2022 Gartner® Magic Quadrant™ SIEM
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Since the early 2000s, Security Information and Event Management (SIEM) has been the go-to security model for the early detection of targeted attacks and data breaches. SIEM combines Security Information Management (the storage and analysis of log data) and Security Event Management (monitoring, correlating, and notification of security events) to help organizations deal with threat detection and response.
However, SIEMs have been unable to keep pace with the security needs of modern enterprise. As early as 2014, Gartner analyst Oliver Rochford said “Implementing SIEM continues to be fraught with difficulties, with failed and stalled deployments common.”
As the volume, complexity, variety, and speed of data continues to increase, traditional SIEMs cannot keep up. Modern malware, data breaches, and security threats are incredibly complex, and they require a more proactive, agile approach to security infrastructure.
SIEM systems work well to defend against known threats with fixed perimeters and signature-based security. But how does this approach translate to today’s cloud-focused, dynamic landscape?
Organizations still shell out more than $1.5 billion annually for SIEM services—but they are still struggling to fend off modern threats. Rule-based and signature-based security systems have failed to prevent the most serious data breaches of the last several years.
Sumo Logic uses advanced security analytics for more robust, scalable security. Security analytics uses machine data to pinpoint anomalies and view resource usage in real-time, allowing you to make fast, informed decisions about complex security threats. Machine data is helping IT teams bring better context to data and create actionable intelligence, which is crucial in the ever-evolving digital security landscape.
According to Sumo Logic’s Global Cloud Security Survey, 83% of respondents report issues when using SIEM in the cloud. These issues can stem from the four critical gaps legacy SIEM tools leave.
1. Ineffective in the cloud.
Legacy SIEM tools weren’t built to ingest, process, and analyze cloud data. Being unable to assimilate cloud data makes it incredibly difficult to understand security compliance needs, leaving these tools ineffective.
2. Not Agile, Too Heavy.
One of the main reasons companies are moving to the cloud is for agility gains that can be achieved in this environment. Legacy SIEM tools, however are too heavy and inefficient because they lack the needed flexibility, and rapid elasticity necessary to keep pace with the increasingly unpredictable volumes of data that needs to be analyzed and prioritized in the cloud, and in many cases require costly full-time resources to support them.
3. Designed for Outdated Technology.
Legacy SIEM tools are outdated because they were built for managing logs in legacy hardware environments, with rules based on known problems and as a result they struggle in providing insights from time-sensitive services like microservices. As companies move to the cloud, the old rules, architectures, and use cases are not effective in this new environment. .
4. Inability to Scale.
Monolithic platforms like legacy SIEM tools can’t scale and lack the ability to incorporate rapid feature changes or bug fixes, they’re also not multi-tenant and version upgrades are an enormous struggle. Growth spikes in the cloud are common and require flexible, dynamic solutions and planning, which legacy SIEM tools simply can’t handle.
Read our white paper about the evolution of SIEM to learn more about Sumo Logic’s holistic approach to security.
Enterprise security teams typically use SIEM solutions to perform two main functions:
Modern companies have transitioned to using microservices, container services, and cloud-based technology to drive innovation and continuous development. The continuous innovation model requires several layered components, including the operating system, applications, storage devices, servers, workstations, and more. Traditional SIEM architecture is not built to handle this volume and variety of data, leading to significant challenges in analyzing and reporting data. This is where Sumo Logic’s security analytics comes in.
SIEM can only identify known events, security analytics uses machine learning algorithms to identify abstract relationships, anomalies, and trends.
With Sumo Logic security analytics, your IT teams can:
Security analytics offers behavior modeling and predictive analytics, helping you look holistically at the entire stack—without relying on rules or predefined schemas. Sumo Logic’s focus on advanced security analytics allows organizations to move beyond the limitations of traditional SIEM.
See how Sumo Logic helps Medidata get real-time security insights for their on-site and cloud-based data centers.
When the volume of modern security threats meets outdated security infrastructure, it creates “alert fatigue.” With so many alerts and so much noise, how does your security team manage and prioritize their efforts?
Sumo Logic generates actionable, high-fidelity alerts through unified logs and metrics, automatically identifying and prioritizing threats—without admins setting policies or rules. Sumo Logic ingestion is data-agnostic, and customizable dashboards make it simple to drill down to individual events (and correlated events).
Sumo Logic also removes the need to invest in hardware and manpower so resources can be spent finding and resolving security issues. And because our technology was designed for cloud security, it easily scales to meet the needs of even the largest enterprises.
See how SPS Commerce uses Sumo Logic to increase visibility across the security environment.
Sumo Logic’s security analytics platform creates information where only data existed. Sumo Logic is a valuable alternative to traditional SIEM systems, built on powerful machine data analytics and continuous intelligence.
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