Big data gets more complex by the day. As a result, it is a constant challenge for enterprises to keep their IT infrastructure, applications, and systems fulfilling SLAs and delivering value. Increasingly, traditional monitoring tools alone are proving inadequate. Conventional performance monitoring approaches fail to keep up with the increasing scale  and pace of change within big data. The answer? Observability

What is Observability?

People often make the mistake of thinking that observability and monitoring are the same thing. However, this isn’t the case. Observability and monitoring are two distinct approaches.

Monitoring answers the “when”. Monitoring collects metrics and logs that provide information on whether the system is working, and it lets you know when something went wrong.

Observability, on the other hand, includes the “why”. Observability gives systems the ability to gather actionable data that provides not only the “when” of an error or issue, but—more importantly—the why. Dynamic reliability analysis of logs, metrics, and traces (often called the three pillars of observability), coupled with continuous monitoring, drastically shortens the duration and reduces the impact of incidents.

The Benefits of Observability

Observability gives IT Ops teams the ability to see, with analytic clarity, all of their cloud-native applications and distributed infrastructure. The big data platform and supported workloads can be overseen in a centralized location, in real time. 

Unlike traditional monitoring, observability allows IT Ops teams to do more than just accurately locate and determine issues faster. Teams are able to identify and address root causes and troubleshoot quicker with observability. With this dynamic analysis, IT Ops teams can determine relationships between objects within the environment. The pillars of observabilitymetrics, traces, and log data—enable teams to pull powerful analytics. 

Ultimately, observability allows organizations to deliver optimized experiences to their end-users, with a consistency and skill that legacy performance monitoring solutions cannot facilitate.

The Added Element: Continuous Tuning

Observability provides you with a clear view of your infrastructure. From here, continuous tuning can supercharge your big data operations.

Manually tuning and optimizing an application is taxing, even with a team of the best and brightest IT Ops experts. Complicated infrastructure, processes, and applications generate thousands of metrics every few seconds. Manual tuning on such a large scale is, unfortunately, beyond human capability.

However, even machine-assisted tuning needs to be rooted in observability. From here, continuous tuning has the information and insights it needs to be most effective. Automated and continuous tuning—augmented by dynamic reliability analysis—can be based on well-correlated data, highly actionable insights, and smart recommendations. With automation, optimal configurations are instantly discovered and applied, and the right amount of resources are allocated and deployed when needed at the infrastructure level. 

The Pepperdata Factor

The Pepperdata suite is built to capitalize on cutting-edge observability and continuous tuning technologies. 

Pepperdata provides a powerful way to achieve observability and continuous tuning for the big data analytics stack. For optimal performance on-premises or in the cloud, the Pepperdata Analytics Stack Performance (ASP) suite offers real-time monitoring and visibility for troubleshooting, debugging, planning, and automated tuning. 

The Pepperdata PepAgent collects hundreds of metrics every few seconds: application, JMX, hardware, cluster, kernel, and other custom metrics. It records user activity data, event data, and performance measures. Pepperdata also enables the creation of customized real-time alerts on specific behaviors, immediately alerting users to critical conditions that could affect system performance. The intuitive Pepperdata UI empowers all users, from seasoned IT professionals to developers, to quickly diagnose bottlenecks and tune performance.

Here, we have only scratched the surface of observability, tuning, and the increasing obsolescence of traditional monitoring solutions. To get the full picture, click below to watch our in-depth webinar on observability.

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