Costs and Effort Drastically Reduced! The New Standard for Smart SIEM Operations via Data Pipelines1/15/2026
- Table of contents
Introduction Ensuring cybersecurity and operational efficiency is becoming increasingly important for corporate information systems. However, while the volume of data to be managed is growing and security requirements are becoming more complex, IT budgets are currently remaining at only moderate growth. In this article, we will explain the latest trends in SIEM (Security Information and Event Management) operations: how to utilize data pipeline products to smartly collect, transfer, and analyze vast amounts of data, along with the benefits of implementation. Based on industry trends and specific use cases, we will guide you from the current challenges to their solutions Current status and challenges in SIEM operation design - The Gap Between Increasing Data Volume and IT Budgets When considering the implementation of a SIEM, many companies struggle with the amount of data to be ingested. In reality, the data that needs to be managed is surging every year, while the increase in IT budgets remains gradual. This indicates that the volume of data companies must manage is growing at a pace that significantly exceeds IT budgets. The background to this includes the spread of remote work, an increase in cyberattacks, and further strengthening of compliance, all of which are accelerating the rapid expansion of data volume. In such a situation, a fundamental challenge arises: "We want to manage all data if possible, but it is difficult in terms of cost." This is because high-performance log analysis tools often charge based on data volume, necessitating practical operational ingenuity. - The Problem of Data Utilization Silos As the data sources to be collected diversify, "siloing"—a state where data operations become individually isolated—is prone to occurring at operational sites. For example, when various connection and transfer methods such as cloud storage, endpoints, and various security products are mixed, individual agents must be introduced or different settings managed each time. As a result, overall optimization becomes difficult, leading to an increase in operational load and personnel costs. - Demands for Flexible Collection, Analysis, and Transfer Needs for data collection, analysis, and transfer are shifting toward those requiring higher speed and versatility. Nowadays, different data processing and masking are required for each purpose, such as "for analysis," "for auditing," and "for incident detection." Conventional individual development and script-based operations have limits in scalability and efficiency, which also hinders timely incident response. Fundamental Challenges of SIEM Operations Solved by Data Pipelines - What is Data Pipeline Products? "Data pipeline products" can centrally manage these operational challenges. A data pipeline seamlessly collects necessary data from various sources, performs deletion of unnecessary items, advanced processing, and masking, and then routes it to the appropriate analysis platform or storage depending on the purpose and priority.  A key feature is that they come standard with various protocol connectors (Syslog/REST API/Cloud, etc.) and are capable of real-time data processing and distribution. As a result, companies can move away from individual development and script-based operations, allowing for the integrated management of overall operations. Benefits of Implementation for SIEM Operations By introducing a data pipeline, the following benefits can be realized:
While SIEM operational costs and manual labor are significantly reduced, this also leads to the advancement of security operations themselves. Use Cases: Replacement of OSS ETL At one major corporation, challenges had arisen in operations using conventional OSS ETL tools, such as data loss on the scale of hundreds of GBs daily and delays in batch processing, which meant incident analysis took a long time. Furthermore, adding new data sources or making operational changes was based on script development, which carried a high risk of individual dependency and low scalability of the analysis platform.  Therefore, the company introduced a data pipeline (Cribl) for the purpose of flexible, real-time streaming data processing and reduction of operational man-hours. Through GUI-based operations, rapid connection and processing became possible, and they migrated to an environment where masking of personal information and log filters for each platform could be processed automatically in real-time. Results Gained from Data Pipeline Optimization
- Advanced Threat Detection and Data Utilization What is important in SIEM operations is the prediction and early discovery of threats, followed by a rapid and comprehensive response. To achieve this, it is essential to appropriately collect vast and diverse data and process and utilize it according to each purpose. By optimizing the operation of data pipeline products, companies can promote overall operational optimization and level up their security operations. Conclusion The environment surrounding SIEM operations continues to evolve rapidly. While budgets and human resources are limited, data pipeline optimization leads to a fundamental resolution of operational challenges. By choosing a smart operational structure utilizing the latest products like Cribl, let’s achieve safer and more efficient cybersecurity. Comments are closed.
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