TL;DR—This is a fundraising post! Yes, even in this economy. Here at Honeycomb, we've always focused more on the problems we help our customers solve rather than playing the meta game of posturing in startup-land—so these fundraising blog posts are usually the least fun to write (and read, probably). But this one is a little different.
The last decade has been nothing but a roller coaster ride for the airline industry. The pandemic has transformed it forever and now it needs to reevaluate its digital transformation priorities on how to manage traveler expectations. Taking it a step further, travelers buying behavior is changing farther as now they will want to book tickets while chatting with an AI interface. The transformation was already underway. In 2020, Google Cloud and Sabre announced a partnership to modernize Sabre. Recently, American Airlines announced their modern rebooking app launched in partnership with IBM. Lufthansa announced industry's first continuous pricing tailored to suit individual customer attributes.
eBPF is a powerful technical framework to see every interaction between an application and the Linux kernel it relies on. eBPF allows us to get granular visibility into network activity, resource utilization, file access, and much more. It has become a primary method for observability of our applications on premises and in the cloud. In this post, we’ll explore in-depth how eBPF works, its use cases, and how we can use it today specifically for container monitoring.
This is part one of a three-part blog series on Observability-the challenges and the solutions.
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!
