Cloud SIEM in 2025: Features, Deployment, and Best Practices

What is cloud SIEM?

A cloud SIEM (Security Information and Event Management) is a cloud-based platform that helps organizations collect, monitor, and analyze security data to identify and respond to threats in real time. It’s a security solution delivered as a service, offering centralized monitoring, analysis, and management of security events across an organization’s IT infrastructure. 

Unlike traditional SIEMs that require on-premises hardware and software, cloud SIEMs leverage the scalability and flexibility of cloud environments. An example of a cloud SIEM is Exabeam New-Scale SIEM.

Cloud-native SIEM also takes advantage of the speed and economies of scale to grow and take advantage of innovations without disruption.

Organizations can leverage cloud SIEM technology to gain better visibility into distributed workloads. Cloud SIEM can help monitor all assets, including servers, devices, infrastructure components, and users connected to the network — through a single cloud-based dashboard.

Key features and benefits of cloud SIEM include:

• Improved incident response: They simplify the incident response process by providing tools for investigation, analysis, and remediation. 
• Centralized monitoring and analysis: Cloud SIEMs provide a unified platform for monitoring security events and logs from various sources, including endpoints, networks, and cloud applications. 
• Real-time threat detection: They enable real-time threat detection by analyzing data streams and identifying suspicious activities, anomalies, and potential security incidents. 
• Scalability and flexibility: Cloud SIEMs can easily scale to accommodate growing data volumes and evolving IT environments, without the need for significant upfront investments in hardware. 
• Faster deployment and integration: Cloud-based solutions are generally faster to deploy and integrate with existing IT infrastructure, including cloud services. 
• Cost-effectiveness: By leveraging the cloud, organizations can reduce hardware costs and simplify system maintenance. 
• Enhanced threat intelligence: Cloud SIEMs often integrate with threat intelligence feeds, providing valuable context and insights into emerging threats. 

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Why use a cloud SIEM?

Cloud SIEM offers faster deployment and easier scalability compared to traditional on-premises SIEMs. Organizations can begin ingesting and analyzing data almost immediately without provisioning hardware or performing complex setups.

Its centralized visibility enables security teams to monitor hybrid and multi-cloud environments from a single interface. This unified view helps detect lateral movement, data exfiltration, and identity-based threats more effectively.

Cloud SIEM platforms also reduce the burden of infrastructure maintenance. Providers handle updates, uptime, and performance optimization, freeing internal teams to focus on threat analysis and response.

Additionally, modern cloud SIEMs integrate with a wide range of data sources and threat intelligence feeds. This extensibility supports faster correlation of events, improved detection accuracy, and automation of incident response workflows.

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Cloud-native SIEM features and capabilities

Cloud SIEM can help organizations to centralize event data from multiple sources, including on-premises and cloud assets. This is especially beneficial for hybrid deployments, which need to combine information on activities and events occurring in multiple data centers.

Key features provided by cloud-based SIEM solutions include:

• Monitoring and analysis – Cloud SIEM platforms centralize monitoring efforts into a single user interface that displays information about integrated systems, workloads, and applications. They can aggregate data from physical and virtual components, located in all environments including multiple clouds and on-premises data centers.
• Threat detection – Cloud SIEM platforms continuously analyze incoming data from across the network, endpoints, cloud services, and applications to identify signs of malicious activity. They use correlation rules, machine learning models, and behavioral analytics to detect threats like brute-force attacks, malware infections, privilege escalation, and insider threats. 
• Scalability and flexibility – Cloud SIEM solutions are designed to handle dynamic workloads and fluctuating data volumes. They can automatically scale storage and compute resources to accommodate spikes in event data, such as during a security incident or compliance audit. This elasticity ensures consistent performance without requiring manual infrastructure provisioning.
• Fast deployment and integration – Unlike traditional SIEMs that require complex on-premises setup, cloud SIEM platforms offer rapid deployment through preconfigured instances or SaaS-based access. Many solutions provide built-in connectors for common log sources like AWS CloudTrail, Azure Monitor, Google Cloud Audit Logs, and popular SaaS applications.
• Cost-effectiveness – Cloud SIEMs eliminate the need for capital investment in hardware and reduce ongoing infrastructure maintenance costs and end of life cycles. Pricing models are typically subscription-based, with charges aligned to data ingestion volume, storage, or number of monitored assets. This pay-as-you-go approach allows organizations to align costs with actual usage.
• Enhanced threat intelligence – Many cloud SIEM platforms integrate with external threat intelligence feeds and commercial threat databases. These integrations provide up-to-date indicators of compromise (IOCs), attack patterns, and adversary tactics, techniques, and procedures (TTPs). Some solutions also support community-driven intelligence sharing and automated threat enrichment.
• Improved incident response – Cloud SIEMs streamline the incident response process by offering integrated investigation and remediation tools. Features like automated alert triage, guided investigation workflows, and playbook-driven response actions enable faster containment and resolution of threats. Some platforms support orchestration with other security tools like SOAR (security orchestration, automation, and response) solutions. 

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Cloud SIEM deployment models

Customer-Deployed Cloud SIEM

In this model, the organization is responsible for deploying and managing the SIEM software on its own cloud infrastructure. The SIEM platform may be installed on a public cloud like AWS, Azure, or Google Cloud but remains under the control of the customer.

This setup provides flexibility and customization. Organizations can tailor integrations, policies, and analytics pipelines to their specific needs. However, it also requires in-house expertise for managing scalability, availability, and security, which can increase operational complexity and cost.

Cloud-Hosted SIEM

Cloud-hosted SIEM refers to traditional SIEM software that vendors offer as a hosted service in the cloud. The core platform is managed and maintained by the vendor, but the architecture is typically a lift-and-shift of on-premises systems rather than re-engineered for the cloud.

This model offers some benefits of cloud — such as reduced hardware dependency and easier access — but may lack the elasticity, integration depth, and automation capabilities found in cloud-native SIEM solutions. Performance and scaling can still depend on older architectural constraints.

Cloud Native SIEM

A cloud-native SIEM is built from the ground up for cloud environments. It uses cloud-native technologies such as containerization, serverless processing, and scalable storage, and is designed to handle modern data velocity, volume, and variety.

These platforms are highly scalable, offer built-in integrations with cloud services, and often include advanced analytics, machine learning, and automation. Cloud-native SIEMs are ideal for organizations with dynamic, hybrid, or multi-cloud workloads that need real-time insights without infrastructure overhead.

Cloud SIEM as Managed Service

This deployment model involves outsourcing the operation and monitoring of a cloud SIEM platform to a managed security service provider (MSSP). The provider handles setup, tuning, threat detection, and even incident response depending on the service level agreement.

Managed service models are attractive for organizations with limited security staff or expertise. They offer rapid deployment and 24/7 coverage, but may reduce visibility or control over configurations, requiring careful coordination with the MSSP.

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SIEM: cloud vs. on-premises

When you implement SIEM, you can deploy the solution in the cloud or on-premises. A cloud solution provider will manage the provisioning and often help with initial configuration — or offer expert professional services to speed deployment — which allows you to start operations immediately. An on-premises implementation requires in-house installation and configuration, so it will likely be longer until you can start using it. Some final advantages of cloud-native SIEMs are faster updates, fewer limits to storage (and thus lower long-term storage costs), and lower total cost of ownership.

IT Resources

In-house IT teams can be short on staff (two-thirds of companies have an IT skills shortage), so it is important to consider giving in-house teams fewer responsibilities because IT teams may be short staffed. A cloud SIEM, especially from a managed service provider, allows you to outsource expertise to maintain security. 

Control

Your required level of control over SIEM and log data is another important consideration. An on-premises implementation like LogRhythm typically offers deep visibility, robust customization, and greater control, which can be critical for highly regulated industries or environments handling restricted or sensitive data. However, the maintenance and start up costs are higher and may be out of reach for smaller organizations seeking rapid deployment or cloud-native scalability.

Cost

The overall cost of implementation can vary widely for cloud SIEM, as there are lower upfront costs, but ongoing subscription and per-usage costs. This enables scalability but can be less cost effective for consistently resource-hungry workloads. On-premises SIEM tends to have higher upfront costs, with the technical debt paid over time. However, upgrades and expansions can also add to costs, as they require installing additional hardware and downtime for upgrades.

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Advantages and disadvantages of a cloud-native SIEM

Here are advantages of cloud SIEM:

• Access to expert knowledge – Organizations deploying cloud SIEM get immediate access to expert knowledge made available by the solution provider. This helps reduce the need to hire experts or train employees to implement the technology. The solution is already pre-configured and is monitored by a team of experts. This translates into a quick deployment and saves time for internal teams.
• Cost savings – Cloud SIEM is a managed service. The SIEM vendor is responsible for the infrastructure, and the organization is not required to purchase hardware and software. Additionally, SIEM services take care of software maintenance and updates, and eliminate the overhead associated with in-house SIEM.
• Fast customization and deployment – Managed SIEM services can quickly customize the implementation. The SIEM vendor can handle ongoing configuration and upgrades, reducing the need for training or certification for in-house security teams.

Here are key disadvantages of cloud-based SIEM technology:

• Migration and data-in-transit – Organizations moving sensitive data offsite always face risks associated with data-in-transit, and may also be exposed to compliance risks. However, most cloud SIEM vendors provide security measures that can mitigate these risks, such as data encryption and strong authentication.
• Limited access to raw log data – Despite the fact that this data comes from the organization’s endpoints and systems, some cloud SIEM vendors might limit access to this information. Instead, the vendor provides aggregated reports based on the collected data. It is critical to select a vendor that uses a data lake architecture, which allows your organization to maintain its raw log data, making it available for forensic analysis and audits.

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Best practices for implementing a cloud SIEM in your organization

There are several practices that organizations should consider when working with a cloud SIEM.

1. Prioritize cloud-native integration

When choosing a cloud SIEM solution, prioritize platforms built natively for the cloud rather than traditional systems retrofitted into hosted environments. Cloud-native SIEMs are designed to integrate deeply with cloud service providers like AWS, Azure, and Google Cloud using their native APIs, event sources, and identity systems.

This native integration allows the SIEM to ingest and process logs from services such as AWS CloudTrail, Azure Monitor, and Google Cloud Audit Logs with minimal configuration. It also enables support for ephemeral resources, such as containers and serverless functions, that traditional SIEMs struggle to track. A cloud-native SIEM automatically adapts to dynamic cloud workloads, ensuring that telemetry coverage scales as infrastructure changes.

Strong integration also supports fine-grained access control, making it easier to enforce least-privilege policies and improve monitoring of account-level activity, IAM role assumptions, and API usage. The result is faster setup, greater visibility, and more relevant detection capabilities across hybrid and multi-cloud environments.

2. Customize detection rules and use cases

Effective detection depends on aligning SIEM rules and use cases with your organization’s unique threat landscape and business context. While most SIEMs come with default rule sets, these are often too generic to provide meaningful coverage out of the box.

Start by assessing your organization’s specific risks, such as targeted threat actors, compliance obligations, or technology stack. Use this analysis to build custom detection logic tailored to real-world attack scenarios, such as privilege escalation attempts in cloud IAM, unusual data access in SaaS applications, or lateral movement across hybrid networks.

Regularly tune and test detection rules using threat intelligence feeds, red team exercises, and past incident data. Use thresholds, correlation logic, and context enrichment to reduce false positives and prioritize the most critical alerts. Maintain a feedback loop where SOC analysts document rule performance and suggest improvements.

Create use-case libraries that map alerts to known MITRE ATT&CK techniques, regulatory controls, and operational risk categories. This structured approach improves coverage, response prioritization, and auditability.

3. Automate incident response workflows

Cloud SIEMs often include or integrate with SOAR platforms, enabling security teams to automate detection-to-response workflows. Automation is critical for reducing mean time to respond (MTTR), especially when dealing with high alert volumes and limited staff.

Begin by identifying common, high-volume incident types that are well-suited for automation — such as brute-force attacks, phishing emails, or malware alerts. Build response playbooks that automate repetitive tasks like enrichment (e.g., IP reputation checks), stakeholder notification, ticket creation, and even containment actions like disabling user accounts or blocking network traffic.

Use conditional logic and approval workflows to strike a balance between full automation and analyst oversight. For example, you might automate triage and enrichment steps but require manual approval before isolating a host.

Document all automated actions and provide transparency through dashboards and audit logs. Regularly review workflow performance, refine playbooks based on incident outcomes, and extend automation coverage incrementally. A mature automation strategy improves consistency, reduces analyst burnout, and accelerates incident resolution.

4. Ensure compliance and audit readiness

Cloud SIEMs play a key role in helping organizations meet security and privacy regulations by centralizing visibility, enforcing policy controls, and generating audit evidence. To ensure compliance, configure the SIEM to collect and retain all relevant logs, including authentication activity, data access events, and configuration changes.

Set up role-based access controls (RBAC) to restrict log access and administrative functions. Use tamper-proof storage options and digital signatures to ensure the integrity of log data. Many SIEMs support compliance modules or templates for standards such as PCI-DSS, HIPAA, SOC 2, and ISO 27001. Leverage these templates to align configurations and generate audit-ready reports.

Schedule periodic compliance assessments and integrate your SIEM with governance, risk, and compliance (GRC) tools to automate evidence collection and control mapping. Maintain continuous monitoring for misconfigurations, unauthorized changes, or suspicious behavior that could indicate policy violations.

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New-Scale SIEM™  from Exabeam

New-Scale SIEM is a next-generation AI-driven security operations platform that unifies threat detection, investigation, and response (TDIR) into one intuitive solution security teams actually want to use. By combining behavioral analytics, automation, and open integrations, it closes the SIEM effectiveness gap and delivers limitless scale to ingest, parse, store, search, and report on petabytes of data from anywhere. Pre-built with hundreds of integrations and the ability to onboard new log sources in minutes, it helps analysts work smarter by reducing alert fatigue by up to 60% and cutting investigation times by as much as 80%. With more than 100 pre-built correlation rules, integrated threat intelligence, and AI-assisted timelines that surface critical incidents faster, security teams can detect and respond to 90% of insider threats before other vendors can catch them while lowering total cost of ownership by up to 35%.

The platform includes Exabeam Nova, a collection of six specialized AI agents embedded across the Exabeam New-Scale SIEM and Security Log Management products. These agents work alongside security analysts to automate complex tasks, accelerate investigations, and improve detection accuracy. From natural language search and automated visualizations to correlation rule building, incident triage, and executive-ready security posture reporting, Nova brings speed, precision, and consistency to every stage of threat detection, investigation, and response.For more information on the cutting edge changes in the SIEM space, we recommend watching this webcast called Agentic AI – Reimagine Threat Detection, Investigation, and Response.