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By Ken Rimple
You may have wrestled with a web application attempting to call an offsite web service, such as an OpenTelemetry Collector, and gotten an odd error with the word CORS in it. Something like: Or, maybe you got a generic thrown error from your fetch statement that states Error: Failed to fetch …and you wondered, “What’s the problem, and how can I fix it?” These kinds of errors are called CORS errors, and they can be a bit confusing.
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By Rox Williams
Another one in the history books: 2024 is (almost!) over. The OpenObservability Talks podcast, hosted by Dotan Horovits, recently featured a lively discussion with Charity Majors, Co-founder and CTO of Honeycomb, to reflect on the trends, achievements, and future of observability.
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By Ruthie Irvin
Space.com sums up the Big Bang as our universe starting “with an infinitely hot and dense single point that inflated and stretched—first at unimaginable speeds, and then at a more measurable rate to the still-expanding cosmos that we know today,” and that’s kind of how I like to think about November 2022 for junior developers.
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By Jamie Danielson
Have you ever had an alert go off that you immediately ignore? It’s a nuisance alert—not actionable—but you keep it around just in case. Or maybe you’ve looked at a trace waterfall and wondered what exactly happened during a gap that just doesn’t drill down deep enough to explain what’s going on. Do you know the feeling where you have just enough information to monitor what’s going on in your systems, but not quite enough to put your mind at ease?
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By Charity Majors
This post was written by Charity Majors and Phillip Carter. In May of 2023, we released the Honeycomb Query Assistant, an LLM-backed feature that lets engineers use natural language to generate and execute queries against their telemetry data. Instead of having to master a domain-specific query language, you can simply type in things like “slow endpoints by status code” and the Query Assistant will generate a relevant Honeycomb query for you to iterate on.
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By Yingrong Zhao
Refinery is a powerful tail-based sampler—but with great power comes great challenges. We heard your feedback and are excited to announce the release of Refinery 2.9, a rather large update that is packed with goodies to make your life easier when running Refinery in your network.
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By David Chang
This post was written by David Chang, Staff Software Engineer at Pinterest, and originally posted on the Pinterest engineering blog on Medium. Develocity, formerly known as Gradle Enterprise, is a powerful tool that speeds up local and CI build time, helps troubleshoot your builds, and analyzes your data. At Pinterest, we have a dedicated team, Mobile Builds, and we ensure that developers can build fast and often. This enables developers to be more productive by getting faster feedback on their code.
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By Alex Boten
We’re always interested in improving the signal-to-noise ratio of our internal telemetry at Honeycomb. In an effort to reduce the amount of noise in our logs, we looked at reducing and deduplicating the logs emitted by our infrastructure and applications.
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By Brian Chang
In the world of digital language learning, Duolingo stands out as a beacon of innovation and user engagement. With millions of users worldwide, their platform is designed not only to teach languages, but also to create a fun and engaging learning experience. Running on the robust AWS cloud infrastructure, Duolingo manages vast amounts of data and user interactions daily. As the company experienced rapid growth, Duolingo remained steadfast in their commitment to delivering a high-quality user experience.
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By Martin Thwaites
It’s very popular to push logs, in a formatted way, to the console output of an application (sometimes referred to as stdout). Although using a push-based approach like OTLP over gRPC/HTTP is preferred and has more benefits, there are many legacy systems that still use this approach. These systems typically use a JSON output for their logs. So, how do we get these JSON logs into a backend analysis system like Honeycomb that primarily accepts OTLP data?
The Director's Guide to Observability Webinar: Leveraging OpenTelemetry for Success - Highlight Reel
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By Honeycomb
In this 3-minute preview of our Director's Guide to Observability.
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By Honeycomb
Liz Fong-Jones walks you through how we debugged our Kubernetes Autoscaler with Honeycomb Log Analytics to achieve cost savings with Graviton4 instances. Having great observability is one way Honeycomb saves money.
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By Honeycomb
In this installment of Ask the Experts, Anijah asks Zach McCoy about distributed and what problems it solves.
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By Honeycomb
When an alert goes off because a Service Level Objective (SLO) is in danger of violation, it comes with a lot of context about what has been going wrong and for how long. Then Honeycomb gives you tools to explore the where & why. Here, Martin Thwaites walks through an example of diagnosing slower performance. What service is the problem, and under what circumstances?
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By Honeycomb
In this episode, Audrey Herndon, Technical Customer Success Manager at Honeycomb, asks #observability expert Dan Ravenstone at Top Hat, about the all-in-one solution.
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By Honeycomb
In this episode, Victoria Perera Roman, Sr. Technical Customer Success Manager at Honeycomb, asks #observability expert Chris Bertinato, Systems Architect at NS1, why some companies resist adopting Honeycomb.
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By Honeycomb
In this episode of Ask the Experts, Victoria Perera Roman, Sr. Technical Customer Success Manager at Honeycomb, asks Dominic Marino, Principal #software #engineer at Cargurus and #observability expert, why some companies resist adopting Honeycomb.
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By Honeycomb
There's a new way to flip through your data in Honeycomb, released this week! It's super for looking at structured logs. It's called: Explore Data. Get directly at the logs, spans, events, or metrics that power the fast analysis you can do with Honeycomb. See all the fields, the whole variety of values — now ordered by timestamp, with pagination. Modify your query and graphs right from the data table. It's all connected!
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By Honeycomb
See how Honeycomb gives you quick insight into web site performance, including Honeycomb gives you the metrics you need to see, and all the context you need to improve them.
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By Honeycomb
Martin investigates: what database queries are taking the longest? Then he digs into the one taking the most time, and asks: What user-initiated requests trigger this query? This kind of question helps developers focus our efforts where they count. And it's possible in Honeycomb with Relational Fields. This is #observability during development, using #OpenTelemetry #tracing and Honeycomb.
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By Honeycomb
Honeycomb is an event-based observability tool, but you can-and should-use metrics alongside your events. Fortunately, Honeycomb can analyze both types of data at the same time. When maturing from metrics-based application monitoring to an observability-based development practice, there are considerations that can make the transformation easier for you and your team.
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By Honeycomb
Evaluating observability tools can be a daunting task when you're unfamiliar with key considerations and possibilities. This guide steps through various capabilities for observability tooling and why they matter.
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By Honeycomb
This document discusses the history, concept, goals, and approaches to achieving observability in today's software industry, with an eye to the future benefits and potential evolution of the software development practice as a whole.
- December 2024 (9)
- November 2024 (7)
- October 2024 (14)
- September 2024 (12)
- August 2024 (10)
- July 2024 (15)
- June 2024 (9)
- May 2024 (10)
- April 2024 (8)
- March 2024 (10)
- February 2024 (11)
- January 2024 (8)
- December 2023 (6)
- November 2023 (8)
- October 2023 (7)
- September 2023 (9)
- August 2023 (8)
- July 2023 (7)
- June 2023 (14)
- May 2023 (16)
- April 2023 (12)
- March 2023 (22)
- February 2023 (7)
- January 2023 (8)
- December 2022 (3)
- November 2022 (8)
- October 2022 (16)
- September 2022 (10)
- August 2022 (11)
- July 2022 (11)
- June 2022 (14)
- May 2022 (6)
- April 2022 (14)
- March 2022 (8)
- February 2022 (9)
- January 2022 (9)
- December 2021 (11)
- November 2021 (7)
- October 2021 (9)
- September 2021 (5)
- August 2021 (4)
- July 2021 (6)
- June 2021 (11)
- May 2021 (2)
- April 2021 (4)
- March 2021 (5)
- February 2021 (9)
- January 2021 (6)
- December 2020 (9)
- November 2020 (7)
- October 2020 (18)
- September 2020 (11)
- August 2020 (4)
- July 2020 (6)
- June 2020 (4)
- May 2020 (6)
- April 2020 (7)
- March 2020 (5)
- February 2020 (4)
- January 2020 (5)
- December 2019 (3)
- November 2019 (3)
- October 2019 (2)
- September 2019 (7)
- August 2019 (6)
- July 2019 (5)
- June 2019 (6)
- May 2019 (6)
- April 2019 (4)
- March 2019 (3)
- February 2019 (3)
- January 2019 (4)
- December 2018 (9)
- November 2018 (8)
- October 2018 (2)
- September 2018 (5)
- August 2018 (11)
- July 2018 (7)
- June 2018 (7)
- May 2018 (7)
- April 2018 (3)
Honeycomb is a tool for introspecting and interrogating your production systems. We can gather data from any source—from your clients (mobile, IoT, browsers), vendored software, or your own code. Single-node debugging tools miss crucial details in a world where infrastructure is dynamic and ephemeral. Honeycomb is a new type of tool, designed and evolved to meet the real needs of platforms, microservices, serverless apps, and complex systems.
Honeycomb provides full stack observability—designed for high cardinality data and collaborative problem solving, enabling engineers to deeply understand and debug production software together. Founded on the experience of debugging problems at the scale of millions of apps serving tens of millions of users, we empower every engineer to instrument and query the behavior of their system.