Systems | Development | Analytics | API | Testing



Transforming Kong Logs for Ingestion into Your Observability Stack

As a Solutions Engineer here at Kong, one question that frequently comes across my desk is “how can I transform a Kong logging plugin message into a format that my insert-observability-stack-here understands, i.e. ELK, Loki, Splunk, etc.?” In this blog, I’m going to show you how to easily accomplish converting a Kong logging payload to the Elastic Common Schema. In order to accomplish this task, we’re going to be running Kong Gateway in Kubernetes and using two Kong plugins.

Kensu partners with Collibra to automate data catalog completion

Kensu announces its partnership with Collibra, the Data Intelligence company, and the availability of an integration between the two solutions. Kensu's observability capacities will enrich Collibra's Catalog with clean, trustworthy, and curated information to enable business users and data scientists to make business decisions based on reliable data.

Does Your Company Need a Data Observability Framework?

You have been putting in the work, and your company has been growing manifold, Your client base is growing more than ever, and the projects are pouring in. So what comes next? it is now time to focus on the data that you are generating. When programming an application, DevOps engineers keep track of many things, such as bugs, fixes, and the overall application performance. This ensures that the application operates with minimum downtime and that any future errors can be predicted.


Integrating Observability into Your Security Data Lake Workflows

Today’s enterprise networks are complex. Potential attackers have a wide variety of access points, particularly in cloud-based or multi-cloud environments. Modern threat hunters have the challenge of wading through vast amounts of data in an effort to separate the signal from the noise. That’s where a security data lake can come into play.


Enhance Observability with Opentelemetry tracing - Part 1

Recently, conversations have been increasing around OpenTelemetry; it is gaining more and more momentum in Node.js development circles, but what is it? How can we take advantage of the key concepts and implement them in our projects? Of note, NodeSource is a supporter of OpenTelemetry, and we have recently implemented full support of the open-source standard in our product N|Solid. It allows us to make our powerful Node.js insights accessible via the protocol.

O'Reilly | Fundamentals of Data Observability

Quickly detect, troubleshoot, and prevent the propagation of a wide range of data incidents through Data Observability, a set of best practices that allow data teams to gain greater visibility of data and its usage. If you're a data engineer, ML engineer, or data architect, or if the quality of your work depends on the quality of your data, this book shows how to focus on the practical aspects of introducing Data Observability in your day-to-day work.

Get Ready for the Next Generation of DataOps Observability

I was chatting with Sanjeev Mohan, Principal and Founder of SanjMo Consulting and former Research Vice President at Gartner, about how the emergence of DataOps is changing people’s idea of what “data observability” means. Not in any semantic sense or a definitional war of words, but in terms of what data teams need to stay on top of an increasingly complex modern data stack.


Distributed tracing with Envoy, Kuma, Grafana Agent, and Jaeger

As a cloud service provider, observability is a critical subject as it's strongly related to the availability of the services running on the platform. We need to understand everything that is happening on our platform to troubleshoot errors as fast as possible and improve performance issues. A year ago, while the platform was still in private beta, we faced a tough reliability issue: users were facing random 500 errors when accessing their applications.


DataOps Observability Designed for Data Teams

Today every company is a data company. And even with all the great new data systems and technologies, it’s people—data teams—who unlock the power of data to drive business value. But today’s data teams are getting bogged down. They’re struggling to keep pace with the increased volume, velocity, variety, complexity—and cost—of the modern data stack. That’s where Unravel DataOps observability comes in.