In today's digital landscape, organizations rely on software applications to meet the demands of their customers. To ensure the performance and reliability of these applications, observability pipelines play a crucial role. These pipelines gather, process, and analyze real-time data on software system behavior, helping organizations detect and solve issues before they become more significant problems. The result is a data-driven decision-making process that provides a competitive edge.

Today, businesses are generating more data than ever before. However, with this data explosion comes a new set of challenges, including increased complexity, higher costs, and difficulty extracting value. With this in mind, how can organizations effectively manage this data to extract value and solve the challenges of the modern data stack?

We are using data wrong. In today’s data-driven world, we have learned to store data. Our data storage capabilities have grown exponentially over the decades, and everyone can now store petabytes of data. Let’s all collectively pat ourselves on the back. We have won the war on storing data! Congratulations!

In data management, numerous roles rely on and regularly use telemetry data. The security engineer is one of these roles. Security engineers are the vigilant sentries, working diligently to identify and address vulnerabilities in the software applications and systems we use and enjoy today. Whether it’s by building an entirely new system or applying current best practices to enhance an existing one, security engineers ensure that your systems and data are always protected.

In today’s fast paced and constantly evolving digital landscape, observability has become a critical component of effective software development. Companies are relying more on and using machine and telemetry data to fix customer problems, refine software and applications, and enhance security. However, while more data has empowered teams with more insights, the value derived from that data isn’t keeping pace with this growth. So how can these teams derive more value from telemetry data?

In today's digital age, organizations increasingly depend on their technology infrastructure to keep their operations running smoothly. These infrastructures include servers, networking equipment, IoT devices, and applications. The data generated by all this infrastructure (logs, metrics, traces) is known as telemetry data, which has a tremendous potential value to organizations. However, it can be challenging to control telemetry data and utilize it effectively.

In data management, numerous roles rely on and regularly use telemetry data. The developer is one of these roles. Developers are the creative masterminds behind the software applications and systems we use and enjoy today. From conception to finished product, they map out, build, test, and maintain software.

As we begin the new year, it is customary to reflect and identify areas we can continue to grow in 2023. Whether it’s joining the local gym, starting a new diet, or taking up a new hobby, this time is always full of promise to continually improve. The same can be said for digital businesses of every size and across every vertical. Macroeconomic trends have especially made this time one of reflection for a number of organizations.

In data management, numerous roles rely on and regularly use observability data. The Site Reliability Engineer is one of these roles. Site Reliability Engineers (SREs) work on the digital frontlines, ensuring performant experiences by using observability data to maintain stability and awareness of software running in various environments across organizations.

Observability is the ability to see and understand the internal state of a system from its external outputs. Logs, Metrics, and Traces, collectively called observability data, are external outputs widely considered to be three pillars of observability.