In today's digital age, businesses are under immense pressure to bolster their cybersecurity. Understanding the financial implications of security tools is vital to ensure optimal ROI through risk reduction and breach resilience. This is particularly true for consumption-based security solutions like Security Information and Event Management (SIEM).
The SIEM Cost Challenge
Having worked both as a SIEM consultant and an industry analyst, I've observed that SIEM costs are a recurring point of contention. As a consequence, SIEM solutions, the cornerstone of many security operations programs, have garnered a reputation for being a financial black hole.
Accurately forecasting SIEM costs has remained elusive. Given that a typical SIEM takes over 6 months to deploy, predicting its data consumption a year in advance is speculative. Even vendors sometimes fall short in providing realistic cost estimates.
Several factors contribute to this unpredictability: outdated benchmark data, scope changes, the evolving threat landscape, and rapid digitalization. These variables often lead to unforeseen price hikes post-deployment, catching many buyers off guard.
SIEM Pricing: Outdated and Ineffective
Traditional SIEM pricing models haven't evolved in tandem with the explosion in data volumes. While security teams now handle data ranging from Megabytes to Petabytes, SIEM licensing remains anchored in a Gigabyte-centric world.
Moreover, the true value of the vast amounts of security data remains ambiguous. Until a breach or intrusion is investigated, it's challenging to determine the significance of the collected data. While the probability that the data is still required decreases over time, we can’t always be sure when it will reach 0.
Quantifying the Value of Security Data
The amount of security data an organization generates doesn't always correlate with its revenue. This discrepancy complicates the task of assessing the business value of security data. Survey data further highlights a disconnect between the perceived and actual value of SIEM systems, with many organizations lamenting rising costs and underwhelming features
Security teams are grappling with rising costs, underutilized features, and a lack of comprehensive coverage, with one study stating that over 40% think they are overpaying for their SIEM, and more than 50% unhappy with their current SIEM providers.
A Shift in Buyer Behavior
Rather than just endlessly expanding security budgets to combat escalating costs, organizations are adopting various strategies:
- Limiting Coverage: Some are narrowing their security monitoring scope, focusing primarily on compliance. However, this approach can compromise threat visibility and increase vulnerability.
- Adopting XDR: Others are transitioning to Extended Detection and Response (XDR) solutions, prioritizing in-depth analysis over breadth. But as XDR gains traction, it may inherit SIEM's cost challenges.
- Building Security Data Lakes: These are becoming increasingly popular due to their cost-effectiveness and advanced analytical capabilities. However, transitioning to a data lake doesn't guarantee reduced consumption. Many organizations will find they are swapping Capex for Opex. Moreover, while data lakes offer certain advantages, they can't fully replace enterprise SIEMs.
Future-proofing Security Operations for Automation and AI
Even with the improved cost efficiencies and economies of scale achieved by using security data lakes and cloud computing, we are beginning to hit affordability limits again.
The integration of new data-intensive tools and technologies, including machine learning and AI, like large language models, further intensifies this demand. While these advances promise enhanced cybersecurity capabilities, they simultaneously usher in a new set of financial challenges that the industry will have to grapple with. Technological advancements have made it feasible to process vast data troves, but the question remains: is it economical?
Finding the precarious balance between achieving cost efficiencies and maintaining robust security resilience is the conundrum facing cybersecurity leaders. What they need to be able to make informed decisions is a comprehensive understanding of these costs and their implications, so that they can strategically navigate these challenges.
Security FinOps with Tenzir Security Data Pipelines
At Tenzir, we aim to redefine how organizations manage security operations expenses. Our security data pipelines address core challenges associated with optimizing SIEM, security data lake, and cloud costs.
Our pipelines enhance data flow and processing by normalizing data formats to reduce complexity and redundancy, performing in-stream enrichments, and applying powerful reshaping to optimally prepare the data for consumption. By optimizing data preprocessing down to the collection point, we curtail unnecessary SIEM ingestion and cloud compute costs. We transfer many workloads to the edge that were previously cost-inefficiently executed centrally. By scaling vertically across cores and pipelines, and horizontally across nodes, organizations can adapt to variable environments and data loads, ensuring deployment flexibility and cost-efficiency.
Furthermore, Tenzir ensures data quality, a vital component for effective DataOps and automation. By filtering out redundant data and prioritizing based on significance, you can ensure efficient resource allocation. Tenzir's instrumented data flows provide clear insights into data usage, facilitating transparent cost benchmarking.
Discover more about our features and benefits in our solution brief and free whitepaper on optimizing SIEM, Cloud and data costs using Tenzir.
Start using Tenzir right away at app.tenzir.com.