Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

A security information and event management (SIEM) solution aggregates and correlates data from across the organization’s complex, interconnected environment. Modern enterprise IT consists of decentralized users and applications that require organizations to implement technologies that provide visibility across disparate security solutions. Simultaneously, SIEMs have a reputation for being difficult and expensive to manage.

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.

Security leaders spent most of the past year testing AI driven security automation. Many discovered that the promise of fully autonomous SOC operations collided with the reality of hallucinations, opaque recommendations, and inconsistent outcomes. McKinsey research now shows that more than 80 percent of organizations have not realized meaningful results from gen AI programs.

Security and observability teams generate terabytes of log data every day—from firewalls, identity systems, and cloud infrastructure, in addition to application and access logs. To control SIEM costs and meet long-term retention requirements, many organizations archive a significant portion of this data in cost-optimized object storage such as Amazon S3, Google Cloud Storage, and Azure Blob Storage.

The evolution of your security stack is similar to the different phases of buying cars. In the beginning, you just need enough to transport a few items, maybe yourself and a few friends. The inexpensive two-door hatchback is perfect. However, as your family grows, whether with small humans or pets, you increasingly need more space and more capacity, leading to purchasing a four-door sedan or, even, a mini-van.

Most teams think of data lakes as cold storage. A long-term archive. A place to keep logs “just in case” while budgets tighten and ingest volumes rise. Functional, sure. But limited. The traditional data lake keeps everything, helps occasionally, and rarely fits the way analysts work. Graylog approaches the data lake differently. In Graylog 7.0, the data lake is not a warehouse. It is a pressure release valve for teams overwhelmed by storage cost, investigation delays, and cloud data sprawl.

AI agents are finally moving past cute demos and into actual production workflows. With AWS AgentCore, teams can build agents that write tickets, call APIs, deploy infrastructure, invoke external tools, and make changes faster than any human operator ever could. That’s powerful, but it also introduces a brand-new operational and security surface. And here’s the uncomfortable truth: most organizations have no idea what their agents are actually doing. Agentic AI isn’t magic.

In today's complex IT environments, comprehensive log collection is crucial for effective auditing and security monitoring. Without this, endpoints, especially those that are VPN-joined, stay out of your reach while auditing. This was the bottleneck faced by our Log360 customer who recently availed OnboardPro, ManageEngine's professional services. They knew Log360 was capable of collecting logs from all their network devices—but what about the endpoints that were connected remotely via VPN?

Not investing in a Security Incident and Event Management (SIEM) solution means you’re missing out on significant business benefits. A SIEM platform provides real-time detection and response to security incidents, helping you reduce the risk of costly compliance violations. Combine that with SIEM use cases such as consolidating and streamlining reporting, and your security team saves time and operational costs.