Data visualization is a way to make sense of the vast amount of information generated in the digital world. By converting raw data into a more understandable format, such as charts, graphs, and maps, it enables humans to see patterns, trends, and insights more quickly and easily. This helps in better decision making, strategic planning, and problem-solving. Visualization and understanding data are critical in platform-as-a-service (PaaS) offerings like Heroku.

While time series data is critical for space industries, managing that data is not always straightforward. While humans have yet to develop light-speed travel, teleportation or lots of the other cool things we see in movies or read in books, that doesn’t mean we aren’t making progress. Advances in technology are starting, ever so slowly, to blur the lines between science fiction and reality when it comes to outer space.

In the past, managing IT infrastructure was a hard job. System administrators had to manually manage and configure all of the hardware and software that was needed for the applications to run. However, in recent years, things have changed dramatically. Trends like cloud computing revolutionized—and improved—the way organizations design, develop, and maintain their IT infrastructure.

Enterprise IT is just a different animal. Whether it’s operating at scale, undertaking massive migrations, working across scores of teams, or addressing tight security requirements, engineers at these organizations can face different obstacles than their counterparts at smaller organizations and startups.

As connected as the world is today, it can feel quite disconnected, especially in IT. Individual teams use various tools, each with specialized interfaces and dedicated dashboards, to present or interpret data each the specific functional team needs.

In this livestream, Cribl’s Ahmed Kira and I explore the challenges of scaling your Cribl Stream architecture to accommodate a large number of agents, providing valuable insights on what you need to consider when expanding your Cribl Stream deployment. Managing data flows from a high volume of agents presents a unique set of challenges that need to be addressed.