Big Data Observability and Continuous Tuning at Scale
Increasingly, many organizations find that their current legacy monitoring solutions are no longer adequate in today’s modern IT world. These enterprises find themselves struggling to manage and understand unprecedented amounts of data. With such large amounts of data needing to be dealt with, it is no wonder why it’s a struggle for enterprises to leverage it for business success. Not to mention that optimizing performance and keeping costs in line is a technical challenge they must face at the same time.
So what’s the solution? Effective observability and continuous tuning. Big data application performance requires observability and continuous tuning to treat infrastructure and application performance as an integrated function. These capabilities capture and correlate the performance data from each domain to fully inform both development and operations teams. This allows for faster troubleshooting, better collaboration between teams, and overall better performance.
Observability is an integral aspect of managing your big data applications and systems. In fact, effective observability is key to understanding the internal states of a big data system so that action can be taken. However, many people are unclear as to what observability actually is, or what makes it so important when optimizing infrastructure. Others mistake observability as simply monitoring. While the two concepts are complementary, they are very different. We’ll cover the differences between the two, and we’ll share how relying solely on traditional monitoring solutions can leave gaps in your teams’ understanding of the big data stack in this white paper.
Download the Big Data Observability and Continuous Tuning at Scale white paper to take the first step towards ensuring your organization is on track towards observability. You’ll come away from the white paper understanding exactly what observability is and isn’t, how continuous tuning compliments observability, which steps your organization can take to achieve observability, how a lack of automation can hinder business success, and much more.