Azure Sentinel is a cloud-based SIEM solution. The ability to detect, collect, investigate and respond is the nature of the Azure Sentinel. It is a birds-eye view across all the enterprises you have set up on azure. Due to a lot of data flow, an organization sometimes misses maintaining track of all the data. In this blog post, we will focus on Azure Sentinel pricing and core features.
As said, Sentinel keeps a bird’s eye on your enterprise and makes sure your data is not compromised. The information is stored with the Azure monitor log analytics space. Sentinel continues to do its work to collect, detect, investigate and respond to any vulnerability, keeping your enterprise safe.
Explanation of Azure Sentinel Pricing, features and requirement in organizations:
Organizations could reach out and get information from various systems, endpoints, devices, servers, workstations, mobile platforms, and Microsoft’s On-premises, cloud-based infrastructure, multi cloud-based infrastructure. With the help of connects, organizations can reach out to other clouds, integrate and pull the information using Azure Sentinel. In addition to this, organizations can detect and investigate millions of different events across the globe in real-time using artificial intelligence, machine learning, and advanced analytics capability.
Pricing structure model of Azure Sentinel:
Azure Sentinel Pricing model is as follows:
Commitment Tiers
With Commitment tiers you are billed a fixed fee based on the selected tier, enabling a predictable total cost for Microsoft Sentinel. The commitment tier provides you with a rebate on the cost based on your selected commitment tier compared to Pay-As-You-Go pricing. You have the flexibility to opt out of the capacity tier any time after the first 31 days of commitment.
| Tier | Price | Effective Per GB Price1 | Savings Over Pay-As-You-Go |
| 100 GB per day | $123 per day | $1.23 per GB | 50% |
| 200 GB per day | $222 per day | $1.11 per GB | 55% |
| 300 GB per day | $320 per day | $1.07 per GB | 57% |
| 400 GB per day | $410 per day | $1.03 per GB | 58% |
| 500 GB per day | $492 per day | $0.99 per GB | 60% |
| 1,000 GB per day | $960 per day | $0.96 per GB | 61% |
| 2,000 GB per day | $1,821 per day | $0.92 per GB | 63% |
| 5,000 GB per day | $4,305 per day | $0.87 per GB | 65% |
Pay-As-You-Go
With Pay-As-You-Go pricing, you are billed per gigabyte (GB) for the volume of data ingested for analysis in Microsoft Sentinel and stored in the Azure Monitor Log Analytics workspace. Data volume is measured by the volume of data that will be stored in GB (10^9 bytes).
| Feature | Price |
| Microsoft Sentinel | $2.46 per GB-ingested |
Free Trial
Try Microsoft Azure Sentinel Pricing free model for the first 31 days. Microsoft Sentinel can be enabled at no extra cost on an Azure Monitor Log Analytics workspace, subject to the limits stated are as follows:
- For the first month or first 31 days, new workspaces can consume up to 10GB of log data every day at no expense. During the 31-day trial period, both Log Analytics data ingestion and Microsoft Sentinel costs are waived. There is a 20-workspace restriction per Azure tenant for this free trial.
- Microsoft Sentinel may be added to existing workstations at no extra cost. During the 31-day trial period, only the Microsoft Sentinel charges are waived.
Data Retention
Once Microsoft Sentinel is enabled on your Azure Monitor Log Analytics workspace, every GB of data ingested into the workspace can be retained at no charge for the first 90 days. Retention past 90 days will be billed per the traditional Azure Monitor Log Analytics retention prices.
Azure Monitor Log Analytics
Microsoft Sentinel is constructed on the demonstrated groundwork of the Azure Monitor Log Analytics platform and enables an extensive query language to evaluate, interact with, and gain insights from huge volumes of operational data in seconds. Microsoft Sentinel is charged pending on the volume of data consumed for analysis in Microsoft Sentinel and stored in Azure Monitor Log Analytics workspace.
Automation and bring your own Machine Learning
Microsoft Sentinel combines with many other Azure services to offer improved facilities for Security Information and Event Management (SIEM) and Security Orchestration and Automation and Response (SOAR). Some of these services may have additional charges:
- You can use Azure Logic Apps to automate your security responses.
- You can bring in your own machine learning models for customized analysis.
Estimating Costs before using Azure Sentinel
If you’re not yet using Microsoft Sentinel, you can take advantage of the Microsoft Azure Sentinel Pricing calculator to estimate potential expenses. Enter Microsoft Sentinel in the Search box and select the resulting Microsoft Sentinel tile. The pricing calculator helps you estimate your likely costs based on your expected data ingestion and retention.
The calculator provides the aggregate monthly cost across these components:
- Log Analytics data ingestion
- Microsoft Sentinel data analysis
- Log Analytics data retention
Essential features of Azure Sentinel
Limitless cloud speed and scale
Azure Sentinel is the first cloud-native SIEM that automatically scales to meet your organizational needs and pay for only the resources you need. However, as a cloud-native SIEM, Azure Sentinel is less expensive and faster in deploying than other on-premises SIEMs.
AI on your side
- Using Azure Sentinel, you can concentrate on discovering genuine threats in no time because this lowers the noise from genuine events with built-in machine learning and knowledge-based on evaluating lots of signals every day.
- Secondly, it accelerates proactive threat hunting with pre-built queries depending on years of security experience.
- Thirdly, Azure Sentinel can allow checking the prioritized list of alerts. Moreover, you can have a correlated analysis of security events and visualize the complete scope of every attack.
- Lastly, The features in Azure Sentinel Pricing model allows you to automate and coordinate typical processes and procedures to streamline security operations and accelerate attack response.
Streamlining Data from numerous resources
With user and entity profiling that enables peer analysis, machine learning, and Microsoft security expertise, you can get a new level of insight by spotting undiscovered dangers and aberrant behavior of compromised users and insider threats. Additionally, utilizing behavioral analytics, Azure Sentinel allows you to gather more information for threat hunting, investigation, and response. Connectors in Azure Sentinel make data collecting easier across a variety of sources, including Azure, on-premises systems, and clouds.
Azure sentinel Reducing the False Alarms
Azure Sentinel can reduce the false positives in the following ways:
- Using Automation Rules allows you to create an exception without changing the rules, and you may apply the same exception to several rules at the same time. In addition, this method:
- Works for detections that aren’t triggered by scheduled alert rules.
- Allows a one-time exception to be applied, such as when maintenance work causes false positives that are actual occurrences outside of the maintenance window.
- Leaves a trail since the exception precludes an incident from being created, but the alert is still recorded for audit purposes.
2. By altering the scheduled alert rule to allow for more comprehensive and intricate exceptions. Subnet-based exceptions and complex Boolean expressions, for instance. Using Watchlists to centralize exception management is also possible after modifying the query.
Working model of Azure Sentinel: How does it work?
Collect data on a large scale on the cloud: Azure Sentinel is entirely cloud-based. Azure Sentinel, which is based on log analytics, has incredible scalability capabilities and can connect to a wide range of data sources for data collecting. This might come from Office 365, various applications, all users, various subscriptions, and even other clouds. Connectors are available that may be used to connect to these various data sources.
- Detect previously unknown attacks: Azure Sentinel uses Microsoft’s analytics and threat intelligence to detect previously unknown threats while also reducing false positives. As a result, the amount of time security personnel spends examining warnings that are triggered but are not true events is considerably reduced.
- Use artificial intelligence to investigate risks: Azure Sentinel employs artificial intelligence to analyze threats and search for any unusual activity at scale. With Azure Sentinel, Microsoft brings its own cybersecurity expertise to the table.
- Respond quickly to incidents and events: Azure Sentinel uses artificial intelligence (AI) to respond quickly to threat occurrences and events. There are several options for tracking out advanced threats and orchestrating appropriate actions. Jupyter notebook, an open-source tool, can also be utilized.
Behavior analytics and its function in Azure Sentinel
Identifying internal risks and their potential impact-whether a compromised entity or a malevolent insider – has always been a time-consuming and labor-intensive task. Sifting through warnings, connecting the connections, and active hunting all add up to a lot of effort and time spent for little reward, and the possibility of advanced threats may simply go undetected. Attacks that are particularly difficult to detect, such as zero-day, targeted, and advanced persistent threats, might be the most destructive to your business, making detection even more important.
Moreover, in the Azure Sentinel Pricing model, you get Microsoft Sentinel’s UEBA capabilities to remove the monotony from your analysts’ workloads and the uncertainty from their efforts, allowing them to focus on investigation and repair.
As Microsoft Sentinel gathers logs and warnings from all of its linked data sources, it analyses them and creates baseline behavioral profiles of your organization’s entities (such as users, hosts, IP addresses, and apps) through time and across peer groups. Microsoft Sentinel can then spot aberrant behavior and assist you to determine if an asset has been hacked using a range of methodologies and machine learning capabilities. It may also determine the relative vulnerability of different assets, identify peer groups of assets, and assess the potential effect of any hacked asset.
Azure Monitor Log Analytics: What is it all about?
Log Analytics is a feature in the Azure portal that allows you to edit and perform log queries using Azure Monitor Logs data, as well as interactively examine the results. To gain a better understanding of the data, Azure log analytics may be used to query and obtain data from numerous monitor logs that fulfill criteria.
Security features in Azure Sentinel
Playbooks are a notion in Azure Sentinel. These playbooks are based on Azure logic applications, and they enable to simplify security orchestration by automating regular operations. There are prebuilt playbooks with 200+ connections, just like there are machine learning analytics rules that allow you to apply custom logic.
- SOC engineers and analysts of all levels may use playbooks to automate and simplify operations like data intake, enrichment, investigation, and remediation.
- Playbooks are great for simple, repeated activities and don’t require any coding experience. Playbooks aren’t designed to handle ad-hoc or complicated task chains or to document and share evidence.
Azure Consultations by EPC Group: Implementing Azure Sentinel
The EPC Group is one of the most well-known Azure consulting firms in the market right now. As a Microsoft gold certified partner, the firm has the ability to provide a managed security detection and response SIEM for multi-cloud and on-premises settings, allowing your IT staff to focus on other tasks while quickly detecting and responding to attacks before they advance. Furthermore, the firm handles their client’s Microsoft Azure Sentinel environment in such a manner that it frees up their IT and security teams by allowing specialists to effectively build, install, optimize, and monitor
Azure Sentinel for their ease and comfort.
Conclusion:
To conclude, the Azure Sentinel Pricing model provides a scalable cloud-native tool that assists in the detection, investigation, and response to threats if any are discovered. Azure Sentinel also aids in the monitoring of an ecosystem, from cloud to on-premises, workstations, and personal devices.
In addition to that, the user company has the benefit of choosing between the Azure Security Center and Azure Sentinel for the successful operation of their business, where Azure Security Center refers to a security posture management for offering threat protection for hybrid cloud workloads and Azure Sentinel can stand by your side by providing intelligent security analytics for the enterprise
