The blog will take you through best practices to observe Kafka-based solutions implemented on Confluent Cloud with Elastic Observability. (To monitor Kafka brokers that are not in Confluent Cloud, I recommend checking out this blog.) We will instrument Kafka applications with Elastic APM, use the Confluent Cloud metrics endpoint to get data about brokers, and pull it all together with a unified Kafka and Confluent Cloud monitoring dashboard in Elastic Observability.

As the world of technology continues to evolve, the demand for cutting-edge solutions to monitor and optimize system performance has never been higher. Today, we’re excited to introduce a revolutionary new concept in observability: Quantum Entangled Observability (QEO). This ground-breaking method leverages the peculiar properties of quantum mechanics to provide unparalleled insights into your systems’ inner workings.

SaaS Observability is a busy, competitive marketplace. Alas, it is also a very homogeneous industry. Vendors implement the features that have worked well for their competition, and genuine innovation is rare. At Coralogix, we have no shortage of innovation, so here are four features of Coralogix that nobody else in the observability world has.

Elastic Observability 8.7 introduces new capabilities that drive efficiency into the management and use of synthetic monitoring and expand visibility into serverless applications and Kubernetes deployments. These new features allow customers to: Observability 8.7 is available now on Elastic Cloud — the only hosted Elasticsearch offering to include all of the new features in this latest release.

During the past quarter, Lightrun has been busy at work producing a wealth of developer productivity tools and enhancements, aiming for greater troubleshooting of distributed workload applications and cost efficiency. Read more below the main new features as well as the key product enhancements that were released in Q1 of 2023!

With the growing popularity of Kubernetes, the need for effective monitoring solutions has become crucial. LogicMonitor, a leading cloud-based monitoring and observability platform, has rolled out a new set of DataSources in its Kubernetes monitoring solution, LM Container, that uses data from the kube-state-metrics service to provide enhanced visibility into the state of Kubernetes objects.

“How do you know your web properties and APIs are up and functioning as expected for users, not just nationally, but across the entire planet?“ Splunk Synthetic Monitoring provides an effective solution to monitor and track the reliability of web properties from locations all over the globe. By generating simulated user or API requests with Splunk Synthetics you’ll quickly be able to measure response times from various locations, devices, and connection types.

The Twelve-Factor App methodology is a go-to guide for people building microservices. In its time, it presented a step change in how we think about building applications that were built to scale, and be agnostic of their hosting. As applications and hosting have evolved, some of these factors also need to. Specifically, factor 11: Logs (which I’d also argue should be a lot higher up in the ordering).

As an operations engineer (SRE, IT Operations, DevOps), managing technology and data sprawl is an ongoing challenge. Cloud Native Computing Foundation (CNCF) projects are helping minimize sprawl and standardize technology and data, from Kubernetes, OpenTelemetry, Prometheus, Istio, and more. Kubernetes and OpenTelemetry are becoming the de facto standard for deploying and monitoring a cloud native application.