Introduction on Sentinel and its New Pricing Model

Microsoft Sentinel is a cloud-native Security Information and Event Management (SIEM) and Security Orchestration, Automation, and Response (SOAR) platform that collects, analyzes, and correlates security data from across your environment to detect threats and automate response. Traditionally, Sentinel stored all ingested data in the Analytics tier (Log Analytics workspace), which is powerful but expensive for high-volume logs. To reduce cost and enable customers to retain all security data without compromise, Microsoft introduced a new dual-tier pricing model consisting of the Analytics tier and the Data Lake tier. The Analytics tier continues to support fast, real-time querying and analytics for core security scenarios, while the new Data Lake tier provides very low-cost storage for long-term retention and high-volume datasets. Customers can now choose where each data type lands—analytics for high-value detections and investigations, and data lake for large or archival types—allowing organizations to significantly lower cost while still retaining all their security data for analytics, compliance, and hunting.

Please flow diagram depicts new sentinel pricing model:

Now let's understand this with below scenarios

Scenario 1A (PAY GO)

Requirement

Suppose you need to ingest 10 GB of data per day, and you must retain that data for 2 years. However, you will only frequently use, query, and analyze the data for the first 6 months.

Solution

To optimize cost, you can ingest the data into the Analytics tier and retain it there for the first 6 months, where active querying and investigation happen. After that period, the remaining 18 months of retention can be shifted to the Data Lake tier, which provides low-cost storage for compliance and auditing needs. But you will be charged separately for data lake tier querying and analytics which depicted as Compute (D) in pricing flow diagram.

Pricing Flow / Notes

• The first 10 GB/day ingested into the Analytics tier is free for 31 days under the Analytics logs plan.
• All data ingested into the Analytics tier is automatically mirrored to the Data Lake tier at no additional ingestion or retention cost.
• For the first 6 months, you pay only for Analytics tier ingestion and retention, excluding any free capacity.
• For the next 18 months, you pay only for Data Lake tier retention, which is significantly cheaper.

 

 

Azure Pricing Calculator Equivalent 

Assuming no data is queried or analyzed during the 18-month Data Lake tier retention period:

Although the Analytics tier retention is set to 6 months, the first 3 months of retention fall under the free retention limit, so retention charges apply only for the remaining 3 months of the analytics retention window. Azure pricing calculator will adjust accordingly.

 

Scenario 1 B (Usage Commitment)

Now, suppose you are ingesting 100 GB per day. If you follow the same pay-as-you-go pricing model described above, your estimated cost would be approximately $15,204 per month.

However, you can reduce this cost by choosing a Commitment Tier, where Analytics tier ingestion is billed at a discounted rate. Note that the discount applies only to Analytics tier ingestion—it does not apply to Analytics tier retention costs or to any Data Lake tier–related charges.

Please refer to the pricing flow and the equivalent pricing calculator results shown below.

Monthly cost savings:
$15,204 – $11,184 = $4,020 per month

Now the question is: What happens if your usage reaches 150 GB per day?
Will the additional 50 GB be billed at the Pay-As-You-Go rate?

No. The entire 150 GB/day will still be billed at the discounted rate associated with the 100 GB/day commitment tier bucket.

Azure Pricing Calculator Equivalent (100 GB/ Day)

 

Azure Pricing Calculator Equivalent (150 GB/ Day)

 

Scenario 2 (Data Lake Tier Only)

Requirement

Suppose you need to store certain audit or compliance logs amounting to 10 GB per day. These logs are not used for querying, analytics, or investigations on a regular basis, but must be retained for 2 years as per your organization’s compliance or forensic policies.

Solution

Since these logs are not actively analyzed, you should avoid ingesting them into the Analytics tier, which is more expensive and optimized for active querying.
Instead, send them directly to the Data Lake tier, where they can be retained cost-effectively for future audit, compliance, or forensic needs.

Pricing Flow

• Because the data is ingested directly into the Data Lake tier, you pay both ingestion and retention costs there for the entire 2-year period.
• If, at any point in the future, you need to perform advanced analytics, querying, or search, you will incur additional compute charges, based on actual usage.
• Even with occasional compute charges, the cost remains significantly lower than storing the same data in the Analytics tier.

Realized Savings

• Savings with no compute activity:
  $1,520.40 – $202.20 = $1,318.20 per month
• Savings with some compute activity (sample value):
  $1,520.40 – $257.20 = $1,263.20 per month

Azure calculator equivalent without compute

Azure calculator equivalent with Sample Compute

Conclusion

The combination of the Analytics tier and the Data Lake tier in Microsoft Sentinel enables organizations to optimize cost based on how their security data is used. High-value logs that require frequent querying, real-time analytics, and investigation can be stored in the Analytics tier, which provides powerful search performance and built-in detection capabilities. At the same time, large-volume or infrequently accessed logs—such as audit, compliance, or long-term retention data—can be directed to the Data Lake tier, which offers dramatically lower storage and ingestion costs. Because all Analytics tier data is automatically mirrored to the Data Lake tier at no extra cost, customers can use the Analytics tier only for the period they actively query data, and rely on the Data Lake tier for the remaining retention. This tiered model allows different scenarios—active investigation, archival storage, compliance retention, or large-scale telemetry ingestion—to be handled at the most cost-effective layer, ultimately delivering substantial savings without sacrificing visibility, retention, or future analytical capabilities.