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.

Monitoring the state of DevOps, multi-cloud, microservices and data centre environments is no easy task. You can’t manage what you can’t see. Gaps in your monitoring capability leave your enterprise vulnerable to catastrophic, customer impacting infrastructure blind-spots.

At OpenObservability, we had the pleasure to sit down with Andre Boutet, the Senior Director of Cloud Operations and Services for OneSpan. Andre had a conversation with our CTO, Jonah Kowall, around what observability means to his team and his organization. Teaser: It’s not just about ensuring uptime and availability for external systems. It’s a philosophy with a foundation on supporting the entire development lifecycle.

Slack recently had a no good very bad day in which some broken external monitoring contributed to a perfect storm. But one passage caught our eye: “After the incident was mitigated, the first question we asked ourselves was why our monitoring didn’t catch this problem. We had alerting in place for this precise situation, but unfortunately, it wasn’t working as intended.

At ecobee, adopting Honeycomb started as a grassroots effort. Engineers signed up for the free tier and quickly started sharing insights with teammates. When it came time for ecobee to make the “build vs. buy” decision for observability tooling, sticking with Honeycomb was the clear choice. Now on the enterprise plan, ecobee’s engineering squads rely on features like SLOs to support the business’s need to map engineering effort to user impact.

According to Forbes, 2.5 quintillion bytes of data are created every day. Data volumes have grown exponentially in recent years due to the growth of the Internet of Things (IoT) and sensors. The majority of data collected has been collected in the last two years alone. For example, the U.S. generates over 2.5 million gigabytes of Internet data every minute, and over half of the world’s online traffic comes from mobile devices.

Honeycomb’s event-based pricing model is pretty simple: we only care about how many events you send. For teams running workloads at scale, the question becomes: are all of my events worth keeping? How can you reduce overall event volume while maintaining fidelity? This HoneyByte is all about sampling strategies you can use to lower costs without sacrificing the value of your data.

Discover how DevOps and SREs can develop more and operate less by applying AI to events, metrics, traces and logs to keep CI/CD agile and your business growing.

We’ve released some improvements to our Java Beeline library! Allow me to share all the interesting new features.

It would not be wrong to say that Observability is the new buzz word for the last couple of years at least and often we find organizations burden themselves with questions like – The answer to these questions lies in understanding the concept of Observability and how it ties in with the digital experience monitoring strategy of your organization and only then can you determine where you stand in terms of Observability.

Observability changes the way you understand and interact with your applications in production. Beyond knowing what’s happening in prod, observability is also a compass that helps you discover what’s happening on the way to production. Pierre Tessier joins us on Raw & Real to talk about how Honeycomb uses observability to improve the systems that support our production applications.

Today, users and customers are driven by response rates to their online requests. It’s no longer good enough to just have a request run to completion, it also has to fit within the perceived limits of “fast enough”. Yet, as we continue to build cloud-native applications with microservice architectures, driven by container orchestration like Kubernetes in public clouds, we need to understand the behavior of our system across all aspects, not just one.

This is the story of how I used Honeycomb to troubleshoot redis/redis-rb#924 and discovered a surprising workaround.