5 Reasons CISO’s Should Empower Teams to Use Amazon S3 for Security Data, Plus 2 You Might Not Expect

Introduction

Security leaders face a familiar, growing dilemma: they’re collecting more telemetry than ever, while budgets stay flat and analyst capacity remains constrained. The modern SOC must scale with data, not against it. The truth is, many teams have already been hoarding years’ worth of raw logs and security telemetry in Amazon S3. What they lack isn’t storage, it’s strategy. What people need is the ability to use that data, turning the S3 archive into an operational advantage across detection, investigation, compliance, and security analytics at scale. Amazon S3, paired with the right architecture and practices, offers a powerful solution to scale, and cost, problems, plus an opportunity to unlock the value of all that idle data.

In our last post, we unpacked the technical best practices for building a high-performance security data lake or lakehouse on Amazon S3. Now, let’s zoom out: why should CISOs and security architects care about building this in the first place?

Here are five compelling reasons to move fast, and two high-leverage benefits that often get overlooked.

1. Dramatically Reduce the Cost of Security Data Storage on S3

Amazon S3’s economics are hard to beat. At \~\$23/TB/month for the standard tier (and lower for infrequent or archival tiers), you’re not just trimming fat, you’re regaining financial control. When compared to the linear and steep ingestion-based pricing of traditional SIEMs, S3 unlocks budget that can be redirected toward prevention, detection content, or hiring.

Practical tip: Use tiered storage policies to lifecycle older data into S3 Glacier or Deep Archive. Couple that with partitioned Parquet files and ZSTD compression to slash your cost per detection query.

2. Break Free from SIEM Lock-In with a Cloud-Native Security Data Lake

Security data lakes built on Amazon S3 decouple storage from compute. That means your team can query the data with Athena today, Trino or DuckDB tomorrow, or switch to a new engine in the future without ever rewriting pipelines or rehydrating from cold storage.

Why this matters to CISOs: It gives you strategic flexibility to pivot technologies based on capability, cost, or compliance without incurring expensive migration projects.

3. Enable Fast, Context-Rich Security Analytics from Amazon S3

A well-structured Amazon S3-based security data lake enables fast queries on years of telemetry using open table formats and indexing. Combined with normalized schemas like OCSF and tools like Query Federated Search, your analysts can access context across EDR, identity, cloud, and SaaS data in a single query without needing to switch tools or memorize every log format.

Bonus tip: Pre-define SQL views for common use cases like lateral movement or DNS tunneling so junior analysts can self-serve high-context answers.

4. Accelerate Detection Engineering with Reusable Security Data Pipelines

Storing raw and enriched security data in a centralized schema allows your detection engineering team to reuse joins, aggregations, and enrichments across multiple detections. The result is faster iteration cycles, fewer redundant transformations, and more resilient detection content.

One CISO’s lesson learned: “We built a security data lake to cut SIEM costs. What we got instead was a detection content engine we actually own.”

5. Prepare for LLMs and Federated Search with Open Security Data Architecture

Maximizing the use of data in Amazon S3, and in other distributed systems, is a foundational principle of the Federated Security approach. Federated Security enables your teams to access, use, and act on data wherever it resides, without moving or duplicating it. This model shifts the focus from centralizing data to centralizing insight, allowing you to operate faster, reduce costs, and maintain control.

With emerging frameworks like the Model Context Protocol (MCP), LLMs can directly tap into structured datasets for summarization, incident triage, and recommendation workflows. Amazon S3 is ideal for storing that structured telemetry at scale, in open formats, and with schema evolution support.

The next frontier: Combining your S3-based security data lake with a federated gateway like Query turns your lake into a plug-and-play data layer for AI copilots and automated SecOps.

Two Benefits You Might Not Expect

1. Simplify Compliance and Auditing Across Business Systems

Many enterprises struggle to answer basic audit questions across ERP, HR, cloud, and productivity systems. If your S3-based security data lake includes access logs, authentications, and asset metadata from these tools, compliance checks become simple queries instead of multi-week projects.

What to do now: Add Okta, Workday, Salesforce, and GitHub logs into your lakehouse with proper normalization and retention. You’ll thank yourself later.

2. Create a Shared Source of Truth for Security and IT Operations

Amazon S3 can become more than cheap storage, it becomes the backbone of a shared operating model between security, DevOps, and IT. When network, identity, and infrastructure telemetry is accessible in one place, cross-team investigations move faster and finger-pointing slows down.

Start small: Map shared use cases with IT like user access reviews or failed login reports and build shared dashboards or views over Amazon S3 data.

Conclusion

The Federated Security approach makes this all possible. By enabling teams to use Amazon S3 and other distributed sources without duplicating or centralizing data, it redefines how security operations extract value from telemetry. It’s not just about having data. It’s about making it usable, in place, and in context.

Amazon S3 isn’t just cheap blob storage, it’s a strategic asset when implemented with intent. With the right structure, compression, formats, and partitioning, it enables security teams to do more than just retain logs. It lets them own their data, accelerate investigations, reduce detection toil, and prepare for the next generation of AI-driven security operations.

If your team is building or refining your S3-based security data architecture, consider these five reasons, and don’t overlook the hidden advantages.

Next Steps:

Evaluate your current SIEM and pipeline costs. Then sketch out what a hybrid architecture with Amazon S3 as the foundation could enable. And if you’re ready to unlock Federated Security across your lake and beyond, you know where to find us.