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As applications grow in complexity, the ability to gather, process, and analyze logs becomes crucial for maintaining system health and troubleshooting issues. Two popular open-source log collectors have emerged as frontrunners in this space: FluentD and FluentBit. But how do you choose between them? This article dives deep into the FluentD vs FluentBit debate, exploring their features, performance, and use cases to help you make an informed decision.

We are excited to announce the launch of Elastic's Support Assistant. This blog takes you through a tour of our latest generative AI tool and some common scenarios where it can help with your own use of Elastic technology.

Docker is a popular platform that enables developers to package, distribute, and run applications within isolated environments called containers. Logs play an important role in the use of Docker for numerous reasons. For example, The running of Docker containers in isolation makes it difficult to handle troubleshooting issues and monitor application behavior effectively in the absence of detailed logging.

Designed in the early 1990s Python was built to emphasize code readability and on the principle that there should be one way to do things. Python is one of the most popular programming languages and is utilized for a range of purposes including machine learning, web applications, and data analysis.

AWS MediaTailor provides a wealth of information via metrics, but one key feature that is very difficult to track is the Transcoding performance. What is transcoding and why is performance important?

Modern enterprises are more dependent than ever on data. That's why it's more important than ever for organizations to ensure that their data is accurate, reliable, and easily accessible. Data observability is a modern method that helps achieve this. It involves real-time monitoring of data to detect unusual patterns. By doing so, it ensures data quality and reliability, which boosts operational efficiency and governance.

Centralizing logs (arranging all records in one place) is often challenging as we need to decide whether to use a log shipper or directly log from the application. If you are not familiar with a log shipper, logging directly from the library might be a suitable option for development (it is easy to configure). However, in production, you'll likely want to use one of the available log shippers, mainly due to buffers, since blocking the application or dropping data (immediately) may not be an option.

Data is wealth. Extracting insights from data is valuable for any organization—data aids in making informed decisions, optimizing operations and costs, and understanding how customers behave. However, reaping the benefits of data requires an investment in the right tools, resources, and people — something smaller organizations may not have the means to do.

System logging protocol, abbreviated as Syslog, is a standard protocol used for message logging. Put simply, it is a standard for collecting and storing log information. A Syslog server collects, parses, stores, examines, and dispatches log messages from devices including routers, switches, firewalls, Linux/Unix hosts, and Windows machines.