I have recently been heads-down working on a large Splunk Cloud PoV (20+ TB / day), and the customer asked if Splunk supported their forwarding technology called Vector. I had never heard of Vector, so I took a note to do further research. I couldn’t find anyone else at Splunk who had seen this technology before, so I embarked on a little research project. What I discovered surprised me—Vector is actually fairly powerful, and cool!

KubeCon Europe 2020 is virtual this year, and Elastic is doing our part to help "keep cloud native connected." We would rather be there in person to shake hands, tell stories, and laugh, but the challenges of a virtual conference also provide the opportunity to share great content and materials that we might not be able to at a crowded booth.

Curious how to get data flowing from your Go application into Honeycomb using OpenTelemetry? This guide will help you step by step through adding OpenTelemetry into your web service and sending the data to Honeycomb.

Java is one of the most popular, flexible and useful programming languages with a very vibrant community to support it. Many of our customers use Java to create amazing applications, it’s an application on a single VM, or based on microservices running on Kubernetes. Naturally, we made it simple to understand the performance of Java-based applications using SignalFx Microservices APM.

Last week Sumo Logic announced our new Observability Suite, which included the public introduction of the closed beta for our distributed tracing capabilities as part of our Microservices Observability solution. This new solution will provide end-to-end visibility into user transactions across services, as well as seamless integration into performance metrics and logs to accelerate issue resolution and root-cause analysis. In this blog, we’ll explore the new solution in detail.

Thank you so much to all who attended Raw & Real Ep. 5 “All Aboard! Bring Your Team Together,” and to any who take the time out of their busy days to watch the recording 🙂 This was a session for those who would describe yourselves as “internal champions” of Honeycomb and Observability.

Today, we made an important announcement that builds on and extends our category leadership in Continuous Intelligence. This blog is to put that announcement into context for our customers, partners and the broader industry. In 2017, we shared our strategy to democratize machine data by building a cloud-native, Continuous Intelligence Platform™ to 1) unify modern application and machine data; 2) support the ongoing proliferation of users and access; and 3) leverage cloud-scale economics.

Holler is a messaging tech company that enriches conversations everywhere by creating and delivering useful, entertaining, expressive visual content to add texture and emotion to messaging environments. As the company has continued to grow, the engineering organization has scaled to meet the demand for its services. However, without a fully staffed Operations team, most of the engineers at Holler perform double duty across DevOps to keep the service performant for consumers.

As organizations build out their serverless footprint, they might find themselves managing hundreds or thousands of individual components (e.g., Amazon S3 buckets, Amazon DynamoDB tables, AWS SQS queues) for just a single application. At the same time, performance issues can crop up at any of these points, which means that having access to detailed observability data from your serverless functions is crucial for effective troubleshooting.

Have you heard the buzz about observability with Honeycomb 🐝? It’s the best tool on the market for observing your systems in real time to reduce toil and delight users. But don’t listen to us, listen to our buzzing community of “Pollinators”–this blog post is dedicated to them 💖 An invite is sent to our shared Slack workspace “Pollinators” to everyone who signs up for Honeycomb.