The irony of being an adult working in IT and security is that where having your head “in the clouds” was inappropriate as a child, today most of your activities require you to have your head in the cloud. Organizations moved their business operations to the cloud because they could achieve various operational benefits, like improved collaboration and reduced costs. Yet, many companies still maintain an on-premises SIEM.
As the organization’s environment generates more data every year, these on-premises deployments no longer make sense. Companies face a difficult trade off trying to decide between increasing storage costs or limiting the data they use to gain insights. A cloud security information and event management (cloud SIEM) solution provides an alternative that solves these problems.
As organizations seek to mature their security programs, they often find that a cloud SIEM makes financial and operational sense, giving them the ability to analyze and correlate more data for better insights.
What is a cloud SIEM?
A cloud SIEM (security information and event management) solution is a cloud-based system that collects, monitors, and analyzes security data. With a traditional on-premises SIEM, security teams often need to balance the security telemetry they use against the costs to store the data.
However, a cloud SIEM enables security teams to store their telemetry in a chosen repository, like a security data lake, which improves their ability to use the data for analytics models and automation. Cloud SIEMs empower security teams by enabling them to integrate real-time threat intelligence and automate threat detection and incident response activities.
Why use a cloud SIEM?
A cloud SIEM offers as an alternative to on-premises SIEMs, enabling security teams to overcome the limitations of traditional systems. Compared to a traditional on-premises SIEM, a cloud SIEM can provide benefits like:
- Flexibility: Operating across both on-premises and cloud environments for comprehensive IT asset visibility.
- Scalability: Adapt to dynamic, cloud-scale environments with large data volumes which improved incident investigations and forensic capabilities.
- Cost-effectiveness: Reducing operational costs by eliminating the need to maintain the on-premises infrastructure.
- Integrations: Connectivity with other security tools to ingest and operationalize security data, like threat intelligence.
- Automation: Streamlined data collection, monitoring, and analysis often aligned with frameworks like MITRE ATT&CK for enhanced threat detection and incident response
What Are Some Cloud SIEM Deployment Models?
Cloud SIEMs come with as many deployment models as organizations have customization needs. When choosing a cloud SIEM, companies can create a deployment that responds to their specific security needs while balancing responsibility, capital expenditure, and data control.
Customer-Deployed Cloud SIEM Model
In this model, the organization places the SIEM platform in a cloud environment, like AWS, Azure, or Google Cloud. Similar to running a private cloud, the customer is responsible for managing infrastructure, data ingestion, scaling, and compliance.
Customers have more control over data residency, integration, and customization, often providing a solution for organizations with strict security, regulatory, or data sovereignty requirements.
However, the organizations must have:
- Financial resources to manage compute and infrastructure costs.
- Staffing to manage infrastructure maintenance.
Cloud-Hosted SIEM Model
This model is essentially the Software-as-a-Service (SaaS) model applied to a SIEM solution. The SIEM vendor hosts and manages the SIEM in its cloud infrastructure. The vendor handles infrastructure management, scaling, updates, and maintenance. The customer managed detection and response. The customer sends data from its environment to the vendor’s cloud for analysis and storage.
This model offers faster deployment, lower operational costs, and built-in scalability. However, it may have limitations around data control and residency.
Cloud-Native SIEM Model
Built to run in the cloud, a cloud-native SIEM leverages technologies like:
- Serverless computing
- Distributed storage
- Elastic scalability
These SIEMs integrate with modern cloud workloads and application programming interfaces, making them suitable for dynamic, hybrid, and multi-cloud environments. A cloud-native SIEM is more than a traditional SIEM moved to the cloud. It is optimized for speed, automation, and cost efficiency, making it ideal for organizations embracing DevOps, microservices, and cloud-first architectures.
Cloud SIEM as Managed Service
This model is the managed service provider (MSP) deployment where a third-party takes on tasks like:
- Log ingestion
- Rule tuning
- Alert triage
- Incident response support
Internal security teams have access to 24/7 monitoring and expertise, making the model perfect for teams who:
- Lack in-house SIEM skills.
- Seek to improve detection and response capabilities without managing a platform.
Best Practices for Getting Started with a Cloud SIEM
Implementing any SIEM – cloud or on-premises – can feel overwhelming. However, the following best practices can help you create a strategy that aligns with your organization’s technical requirements and security objectives.
Understand the Current Environment
Planning your deployment requires knowing all your current digital assets, both on-premises and in the cloud. As part of choosing and deploying your cloud SIEM, you should ensure that the solution integrates with your current IT and security technology stack.
Outline Use Cases And Security Roadmap
Since a cloud SIEM can cost-effectively ingest more security data than an on-premises deployment, your planning should revolve around your security objectives. Some considerations include:
- Use cases, like credential stuffing or intrusion detection rules
- Data sources, like Identity and Access Management (IAM) or firewalls
- Data repositories, like a security data lake
- Threat detection mapping or data, like ATT&CK or indicators of compromise (IoCs)
These will help you define the detections you need and any automation that will improve your incident response.
Define Goals
Defining your goals typically means the outcomes you seek to achieve from your deployment. For example, you can consider aligning your strategy and goals with the National Institute of Standards and Technology (NIST) Cybersecurity Framework (CSF). These goals will help you define the security controls that your SIEM monitors.
Establish Operational Processes and Roles
Defining threat detection and incident response processes and responsibilities is critical. If you plan to automate response activities, you need to know the order for workflows. If you plan to connect your cloud SIEM to a ticketing system or IT service management (ITSM) solution, you need to assign users responsibility for different processes or escalations.
Build Detections and Alerts
Once your cloud SIEM is ingesting data, you can build detections and alerts. Detections like Sigma rules can identify specific abnormal activities that may indicate a potential security incident. However, the real power comes from correlating these detections and linking together multiple events. By defining relationships between events, you can create high-fidelity alerts that flag suspicious patterns across a complex environment.
Build Dashboards and Reports
With your data sources defined and your alerts created, you have insight into the things you want to track and how you can do it. Dashboards give you visualizations for at-a-glance insight into the systems, networks, applications, devices, and users you want to monitor. Further, if you align your monitoring and dashboards to compliance objectives, then you can use them to generate compliance reports for senior leadership.
Graylog Security: Cloud SIEM Without Compromise
Using Graylog Cloud, you can rapidly mature your threat detection and incident response capabilities. Graylog Security’s Illuminate bundles include rulesets with content that includes Sigma detections, enabling you to uplevel your monitoring by incorporating threat hunting capabilities and correlations to ATT&CK TTPs.
By leveraging our cloud-native capabilities and out-of-the-box content, you gain immediate value from your logs. Our anomaly detection ML improves over time without manual tuning, adapting rapidly to new data sets, organizational priorities, and custom use cases so that you can automate key user and entity access monitoring.
With our intuitive user interface, you can rapidly investigate alerts. Our lightning-fast search capabilities enable you to search terabytes of data in milliseconds, reducing dwell times and shrinking investigations by hours, days, and weeks.
To learn how Graylog Security can help you implement robust threat detection and response, contact us today.
