Abstract: Disclosed are various embodiments for predicting and classifying events that create a sudden or substantial increase in network traffic activity. To begin, an increase of network activity can be detected. Upon detecting the increase in network activity, it can be determined that the increase in network activity is unexpected in view of one or more predicted activity events. The system can be adjusted to reduce the network activity in response to determining that the increase in network activity is unexpected.

Abstract: A computing resource service provider may operate a secure proxy fleet within a content delivery network. The secure proxy fleet may protect sensitive data communicated between a client device and a backend service over one or more networks, for example, over the content delivery network to a computing resource service provider environment. The secure proxy fleet may protect sensitive data by encrypting the sensitive data before it is forwarded to a destination.

Abstract: Technologies are disclosed herein for statistical machine translation. In particular, the disclosed technologies include extensions to conventional machine translation pipelines: the use of multiple domain-specific and non-domain-specific dynamic language translation models and language models; cluster-based language models; and large-scale discriminative training. Incremental update technologies are also disclosed for use in updating a machine translation system in four areas: word alignment; translation modeling; language modeling; and parameter estimation. A mechanism is also disclosed for training and utilizing a runtime machine translation quality classifier for estimating the quality of machine translations without the benefit of reference translations.

Abstract: A computing resource service provider may operate a secure proxy fleet responsible for directing network traffic to one or more backend services. The network traffic may be received over a cryptographically protected communications session at a secure proxy device. The secure proxy device may detect sensitive data included in the network traffic and encrypt the sensitive data to protect the sensitive data during transmission to the backend service.

Abstract: A computing resource service provider may operate a secure proxy fleet responsible for directing network traffic from one or more backend services to one or more client devices. The network traffic may be encrypted or otherwise obfuscated to protect sensitive data. The secure proxy device may detect encrypted data and may decrypt the data prior to forwarding the data to the one or more client devices.

Abstract: A computing resource service provider may operate a secure proxy fleet within a content delivery network. The secure proxy fleet may protect sensitive data communicated between a client device and a backend service over one or more networks, for example, over the content delivery network to a computing resource service provider environment. The secure proxy fleet may protect sensitive data by encrypting the sensitive data before it is forwarded to a destination.

Abstract: Disclosed are various embodiments for predicting and classifying events that create a sudden or substantial increase in network traffic activity. To begin, an increase of network activity can be detected. Upon detecting the increase in network activity, it can be determined that the increase in network activity is unexpected in view of one or more predicted activity events. The system can be adjusted to reduce the network activity in response to determining that the increase in network activity is unexpected.

Abstract: Disclosed are various embodiments for predicting and classifying events that create a sudden and substantial increase in network traffic activity. To begin, a sales event may be predicted based on the results following the search for one or more prediction factors that occur during a predefined period of time. Based either on the individual results of each evaluation or a combination of results of the search of two or more of the prediction factors, a sales event may be predicted. Additionally, upon detection of a sudden and substantial increase in network traffic activity, one or more classification factors may be evaluated to determine whether the cause of the increase is due to a sales event or other type of alternative activity event.