Both DevOps and Security Information and Event Management (SIEM) play crucial roles in modern IT and security operations, but they focus on different aspects of system management and operations. DevOps is a set of practices aimed at improving collaboration between development and operations teams to streamline software development and deployment, while SIEM is a solution focused on security monitoring, incident response, and compliance management through the collection and analysis of security-related data.

In this post, we will explore the key differences between DevOps and SIEM, detailing their major features, and goals, and how they serve distinct yet complementary purposes in an organization’s IT and security landscape.

1. Definition and Scope

DevOps:

• Collaboration and Automation:
  • DevOps is a cultural and technical approach designed to improve collaboration between development and IT operations teams. It emphasizes automation, continuous integration, and continuous delivery (CI/CD) to accelerate the software development lifecycle.
• Focus on Software Delivery:
  • The primary goal of DevOps is to streamline the development, testing, and deployment of software. By automating repetitive tasks and promoting collaboration, DevOps helps reduce deployment times and increase the frequency of software releases.
• End-to-End Process:
  • DevOps covers the entire software development lifecycle, from planning and development to testing, deployment, and ongoing monitoring and maintenance.

SIEM:

• Security Monitoring and Incident Management:
  • SIEM refers to a security management approach that provides real-time analysis of security alerts generated by applications, hardware, and other infrastructure components. It focuses on aggregating and analyzing log data to identify potential security threats.
• Centralized Security Data:
  • SIEM systems aggregate log and event data from various sources, such as firewalls, intrusion detection systems (IDS), and servers, to provide a centralized view of an organization’s security posture.
• Security Operations Center (SOC) Integration:
  • SIEM tools are typically integrated with Security Operations Centers (SOCs) to help security analysts monitor, investigate, and respond to security incidents quickly and effectively.

2. Objectives and Goals

DevOps:

• Accelerating Software Delivery:
  • DevOps aims to shorten the development cycle, allowing teams to develop, test, and deploy software faster and more reliably. This is achieved through continuous integration, automated testing, and automated deployments.
• Improved Collaboration:
  • DevOps fosters a culture of collaboration between development, IT operations, and other stakeholders. By aligning goals and workflows, DevOps reduces friction between teams, ensuring that all parties are focused on delivering high-quality software.
• Scalability and Automation:
  • DevOps practices, such as infrastructure automation and configuration management, ensure that systems can scale efficiently and without downtime. Tools like Terraform and Docker enable automation at every stage of the lifecycle.

SIEM:

• Real-Time Threat Detection:
  • The primary goal of SIEM is to provide continuous monitoring of security events to detect and respond to threats in real-time. SIEM systems help organizations identify suspicious activities, data breaches, and vulnerabilities before they escalate.
• Compliance and Auditing:
  • SIEM systems are also used to ensure compliance with regulatory requirements, such as GDPR, HIPAA, or PCI-DSS. They provide detailed logging and reporting capabilities to help organizations meet auditing and compliance standards.
• Incident Response and Forensics:
  • SIEM tools provide valuable insights that aid in security incident response and forensics. By analyzing security data and logs, SIEM systems help teams understand the nature of incidents, trace their origins, and mitigate their impact.

3. Tools and Technologies

DevOps:

• CI/CD Tools:
  • DevOps heavily relies on continuous integration and continuous delivery tools such as Jenkins, GitLab, Travis CI, and CircleCI to automate code integration, testing, and deployment.
• Infrastructure Automation:
  • DevOps uses tools like Terraform, Ansible, Chef, and Puppet for automating infrastructure provisioning, configuration management, and deployment.
• Monitoring and Logging:
  • DevOps practices often include monitoring and logging tools like Prometheus, Grafana, and ELK Stack to track application performance, system health, and overall infrastructure reliability.

SIEM:

• Log Aggregation and Analysis:
  • SIEM tools aggregate logs and event data from various sources for analysis. Common SIEM platforms include Splunk, IBM QRadar, ArcSight, and SolarWinds.
• Threat Detection and Analysis:
  • SIEM platforms are equipped with advanced algorithms and analytics to detect security incidents. They use techniques like correlation rules, machine learning, and pattern recognition to identify unusual behavior in security events.
• Incident Management:
  • SIEM platforms often integrate with incident management tools like ServiceNow or PagerDuty to provide streamlined workflows for responding to security incidents, assigning tasks, and tracking resolutions.

4. Collaboration and Roles

DevOps:

• Shared Responsibility:
  • DevOps promotes shared responsibility between development, operations, security, and other teams. Everyone involved in the software lifecycle, from developers to operations personnel, works together to ensure the software is delivered and maintained efficiently.
• Cross-Functional Teams:
  • DevOps fosters the creation of cross-functional teams that collaborate on code development, testing, deployment, and monitoring. This improves communication and speeds up problem resolution.
• Automation and Feedback Loops:
  • Automation plays a key role in DevOps, ensuring that repetitive tasks are handled automatically. Feedback loops, from testing and staging environments to production monitoring, help drive continuous improvement.

SIEM:

• Security Analysts and Operations Teams:
  • SIEM is typically used by security analysts, SOC teams, and incident responders who are responsible for monitoring and investigating security incidents. These teams rely on the data collected by SIEM platforms to detect, assess, and respond to potential threats.
• Collaboration Between IT and Security:
  • While DevOps promotes collaboration between developers and operations teams, SIEM requires collaboration between IT operations and security teams. These teams must work together to interpret security data and respond to incidents.
• Security and Compliance Roles:
  • SIEM tools also support roles that focus on security compliance and auditing. These teams use SIEM reports and logs to ensure that the organization adheres to security standards and regulatory requirements.

5. Impact on Development and Operations

DevOps:

• Faster Time-to-Market:
  • DevOps enables faster time-to-market by automating the software delivery pipeline. This leads to more frequent releases and faster feedback, which accelerates the development process and increases business agility.
• Reliability and Stability:
  • DevOps practices such as automated testing, CI/CD pipelines, and continuous monitoring ensure that software is stable and reliable, even during frequent updates or scaling operations.
• Efficiency and Cost Reduction:
  • By automating manual tasks and optimizing workflows, DevOps helps reduce operational costs and improve resource utilization. The automation of deployment and infrastructure management also minimizes downtime and operational overhead.

SIEM:

• Enhanced Security Posture:
  • SIEM improves an organization’s security posture by providing real-time visibility into security threats and vulnerabilities. It helps prevent data breaches and cyberattacks by detecting malicious activities early.
• Proactive Threat Management:
  • SIEM enables teams to take a proactive approach to security. Instead of reacting to incidents after they happen, SIEM systems help identify threats in real-time, enabling rapid response and minimizing damage.
• Regulatory Compliance and Risk Management:
  • SIEM plays a crucial role in managing compliance and reducing risk by providing the necessary logs, alerts, and reports to satisfy regulatory requirements. It also helps organizations identify and mitigate risks before they escalate.

6. Integration and Use Cases

DevOps:

• Software Development Lifecycle:
  • DevOps is widely used in environments where software needs to be developed, tested, and deployed rapidly. It is commonly used for web applications, mobile applications, and microservices architectures.
• Cloud and Hybrid Environments:
  • DevOps integrates well with cloud-based infrastructure and hybrid environments, where scalable and flexible resources are needed to support dynamic workloads.
• Continuous Monitoring and Improvement:
  • DevOps ensures that applications are continuously monitored, and performance issues are quickly detected and addressed, leading to continuous improvement.

SIEM:

• Security Operations and Incident Response:
  • SIEM is used primarily in security operations to monitor networks, systems, and applications for suspicious activities and potential threats. It is critical for incident detection, response, and forensics.
• Compliance and Auditing:
  • SIEM tools are crucial for industries requiring strict security and compliance standards, such as healthcare, finance, and government sectors.
• Data Breach Prevention:
  • SIEM systems are widely used to detect and prevent data breaches by monitoring system logs and correlating data to identify potential vulnerabilities or unauthorized access.

DevOps vs SIEM

In conclusion, while DevOps and SIEM serve different purposes, they complement each other. DevOps focuses on improving the speed and reliability of software delivery through automation, collaboration, and continuous improvement. In contrast, SIEM focuses on the security of systems by providing real-time monitoring, threat detection, and incident response capabilities.

Both DevOps and SIEM are essential for modern IT and security operations. By integrating both practices, organizations can ensure faster, more secure software delivery while maintaining a strong security posture and compliance with industry regulations.

Sumo Logic this week announced it is making a security information event management (SIEM) platform available on the Amazon Web Services (AWS) cloud.

Jabari Norton, vice president of partners and alliances for Sumo Logic, said the Sumo Logic Cloud SIEM Powered by AWS extends the reach of the Sumo Logic Continuous Intelligence Platform for analyzing data into the realm of cybersecurity.

The Sumo Logic Continuous Intelligence Platform is already hosted on AWS. The challenge the company faced was extending the reach of that platform to create a SIEM that can collect data from multiple third-party data sources spanning everything from on-premises IT environments to software-as-a-service (SaaS) applications, said Norton. Those capabilities make it possible to now analyze security data using machine learning algorithms to detect threats and correlate security intelligence, noted Norton.

The Sumo Logic Cloud SIEM is also tightly integrated with AWS security services such as Amazon GuardDuty and AWS CloudTrail in addition to all the cloud services that AWS continuously updates, added Norton. While the relationship with AWS is not exclusive, Norton said Sumo Logic has no plans to host of a version of its SIEM on any other public cloud at this time.

In effect, Sumo Logic is now applying the same observability capabilities it provides to IT operations and DevOps teams to analyzing security data. In theory, that approach should make it easier for all those teams to collaborate around a platform that aggregates data from across the extended enterprise. That’s critical because while security teams are mainly tasked with discovering vulnerabilities they typically need to rely on DevOps and IT operations teams to remediate them.

In the meantime, the rate at which security platforms are shifting to the cloud continues to accelerate in the wake of the COVID-19 pandemic. Security teams that now need to work from anywhere are finding it simpler and more cost effective to employ cloud platforms to analyze security data. In many cases, the rise of cybersecurity AI will soon force the cloud migration issue. Few organizations have the infrastructure resources required to aggregate the volume of data that is required to train an AI model. The need for those AI models is becoming increasingly pressing because the rate at which cybersecurity attacks are being launched is increasing beyond the abilities of any cybersecurity team, on their own, to analyze.

Of course, there is no shortage of SIEM platforms available in the cloud. Sumo Logic is betting many organizations will simply extend their existing subscriptions to now include a SIEM service.

It may still be some time before the bulk of security platforms employed by any organization reside in the cloud. However, at this juncture, it’s now more a question of time. The less time understaffed cybersecurity teams spend managing infrastructure themselves, the more time they should have available to uncover threats. The issue, of course, is finding the time and resources to make transition in the middle of what is now often a daily cybersecurity firefight.

Security teams are longing for automation capabilities. And, in recent years, their options have improved with Security Orchestration, Automation and Response (SOAR) and other security solutions like Security Information and Event Management (SIEM), Identity and Access Management (IAM), Endpoint Detection and Response (EDR), and Cloud Detection and Response (CDR) offering automation in a narrow capacity.

A recent RSAC blog post suggested that SOAR, because of its likeness to infrastructure as code, is equal to DevSecOps. The article points out that automation and coding are important to security teams, but DevSecOps is more nuanced than that. Though there are elements of workflow automation in SOAR, what sets DevSecOps apart from SOAR is its hyper-reliance on open source and its adoption of an agile approach.

What is SOAR?

Gartner® defines SOAR as “technologies that enable organizations to collect inputs monitored by the security operations team.” SOAR tools ingest data from SIEM systems to define incident analysis and response procedures in a digital workflow format.

What is DevSecOps?

DevSecOps is a modern process methodology typically applied to software development. The goals of DevSecOps are to increase release velocity, eliminate silos between teams, reduce frequency and impact of bugs in production releases, and move security further left in the software delivery process.

These goals are achieved in two ways. One, a cultural shift where teams work together on one platform. In other words, software-defined everything. Two, the use of continuous integration and continuous delivery (CI/CD). CI/CD is a category of software tools that integrate and push code frequently to make sure new versions of an application work. CI/CD tests all aspects of the pipeline, including security, before code is pushed to production.

Why SOAR is unlike DevSecOps

One might confuse the mechanics of SOAR with that of DevSecOps because security teams using a SOAR tool are, in a very high-minded way, embracing the spirit of DevSecOps, which is to use code to automate their work.

But, to be clear, this is where the similarity starts and ends. The two fundamental differences, outlined below, are what really set DevSecOps apart from SOAR.

(1) SOAR has limited support for open source: SOAR tools rarely integrate with open source tools because by nature they primarily integrate with third-party tools like Cisco, Exabeam, Okta or Splunk. The lack of open source integration is a huge deterrent for DevOps teams that rely heavily on open source tools like Git, Ansible and Kubernetes for their work. This impasse isolates security teams from production and discourages DevOps teams from collaborating.

(2) SOAR does not take an agile approach to deliver automation: When security teams using SOAR tools talk about automation, it is within the context of ingesting data from SIEM, managing that data and then automating incident response workflows. This is different from using CI/CD, as in DevSecOps, which allows developers to integrate their new source code, test it, push it and then deploy it to production frequently.

Especially for security teams, CI/CD allows them to iterate in an agile approach, scan the codebase or application for known security vulnerabilities, or run infrastructure and applications against security benchmarks that improve product safety and company-wide security posture.

Therefore, DevSecOps embraces open source and takes an agile approach to automation, whereas SOAR does not on both counts. However, the option for open source is actually ideal for security teams, which like the support and accountability afforded by a large community. Similarly, access to CI/CD is beneficial for security teams, which have long wanted to shift left. In other words, have Dev introduce them early into the software development process so that they can troubleshoot before code makes it to production.

Achieving agility with CI/CD, a DevSecOps focus

SOAR is exclusively a security platform whereas DevSecOps holistically addresses the needs of all teams by embracing CI/CD and open source tools. While SOAR cannot stand in for DevSecOps, DevSecOps solves pain points inherent to SOAR while also offering general-purpose automation that elevates the role and work of security.

Some security teams may be reticent to pursue a DevSecOps solution because CI/CD is traditionally heavily reliant on code. But there are plenty of low-code/no-code options these days. Ideally, teams should source a DevSecOps platform that is all-inclusive; one that contains a visual interface where all levels of coders can collaborate but also contains a powerful back end that caters to DevOps.

The threat landscape is ever-shifting. With security teams needing to do more despite a talent shortage, automation must gain traction to ease the pressures mounting in their domain. Security teams benefit greatly from CI/CD pipelines, which not only replicate and accelerate their manual capabilities but also carve out precious time needed for modernizing their daily work processes. By embracing the spirit and practices of DevSecOps, security teams can become agile through their CI/CD processes.

NEW YORK, Oct. 6, 2020 /PRNewswire/ — IntSights, the threat intelligence company focused on enabling enterprises to Defend Forward™, announced today the availability of the new certified IntSights Application for Splunk. This partnership between the market’s only all-in-one External Threat Protection Suite, IntSights, and Splunk, provider of the Data-to-Everything® Platform, empowers joint customers to seamlessly access enterprise-specific threat intelligence from IntSights directly within existing Splunk deployments.

Effective cyber defense extends beyond the corporate perimeter. Understanding how, when, and where attacks are likely to strike is critical. When organizations augment SIEM solutions with integrated threat intelligence, they can proactively defend and neutralize threats at the source.

The new IntSights App for Splunk introduces a revolutionary approach for connecting threat intelligence from multiple sources across the clear, deep, and dark web with a customer’s Splunk environment. The IntSights app is a unique bidirectional integration that correlates, enriches, and manages organization-specific vulnerabilities, and offers the ability to easily conduct comprehensive IntSights-driven investigations… all within Splunk.

“With this robust app, security teams can directly access IntSights-enriched IOCs from within their Splunk environment. This gives those on the front line vital real-time context for informed and prioritized risk management,” noted Yaron Paryanty, VP of Product Management at IntSights.

IntSights for Splunk enables SOC teams to:

Expand real-time visibility of threat actors and malware targeting the enterprise’s digital assets
Generate automatic alerts for relevant active indicators in an organization’s network environment
Seamlessly conduct advanced IntSights investigations from within the app
Accelerate informed decision-making and automate incident response
Instantly identify and rapidly remediate critical threats before business impact

Stay tuned for additional enhancements to the IntSights App for Splunk. In the near future, mutual customers will be able to continuously access IntSights organization-specific threat alerts and risk-scored CVEs from within their Splunk environments.

About IntSights

IntSights is revolutionizing cybersecurity operations with the industry’s only all-in-one external threat protection platform designed to neutralize cyberattacks outside the wire. Our unique cyber reconnaissance capabilities enable continuous monitoring of an enterprise’s external digital profile across the clear, deep, and dark web to identify emerging threats and orchestrate proactive response. Tailored threat intelligence that seamlessly integrates with security infrastructure for dynamic defense has made IntSights one of the fastest-growing cybersecurity companies in the world. IntSights has offices in Amsterdam, Boston, Dallas, New York, Singapore, Tel Aviv, and Tokyo. To learn more

What Is SIEM Software?

SIEM platforms aggregate and correlate security event data from across an organisation’s infrastructure—servers, network devices, applications, cloud services, and endpoints. By centralising this data, a SIEM can detect anomalies, generate alerts, and produce audit trails required for compliance frameworks such as PCI-DSS, HIPAA, and SOC 2.

Core capabilities typically include:

• Log collection and normalisation – ingesting structured and unstructured log data from heterogeneous sources
• Real-time correlation – applying rules and machine learning to identify suspicious patterns across events
• Alerting and incident response workflows – triggering notifications or automated playbooks when thresholds are breached
• Long-term log retention and search – storing event history for forensic investigation and compliance audits
• Dashboards and reporting – presenting security posture to both operational and executive stakeholders

Major SIEM Vendors

The SIEM market is served by a mix of large platform vendors and specialist providers. The following companies are among the most widely referenced in enterprise evaluations:

• Splunk – A widely adopted platform known for its powerful search processing language (SPL) and broad ecosystem of integrations. Splunk Enterprise Security is its dedicated SIEM product.
• IBM Security QRadar – An enterprise-grade SIEM with deep network flow analysis, widely deployed in regulated industries.
• LogRhythm – Combines SIEM, UEBA (User and Entity Behavior Analytics), and SOAR capabilities in a unified platform, available as both on-premises and cloud deployments.
• AlienVault (now AT&T Cybersecurity USM) – Known for bundling threat intelligence feeds with SIEM functionality, making it popular with mid-market organisations.
• Micro Focus ArcSight – A long-established SIEM with strong compliance reporting, now part of OpenText after the Micro Focus acquisition.
• SolarWinds Security Event Manager – Targets small to mid-sized organisations with a lower-complexity deployment model.
• Logsign – A cloud-native SIEM and SOAR platform with a focus on unified security operations.
• McAfee (now Trellix) Enterprise Security Manager – Integrates with the broader McAfee/Trellix endpoint and network security portfolio.
• Trustwave – Offers managed SIEM services alongside its broader managed security service provider (MSSP) portfolio.
• Netsurion – Positions as a managed SIEM provider targeting organisations without large in-house SOC teams.
• HelpSystems (now Fortra) – Offers security and automation tooling; its SIEM-adjacent products focus on data security and compliance.

Deployment Models: Cloud-Based vs. On-Premises

SIEM deployments broadly fall into two categories, each with distinct trade-offs:

Cloud-Based SIEM

Cloud-delivered SIEM (sometimes called SaaS SIEM or cloud-native SIEM) offloads infrastructure management to the vendor. Teams benefit from elastic scaling, faster onboarding, and reduced operational overhead. Examples include Splunk Cloud, Microsoft Sentinel, and Logsign’s cloud offering. This model is increasingly preferred by organisations running primarily cloud-native workloads, where log sources are already accessible via APIs.

On-Premises / Self-Hosted SIEM

Traditional on-premises deployments give organisations full control over data residency and retention policies—important for highly regulated sectors or environments with strict data sovereignty requirements. The trade-off is higher operational burden: teams must manage hardware, upgrades, storage scaling, and high availability themselves. Many vendors now offer a hybrid model, where log collection occurs on-premises but analytics and storage run in the cloud.

Who Uses SIEM Platforms?

SIEM tools serve two broad organisational segments:

Large Enterprises

Enterprise security operations centres (SOCs) rely on SIEM as their primary visibility layer across complex, multi-cloud and hybrid environments. At this scale, integration depth, custom correlation rules, and SOAR (Security Orchestration, Automation, and Response) integrations are critical selection criteria. Cost is typically tied to data ingest volume, which can become significant at enterprise scale.

Small and Medium Enterprises (SMEs)

SMEs increasingly adopt SIEM to meet compliance requirements or cyber insurance prerequisites. Managed SIEM services—where a third-party MSSP operates the platform—lower the barrier to entry for teams without dedicated security analysts. Vendors such as Netsurion and Trustwave target this segment explicitly.

SIEM and DevOps: Where They Intersect

DevOps teams are increasingly expected to instrument their pipelines and runtime environments to feed data into SIEM platforms. Practical integration points include:

• CI/CD pipeline logs – detecting unusual build patterns, dependency changes, or privilege escalation in pipeline service accounts
• Container and Kubernetes audit logs – forwarding API server audit logs and container runtime events to the SIEM for anomaly detection
• Cloud provider logs – AWS CloudTrail, Azure Activity Log, and GCP Cloud Audit Logs are common SIEM data sources
• Application-level structured logging – emitting security-relevant events (authentication failures, permission denials, unusual API calls) in a structured format that the SIEM can parse and correlate
• Infrastructure-as-code change tracking – alerting when Terraform state changes or configuration drift is detected outside approved workflows

Choosing log formats that align with your SIEM’s parser library (e.g., Common Event Format for ArcSight, or JSON-based structured logging for Splunk HEC) reduces integration friction significantly.

Key Factors When Evaluating a SIEM

When assessing SIEM platforms for your environment, consider the following criteria:

• Ingest pricing model – per-GB, per-event, or per-host licensing has a significant impact on total cost of ownership at scale
• Out-of-the-box integrations – does the platform ship parsers for your existing log sources without custom development?
• Detection content library – pre-built correlation rules mapped to MITRE ATT&CK reduce time to initial value
• Query performance – investigate how the platform handles high-volume retroactive searches across months of data
• SOAR integration or native automation – automated response reduces mean time to respond (MTTR) for common alert types
• Compliance reporting – pre-built report templates for PCI-DSS, HIPAA, ISO 27001, and similar frameworks
• Vendor support and community – active community forums, documentation quality, and SLA-backed support tiers matter operationally

Regional Market Considerations

SIEM adoption and vendor preference varies by region, driven primarily by local regulatory requirements:

• North America – mature market with strong adoption in financial services, healthcare, and government; US federal procurement frequently specifies FedRAMP-authorised cloud SIEMs
• Europe – GDPR data residency requirements influence cloud SIEM selection; on-premises or EU-hosted deployments are common in regulated sectors
• Asia Pacific – fast-growing adoption driven by digital transformation in financial services; data localisation laws in markets such as India and China affect deployment architecture
• Latin America – emerging adoption, often via managed SIEM services; Brazil’s LGPD privacy law is increasing compliance-driven demand
• Middle East and Africa – government and critical infrastructure sectors drive growth; sovereign cloud requirements are a common deployment constraint

Summary

SIEM platforms remain a foundational component of enterprise security operations, and their relevance to DevOps teams is growing as organisations shift left on security. Whether you are evaluating a cloud-native SIEM for a greenfield Kubernetes environment or integrating an existing on-premises platform into your CI/CD observability stack, understanding the vendor landscape, deployment trade-offs, and integration points will help you make a more informed decision. The market includes both broad-platform vendors like Splunk and IBM QRadar and specialist providers targeting specific organisation sizes or verticals—making a clear requirements definition the essential first step in any evaluation.

What Is Azure Sentinel?

Azure Sentinel is Microsoft’s cloud-native Security Information and Event Management (SIEM) and Security Orchestration, Automation, and Response (SOAR) platform. Unlike traditional on-premises SIEM products, Azure Sentinel requires no infrastructure provisioning or complex installation — it runs entirely in the cloud and scales automatically to meet data volume demands.

What sets Azure Sentinel apart from conventional SIEM tools is its breadth of data ingestion and its AI-powered analytics engine. It is designed to monitor not only Azure-native resources, but also on-premises workloads, Office 365, AWS, and a wide range of third-party security products. This makes it a genuine hybrid-cloud security solution rather than a siloed, single-vendor tool.

The Four Core Stages of Azure Sentinel

Azure Sentinel organises its capabilities around four sequential stages, each addressing a distinct phase of the threat-management lifecycle:

• Collect — Ingests data at cloud scale from users, devices, applications, and infrastructure across multiple clouds and on-premises environments.
• Detect — Identifies threats in near-real time using built-in analytics rules, reducing mean time to detect (MTTD).
• Investigate — Applies machine learning and AI to surface correlated alerts and map attack timelines across all monitored assets.
• Respond — Automates responses to confirmed threats using Logic App-based Playbooks, eliminating slow manual remediation steps.

Supported Data Sources and Connectors

Once a Log Analytics workspace is connected to Azure Sentinel, you configure Data Connectors to forward logs and telemetry into the platform. At the time of the original preview, available connectors included:

• Azure Active Directory (sign-in logs, audit logs)
• Azure Active Directory Identity Protection (requires Azure AD Premium P1/P2)
• Office 365 (Exchange, SharePoint, Teams activity)
• Microsoft Cloud App Security
• Azure Information Protection
• AWS CloudTrail
• Third-party security appliances: Cisco ASA, Fortinet, Barracuda, F5
• Any syslog source supporting Common Event Format (CEF)

Each connector has its own configuration blade with step-by-step instructions. Some connectors, such as Azure AD Identity Protection, connect with a single click (provided licensing prerequisites are met), while others — particularly CEF-based connectors — require agent installation on a log-forwarding server.

Getting Started: Initial Setup

Setting up Azure Sentinel for the first time involves a small number of steps:

1. Navigate to Azure Sentinel in the Azure Portal — either via the Marketplace, All Services, or the search bar.
2. Click + Add and select an existing Log Analytics workspace, or create a new one in a supported region.
3. Click Add Azure Sentinel to attach the workspace.
4. Open the Data Connectors blade and enable the relevant connectors for your environment.

After connectors are configured, Azure Sentinel begins ingesting data. It can take several minutes before events and alerts start appearing in the dashboards. The longer the platform runs, the richer the historical context it builds for anomaly detection.

Note on regions (as of early 2019 preview): At the time of writing, Azure Sentinel workspaces were supported only in a limited set of regions: Australia Southeast, Canada Central, Central India, East US, East US 2 EUAP, Japan East, Southeast Asia, UK South, West Europe, and West US 2. This list has expanded significantly since general availability. Always check the official Microsoft documentation for the current list of supported regions.

The Azure Sentinel Dashboard

The main Azure Sentinel overview presents a centralised security posture at a glance:

• Events and Alerts counters — rolling totals for ingested events and triggered alerts.
• Events and Alerts over time graph — a time-series view useful for spotting sudden spikes in activity.
• World map — plots the geographic origin of suspicious events, helping analysts prioritise threats by source location.
• Threat Management and Configuration panel — left-hand navigation providing access to Analytics, Playbooks, Hunting, Cases, and Settings.

Writing Custom Alert Rules with Kusto Query Language (KQL)

Azure Sentinel surfaces Log Analytics directly through the Logs blade, allowing analysts to write and test queries using Kusto Query Language (KQL) against the connected Log Analytics workspace. This is particularly powerful for building custom detection logic tailored to your environment.

As a practical example, the following KQL query searches for Windows Security Event ID 4625 — a failed logon attempt — which is a common indicator of brute-force activity:

SecurityEvent
| where EventID == 4625
| summarize FailedLogons = count() by Account, Computer, bin(TimeGenerated, 1h)
| where FailedLogons > 10
| order by FailedLogons desc

Once you have a working query, you can promote it into a scheduled Analytics Rule by:

1. Navigating to Analytics and clicking + Add.
2. Entering a rule name, description, severity level, and status (enabled/disabled).
3. Pasting your KQL query into the Set Alert Query field — the Logic pane renders a preview graph of matching results.
4. Clicking View Query Results to validate the query directly in Log Analytics before saving.
5. Setting an alert threshold and a run frequency (e.g., every 5 minutes, every hour).
6. Clicking Save to activate the rule.

When the query matches results exceeding the defined threshold, Azure Sentinel raises an alert and, optionally, creates a Case for analyst triage.

Automating Responses with Playbooks

Azure Sentinel Playbooks are Azure Logic App workflows triggered by alerts. They enable security teams to automate repetitive response tasks, dramatically reducing mean time to respond (MTTR). Example automated actions include:

• Sending an email or Teams notification when a brute-force threshold is breached.
• Blocking inbound traffic from a known-malicious IP address via a firewall API call.
• Disabling or locking a compromised user account in Azure Active Directory.
• Isolating a virtual machine by removing it from a network security group.
• Shutting down a compromised VM to contain lateral movement.
• Opening a ticket in an ITSM platform such as ServiceNow or Jira.

Because Playbooks are standard Logic Apps, they benefit from the full Logic Apps connector ecosystem — hundreds of pre-built integrations with Microsoft and third-party services.

Azure Sentinel Fusion: AI-Powered Threat Correlation

Azure Sentinel Fusion is an advanced, machine-learning-driven correlation engine that links seemingly unrelated low-fidelity alerts across multiple data sources into high-confidence security incidents. It is designed to reduce alert fatigue by surfacing the small number of incidents that truly warrant analyst attention, rather than flooding dashboards with individual, unconnected alerts.

During the preview period, Fusion was not enabled by default and had to be activated via Azure Cloud Shell. As of general availability, Fusion is integrated into the platform’s analytics rules and enabled automatically for supported detection scenarios. Check the current Microsoft documentation for the latest configuration requirements.

Key Advantages Over Traditional On-Premises SIEM

Prerequisites Summary

• An active Azure subscription with Contributor permissions.
• A Log Analytics workspace created in a supported Azure region.
• Appropriate licensing for premium connectors (e.g., Azure AD Premium P1/P2 for Identity Protection).

Further Reading

For the most current feature set, pricing, and regional availability, refer to the official Microsoft Azure Sentinel (now Microsoft Sentinel) documentation. Note that Microsoft rebranded the product as Microsoft Sentinel in November 2021.