Register for the Webinar Large-scale cyber breaches continue to dominate headlines, amplifying the damaging ramifications of failing to secure your organization. Even with a substantial investment in your SOC, outcomes continue to fall short of promises. Breaches lead to massive data leaks, steep financial losses, and tarnished reputations, underscoring the urgent need for effective SIEM technology.

When evaluating a SIEM, two key factors stand out: flexibility in data handling and open architecture. These two elements significantly enhance a platform’s efficiency and adaptability in managing cybersecurity threats. Whether you’re evaluating your current SIEM or looking for a more modern solution, here are five questions to ask to gauge its flexibility.

Does your security team have dozens of tools to manage, all with disparate user experiences, data models, and capabilities? Unfortunately, this is the result of many traditional SIEM solutions that lack the ability to integrate all features. This creates a big challenge for your SOC because analysts have to ensure they’re using the right tool at the right time to detect attacks. But today, there’s a better option.

Time is a luxury your SOC can’t afford to waste. To keep your SOC efficient and effective, real-time analytics are crucial. Modern security data platforms give your team this ability by not indexing data on ingest, which ensures that security data is available for immediate analysis and allows your SOC to react swiftly to threats. Here are some of the other reasons why real-time analytics help keep your organization secure.

The ability for your SIEM to ingest data at scale is critical, especially in a world where threats target a vast array of attack surfaces. Ensuring full visibility of all log data is paramount, and you need a SIEM that can ingest any event, in any format, to effectively hunt for threats. Remember, you can’t secure what you can’t see. Whether you’re taking a close look at your current solution or evaluating new potential vendors, here’s what to consider around SIEM data ingestion.

The Federal Risk and Authorization Management Program (FedRAMP®) authorization has, for years, been seen as an arduous undertaking only for companies that want to do business with government agencies and their contractors. However, with growing cybersecurity risks, coupled with tightening data privacy regulations across industries, FedRAMP’s fundamental security requirements are becoming best practices for all organizations handling sensitive data.

Although SIEMs have existed for more than 20 years, many organizations still fail to achieve full data visibility into their environments. Two problems compound this challenge. First: attack surfaces. As organizations scale their digital infrastructures and bring on new applications, the amount of data analysts need to monitor and analyze increases exponentially.

As the new year approaches, security professionals and analysts alike are taking a step back to review what has transpired over the past twelve months. At Devo, 2023 was an exciting year full of change and progress. As we look forward to 2024, we want to take some time to reflect on Devo’s year across product enhancements, analyst recognition, partnerships, and community engagement.

Cybersecurity is a team sport, as malicious actors and advanced persistent threats are constantly evolving their tactics. In this ever-changing landscape, it is crucial for organizations to collaborate and learn from one another’s experiences. At Devo, we recognize the importance of teamwork in combating these threats. We are committed to enhancing our product capabilities and content to empower every customer to participate in this collective defense.

What you’re doing isn’t working. Despite best efforts, the scale of cybersecurity data is outpacing the ability of security information and event management (SIEM) solutions to identify and stay ahead of digital threats. Incremental improvements can’t keep pace with the scale of data contained in cloud solutions and the scope of data created by new tools, like generative AI. The result?