In today’s landscape, what’s considered security data has expanded to encompass more diverse data types like network data, behavioral analytics, and application metrics. These sources are now essential for a comprehensive security strategy, and visibility into all that data makes proactive threat detection possible. That said, organizations often struggle to process data from various vendors and merge telemetry sets to gain a complete view of their environments.

Traditional logging tools are struggling to keep up with the explosive pace of data growth. Data collection isn’t the most straightforward process — so deploying and configuring all the tools necessary to manage this growth is more difficult than ever, and navigating evolving logging and monitoring requirements only adds another layer of complexity to the situation.

Getting your organization to invest in a new tool requires telling a story that helps decision-makers understand its benefits. In a recent webinar, our experts discussed how to define an ROI for Cribl Stream. They also shared a sample proposal you can use to craft the story you’ll tell to leadership, and gave some tips and tricks for justifying the purchase of these key tools for your business. Engineers and architects understand core technical problems better than anyone.

In today’s world of relentless data growth, security-relevant logs represent a small snapshot of an organization’s overall environment. Teams are beset with a variety of data types, including performance metrics and traces, asset configuration and state, audit logs, and much more. On top of that, teams are expected to scan all of this to compare against industry best practices and join this data with logs and metrics for added context.

The challenge for every organization is gathering actionable observability information from all your systems, in a timely manner, without creating a substantial operational burden for the teams managing the collection tooling. While each observability solution has its unique benefits and challenges, the one common burden expressed by teams is the management of the metadata of the metrics, traces, and logs.

Data growth has significantly out-pacing budgets; the products we use, have to do more. This is where optimization comes into play. Generally, optimization is associated with reduction which may be intimidating…what if something important is reduced? How can you identify what should be reduced? Reduction isn’t about removing context, but about removing repetitive data, meaningless fields, or even flattening JSON.

So many businesses today are playing “Hungry, Hungry, (Data) Hippo,” devouring every marble of information they can get their hands on. While it seems like every company has a robust data aggregation system, what most companies don’t have is an efficient way to control what data they store and where that data goes. We all want to make data-driven business decisions, but sorting through tons of data to find useful business insights can be like finding a needle in a whole farm.

In a previous webinar, we discussed the importance of ensuring that your enterprise is cyber resilient and the politics around establishing a thriving cybersecurity practice within your organization. This week’s discussion covers specific tactics and solutions you can implement when you begin this initiative — watch the full webinar replay to learn more about how Cribl supports your cyber resiliency efforts.

In this live stream, Cjapi’s James Curtis joins me to discuss the challenges of building a distributed global security team. Watch the full video or read on to learn about some hard-won examples of how to be successful with remote team building and management. Talent is hard to find, and companies are hiring from all over the world to build the best teams possible, but this trend has a price.

In this livestream, Cribl’s Ahmed Kira and I explore the challenges of scaling your Cribl Stream architecture to accommodate a large number of agents, providing valuable insights on what you need to consider when expanding your Cribl Stream deployment. Managing data flows from a high volume of agents presents a unique set of challenges that need to be addressed.