Abstract: In some aspects, the techniques described herein relate to a system that is configured to perform operations including: generating first transfer data associated with transferring a first container image to a destination computer system, wherein the first container image is associated with a first layer and a second layer; storing first tracking data representing that the first layer and the second layer have been transferred to the destination computer system; receiving a first request to transfer a second container image to the destination computer system, wherein the second container image includes the first layer and a third layer; and based on receiving the first request, generating second transfer data associated with the second container image based on the first tracking data, wherein the second transfer data includes the third layer and a first indication that the second container image is associated with the first layer.

Abstract: Techniques for data correlation across data sources are presented herein. In some examples, a method includes the steps of retrieving a first datagram from a first data structure, wherein the first datagram represents a first update to a first data source; determining, by a first routine, a first correlation between the first datagram and a second datagram that is stored in a second data structure; based on determining the first correlation, updating the second datagram in accordance with first datagram; determining, by a second routine, whether the second datagram satisfies a completion condition; and based on determining that the second datagram satisfies the completion condition, storing the second datagram in the first data structure.

Abstract: Techniques for data correlation across data sources are presented herein. In some examples, a method includes the steps of retrieving a first datagram from a first data structure, wherein the first datagram represents a first update to a first data source; determining, by a first routine, a first correlation between the first datagram and a second datagram that is stored in a second data structure; based on determining the first correlation, updating the second datagram in accordance with first datagram; determining, by a second routine, whether the second datagram satisfies a completion condition; and based on determining that the second datagram satisfies the completion condition, storing the second datagram in the first data structure.

Abstract: Techniques for performing sequential data enrichment are presented herein. In some examples, a data enrichment system includes an input pipeline and a set of enrichment routines. In some examples, a datagram is retrieved from the input pipeline and an enrichment type associated with the retrieved datagram is determined. In some examples, after determining the enrichment type that is associated with the retrieved datagram, the datagram is processed by the enrichment routine that corresponds to the enrichment type to determine an enriched datagram. In some examples, the enriched datagram is stored in the input pipeline, which can enable determining a new enrichment type associated with the enriched datagram or storing the enriched datagram in an output pipeline if it is determined that the enriched datagram is not associated with any enrichment types.

Abstract: Techniques for enabling secure access to data using data blocks is described. Computing device(s) can provide instruction(s) to a component associated with an entity, wherein the instruction(s) are associated with an identifier corresponding to a data block of a plurality of data blocks. The computing device(s) can receive, from the component, data associated with the component, wherein the data is associated with the identifier and is indicative of a state of the component. The computing device(s) can store the data in the data block and monitor, using rule(s), changes to the state of the component based at least partly on the data in the data block. As a result, techniques described herein enable near real-time—and in some examples, automatic—reporting and/or remediation for correcting changes to the state of the component using data that is securely accessed by use of data blocks.

Abstract: Techniques for enabling secure access to data using data blocks is described. Computing device(s) can provide instruction(s) to a component associated with an entity, wherein the instruction(s) are associated with an identifier corresponding to a data block of a plurality of data blocks. The computing device(s) can receive, from the component, data associated with the component, wherein the data is associated with the identifier and is indicative of a state of the component. The computing device(s) can store the data in the data block and monitor, using rule(s), changes to the state of the component based at least partly on the data in the data block. As a result, techniques described herein enable near real-time—and in some examples, automatic—reporting and/or remediation for correcting changes to the state of the component using data that is securely accessed by use of data blocks.

Abstract: Techniques for monitoring user experience for cloud-based services, availed via an entity, are described. Server computing device(s) can receive, from a user device using a cloud-based service, data associated with component(s) of the user device, wherein the data is indicative of a user experience associated with the user device while using the cloud-based service. The server computing device(s) can monitor, using rule(s) and based at least partly on the data, changes to a state of the user device. The server computing device(s) can determine, based at least partly on the monitoring, an occurrence of a trigger event associated with a remedial action and can effectuate the remedial action. As a result, techniques described herein enable near real-time—and in some examples, automatic—reporting and/or remediation for preventing and/or correcting changes to the state of the user device that can cause poor user experiences.