Operations | Monitoring | ITSM | DevOps | Cloud

In the second video of our series, we delve into the nuts and bolts of configuring Cribl Search to access the data that we've stored in the S3 bucket. The video guides you step-by-step through the process of configuring the Search S3 dataset provider by using the Stream Data Lake destination as a model for the authentication information. From there, we proceed to walk through the process of creating a Dataset to access the Provider that we've just established. To wrap things up, we demonstrate how to search through the test data that we've previously stored in the S3 bucket.

In the very first video of the series, we delve into the concept of a data loop and why it is beneficial to use Cribl Search and Cribl Stream to optimize the use of a data lake. The video gives a concise overview of Cribl Search and Cribl Stream, and how they work in tandem to create a data loop. We then provide step-by-step instructions on how to configure the Cribl Stream "Amazon S3 Data Lake" Destination to transfer data from Stream to an S3 bucket that has been optimized specifically for Cribl Search's access. Finally, we demonstrate sending sample data to the S3 bucket and present a before-and-after view of the bucket to showcase the impact of the test data.

In the second video of our series, we delve into the nuts and bolts of configuring Cribl Search to access the data that we've stored in the S3 bucket. The video guides you step-by-step through the process of configuring the Search S3 dataset provider by using the Stream Data Lake destination as a model for the authentication information. From there, we proceed to walk through the process of creating a Dataset to access the Provider that we've just established. To wrap things up, we demonstrate how to search through the test data that we've previously stored in the S3 bucket.

The third video of our series focuses on utilizing Cribl Stream to manage data. The presenter takes us through the process of configuring the Cribl Stream in_cribl_http source in tandem with the Cribl Search send operator to collect data. We are able to witness live data results being sent from Search to Stream. Afterward, we demonstrate creating a Route in Stream to direct the incoming data from Search (via the in_cribl_http) Source to the Data Lake by using the Amazon S3 Data Lake Destination. This step employs a passthrupipeline to ensure that the data is not altered in transit.

The final section of our video series showcases how to put the data loop to use with a real-world dataset. We utilize the public domain “Boss of the SOC v3” dataset, which is readily available on GitHub. First, we employ Cribl Search to sift through and explore the BOTSv3 data that is stored in an S3 bucket to locate some specific data.

Join Ed Bailey from Cribl and John Alves from CyberOne Security as they discuss the struggles faced by many SIEM teams in managing their systems to control costs and extract optimal value from the platform. The prevalence of bad data or an overwhelming amount of data leads to various issues with detections and drives costs higher and higher. It is extremely common to witness a year-over-year cost increase of up to 35%, which is clearly unsustainable.

Deploying new tools can be challenging for Operations and Security data teams. However, we recently released a reference architecture for Cribl Stream to streamline this process and reduce trial and error. During a live discussion, Cribl's Ed Bailey and Eugene Katz will share a real-life example of how a customer would start the deployment planning process using real-world examples. We will start with requirements and finish with a diagram to help guide a production deployment.

Deploying new tools can be a challenging process for Operations and Security data teams. However, we recently released a reference architecture for Cribl Stream to streamline this process and reduce trial and error. During a live discussion, Cribl's Ed Bailey and SpyCloud's Ryan Sauders will share a real-life example of how a long-time customer utilized this reference architecture to build a scalable deployment. Ryan will explain how this approach enabled SpyCloud to grow alongside its evolving needs, without requiring significant rework.

Control your SIEM costs by optimizing and reducing the data you are ingesting while keeping a full-fidelity copy for compliance and investigations.

The cybersecurity industry is experiencing an explosion of innovative tools designed to tackle complex security challenges. However, the hype surrounding these tools has outpaced their actual capabilities, leading many teams to struggle with their complexity and struggle to extract value from their investment.