Organization Overview
A classified defense cyber operations command is responsible for protecting critical military systems, sensitive intelligence platforms, and mission support infrastructure. The organization coordinates cyber defense activities across multiple environments and must maintain strict operational security, intelligence protection, and cybersecurity capabilities.
The command operates in highly regulated environments with demanding requirements for auditability, incident response, and continuous monitoring. Its teams manage sensitive information systems that support classified missions, near real-time intelligence analysis, and strategic military decision making.
To support these missions, the command's infrastructure must handle large volumes of security telemetry while aligning with federal cybersecurity frameworks and defense-specific security policies. Cybersecurity personnel need reliable visibility into events without being overwhelmed by noise or unsustainable tooling costs.
Challenge
Before implementing LogZilla as a Splunk pre-processor, the classified defense cyber operations command faced escalating log management costs and resource constraints that were starting to impact its security operations and analytic capacity.
Escalating Splunk licensing costs
The organization generated very high volumes of log data from distributed military and defense infrastructure. Traditional Splunk licensing models, based on daily data ingestion volumes, were driving steep cost growth as monitoring requirements expanded. The cost per gigabyte for Splunk ingestion began to consume a growing share of the cybersecurity budget, limiting investment in other critical security initiatives.
Resource constraints on analytical platforms
The volume of raw log data entering Splunk was stressing analytical infrastructure and creating performance bottlenecks. Security analysts had to wait longer for queries to complete and dashboards to update. High data volumes consumed compute and storage resources that were needed for advanced analytics, threat hunting, and incident response.
Operational inefficiency from data noise
Much of the ingested data consisted of duplicate events, repetitive status messages, and low-value telemetry that offered little analytical benefit but still consumed expensive licensing capacity. This noise reduced analyst efficiency by making it harder to isolate meaningful signals during investigations and routine monitoring.
Budget optimization requirements
As a defense organization operating under federal oversight, the command had to demonstrate responsible and efficient use of cybersecurity funding. The team needed to reduce platform and licensing costs while preserving or improving the quality of security monitoring.
Compliance and audit expectations
Federal cybersecurity frameworks and defense security policies require rigorous log retention and analysis. The command had to maintain a complete and auditable security event record while reducing operational costs. Any solution had to preserve audit trails and support compliance reviews.
Solution
The classified defense cyber operations command deployed LogZilla as an intelligent preprocessing layer in front of its Splunk environment. This architecture reduced ingest volume and cost while improving analytical performance and day-to-day operational efficiency.
Intelligent log deduplication and preprocessing
LogZilla was placed in the data path so that all logs flowed through it before reaching Splunk. Deduplication rules and filtering reduced redundant events and low-value messages, while preserving critical security information. This approach allowed the command to maintain broad log visibility with significantly lower Splunk ingest volumes.
Cost-optimized data pipeline architecture
The team adopted a two-tier architecture where LogZilla handled initial log processing, deduplication, and normalization, and Splunk was reserved for high-value analytics and investigations. By forwarding only unique and relevant events into Splunk, the command reduced licensed ingest while retaining the ability to reconstruct context when needed.
Resource optimization for analytical platforms
With reduced data volumes, Splunk infrastructure no longer had to manage the same level of ingestion and indexing load. Capacity could instead support search performance, more concurrent users, and additional use cases. Analysts benefited from faster queries and more responsive dashboards.
Improved signal-to-noise ratio
LogZilla's preprocessing improved the quality of data that reached Splunk by removing duplicates and low-value log streams. Analysts spent less time sorting through repetitive noise and more time focusing on genuine threats, investigations, and tuning detection logic.
Implementation highlights
The implementation showcased how defense-focused organizations can optimize Splunk usage while maintaining strict security and audit expectations.
Splunk pre-processing architecture
LogZilla was configured as a central collection and processing tier between log sources and Splunk. All security-relevant events flowed through LogZilla first, where correlation, deduplication, and tagging were applied. Only the events required for analytics and compliance were forwarded for indexing.
Advanced deduplication strategies
The command tuned LogZilla's deduplication policies to match common defense and federal log patterns. High-frequency, low-change messages were consolidated, while essential state changes and security events were preserved in full. This preserved security value while reducing ingest volumes.
Alignment with federal cybersecurity frameworks
LogZilla was configured so that data handling, retention behavior, and enrichment fields supported federal cybersecurity guidelines and defense policy expectations. The preprocessing tier helped preserve evidence required for investigations and audits while reducing day-to-day platform load.
Resource allocation and tooling strategy
By lowering Splunk ingest and infrastructure requirements, the command could reinvest budget in people, processes, and additional security capabilities. Analyst time was redirected from managing tooling constraints to higher value activities such as threat hunting and control tuning.
Results
The LogZilla deployment delivered strong cost and operational benefits for the classified defense cyber operations command. The organization achieved major Splunk cost savings and resource optimization by treating LogZilla as a Splunk pre-processor.
Splunk cost reduction
Deduplication and preprocessing significantly reduced the volume of data that entered Splunk while preserving essential context. This translated into lower licensing and infrastructure spend for analytics, which security leadership viewed as a major operational benefit.
Improved analytical performance
With a leaner and more focused dataset, Splunk clusters delivered faster searches and better responsiveness. Analysts were able to run more interactive queries, maintain additional dashboards, and support more stakeholders without saturating resources.
Higher operational efficiency
The combination of reduced noise and improved performance allowed analysts to spend more time on genuine investigations and less time on routine triage. Time-to-insight improved, and investigations became more focused because data was already normalized and filtered.
Better budget utilization
The command was able to show that it had reduced platform costs while maintaining or improving security outcomes. Savings from reduced Splunk ingest and infrastructure helped fund other security improvements and capabilities.
Why LogZilla
The classified defense cyber operations command selected LogZilla because it combined cost optimization with the security and compliance posture required in defense environments.
Experience in defense and federal environments
LogZilla's work with federal and defense customers informed its approach to data handling, retention, and integration. The platform supported the reporting and audit needs common in regulated public sector environments.
Advanced deduplication technology
LogZilla's deduplication and preprocessing features delivered the level of cost optimization required to keep Splunk licensing sustainable in a high-volume environment. The ability to filter and aggregate without losing security fidelity was central to the decision.
Security and compliance alignment
The platform's security controls and deployment patterns aligned with defense requirements for secure data handling and auditability. LogZilla could be deployed in architectures that support classified and sensitive systems.
Focus on operational outcomes
LogZilla's emphasis on operational efficiency and cost control matched the command's need to improve both financial and security outcomes. The platform helped turn an ingest and cost problem into an opportunity to redesign the security data pipeline.
Next steps
Building on the success of this deployment, the defense cyber operations command is evaluating broader use of preprocessing for other analytics platforms and data sources. The team is also exploring additional correlation and enrichment use cases within LogZilla to further streamline investigations and incident response.
The model demonstrated that a preprocessing tier can make advanced analytics platforms more sustainable for defense organizations, while improving visibility and control over security data.