Democratising Log Analytics with Open Data and Open Source

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Log analytics is the process of collecting, analyzing, and visualizing log data generated by various infrastructure components. It provides crucial insights into the health, performance, and security of digital environments. Traditionally, log analytics tools have been associated with high costs, complex setups, and proprietary solutions, creating a significant barrier to entry for smaller organizations and startups.

This talk will delve into the following key points:

1. The Power of Open Data: We will discuss the significance of open data format like Parquet.

2. Open Source Tools and Frameworks: Modern, Open Source log stack tools, like Vector, FluentBit, Parseable have gained popularity for their flexibility, scalability, and cost-effectiveness. We will explore how these tools can be leveraged to build robust log analytics pipelines.

3. Challenges and Solutions: Democratizing log analytics also comes with its own set of challenges, such as data privacy, security, and scalability. We will discuss strategies and best practices for addressing these challenges while ensuring the responsible use of open data.

4. Real-world Use Cases: Through case studies and practical examples, we will demonstrate how organizations, regardless of size or budget, can implement open-source log analytics solutions to gain valuable insights into their systems, troubleshoot issues, and proactively optimize their operations.

By attending this talk, participants will gain a comprehensive understanding of how Open Data and Open Source technologies are democratizing log analytics, enabling organizations to harness the power of their data without breaking the bank. Whether you are a developer, system administrator, data scientist, or business leader, this talk will provide valuable insights into the democratization of log analytics and its potential to drive innovation and efficiency in your organization.

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