The Future of Learning: Embracing Social Learning for SuccessSaba Software
Today, the world is grounded in a vast and dynamic world of information and technology. Organizations
have access to content like never before, compounded by the Web 2.0 movement. This ability to
communicate swiftly evolved into collaboration that has become an intense driver of the “knowledge
economy.”
During the last two years we have seen how knowledge management and leadership development
via learning are being incorporated more frequently as strategies to increase organizational agility.1
Additionally, learning organizations that act as strategic enablers for the business are more focused on
connecting people to people and content through knowledge management and social technology.
Saba Software partnered with Human Capital Media (HCM) Advisory Group to better understand how
business is taking advantage of social learning. In the 2013 survey, HCM examined how organizations are
approaching social learning, which methods have proven to be successful and where challenges are experienced.
Hardware fails, applications fail, our code... well, it fails too (at least mine). To prevent software failure we test. Hardware failures are inevitable, so we write code that tolerates them, then we test. From tests we gather metrics and act upon them by improving parts that perform inadequately. Measuring right things at right places in an application is as much about good engineering practices and maintaining SLAs as it is about end user experience and may differentiate successful product from a failure.
In order to act on performance metrics such as max latency and consistent response times we need to know their accurate value. The problem with such metrics is that when using popular tools we get results that are not only inaccurate but also too optimistic.
During my presentation I will simulate services that require monitoring and show how gathered metrics differ from real numbers. All this while using what currently seems to be most popular metric pipeline - Graphite together with metrics.dropwizard.io library - and get completely false results. We will learn to tune it and get much better accuracy. We will use JMeter to measure latency and observe how falsely reassuring the results are. Finally I will show how HdrHistogram helps in gathering reliable metrics. We will also run tests measuring performance of different metric classes.
