Abstract: Techniques are disclosed for a client-and-server architecture where the client makes scheduled execution of instances to the server. The server may then launch occurrences as indicated by one of these API calls at each of the scheduled times. The server may also implement operations to selectively execute particular occurrences, such as executing a new occurrence only when no other occurrences are still running. In other embodiments, the server may implement pricing information in a determination of whether to execute a particular occurrence.

Abstract: A multi-tenant provider network may implement confidential data capture and analysis for virtual computing resources. Network traffic for virtual compute instances may be evaluated to identify possible malicious behavior of the virtual compute instances. In some embodiments, a stream of raw metering data for individual network communications to the virtual compute instances may be evaluated. A confidential analysis may be performed for identified virtual compute instances, evaluating confidential data utilized by the virtual compute instances for malicious software. Results of the confidential analysis may be generated according to an access policy that restricts access to the confidential data. The results may be provided to a client that is restricted from accessing the confidential data according to the access policy.

Abstract: Techniques are disclosed for a client-and-server architecture where the client makes scheduled execution of instances to the server. The server may then launch occurrences as indicated by one of these API calls at each of the scheduled times. The server may also implement operations to selectively execute particular occurrences, such as executing a new occurrence only when no other occurrences are still running. In other embodiments, the server may implement pricing information in a determination of whether to execute a particular occurrence.