRBG [SP 800-90A r1] AES-256 CTR_DRBG0 码力 | 16 页 | 551.69 KB | 1 年前3
 Stream processing fundamentals - CS 591 K1: Data Stream Processing and Analytics Spring 2020a mathematical structure, e.g. a sequence of (finite) relation states over a common schema R: [r1(R), r2(R), ..., ], where the individual relations are unordered sets. src dest bytes 1 2 20K 2 relations. • as a list of tuple-index pairs, where Stream processing fundamentals - CS 591 K1: Data Stream Processing and Analytics Spring 2020a mathematical structure, e.g. a sequence of (finite) relation states over a common schema R: [r1(R), r2(R), ..., ], where the individual relations are unordered sets. src dest bytes 1 2 20K 2 relations. • as a list of tuple-index pairs, where- indicates that t ∈ rj • as a serialization of r1 followed by a series of delta tuples that indicate updates to make to obtain r2, r3, ..., etc. 20K 2 5 32K 2 3 28K src dest bytes 1 2 20K 2 5 32K src dest bytes 2 5 32K 2 3 28K 1 2 28K R1 R2 R3 • concatenation (1, 2, 20K), (2, 5, 32K) EOR (1, 2, 20K), (2, 5, 32K), (2, 3, 28K) EOR (2, 0 码力 | 45 页 | 1.22 MB | 1 年前3
 Istio at Scale: How eBay is building a massive Multitenant Service Mesh using Istiolocations across globe peering with the Internet closer to the customer ○ PoPs are mini AZs Region R1 AZ 1 AZ 2 AZ n Data Center DC1 Region Rn #IstioCon Application Deployment: Cloud Layout ● Multiple scenario Region R1 AZ 1 AZ 2 AZ n Data Center DC1 K8s Cluster K8s Cluster K8s Cluster K8s Cluster K8s Cluster K8s Cluster Region Rn #IstioCon Application Specs Region R1 Application specs ● Standardization provides flexibility to switch backend implementations to software Region R1 AZ 1 AZ 2 AZ n Data Center DC1 K8s Cluster K8s Cluster K8s Cluster K8s Cluster AZ0 码力 | 22 页 | 505.96 KB | 1 年前3 Istio at Scale: How eBay is building a massive Multitenant Service Mesh using Istiolocations across globe peering with the Internet closer to the customer ○ PoPs are mini AZs Region R1 AZ 1 AZ 2 AZ n Data Center DC1 Region Rn #IstioCon Application Deployment: Cloud Layout ● Multiple scenario Region R1 AZ 1 AZ 2 AZ n Data Center DC1 K8s Cluster K8s Cluster K8s Cluster K8s Cluster K8s Cluster K8s Cluster Region Rn #IstioCon Application Specs Region R1 Application specs ● Standardization provides flexibility to switch backend implementations to software Region R1 AZ 1 AZ 2 AZ n Data Center DC1 K8s Cluster K8s Cluster K8s Cluster K8s Cluster AZ0 码力 | 22 页 | 505.96 KB | 1 年前3
 Flow control and load shedding - CS 591 K1: Data Stream Processing and Analytics Spring 2020L2=18.75 O2 I1 c=10 s=0.5 c=10 s=0.8 c=5 s=1.0 O1 c=10 s=0.9 L1=26.5 5 14 5 5 19 5 r1=10 r/s r2=20 r/s ??? Vasiliki Kalavri | Boston University 2020 13 I2 c=10 s=0.7 c=10 s=0.5 L2=18.75 O2 I1 c=10 s=0.5 c=10 s=0.8 c=5 s=1.0 O1 c=10 s=0.9 L1=26.5 5 14 5 5 19 5 r1=10 r/s r2=20 r/s LT=? ??? Vasiliki Kalavri | Boston University 2020 13 I2 c=10 s=0.7 c=10 s=0 L2=18.75 O2 I1 c=10 s=0.5 c=10 s=0.8 c=5 s=1.0 O1 c=10 s=0.9 L1=26.5 5 14 5 5 19 5 r1=10 r/s r2=20 r/s LT=640 cycles/s ??? Vasiliki Kalavri | Boston University 2020 Reacting to overload0 码力 | 43 页 | 2.42 MB | 1 年前3 Flow control and load shedding - CS 591 K1: Data Stream Processing and Analytics Spring 2020L2=18.75 O2 I1 c=10 s=0.5 c=10 s=0.8 c=5 s=1.0 O1 c=10 s=0.9 L1=26.5 5 14 5 5 19 5 r1=10 r/s r2=20 r/s ??? Vasiliki Kalavri | Boston University 2020 13 I2 c=10 s=0.7 c=10 s=0.5 L2=18.75 O2 I1 c=10 s=0.5 c=10 s=0.8 c=5 s=1.0 O1 c=10 s=0.9 L1=26.5 5 14 5 5 19 5 r1=10 r/s r2=20 r/s LT=? ??? Vasiliki Kalavri | Boston University 2020 13 I2 c=10 s=0.7 c=10 s=0 L2=18.75 O2 I1 c=10 s=0.5 c=10 s=0.8 c=5 s=1.0 O1 c=10 s=0.9 L1=26.5 5 14 5 5 19 5 r1=10 r/s r2=20 r/s LT=640 cycles/s ??? Vasiliki Kalavri | Boston University 2020 Reacting to overload0 码力 | 43 页 | 2.42 MB | 1 年前3
 Streaming languages and operator semantics - CS 591 K1: Data Stream Processing and Analytics Spring 2020denoted S ⊆τ R. In general, if S1, ..., Sn and R1, ..., Rn be timestamped sequences, then (S1, ..., Sn) ⊆τ (R1, ..., Rn) when (S1, ..., Sn) = (R1, ..., Rn) for some τ . 47 Vasiliki Kalavri | Boston0 码力 | 53 页 | 532.37 KB | 1 年前3 Streaming languages and operator semantics - CS 591 K1: Data Stream Processing and Analytics Spring 2020denoted S ⊆τ R. In general, if S1, ..., Sn and R1, ..., Rn be timestamped sequences, then (S1, ..., Sn) ⊆τ (R1, ..., Rn) when (S1, ..., Sn) = (R1, ..., Rn) for some τ . 47 Vasiliki Kalavri | Boston0 码力 | 53 页 | 532.37 KB | 1 年前3
 动手学深度学习 v2.0。假设我们读取了一个 批量的样本X,其中特征维度(输入数量)为d,批量大小为n。此外,假设我们在输出中有q个类别。那么小 批量样本的特征为X ∈ Rn×d,权重为W ∈ Rd×q,偏置为b ∈ R1×q。softmax回归的矢量计算表达式为: O = XW + b, ˆY = softmax(O). (3.4.5) 相对于一次处理一个样本,小批量样本的矢量化加快了X�W的矩阵‐向量乘法。由于X中的每一行代表一个数 variable)或隐藏变量(hidden variable)。因为隐藏层和输出层都是全连接的,所以我们有隐藏层权重W(1) ∈ Rd×h 和隐藏层偏置b(1) ∈ R1×h 以及输出层权重W(2) ∈ Rh×q 和输出层偏置b(2) ∈ R1×q。形式上,我们按如下方式计算单隐藏层多层感知机 的输出 O ∈ Rn×q: H = XW(1) + b(1), O = HW(2) + b(2). (4 3)中,我们拥有的隐藏层权重参数为Wxh ∈ Rd×h,偏置参数为bh ∈ R1×h,以及隐藏单元的数目为h。 因此求和时可以应用广播机制(见 2.1.3节)。接下来,将隐藏变量H用作输出层的输入。输出层由下式给出: O = HWhq + bq, (8.4.4) 其中,O ∈ Rn×q是输出变量,Whq ∈ Rh×q是权重参数,bq ∈ R1×q是输出层的偏置参数。如果是分类问题, 我们可以用softmax(O)0 码力 | 797 页 | 29.45 MB | 1 年前3 动手学深度学习 v2.0。假设我们读取了一个 批量的样本X,其中特征维度(输入数量)为d,批量大小为n。此外,假设我们在输出中有q个类别。那么小 批量样本的特征为X ∈ Rn×d,权重为W ∈ Rd×q,偏置为b ∈ R1×q。softmax回归的矢量计算表达式为: O = XW + b, ˆY = softmax(O). (3.4.5) 相对于一次处理一个样本,小批量样本的矢量化加快了X�W的矩阵‐向量乘法。由于X中的每一行代表一个数 variable)或隐藏变量(hidden variable)。因为隐藏层和输出层都是全连接的,所以我们有隐藏层权重W(1) ∈ Rd×h 和隐藏层偏置b(1) ∈ R1×h 以及输出层权重W(2) ∈ Rh×q 和输出层偏置b(2) ∈ R1×q。形式上,我们按如下方式计算单隐藏层多层感知机 的输出 O ∈ Rn×q: H = XW(1) + b(1), O = HW(2) + b(2). (4 3)中,我们拥有的隐藏层权重参数为Wxh ∈ Rd×h,偏置参数为bh ∈ R1×h,以及隐藏单元的数目为h。 因此求和时可以应用广播机制(见 2.1.3节)。接下来,将隐藏变量H用作输出层的输入。输出层由下式给出: O = HWhq + bq, (8.4.4) 其中,O ∈ Rn×q是输出变量,Whq ∈ Rh×q是权重参数,bq ∈ R1×q是输出层的偏置参数。如果是分类问题, 我们可以用softmax(O)0 码力 | 797 页 | 29.45 MB | 1 年前3
 Streaming in Apache FlinkReduceFunction Streaming in Apache FlinkReduceFunction- { public SensorReading reduce(SensorReading r1, SensorReading r2) { return r1.value() > r2.value() ? r1 : r2; } } private static class MyWindowFunction extends ProcessWindowFunction< 0 码力 | 45 页 | 3.00 MB | 1 年前3
 High-availability, recovery semantics, and guarantees - CS 591 K1: Data Stream Processing and Analytics Spring 2020false, it definitely isn’t Separate bloom filters for every 10-minute range to avoid saturation r1 is delivered a second time and a catalog lookup is issued to verify it is a duplicate Vasiliki false, it definitely isn’t Separate bloom filters for every 10-minute range to avoid saturation r1 is delivered a second time and a catalog lookup is issued to verify it is a duplicate r8 is a0 码力 | 49 页 | 2.08 MB | 1 年前3 High-availability, recovery semantics, and guarantees - CS 591 K1: Data Stream Processing and Analytics Spring 2020false, it definitely isn’t Separate bloom filters for every 10-minute range to avoid saturation r1 is delivered a second time and a catalog lookup is issued to verify it is a duplicate Vasiliki false, it definitely isn’t Separate bloom filters for every 10-minute range to avoid saturation r1 is delivered a second time and a catalog lookup is issued to verify it is a duplicate r8 is a0 码力 | 49 页 | 2.08 MB | 1 年前3
 Dapr september 2023 security audit reportRepeat("Abc", 10000000000) r1 := strings.NewReader(longString) r2 := strings.NewReader(longString) r3 := strings.NewReader(longString) body := io.NopCloser(io.MultiReader(r1, r2, r3)) resp := &http.Response{Body:0 码力 | 47 页 | 1.05 MB | 1 年前3 Dapr september 2023 security audit reportRepeat("Abc", 10000000000) r1 := strings.NewReader(longString) r2 := strings.NewReader(longString) r3 := strings.NewReader(longString) body := io.NopCloser(io.MultiReader(r1, r2, r3)) resp := &http.Response{Body:0 码力 | 47 页 | 1.05 MB | 1 年前3
 OpenShift Container Platform 4.9 节点中调度的一个重要用例是支持灵活的关联性和反关联性策略。 3.1.1.1. 基 基础 础架 架构 构拓扑 拓扑级别 级别 管理员可以通过在节点上指定标签,为基础架构(节点)定义多个拓扑级别。例 如,region=r1、zone=z1、rack=s1。 这些标签名称没有特别的含义,管理员可以自由为其基础架构级别命名,比如城市/楼宇/房间。另外,管 理员可以为其基础架构拓扑定义任意数量的级别,通常三个级别比较适当(例如:regions 1. 带 带有添加卷的部署配置示例 有添加卷的部署配置示例 添加卷源 添加卷源 emptyDir。 。 为 为复制控制器 复制控制器 r1 添加含有 添加含有 secret secret1 的卷 的卷 v1 并挂 并挂载 载到容器中的 到容器中的 /data: : 提示 提示 kind: DeploymentConfig ports: - containerPort: 8080 protocol: TCP $ oc set volume rc/r1 --add --name=v1 --type=secret --secret-name='secret1' --mount- path=/data OpenShift Container Platform0 码力 | 374 页 | 3.80 MB | 1 年前3 OpenShift Container Platform 4.9 节点中调度的一个重要用例是支持灵活的关联性和反关联性策略。 3.1.1.1. 基 基础 础架 架构 构拓扑 拓扑级别 级别 管理员可以通过在节点上指定标签,为基础架构(节点)定义多个拓扑级别。例 如,region=r1、zone=z1、rack=s1。 这些标签名称没有特别的含义,管理员可以自由为其基础架构级别命名,比如城市/楼宇/房间。另外,管 理员可以为其基础架构拓扑定义任意数量的级别,通常三个级别比较适当(例如:regions 1. 带 带有添加卷的部署配置示例 有添加卷的部署配置示例 添加卷源 添加卷源 emptyDir。 。 为 为复制控制器 复制控制器 r1 添加含有 添加含有 secret secret1 的卷 的卷 v1 并挂 并挂载 载到容器中的 到容器中的 /data: : 提示 提示 kind: DeploymentConfig ports: - containerPort: 8080 protocol: TCP $ oc set volume rc/r1 --add --name=v1 --type=secret --secret-name='secret1' --mount- path=/data OpenShift Container Platform0 码力 | 374 页 | 3.80 MB | 1 年前3
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 RancherKubernetesCryptographicLibraryFIPS140NonProprietarySecurityPolicyStreamprocessingfundamentalsCS591K1DataProcessingandAnalyticsSpring2020g2sIstioAtScaleeBaySudhiFlowcontrolloadsheddingStreaminglanguagesoperatorsemantics动手深度学习v2inApacheFlinkHighavailabilityrecoveryguaranteesDaprseptember2023securityauditreportOpenShiftContainerPlatform4.9节点













