Abstract: Methods, systems, and computer-readable media for energy-optimizing placement of resources in data centers are disclosed. A resource placement manager determines information descriptive of energy usage by one or more data centers. The one or more data centers comprise a plurality of computing resources in a plurality of corresponding locations. The resource placement manager selects, from the plurality of computing resources in the plurality of corresponding locations, a particular computing resource in a particular location for performing one or more computing tasks. The particular computing resource in the particular location is selected based at least in part on reducing energy usage associated with the one or more data centers according to the information descriptive of energy usage. The particular computing resource in the particular location is used to perform the one or more computing tasks.

Abstract: A system can be configured to determine whether a user is a human or a computer based on whether the user is capable of intuitive-based decision making to identify requested features. The system can generate a challenge that includes a question emphasizing mental shortcuts and associations developed through social and cultural interactions. The challenge also includes one or more media objects that are distinguishable to a human user due to the mental shortcuts and associations that permit selection of the correct media object in light of the question. Intuitive connections between statements and media objects are often difficult to implement within computer programs and algorithms due to the two-stage challenge requiring both comprehension and recognition of important features.

Abstract: Techniques for database performance degradation detection and prevention are described. A statement performance monitor observes queries executed against a database engine and clusters the queries into groups of queries. The index utilization of the query groups and execution metrics are tracked over time, and a sudden change of index utilization can be detected. The change can be reported to users and/or new indexes may be automatically generated to serve affected query groups. Additionally, a statement performance monitor may be deployed to statically analyze code to identify modified queries and the resultant change of use of query indexes.

Abstract: Technologies are provided for dynamically adaptive Bloom filters. After processing a lookup operation using a Bloom filter, a feedback message is received which can be used to determine whether the Bloom filter produced a false-positive lookup result. A Bloom filter accuracy score can be updated based on the feedback message. If the accuracy score for the Bloom filter falls below a specified threshold then the Bloom filter can be changed, or replaced with a different Bloom filter. In at least some embodiments, a plurality of Bloom filters can be created. One of the Bloom filters, designated as an active Bloom filter, can be used to process lookup operations. When a feedback message is received, accuracy scores can be updated for each of the Bloom filters. Based on the accuracy scores, the active Bloom filter can be deactivated and another Bloom filter, with a better accuracy score, can be activated.

Abstract: Systems and techniques are described for predicting future overlap in requests for a compute resource to address a system overload before it occurs. Requests for a resource may be tracked in time and grouped based on one or more common characteristics of the requests, such as a time of occurrence of the requests and a period that they repeat. Once grouped, different groups of requests for the resource may be tracked across at least one dimension, such as a periodic time of occurrence, a volume of requests, or a length of time of each occurrence of a group, to generate tracking data. Based on the tracking data, predictions may be generated indicating whether and to what extent the groups of resources will overlap at a future time. Additional resources may be provisioned to process the requests to prevent or reduce the likelihood of a system overload at the future time.