Operations | Monitoring | ITSM | DevOps | Cloud

As more and more applications are delivered daily, it’s becoming increasingly difficult for teams to onboard and manage them manually. To keep up with this demand, many teams are embracing automation in application delivery and management, with Kubernetes being a popular tool of choice. While Kubernetes’ scalability helps manage application infrastructure sprawl, there is still a need to collect data from the applications directly and from Kubernetes to monitor the growing beast itself!

Last time we spoke, I told you about our (then) brand-spankin’-new OTel over HTTP implementation, in both our OpenTelemetry Source and Destination. That was a little over a year ago, also known as a lifetime in tech! I wanted to take another opportunity to speak to you and introduce some of our new OpenTelemetry features, and share how you can put them into practice!

Data is wealth. Extracting insights from data is valuable for any organization—data aids in making informed decisions, optimizing operations and costs, and understanding how customers behave. However, reaping the benefits of data requires an investment in the right tools, resources, and people — something smaller organizations may not have the means to do.

Despite new technologies and telemetry formats, like Model-driven Telemetry/Streaming Telemetry and OpenTelemetry, SNMP traps continue to be a significant source of events for monitoring teams. If you’ve been in IT operations, you’ve likely had a request to parse SNMP traps into a human-readable format so that they can be analyzed, probably deduplicated, and passed to a ticketing system for triage and remediation. The challenge? SNMP traps can be excessively chatty.

I’m so excited to share that Cribl has closed a $319M Series E round! The oversubscribed round was led by GV (Google Ventures), joined by new investor CapitalG along with participation from existing investors GIC, IVP, and CRV. This round values Cribl at $3.5 billion, up 40% from our Series D round in 2022, and includes both primary and secondary.

As a solutions engineer, I always handle the complex challenge of collecting IT and security data. The variety of modern ephemeral systems increases the complexity of collection requirements. Cloud, PCF, and Kubernetes emit metrics, logs, and traces through methodologies like Cloud Foundry’s Nozzle, Prometheus scrapers, and OpenTelemetry collectors. I often find all of these deployed in parallel in a single enterprise environment to meet the evolving needs of IT Ops or SecOps.

As a product manager for Cribl Stream, I enjoy listening to customer challenges and bringing new features and enhancements into the product to help reduce pain points and better enable customers.

Cribl Search empowers users to explore and analyze data directly at its source. However, finding sample data for testing these queries can be time-consuming. To overcome this, Cribl Search provides $vt_dummy, a built-in virtual table designed to generate dummy events on demand.

One of our most commonly asked questions is when we will support Worker Groups in Azure. We’ve heard you loud and clear; some exciting news will make your data management much more straightforward. We’re introducing a Cribl-managed Cribl Stream data plane, also known as Worker Groups, in Microsoft Azure. These Worker Groups are oil to your engine—essential for data operations, handling everything from shaping and transforming to enriching and processing your data.

Cribl Lake is simple, it’s storage, it’s simplified storage to keep large volumes of IT and security data for long retention periods. And now it’s even easier for you to start using Cribl Lake. In addition to Cribl-managed Cloud Worker Groups, cloud customers can now use self-managed Hybrid Worker Groups to send data directly to Cribl Lake. This means all your worker groups, whether hybrid or cloud, can write data to Cribl Lake — all coordinated by your Cribl.Cloud Leader.