At Cribl, we value the simplest and quickest path to shipping new things. This is especially true with shipping new products. We took this approach with Cribl Edge, so we could get it into the hands of existing and potential customers as soon as possible to learn more about their needs and requirements. In order to ship a high-quality Edge product quickly, we based all of the systems for management and data streaming directly on the existing, battle-tested systems we built for Stream.

As an SRE, analyzing applications is more complex than ever. Not only do you have to ensure the application is running optimally to ensure great customer experiences, but you must also understand the inner workings in some cases to help troubleshoot. Analyzing issues in a production-based service is a team sport. It takes the SRE, DevOps, development, and support to get to the root cause and potentially remediate. If it's impacting, then it's even worse because there is a race against time.

The kubectl logs tail command is a tool that allows users to stream the logs of a pod in real-time while using Kubernetes. This command is particularly useful for debugging and monitoring applications, as it enables users to view log output as it is generated and quickly identify any issues or problems with their application. In this article, we will see how to use the kubectl logs tail command to stream logs, the benefits of using the command, and an advanced tool for streaming logs.

Scaling cloud services is a critical task for Site Reliability Engineers, and it’s a challenging one. As organizations grow, the amount of data and the number of users of it grow like crazy, pushing traditional data management methods to their limits. SREs not only have to keep everything running, they’ve got to make sure it runs smoothly, efficiently, and swiftly.

Cribl is an integrations company at heart. We want to help every company develop a data strategy that gives them more control, improves security, and provides flexibility to adapt to their ever-changing data needs. Today, we’re thrilled to announce that we are a Certified Wiz Integration (WIN) Partner to help customers take their cloud security game to the next level.

Observo.ai is excited to share that we now integrate with Panther Labs, a modern SIEM built for the cloud. This enables Panther users to leverage Observo.ai’s powerful telemetry data pipeline features. Observo.ai was created to help Security and DevOps teams solve their biggest telemetry problems. Using Artificial Intelligence, Observo.ai optimizes and transforms data from any source and routes it to the destinations where it has the most value.

Observability isn’t new. But organizations are struggling to adopt mature observability practices, and the impact on business is palpable. Organizations are seeing the value of observability for their applications and infrastructure—the results of our 2024 Observability Pulse survey of 500 global IT professionals reflects that across the board.

We are delighted to announce the alpha release of the Elastic OpenTelemetry Distribution for Node.js. This distribution is a light wrapper around the OpenTelemetry Node.js SDK that makes it easier to get started using OpenTelemetry to observe your Node.js applications.

Here at Mezmo, we see the purpose of a telemetry pipeline is to help ingest, profile, transform, and route data to control costs and drive actionability. There are many ways to do that as we’ve previously discussed in our blogs, but today I’m going to talk about real-time alerting on data in motion, yes - on streaming data, before it reaches its destination.

We are excited to announce the release of Graylog 6.0, which brings updates across our entire product line!