The new wave of data observability

You’ve almost certainly heard the term observability used to describe the next generation of data monitoring. Observability has become increasingly important in recent years, as software systems have become more complex and distributed, allowing organizations to measure, monitor, and understand the behavior of their various systems.

Analysts began to coin the term observability only 2-3 years ago, noting that a sharp increase in complexity required more than monitoring. If the first wave was monitoring, the second wave was observability, and the third wave – the wave we are currently in, is applied observability.

The main challenge facing today’s organizations is that it is clear that monitoring alone is not enough. Monitoring doesn’t tell you why an element is faster or slower than it was yesterday, or why it’s suddenly not working at all. Observability can not only tell you what is breaking but why it is breaking – and what to do to improve – in real time.

“By looking into how our workloads are running, we can make recommendations about how they can run better,” said Wim Stoop, senior director, product marketing for Cloudera. “And getting a handle on your costs is always a good thing.”

According to a report by Flexera, 30% of all public cloud spend on resource utilization is wasted. Optimization saves time while making efficient use of resources, ultimately allowing you to pay less, a key to financial governance.

To mitigate the surprise of enormous cloud bills, the most effective solution is to keep a tight watch on who is using what, and when. Similar to a prepaid phone plan, allocating a specific amount of resources to each use case can help prevent going over budget. Once that use case has “used up” its allotted budget each month, it will stop working, just like the prepaid cell phone.

In this context, observability has become crucial for understanding how different components of a system are interacting and affecting each other. Traditionally, monitoring software systems involved collecting logs and simple metrics. However, this approach is no longer sufficient for complex systems that operate at scale. Modern software systems can have many different components, each of which generates a vast amount of data. For example, a typical microservices-based architecture may consist of dozens or even hundreds of different services, each generating its own logs and metrics.

Observability involves collecting data from different sources and using it to provide a comprehensive view of the system’s behavior. This data includes logs, metrics, traces, and other signals that help to reveal how different components are interacting and affecting each other.

One of the key benefits of observability is that it enables system administrators and developers to detect and diagnose issues in real time. This is essential for maintaining system performance and reliability. In complex systems, issues can be hidden in the interactions between different components. Observability provides a way to detect these issues and diagnose their root causes quickly.

The Cloudera Data Platform (CDP) allows for software and workload observability as it is applied on infrastructure to determine root cause analysis of problems and make suggestions for improvements.

“Cloudera observability is different because we provide the bottled collective skills, knowledge, and resources from our professional services and support. We know better than anyone how to make our platform hum and how to make it run as smoothly and fast as possible,” said Stoop.

You can think of observability in action, or “applied observability,” akin to the Nintendo game cartridges that plugged into your old Gameboy device. Each “cartridge” looks for different challenges across your environment, just as each game lets you solve different challenges or quests in entirely different worlds. Once the engine is in place, there is no limit on how many different cartridges you can build and implement. This means the future use cases for observability are practically unlimited – scaling beyond our imagination.

Learn more about CDP.

Data Management