Software developers and service operators need log files to identify issues, detect anomalies and trace execution behaviour. The amount of generated log data is increasing, and often log files need to be kept for longer periods of time due to regulations. To preserve logs in a cost-efficient manner, they are typically compressed, at certain cost for running the compression, and then stored in long-term archives, again at certain cost per size-duration products. The goal is decrease both cost components, but there are certain trade-offs, for instance a highly efficient compression that consumes a lot of CPU but leads to better compression ratios, consuming less storage capacity as a result. The decision which compression tools and parameters to use is usually hardcoded. We present a smart knowledge-based advisor service to query goal-based adaptive compression commands to maximise savings.
Automation is one of the key concerns in cloud environments. The need to introduce effort-saving automation around the process of bringing new applications to powerful cloud environments ranges from developer tooling over testing and deployment to operational concerns. According to Nokia’s Eric Bauer, application service efficiency is the ratio of service output produced to resource input consumed, and automation can significantly reduce the input effort.
Many providers of hosted services, including cloud applications, are subject to a contradiction in handling log data. On the one hand, storing logs consumes resources and should be minimised or avoided altogether to save resource cost. On the other hand, regulatory constraints such as keeping the data for the purpose of future audits exist. A smart solution to encode the data appropriately needs to be found. The coding encompasses both compression, to keep resource use low, and encryption, to prevent leaking information to unauthorised parties, for instance when logging for the purpose of intrusion detection. On an algorithmic level, the encoded data should still be usable for computation, in particular comparison and search. In this blog post, based on the didactic log example shown in the figure below, we present algorithms and architectures to handle cloud log files in a smart way.
The University of Sharjah is the national university of the Emirate of Sharjah in the UAE. Located in the University City, the world’s largest campus, its buildings convey the uniqueness that underpins its research activities, including in computer science and engineering. We are proud to have started cooperative research and the exchange of researchers many months ago. In this blog post, our latest joint work on multi-paradigm computating in a trilateral constellation with Penta is presented.