Database optimization: automation, security, and resiliency

Database optimization is traditionally thought of as the process of improving the speed and efficiency of data retrieval from a database. This type of optimization results in reduced latency and increased performance and throughput of the system. Techniques to optimize database performance often include query tuning, solid state drive (SSD) storage selection, efficient schema design, and the use of indexes. Expanding database optimization to include security and resiliency ensures an organization can quickly respond to disruptive events such as a cyberattack or natural disaster. This not only improves the database performance efficiency and optimization but also reliability, sustainability and may help optimize cost. Automating database optimization processes and best practices reduces human error and protects all of the data associated workloads while alerting leadership to progress on key performance indicators. This paper describes processes, techniques and tools that can be used to help automate database optimization through a security or resiliency lens. Publicly available large datasets were used to demonstrate the application of database optimization techniques that included automating routine tasks and performing data analytics to help identify and alert administrators to issues requiring additional action.