Observability:
Use-Cases and Examples
Observability is the practice of measuring the state of a system based on external output using metrics, logs, and traces. It is the evolution of monitoring, as it helps you learn about your IT environment’s critical aspects and discover potential problems before they arise.
Observability transforms the speed, cost, and efficiency of your machines. While Observability benefits most enterprises, the amount of observability employed should be determined by your business needs.
2025 outlook for security and telemetry data
2025 will be a year marked by significant shifts in cybersecurity regulation, the rapid growth of observability technology, and the continued burdens of managing telemetry data in a world driven by artificial intelligence and cloud migration. In this eBook, we explore for you the emerging trends and predictions that shape the future of enterprise IT and Security.
Your enterprise’s business goals include strong security, high-service stability, monitoring tools, and increased customer experience. To understand how you’re meeting those goals, you must collect and analyze data correlated with your desired outcomes.
You can start by collecting and analyzing the three main components of Observability – metrics, logs, and traces. For example, organizations collect data from different data sources and analyze it with the proper observability tools and in the right format to have a comprehensive view of how your environment is performing.
The observability platform monitors the software for any abnormal activity and network breaches. The engineers are then alerted and can mitigate the issues while adhering to data governance principles.
Data in logging systems are usually unstructured or noisy. The operations team can implement observability to process data through the pipeline, convert it in related formats and eliminate the noise from it.
Observability gives engineers control over data to identify unknowns in the system. It allows them to monitor the underlying logs, metrics, and traces for the environment to track the enterprise's digital transformation.
Observability helps organizations understand and optimize their IT systems. To use observability effectively, you should understand how your IT systems impact your goals, make a list of questions about how your systems are operating, translate those questions into things you can measure, and decide what measurements are acceptable. You can collect data for observability using servers, log scrapers or forwarders, and agents (software that collects metrics from endpoints). This will help you understand what is happening within your environment.
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With an observability pipeline, you can take data from any source and route it to any tool. Put data where it has the most value. Route data to the best tool for the job — or all the tools for the job.
An observability pipeline can help you reduce less-valuable data before you pay to analyze or store it. This process can help you dramatically slash costs, eliminate null fields, remove duplicate data, and drop fields you’ll never analyze. Using an observability pipeline means you keep all the data you need and only pay to analyze and store what’s important to you now.
Take the data you have and format it for any destination, without having to add new agents. By transforming the data you already have, and sending it to the tools your teams use, this increases flexibility without incurring the cost and effort of recollecting and storing the same data multiple times in different formats.
The Stream Sandbox lets you experience a full version of Stream LIVE right now with pre-made sources and destinations. The main course, Stream Fundamentals, will guide you interactively through the main features of Cribl Stream, and upon completion, you will earn a completion certificate.
