Microsoft Sentinel ingests 50 billion events a day across your entire environment and uses AI to find what matters. We deploy, tune, and manage it so you don't need a dedicated SOC team.
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Microsoft Sentinel is a cloud-native SIEM (Security Information and Event Management) and SOAR (Security Orchestration, Automation, and Response) platform built on Azure. It collects log data from your entire environment — Microsoft 365, Azure, on-premises servers, firewalls, network devices, and third-party tools — and uses built-in AI and machine learning to detect threats that rules-based systems miss. Sentinel scales automatically with your data volume and eliminates the infrastructure overhead of traditional on-premises SIEM deployments.
Sentinel is built on Azure Log Analytics, giving you a powerful query engine (KQL) to search, correlate, and analyze logs across every data source in your environment in real time.
Built-in machine learning models and Microsoft's global threat intelligence baseline flag anomalous behavior that signature-based rules miss, reducing detection time from days to minutes.
Logic App-based playbooks automatically respond to confirmed threats — isolate a device, disable a compromised account, send Slack/Teams alerts, create tickets — without waiting for a human analyst.
Pre-built and custom Azure Monitor Workbooks give security teams and executives real-time visibility into security posture, active incidents, data ingestion health, and compliance status.
Microsoft Sentinel natively ingests threat intelligence from Microsoft Defender TI, TAXII feeds, and custom IOC lists, so detection rules automatically benefit from the latest attacker infrastructure data.
Sentinel connects to Azure, AWS, GCP, and on-premises environments through 200+ built-in data connectors, giving you a single pane of glass regardless of where your infrastructure lives.
Legacy on-premises SIEM tools were designed for a world where everything lived in the data center. Sentinel was built for the cloud-first environments most organizations run today.
| Capability | Traditional SIEM | Microsoft Sentinel |
|---|---|---|
| Infrastructure required | On-premises servers + storage | None — fully cloud-native |
| Scaling model | Manual capacity planning | Automatic, pay-per-GB |
| Upfront cost | $100K–$500K+ | No upfront cost |
| Detection method | Rules-based only | AI + ML + rules + TI |
| Microsoft 365 integration | Complex/limited | Native, zero config |
| Automated response (SOAR) | Separate product/add-on | Built in — Logic Apps |
| Time to deploy | 3–12 months | 4–6 weeks |
A Sentinel deployment done wrong means alert fatigue, missed detections, and a tool no one trusts. Our structured approach builds a SIEM that your team actually uses and that catches threats that matter.
We catalog every log source in your environment: Microsoft 365, Azure, on-premises AD, firewalls, endpoints, and third-party SaaS. We classify by security value, data volume, and ingestion cost to build a prioritized connector plan.
We design your Log Analytics workspace with retention tiers, data collection rules, and table-level RBAC. For multi-tenant environments or regulated industries, we implement workspace separation and centralized management.
We deploy and validate all data connectors, verify log ingestion completeness, and write custom parsers for non-native sources. We confirm signal fidelity before enabling detection rules.
We enable and tune Microsoft's built-in analytic rules, translate any existing detection logic from your prior SIEM, and write custom KQL rules for environment-specific threats. Every rule is tested and false-positive-validated before going live.
We build automated response playbooks for your most common alert scenarios: compromised account lockdown, phishing email quarantine, endpoint isolation, and ticket creation. Automation handles the first 80% of alerts without analyst intervention.
We deliver workbook dashboards, runbooks, and escalation procedures, then take over ongoing alert triage, monthly tuning, and quarterly rule reviews. Your Sentinel investment keeps improving over time.
Sentinel is not just a log aggregator. It's a full security operations platform that replaces tools most organizations are paying for separately.
User and Entity Behavior Analytics builds baselines of normal activity for every user and device. Deviations — a user logging in from a new country, an account accessing 10x its normal file volume — trigger scored anomaly alerts.
Sentinel groups related alerts into incidents automatically, reducing alert volume by up to 90%. Each incident includes an attack timeline, entity mapping, and recommended investigation steps drawn from Microsoft's global threat research.
Built-in hunting queries and a Jupyter Notebook integration let security analysts proactively search for attacker activity that hasn't triggered a detection rule yet. Hunting findings can be promoted directly to incidents.
Sentinel supports hot (90 days), warm (2 years), and cold (7+ years) retention tiers. Compliance requirements for HIPAA, SOC 2, PCI-DSS, and CMMC are met without the storage costs of keeping everything in hot tier.
Azure Machine Learning notebooks integrated into Sentinel give analysts advanced investigation capabilities — graph analysis, statistical modeling, and custom visualizations — directly from incident context.
Sentinel integrates with Microsoft Security Copilot to give analysts natural language query, automated incident summaries, and AI-assisted investigation guidance — dramatically reducing mean time to respond.
Sentinel delivers the most value when you have enough data sources to justify centralized analytics and enough regulatory or risk pressure to need auditable threat detection. Here's what typically signals a good fit.
Healthcare (HIPAA), finance (SOX/PCI-DSS), defense contractors (CMMC), and legal organizations that need long-term, auditable log retention and demonstrable incident response capability.
Organizations running workloads across Azure, AWS, and GCP that need a single security analytics plane instead of separate SIEM tools for each cloud provider.
Organizations running Splunk, QRadar, ArcSight, or other legacy tools that face rising costs, aging infrastructure, or lack of cloud-native integration capabilities.
Organizations between 100 and 2,500 employees that have outgrown their current security tooling but cannot justify the six-figure investment in traditional enterprise SIEM infrastructure.
Microsoft Sentinel is a cloud-native SIEM and SOAR platform built on Azure. It ingests log data from across your entire environment — Microsoft 365, Azure, on-premises systems, and third-party tools — and applies AI-powered analytics to detect threats, correlate signals, and automate responses. Unlike legacy SIEM tools, Sentinel scales automatically and has no infrastructure to manage.
Sentinel pricing is consumption-based, charged per GB of data ingested per day. Microsoft 365 E5 customers get up to 5 MB per user per day of Microsoft data ingestion at no additional cost. Compared to legacy on-premises SIEM tools with six-figure hardware and licensing costs, Sentinel typically delivers 70% or greater cost reduction. BluetechGreen will model your exact data volumes and project monthly costs before any commitment.
Defender XDR correlates threats specifically across Microsoft security surfaces (email, identity, endpoints, cloud apps) and is focused on detection and response within the Microsoft ecosystem. Sentinel is a broader SIEM that ingests data from any source — AWS, GCP, on-premises systems, firewalls, network devices, and custom applications — and applies analytics across the full picture. Many organizations use both: Defender XDR for Microsoft-native detection and Sentinel as the centralized analytics and long-term retention layer.
Yes. Sentinel supports data connectors for most major SIEM sources including Splunk, QRadar, ArcSight, and common network and endpoint vendors. BluetechGreen handles the migration of detection rules, custom parsers, and alert logic from legacy platforms to Sentinel's KQL-based analytics. Most migrations complete in 4-8 weeks depending on the complexity of existing rule libraries.
A standard Sentinel deployment for an SMB or mid-market organization takes 4-6 weeks: one week for data source inventory and workspace design, two to three weeks for connector deployment and initial rule configuration, and one to two weeks for workbook setup, SOAR playbook testing, and tuning. Organizations migrating from a legacy SIEM should budget additional time for rule translation.
We'll audit your current log sources, model your ingestion costs, and build a deployment plan that gets you to full SIEM coverage without the complexity of a legacy tool.