The role of SIEM has never gone away. From the beginning, it’s been the backbone of security operations: the system where logs converge, alerts are analyzed, and incidents are investigated. What’s changed is our ability to use it correctly.
Legacy, traditional SIEM tools forced trade-offs. Teams filtered data at ingest, dropped logs to control costs, or siloed analytics into disconnected point tools. The result was a SIEM that felt heavy, reactive, and underwhelming. A modern, cloud-native SIEM brings a platform where compliance, detection, investigation, and response can all run from the same data foundation.
By ingesting and retaining all the telemetry and analyzing it with modern analytics and automation, SIEM becomes a detection tool and the security data platform every SOC can depend on. The ten use cases below show how organizations are now using SIEM in the way it was always intended.
1. Threat detection and monitoring
Threat detection is the core of any SIEM platform. Bad actors attempt credential abuse, privilege escalation, insider misuse, and ransomware campaigns daily. Trying to connect weak signals across diverse domains, such as an odd login in Active Directory, a strange DNS query, or a suspicious API call in AWS, is challenging for any security team. A modern SIEM solution correlates across these signals, enriched with threat intelligence and behavioral baselines, to deliver insights that rise above the noise.
The difference today is scale. With a cloud-native SIEM, teams no longer have to limit what telemetry feeds to detections. DNS, SaaS, endpoint, and cloud audit logs can all be retained and analyzed in real time. That breadth improves fidelity, lowers false positives, and aligns detections to frameworks like MITRE ATT&CK, resulting in faster identification of real threats before they become breaches.
2. Compliance and audit
For many organizations, compliance is the first reason SIEM is purchased. Frameworks like PCI DSS, HIPAA, SOX, GDPR, FedRAMP, and DORA all require centralized log retention and reporting. Without SIEM, proving compliance means manually stitching together evidence from disparate systems, which can be an inefficient and error-prone process.
Cloud-scale SIEM changes the economics of compliance. Years of logs can remain online, queryable, and easily visualized in reports. Pre-built dashboards help security teams demonstrate adherence to specific controls, while auditors get verifiable trails at their fingertips. Instead of a painful annual exercise, compliance becomes a continuous, transparent process woven into daily operations.
3. Cloud and multi-cloud security monitoring
As infrastructure spreads across AWS, Azure, GCP, and SaaS platforms, security teams face blind spots. While native tools provide narrow visibility, they don’t connect across providers or with on-prem environments. This fragmentation makes it harder to detect cross-cloud risks or misconfigurations that could open doors to attackers.
A modern SIEM ingests and normalizes data from all cloud providers alongside traditional sources, giving teams a single source of truth. At cloud scale, it can handle the enormous telemetry generated by API calls, IAM events, and audit trails. Analysts gain unified visibility, enabling them to identify risks and threats that cut across hybrid and multi-cloud environments.
4. Insider threats and entity analytics
External attackers often get the spotlight, but insider threats, ranging from compromised accounts to intentional misuse, are just as dangerous, if not more, because they can appear as normal activity. Dormant accounts waking up, privileged users accessing unusual data, or service accounts behaving erratically are all red flags that other tools may miss.
Modern SIEM solutions leverage User and Entity Behavior Analytics (UEBA) to baseline regular activity and flag deviations. With cloud-scale retention, those baselines are a rolling and learning standard, improving accuracy and reducing false positives. By focusing on entities, not just events, SIEM helps identify subtle anomalies that reveal insider risk before damage is done.
5. Threat hunting
Reactive alerts only catch what’s predefined. Proactive teams use SIEM for threat hunting, forming hypotheses, querying normalized telemetry, and pivoting through related logs to find stealthy compromises. This requires not just data but data in full fidelity.
Cloud-native SIEM makes that possible. Hunters can query DNS, NetFlow, SaaS, and endpoint data without worrying that it was filtered out at ingest. They can test theories against months of historical data, pivot across data sets, and uncover attack patterns that slip past signature-based tools.
6. Incident investigation and forensics
When incidents occur, leadership and regulators demand answers. What happened? How did the attacker get in? What data was touched? Traditional SIEM solutions often fell short because archived logs were slow or inaccessible, leaving investigators with an incomplete picture.
Cloud-scale SIEM changes that. It provides access to logs from days, months, or years ago on the same platform. Investigators can reconstruct attack timelines, correlate events across domains, and prove scope with evidence rather than speculation.
7. Incident response automation
Detection is useless if it doesn’t drive action. Modern SIEMs must integrate automation to triage alerts, enrich events, and launch response playbooks, which reduces dwell time and analyst workload. But automation is only as good as the data it draws from.
With a cloud-native SIEM, automation can utilize full context, including historical baselines, threat intel, peer comparisons, and more. This ensures faster and smarter response actions, such as resetting the right account, blocking the right IP, and escalating the right incident. Automation becomes a force multiplier for the SOC, not a source of risk.
8. Noise reduction and alert prioritization
SOC burnout is real. Analysts face thousands of alerts daily, many of which are false positives or redundant. Traditional SIEMs sometimes amplify this noise by generating even more alerts.
Cloud-scale SIEM flips the equation. Correlating across massive datasets and applying advanced analytics can suppress noise and elevate what truly matters. Instead of ten alerts about the same incident, analysts see one correlated insight. With AI and scoring models layered on top, alerts become prioritized by risk, not just volume, preserving analyst focus and reducing fatigue.
9. Operational and business monitoring
SIEM’s value isn’t confined to security. Because it ingests and stores all telemetry, as well as supporting IT, DevOps, and fraud teams, application performance logs, transaction records, and uptime metrics can be analyzed alongside security data, delivering cross-functional visibility.
For example, a retailer might track point-of-sale uptime, a bank might monitor fraudulent withdrawals, or a SaaS provider might investigate application latency concerns. This dual use of SIEM data strengthens the business case and fosters collaboration across teams, making SIEM not just a SOC tool but a single source of truth for DevSecOps.
10. Third-party and supply chain risk monitoring
Organizations can no longer operate in isolation. Vendors, partners, and SaaS providers all expand the attack surfaces. Supply chain attacks thrive in blind spots where telemetry is absent or siloed.
A cloud-scale SIEM ingests logs from partners, MSPs, and SaaS integrations, normalizing and correlating them with internal data. This provides visibility into external dependencies and highlights potential risks associated with vendor access or API usage. In a world where supply chain compromises are becoming increasingly common, SIEM provides a crucial layer of defense.
The Sumo Logic difference
Many SIEMs promise to fulfill these use cases. Few deliver them with the scale and simplicity required in intelligent security operations. That’s where Sumo Logic Cloud SIEM stands apart with these capabilities.
- Logs-first foundation: Built on a heritage of log analytics, Sumo Logic ingests and normalizes diverse telemetry at scale with no blind spots or data left behind.
- Cloud-native architecture: With an elastic, multi-tenant, and cost-efficient platform, there are no tiers to manage, no compromises on retention, and data is always available and queryable.
- Entity-centric analytics: UEBA, threat intelligence integration, and correlation across identity, endpoint, network, and cloud — turning noise into high-confidence insights.
- Automation services: Embedded response workflows streamline TDIR without the complexity of bolt-on SOAR platforms.
- Cross-functional value: Extend SIEM beyond the SOC to IT, DevOps, and fraud teams, all on the same cloud-scale platform.
Sumo Logic Cloud SIEM fulfills the vision of SIEM with cloud-scale storage, advanced analytics, and integrated responses, helping your team turn massive amounts of data into meaningful, timely actions.
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