Is it Time to Put Your SIEM on a Diet?
好的,我现在需要帮用户总结一篇文章,控制在100字以内。用户的要求是直接写文章描述,不需要以“文章内容总结”或“这篇文章”开头。 首先,我得通读文章,理解主要内容。文章主要讲SIEM(安全信息和事件管理)系统在数据摄入方面的问题。过去它们高效处理日志和指标,但现在变得臃肿、缓慢,因为摄入了过多不必要的数据。 接下来,作者提到数据摄入的策略问题,大多数组织将所有数据都导入SIEM,导致预算增加、性能下降和ROI降低。解决方案是采用分层数据管理策略:将高价值数据存放在快速存储中,中等价值的数据存放在较慢存储中,低价值的数据则存放在低成本存储中。 然后,作者详细解释了分层策略的三个层级,并讨论了如何根据数据的年龄、重要性、访问需求等因素来分类数据。最后强调这种策略不仅能降低成本,还能提升性能和合规性。 现在我需要将这些要点浓缩到100字以内。重点包括:SIEM因过量摄入低价值数据而臃肿;分层存储策略根据数据重要性和访问频率分类;优化后能降低成本、提升性能并支持敏捷环境。 确保语言简洁明了,不使用复杂的术语。最后检查字数是否符合要求。 </think> 文章指出SIEM系统因过量摄入低价值数据而变得臃肿低效,并提出采用分层存储策略优化数据管理。高价值实时数据存入快速存储,历史或合规性数据则存入成本较低的存储层级。这种策略可降低成本、提升性能并支持更敏捷的安全架构。 2025-10-28 05:18:39 Author: securityboulevard.com(查看原文) 阅读量:7 收藏

Our SIEMs have developed quite an appetite over the years. 

What were formerly lean, mean systems consuming all logs and metrics in their path have, in numerous instances, become bloated, sluggish behemoths. Like a once-svelte cat gradually climbing the “chonk chart,” SIEMs nowadays are gorging themselves at an all-you-can-eat buffet of observability, telemetry and security data, whether they actually require it all or not. 

Cruise Con 2025

The result? Bloated budgets, lagging performance, and lower ROI. 

Perhaps it’s time to rethink what we’re feeding our SIEMs and how much. That doesn’t mean starving your tools of the information they need. It means taking a smarter, tiered approach to data management that balances real-time needs with the cost considerations of longer-term storage. 

Data Gluttony Isn’t Sustainable 

The contemporary approach to SIEM data ingestion often boils down to this: Shove it all in and sort it out later. It sounds great — until you receive the bill. In reality, not all data is created equal. Some are protein-rich: high-value, time-sensitive logs that are critical for real-time detection and response. But much is digital filler, low-calorie content that’s rarely, if ever, needed in a hurry. 

Despite that, the majority of organizations forward all their “just-in-case” data to their SIEMs so it can be searched. That’s functional, but it’s terribly inefficient for the SIEM’s primary function of security detections. And that inefficiency shows up in all the usual complaints: High costs, slow performance, poor scalability and agonizing bottlenecks. The issue may not be the SIEM itself. It may simply be overfed and under-optimized. 

Enter: Data Tiering 

If your storage approach remains “keep everything, just in case,” it’s time to upgrade. Data tiering is the process of matching where and how data is stored to its value, relevance, and frequency of use. 

Let’s take it apart: 

Top Tier: This is the high-value, high-access information your SIEM really lives for — security event logs, IAM activity, endpoint information, and other telemetry that requires real-time visibility. It should reside in fast, searchable storage to facilitate quick detection and investigation. If it’s normalized for your SIEM and you’ve got a detection rule for it, then that data fits here. 

Middle Tier: This is where you put the data you still need available, such as historical logs for trend reporting or incident post-mortems, but that doesn’t require split-second access. Consider it the leftovers that you want to refrigerate, not freeze. Put it in inexpensive formats with enough performance to allow delayed but eventual access. 

Bottom Tier: This tier is for the compliance crowd. Seldom used but frequently kept, it consists of things like old audit logs or system configurations. Storage in this tier prioritizes retention and cost over performance. 

Knowing What Goes Where 

So how do you decide what information belongs in each tier? It all comes down to some simple but powerful factors: 

Age: Newer data is typically more desirable. Older data isn’t, but may still be necessary for compliance or investigations. 

Criticality: Production system logs usually matter more than those from a test environment. 

Accessibility: How quickly do you need it? Who needs access? 

Volume: More logs don’t always mean more value. In fact, the inverse is often true. 

Environment State: In a breach, everything might be relevant. Outside of one, maybe not. 

The key is realizing that data value isn’t fixed. It changes based on context, and your architecture should be flexible enough to reflect that. 

Building a Leaner, Smarter SIEM Strategy 

Modern environments demand agility. Compute and storage should scale independently. Analysts need to search across tiers without barriers. And the systems handling telemetry data, whether SIEMs, APMs, or observability tools, must function as part of a connected ecosystem, not isolated silos. 

A tiered data strategy doesn’t just reduce costs. It improves performance where it matters, streamlines compliance and helps your teams move faster with the right data at the right time. 

So, is it time to put your SIEM on a diet? Not necessarily. But it might be time to stop letting it consume everything in sight. 


文章来源: https://securityboulevard.com/2025/10/is-it-time-to-put-your-siem-on-a-diet/
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