What Is Azure Sentinel (Renamed to Microsoft Sentinel)?

What Is Azure Sentinel (Renamed to Microsoft Sentinel)?
7 min read
31 October 2022

Microsoft Sentinel, formerly known as Azure Sentinel, is a cloud-native security orchestration, automation, and response (SOAR) and security information and event management (SIEM) solution that utilizes the Azure cloud. By offering capabilities for data collection, detection, response, and investigation, it seeks to facilitate comprehensive security operations.

For security event analysis in on-premises and cloud environments, use Microsoft Sentinel. Typical use cases comprise:

  • The display of log data.
  • Finding anomalies and alerting
  • Examination of security-related incidents
  • Active threat detection
  • Response by automation to security events 


Features and capabilities of Microsoft Sentinel (previously known as Azure Sentinel)

These are Azure Sentinel's main capabilities:

  • Sentinel can be deployed through the Azure portal in a matter of minutes without the need to install servers on-site or in the cloud.
  • There are hundreds of connectors available through Sentinel, including native codeless connectors, Logic Apps, Agents, Syslog, and Function Apps.
  • Sentinel's automated threat response features rely on playbooks and Azure Logic Apps, and they are provided by the automated threat response feature.
  • Cloud-native solutions are simple to scale, require little up-front money and have minimal overhead.
  • Able to ingest and analyze data from both on-premises and cloud-based systems in a hybrid environment.
  • Contains a data lake—is built with an inexpensive, infinitely scalable data lake that is hosted in the Azure cloud.
  • Microsoft research makes use of the company's machine learning analysis of security data expertise.
  • Integration with Microsoft security products: Microsoft 365 Defender and Azure Defender for Cloud are both tightly integrated with the Microsoft SIEM.

How to Use Microsoft Sentinel

Your efforts to collect, identify, respond to, and investigate threats are centralized by Azure Sentinel, now known as Microsoft Sentinel. Threat visibility, alert detection, threat response, and proactive hunting are made possible by the threat intelligence and intelligent security analytic capabilities it offers.

Microsoft Sentinel operates in accordance with a cycle that begins with log management and includes automated alert responses before moving on to schema normalization, data validation, detection, and investigation. Sentinel provides this end-to-end functionality in the following ways:

  1. Sentinel collects information from all users, applications, devices, and infrastructure, including those that are housed on-site and in various clouds. What detections can be performed on data depends on how it is collected.
  2. Sentinel offers analytics and threat intelligence capabilities to help identify threats that have already been discovered and minimize false positives. Detections can be saved as code and are written in KQL.
  3. Sentinel offers artificial intelligence technology to assist with your investigation of suspicious activity on a large scale. Successful SOC operations depend on both enrichment automation and containment automation.
  4. Response—Sentinel enables specialized orchestration and automation for routine security and business integration tasks, enabling teams using Microsoft technologies to respond to incidents quickly.

Microsoft Sentinel Managed Service

The modules are a part of CYBERSHIELD, and they all add to its value to us and the customer by allowing us to complete tasks more quickly and efficiently.

  • We have ISO 9001 and 27001 certifications, and we are a Microsoft Gold Partner.
  • A highly qualified and educated team of SOC analysts and Microsoft Security Stack professionals.
  • Our CTI (Cyber Threat Intelligence) Team is independent. They gather information and create reports known as Threat Intelligence (TI), which we utilize to create profiles of our clients in order to create new threat detection criteria and distribute security advisories (SA is a module inside CYBERSHIELD).
  • We handle the full incident response as part of our Microsoft sentinel managed service, and DFIR (Digital Forensic Incident Response) is also included as part of the package if needed (optional extra/add-on for an additional fee).

Data Connectors for Microsoft Sentinel Key Components

Microsoft Sentinel can ingest data from numerous sources thanks to data connectors. In some circumstances, you can add a service by clicking a button, such as Azure activity logs. Syslog and other services might need to be configured. The official documentation contains references to data source schemas.

Sentinel offers data connectors for popular sources and use cases, such as Syslog, cloud services like Amazon Web Services (AWS) and Microsoft Azure, Common Event Format (CEF), and Trusted Automated eXchange of Indicator Information (TAXII). Microsoft Sentinel can also be integrated with custom applications, distinctive non-security logs, and physical security (OT) logs.


You can integrate Workbooks with Sentinel to track, evaluate, and manage your data. Starting with a variety of templates that can view them in Sentinel, users can start creating customized and interactive workbooks. After connecting a data source, you can use built-in Sentinel workbook templates to gain insights right away. To assist with investigation workflow, executive reporting, or to keep an eye out for particular WAF anomalies, for instance, custom workbooks can be made.

Retention of logs

Sentinel uses Log Workspaces to store ingested data. Additionally, logs may be forwarded to ADX for long-term archival. Understanding the Kusto Query Language is required to perform queries in Microsoft Sentinel (KQL). Here is an excellent tutorial from Microsoft on the fundamentals of how to begin using KQL.


Correlating alerts into incidents is done using analytical rules, or SIEM content. Scheduled queries for analytical rules as well as on-demand queries are both possible. A collection of connected alerts that together constitute a potential threat are included in an incident. You can investigate and address multiple alerts by grouping them into groups of alerts.

Sentinel comes with built-in correlation rules and machine learning rules to help map your network's behavior and find anomalies, but to get the most out of it, your environment will need to be tuned. A potential high-fidelity security incident is created by some rules that combine low-fidelity alerts on various entities. While requiring an initial investment, customizing rules can prevent hours of wasted time investigating false positives.

Threat assessment

The scope of threat hunting can go beyond EDR if Microsoft 365 logs are sent to Sentinel. Microsoft has released specific detection content that can be used in successful threat-hunting activities, along with other threat intelligence. Hunting for threats entails finding dangers that have evaded other environmental detection mechanisms. When performing threat hunting, security analysts adopt a "zero trust," "assume breach" mentality and are able to spot sophisticated threats that are already present in the environment.

Investigations and Incidents

When an alert is raised, Sentinel records an incident. Automation may also be connected to a fired employee incident. You can look into these occurrences using the following tools:

Assignment and incident status — You can assign an incident to a particular person for investigation or change its status.

Sentinel's investigation capabilities include an automatic mapping of entities between incidents along a timeline that allows for a visual investigation of simultaneous or multifaceted attacks.

Playbooks for automation

Sentinel offers SOAR functionality that can help with enrichment, containment, integration with an ITSM, or other customized automated incident response. Automated playbooks using Azure Logic Apps or Azure Functions can speed up response times, cut down on analyst workload, and integrate workflows between security and observability.




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