If you're aiming for a position that demands strong monitoring and observability skills, thorough preparation is essential. In this comprehensive guide, we will provide an extensive list of the most frequently asked interview questions about the three pillars of observability; logs, metrics and tracing. Each question is also accompanied by detailed, well-explained answers to ensure that you fully understand the concepts and can confidently demonstrate your expertise.

As an Observability Strategist at Splunk, I have the unique privilege of partnering with a diverse range of Splunk customers across various industries. This partnership offers me a deeper insight into their essential Observability use cases, how they are utilizing Splunk’s Observability solutions, and their specific needs to maximize both value and efficiency in their Observability practices.

The term “observability” is a strange one. We understand its value as a way to describe a sophisticated approach to monitoring complex distributed systems and microservices. But the term is inherently passive (and let’s be honest. It’s a bit of a loaded marketing term). Simply “observing” doesn’t help you solve problems – especially if you are inundated with loads of non-actionable data.

Artificial intelligence is a game-changing technology across industries and business processes, designed to make workers more efficient, reduce the steps it takes to complete a task, and gain answers and insights faster. But those powerful capabilities also put new demands on compute infrastructure and this requires a new class of infrastructure observability metrics.

Computing environments are more dynamic, distributed, and complex than ever. Observability tools help collect, monitor, and interpret the data they generate — like logs, metrics, and traces — to give IT teams and leaders real-time insights that can help detect issues, troubleshoot solutions, and improve the reliability of their IT systems. But observability tools can’t do their job without a strong infrastructure foundation and the right tools to manage it.

So, your company uses LLMs? You’re not the only ones. A survey by Gartner in October 2023 revealed that 55% of organizations were piloting or releasing generative AI projects, and it’s safe to assume that this number has increased since that survey was published. From personalized recommendations in e-commerce, to automated grading in education and fraud detection in finance, LLMs have helped many organizations level up.

If your application is as busy as a highway with multiple lanes, intersections, and exits, imagine trying to track the journey of a single car from start to finish. Sounds tricky, right? Well, that's what happens when you're dealing with modern, complex software systems. Enter distributed tracing, your trusty GPS for navigating the intricate web of microservices and dependencies within your applications.

Autonomous IT operations requires 100 percent visibility of hybrid IT environments. With that in mind, OpsRamp, a Hewlett Packard Enterprise company, today announced a new network observability solution to help enterprise IT organizations, global systems integrators (GSIs) and managed service providers (MSPs) better manage the mission-critical network infrastructure that connects and powers their hybrid cloud systems.

Full stack observability is not merely about collecting data but about providing actionable insights. It empowers you to see beyond isolated metrics and logs, facilitating a deeper understanding of the interconnected nature of modern software systems. By implementing full stack observability, you can maintain operational integrity, swiftly address performance issues, and ensure a seamless user experience.

In today's fast-paced digital landscape, maintaining robust and efficient IT operations is more critical than ever. As organizations embrace complex infrastructures, integrating cloud services, microservices, and distributed architectures, the need for comprehensive visibility across the entire stack becomes paramount.