What is our primary use case?
We have been using Microsoft Sentinel for the last 2.5 years. Our primary use case for Microsoft Sentinel is centralized security monitoring and incident response for our corporate IT environment, supporting around 1,200 to 1,500 users. We mainly use it to collect, correlate, and analyze security logs from multiple sources and convert raw events into actionable incidents for the SOC team.
The tasks we use Microsoft Sentinel for most often include threat detection and alert correlation. Microsoft Sentinel helps us identify suspicious activities by correlating logs across identity, endpoint, and network sources. We also use it for identity and user activity monitoring to monitor abnormal sign-ins, privilege misuse, and unusual user behavior across the corporate environment. Additionally, incident investigation and response is very important for our organization, and we also use threat hunting with KQL, Kusto Query Language.
We use Microsoft Sentinel mainly for centralized SIEM, Security Information and Event Management, and SOAR, Security Orchestration, Automation, and Response operations, enabling threat detection, incident investigations, and automation response across nearly 1,500 users in BFSI corporate IT.
One practical example is an abnormal user sign-in incident in our corporate IT environment. Microsoft Sentinel correlated multiple low-severity alerts, such as unusual sign-in locations, multiple failed authentication attempts, and sudden access to applications not normally used by that user. Individually, these events did not look critical. However, Microsoft Sentinel correlated them into a single incident, which allowed the SOC to identify a potential account compromise early. Using Microsoft Sentinel's investigation view, we quickly analyzed the user timelines and confirmed the suspicious behavior. The SOC then triggered a SOAR playbook to notify the security team and take immediate containment actions. Because of this correlation and centralized visibility, the incident was detected and contained early, preventing further lateral movement or misuse of the account. Microsoft Sentinel helped detect a potential account compromise by correlating abnormal sign-in behavior and access patterns into a single incident, allowing the SOC to respond and contain the issue early.
What is most valuable?
Based on real operations used in our corporate IT environment, the key features include log correlation and incident view. Microsoft Sentinel's biggest strength is how it correlates multiple related alerts into a single incident. This significantly reduces alert noise and helps the SOC focus on real threats instead of isolated events.
Another valuable feature is KQL-based threat hunting with Kusto Query Language. The flexibility of this language allows us to build custom hunting queries based on our environment's behavior. This is extremely useful for detecting low and slow threats or hidden threats that default rules may miss.
Cloud-native scalability and stability is another important feature. Being cloud-native, Microsoft Sentinel scales well for medium to large corporate environments without infrastructure management. Stability has been solid in day-to-day production.
SOAR automation using playbooks is a feature we highly recommend. Microsoft Sentinel's SOAR functionality helps automate repetitive SOC tasks like alert enrichment and notification. This saves analyst time and improves response consistency.
What needs improvement?
Microsoft Sentinel does not require extensive improvements, but there are some areas where enhancements would be beneficial. Cost visibility and control need to be simpler. Cost management is still one of the biggest pain points. Log ingestion and retention costs can grow quickly, and understanding which data source is driving cost is not always straightforward.
Better built-in cost breakdown and predictive alerts would help SOC and management teams plan more effectively. Microsoft Sentinel is a strong SIEM tool, but it would benefit from better cost transparency and easier onboarding for analysts.
For how long have I used the solution?
We have been using Microsoft Sentinel for the last 2.5 years.
What do I think about the stability of the solution?
We have found Microsoft Sentinel very stable from a day-to-day SOC operation perspective. Microsoft Sentinel itself has not been a point of failure for us. The Microsoft Sentinel service in core SIEM, which means security information and event management, functions have been consistently available. Incident creations, analytics rules, investigations, and workflows have been reliable. We have not experienced Microsoft Sentinel-side outages that block the SOC operations.
What do I think about the scalability of the solution?
Microsoft Sentinel scales smoothly, but only if log onboarding and tuning are done properly. As users, endpoints, and security tools increased, Microsoft Sentinel handled higher log ingestion without performance issues. There is no need to add hardware or redesign infrastructure because it is cloud-native. Scaling was automatic from the platform perspective. The real work was deciding what logs to ingest, not worrying about capacity.
Microsoft Sentinel scales reliably as log volume and users grow with no infrastructure bottlenecks. The main challenge is in managing ingestion and the cost, not platform performance.
How are customer service and support?
Microsoft support is very helpful and outstanding. We have interacted with Microsoft support mainly for ingestion issues, analytic behavior, and connector-related problems. All of these interactions were positive.
I would rate customer support for Microsoft Sentinel seven out of ten. The reasons include good escalation support for high-severity issues, knowledgeable engineers once the case reaches the right level, and clear explanation for platform or ingestion-related problems. I rate Microsoft Sentinel support seven out of ten because escalation support is solid, but the initial response and complex issues resolution can take time without premium support. It depends on the support tier and case severities.
How would you rate customer service and support?
How was the initial setup?
Microsoft Sentinel goes beyond a simple data lake. A data lake mainly stores logs without naturally understanding security context, relationships, or behaviors. Microsoft Sentinel, on the other hand, actively correlates data across multiple sources and converts raw events into security incidents.
The practical impact of multiple sources correlation can be seen in the detection of multi-stage attacks. Microsoft Sentinel correlates signals from identity, endpoint, network, and cloud services. Individually, these events look low-risk, but when combined, Microsoft Sentinel detects attack patterns that a data lake would never surface on its own. For example, unusual sign-in followed by endpoint activity, followed by access to uncommon resources. A data lake stores these events separately, while Microsoft Sentinel links them into one incident with context.
Microsoft Sentinel also provides security context and entity awareness. Microsoft Sentinel understands users, devices, IP addresses, and applications as entities, not just a log field. This entity-based model allows behavior analysis over time, which a raw data lake does not provide without heavy custom engineering.
What about the implementation team?
The real setup cost is engineering effort and time spent on boarding data connectors, alert tuning, and cost optimization. From the banking SOC perspective, this is acceptable and expected.
One very important metric is audit and reporting time savings. Earlier, audit data collection took days across tools. But with Microsoft Sentinel's centralized logs and incident records, audit data preparation was reduced to hours. This saved time across SOC, compliance, and security management teams.
Microsoft Sentinel delivers ROI mainly by reducing response time, improving analysis efficiency, and simplifying audits. We did not cut staff, but significantly increased SOC output with the same team.
What was our ROI?
We have seen a clear return on investment mainly through time saving, operational efficiency, and better use of existing SOC resources rather than direct headcount reduction.
ROI impact from Microsoft Sentinel, which we observed in real metrics, includes improvements in incident response time. Our MTTR, mean time to response, improved by forty to fifty percent. Earlier, medium-severity incidents took two to three hours to resolve. Now, after Microsoft Sentinel, it is forty to fifty-five minutes. This came from alert correlation to a single incident, faster investigation timeline, and automation handling first-level tasks, which is the biggest and most visible ROI.
Another metric is analysis productivity. The same team handles twenty-five to thirty percent more alerts and incidents, with less time spent on manual enrichment and repetitive actions. SOAR playbooks remove routine work like incident tagging, initial contact gathering, and notifications. ROI here is capacity gain, not layoffs.
We also achieved reduction in wasted effort from false positives. After tuning, we saw a thirty to forty percent reduction in low-volume alerts. Analysts stopped spending time on isolated, non-actionable events. This directly translates to fewer wasted analyst hours and better focus on real security risk.
What's my experience with pricing, setup cost, and licensing?
Microsoft follows a usage-based pricing model, mainly driven by log ingestion volume and data retention. From our experience, pricing is transparent but not always predictable at the beginning. Cost increases as more data sources are onboarded. Without log filtering and tuning, spend can grow quickly in a two-thousand user environment.
Once we optimized and selected only security-relevant logs, adjusted retention periods, and tuned analytics rules, the cost became manageable and justifiable. Microsoft Sentinel is not a low-cost SIEM. There is no traditional setup or infrastructure cost. There is no hardware, server provisioning, or on-premises SIEM installations.
Which other solutions did I evaluate?
I highly recommend Microsoft Sentinel as a solution.
What other advice do I have?
My advice would be straightforward. Microsoft Sentinel is a powerful SIEM, but success depends on more than just the tool itself. I would give three key pieces of advice to organizations considering it.
First, plan your log ingestion strategy carefully. Do not try to onboard everything at once. Prioritize critical data sources, use filtering to reduce noise and cost, and define your data retention policies upfront.
Second, invest early in KQL skills. Do not rely only on built-in analytics. KQL is the key to unlocking advanced threat hunting, custom detections, and deep investigation. Train your analysts.
Third, tune default analytics rules and correlations. Do not assume the out-of-the-box settings are perfect for your environment. Continuously refine rules, create baselines, and reduce false positives to improve signal quality.
Fourth, use SOAR for what it is good for. Automate repetitive, high-volume, low-risk tasks like enrichment and notifications, but not complex investigation decisions.
Finally, monitor cost constantly. I rate this review seven out of ten overall.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?