Instrument your Go apps with OpenTelemetry

Instrument your Node.js apps with OpenTelemetry

Instrument your Java apps with OpenTelemetry

Instrument your .NET apps with OpenTelemetry

Instrument your Python apps with OpenTelemetry

Instrument your Ruby apps with OpenTelemetry

Manage OTel data before sending to Honeycomb

Send your ADOT data directly to Honeycomb

We here at Honeycomb really like OpenTelemetry and goodie bags, so we have a nice little OpenTelemetry-flavored holiday goodie bag to share with you before you’re off for the holidays!

In the last few years, the usage of databases that charge by request, query, or insert—rather than by provisioned compute infrastructure (e.g., CPU, RAM, etc.)—has grown significantly. They’re popular for a lot of the same reasons that serverless compute functions are, as the cost will scale with your usage. No one is using your site? No problem: you’re not charged.

Recently, Honeycomb held a roundtable discussion (available on demand) with Camal Cakar, Senior Site Reliability Engineer at Jimdo; Pierre Lacerte, Director of Software Development at Upgrade; and Kristin Smith, DevOps Engineer at Campspot. We talked about using OpenTelemetry and explained some important lessons the panelists learned—and are still learning in some cases. 

Here are five best practices based on these lessons and Honeycomb’s own experience with OpenTelemetry.

When you want to direct your observability data in a uniform fashion, you want to run an OpenTelemetry collector. If you have a Kubernetes cluster handy, that’s a useful place to run it. Helm is a quick way to get it running in Kubernetes; it encapsulates all the YAML object definitions that you need. OpenTelemetry publishes a Helm chart for the collector.

Today, I’d like to share with you a new community-contributed integration that helps you optimize and debug your Gradle builds. This new Gradle plugin is available today, is free to use, and you can use it immediately with a free Honeycomb account.

Just a few short months ago, we talked about a bunch of updates to Honeycomb’s support for OpenTelemetry. To the surprise of no one, we’ve got more updates to share!

Learn how Jimdo, Upgrade, and Campspot benefited from OpenTelemetry, whether in improved performance, or by avoiding vendor lock-in.

In this post, we’ll look at how to host the OpenTelemetry Collector in Azure Container Apps. There are a few gotchas with how it’s deployed, so hopefully this will stop you from hitting the same issues.

We’ve got a lot of OpenTelemetry-flavored honey to send your way, ranging from OpenTelemetry SDK distribution updates to protocol support. We now support OpenTelemetry logs, released a new SDK distribution for OpenTelemetry Go, and have some updates around OpenTelemetry + Honeycomb to share. Let’s see what all the buzz is about this time!

In this post, we’ll look at how you can use OpenTelemetry to monitor your unit tests and send that data to Honeycomb to visualize. It’s important to note that you don’t need to adopt Honeycomb, or even OpenTelemetry, in your production application to get the benefit of tracing. This example uses OpenTelemetry purely in the test project and provides great insights into our customer’s code.

The scenario: you want to see distributed traces, maybe for your web app. You’ve set up an OpenTelemetry collector to receive OTLP traces in JSON over HTTP, and send those to Honeycomb (how to do that is another post, and we’ll link it here when it’s up).

The question: does it work?

Let’s test the collector and its connection to Honeycomb by sending a test span.

One of the reasons that OpenTelemetry is great at doing this is that a lot of the common attributes you may find on a span are given standard names, so the systems receiving the data to visualize them don’t need to know the specifics of your system. This is really a superpower of OpenTelemetry, as it gives a level playing field for consumers of that information—meaning that you, as a developer, can forget about vendor-specific things.

“How do I get started on instrumentation with OpenTelemetry, while also following best practices for the long-term?” This article is all about taking you from A to Z on instrumentation. Learn how to create immediate observability and see traces in your application right away, without changing code—and more!

Dear Miss O11y, I’ve been told I need to use the OpenTelemetry Collector, but I have no idea what it is, or why I need it? Should I be using it? What value does…

Today, the Honeycomb OpenTelemetry Distribution for Java reaches a major milestone with a 1.0 release. This is the first Honeycomb OTel Distro to come out of beta and go into the general release category,…

I’m adding instrumentation code to my app. To set it up, I have to create a Resource. What does that mean? What can I do with it? Ah, I too have wondered about this….

The promise of OpenTelemetry is that it can help you avoid vendor lock-in by allowing you to instrument your applications once, then send that data to any backend of your choice. This post shows…

We want to measure the time that a user waits between pushing a button and seeing their result. The examples for creating a trace span only work within a single page, and the button…

“What is up with the Context in OpenTelemetry? Why do I need to mess with it at all? Why, when I set a span as active, don’t subsequent spans just use it as a…

“There’s a lot to understand in OpenTelemetry; for instance, what is the difference between a Tracer and a TracerProvider? How should I use them?” OpenTelemetry is a strong standard for instrumentation because it is…

One of the most common questions we get at Honeycomb is “What insights can you get in the browser?” Browser-based code has become orders of magnitude more complex than it used to be. There…

You might already know that OpenTelemetry is the future of instrumentation. It’s an open-source and vendor-neutral instrumentation framework that frees you from the trap of using proprietary libraries simply to understand how your code…

OpenTelemetry (or “OTel”) helps you get your instrumentation started quickly, and it helps you get the most out of that telemetry data by providing flexible exporting options. As a result, it’s emerging as the…

The current landscape of what our customers are dealing with in monitoring and observability can be a bit of a mess. For one thing, there are varying expectations and implementations when it comes to…

It’s easy to get started with Java and Honeycomb using OpenTelemetry. With Honeycomb being a big supporter of the OpenTelemetry initiative, all it takes is a few parameters to get your data in. In…

We’ve released support for tracing header interoperability in all of our Beelines. This means you can now mix and match distributed services instrumented with Beelines or with OpenTelemetry, and your traces will be preserved in Honeycomb!

We often get questions about the difference between using our Beeline SDKs compared with other integrations, especially OpenTelemetry (abbreviated “OTel”). That’s why the team decided to do some integration dogfooding by instrumenting our own code with OpenTelemetry alongside existing Beeline instrumentation.

Honeycomb allows you to send in data from a variety of sources. The steps to get there are a choose-your-own-adventure path and the choices to make may not always be clear to folks new…

Instrumented apps using Jaeger, Zipkin, OpenTracing or OpenCensus can send trace data to OpenTelemetry and Honeycomb.io San Francisco, Calif.–OpenTelemetry, an open source project designed to capture critical telemetry data from production services and apps…

We’re really big fans of OpenTelemetry at Honeycomb. As we’ve blogged about before, OpenTelemetry is the next phase of the OpenTracing and OpenCensus projects. Instead of working on separate but similar efforts, those two…

There’s been a fair bit of buzz lately about OpenTelemetry, which is the next major version of the OpenTracing and OpenCensus projects. The leadership of those two projects have come together to create OpenTelemetry,…

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.

Dear Miss O11y,

I want to make my microservices more observable. Currently, I only have logs. I’ll add metrics soon, but I’m not really sure if there is a set path you follow. Is a guide of some sort, or best practice, like you have to have x kinds of metrics?

I just want to know what all possibilities are out there. I am very new to this space.

The open source community talks a lot about the problem of aligning incentives. If you’re not familiar with the discourse, most of this conversation so far has centered around the most classic model of open source: the solo unpaid developer who maintains a tiny but essential library that’s holding up half the internet. For example, Denis Pushkarev, the solo maintainer of popular JavaScript library core-js, announced that he can’t continue if he’s not better compensated. 

Debug your AWS Lambda apps with OTel

It’s been a minute since our last Feature Focus, and we have a bit of catching up to do! I’m happy to report we’ll resume monthly updates next month, but until then, please enjoy this super-sized winter digest of what we’ve been up to at Honeycomb.

So you’re used to debugging systems using a distributed trace, but your system is about to introduce a message queue—and that will work the same… right? Unfortunately, in a lot of implementations, this isn’t the case. In this post, we’ll talk about trace propagation (manual and OpenTelemetry), W3C tracing, and also where a trace might start and finish.

Distributed tracing enables you to monitor and observe requests as they flow through your distributed systems to understand whether these requests are behaving properly. You can compare tiny differences between multiple traces coming through your microservices-based applications every day to pinpoint areas that are affecting performance. As a result, debugging and troubleshooting are simpler and faster. No one has to guess or spend countless hours researching possible causes for issues, like you would if traditional logging methods were your only resource.

Growing pains can be a natural consequence of meteoric success. We were reminded of that in our recent panel discussion with SumUp’s observability engineering lead, Blake Irvin, and senior software engineer Matouš Dzivjak. They shared how SumUp’s rapid growth spurt compelled them to change their resolution process—both logistically and culturally—to ensure a service level quality that reflects their customer obsession.

When an organization signs up for Honeycomb at the Enterprise account level, part of their support package is an assigned Technical Customer Success Manager. As one of these TCSMs, part of my responsibilities is helping a central observability team develop a strategy to help their colleagues learn how to make use of the product. At a minimum, this means making sure that they can log in, that relevant data is available, that they receive training on how to query, and perhaps that they collaborate with the rest of Honeycomb’s CS department to solve problems as they arise.

The best mechanism to combat proliferation of uncontrolled resources is to use Infrastructure as Code (IaC) to create a common set of things that everyone can get comfortable using and referencing. This doesn’t block the ability to create ad hoc resources when desired—it’s about setting baselines that are available when people want answers to questions they’ve asked in the past.

We’re here to show you three ways you can jumpstart a distributed tracing effort, starting small and expanding as it makes sense. These examples involve only a little code and perhaps a bit of a mindset change. Starting small with distributed tracing can even be fun, because who doesn’t like getting customized results without much work? 

As 2022 draws to a close, the Honeycomb team is getting ready to take some time to recharge our collective batteries and get ready for the new year. For some of us, that means spending some well-earned time away from our keyboards. For others, it means we get to spend our computer time doing something just for fun.

Today, we’re announcing the expansion of Honeycomb integrations with various AWS services. This update now covers a much wider swath of AWS services, makes it easier than ever to integrate your AWS stack with Honeycomb, and with our new BubbleUp enhancements, you’ll be identifying and debugging hidden issues in your AWS stack faster than ever.

In our Feature Focus October 2022, we’ve updated documentation and derived columns, provided guides to make CI/CD easier, and more.

Today, we’re announcing the launch of Honeycomb Service Map. This isn’t your grandparent’s version of a service map. This feature reimagines what it is that you want to know or investigate when looking at visualizations of how your services communicate with one another.

Getting existing telemetry into Honeycomb just got easier! With the release of the Datadog APM Receiver, you can send your Datadog traces to the OpenTelemetry Collector, and from there, to any OpenTelemetry-compatible endpoint.

I am thrilled to share with you that Honeycomb now has a Field CTO: our very own Liz Fong-Jones.

How do you solve the people and culture problems that are necessary in making the shift to adopt observability practices? And once you instill those changes, how do measure the benefits?

Today, I’d like to tell you about a new community-contributed integration that connects Honeycomb to your ServiceNow workflows. My new integration reimagines what’s possible when connecting observability tools with ITSM systems. This post explains how it works and how to get started with it.

Feature Focus: September 2022. Here’s a look at improvements we’ve made to Honeycomb in September, including: updates to a buuunch of APIs, new integrations, and Refinery upgrades.

In the beginning, there were people who wrote and ran software. At some point, we spun away ops skills from dev skills into two different professions, but that turned out to be a ginormous mistake, so along came DevOps to reunify them. Nowadays, ops as an independent profession is in the process of fading out. Companies are spinning down their ops teams left and right. Engineers who formerly identified as sysadmins or operations have turned into DevOps engineers, and soon there will just be “software people” again. This is the way of things.

Feature Focus: August 2022. Here’s a look at improvements we’ve made to Honeycomb in August, including: better filtering capabilities, derived columns editor, and a new copy button.

Observability is about understanding systems, which means more than just production. Moving from logs to tracing and showing causality can be done locally, as well. We can give developers the same superpowers that SREs have: observability-driven development. 

People use “observability team” as a catchall basket for all kinds of things these days—from cutting-edge tech to truly heinous hacks. Eh, it is what it is. The industry may be in a roiling state of massive flux, but I’m cautiously excited about the changes beginning to take shape and emerge from the muck. And I definitely think it’s worth spending some time talking about what observability teams can and should be.

In the same way as the business is likely ok with you writing developer-based tests (unit, automation, integration), instrumentation is the same. The conversation we need to have is that instrumentation, or knowing the system is healthy, is the work we need to do for the feature. In my opinion, it’s even more important than those.

Two of our folks went to Monitorama 2022, and they gleaned a few pearls of wisdom they’d love to share with you, including an unexpected, but surprisingly insightful talk on carbon impact reporting. Read more now.

Are you overspending on monitoring and APM tools? Forrester’s Total Economic Impact analysis of Honeycomb identified significant ROI in customers using us to reduce spend on less efficient APM workflows. But this isn’t about…

This post will talk about using a derived column to directly connect individual customer experiences to the cost of providing that service with AWS Lambda. By leveraging these tools, we can better understand when our product is used in costly ways, and also provide tooling to better analyze and understand the cost effects of configuration changes.

“It’s expensive. It’s difficult. Our APM works just fine.” The three myths of observability can lead to being on call with under-instrumented tools. That’s exactly what happened to Paige Bernier, retired SRE. Let’s learn about her experience and see how we can avoid being in the same situation.

The software industry is moving toward teams that own the services they build. This concept encloses principles and possibilities from movements toward microservices, DevOps, Agile, and Project to Product. In these paradigms, a team of people delivers software that provides valued capabilities. These capabilities help customers get their work done, support business operations, or enable other software to do these. Writing code is only part of this; capabilities only work if the software is running in production. Service-ownership teams carry this responsibility. To own production, a team needs visibility into production. Honeycomb recognizes service ownership and supports it.

Our Author’s Cut series takes a deep dive into our O’Reilly Observability Engineering book. Join us for this session on structured events.

I’m Phillip, a product manager here at Honeycomb. After eleven-ish months of working on our product, I totally understand observability, right? …Kinda? Sorta? Maybe? I’m not sure—but, I have been sitting in this space…

Dear Miss O11y, I use .NET and I keep seeing something called `Activity` but in OpenTelemetry there is only talk about “Span” and “Trace,” why? And what should I be using? Kthxbye This is…

Dear Miss o11y, What’s the first small thing to do in o11y that would teach me something, bring something valuable, and open the way for something else? Observability doesn’t have to be a big,…

The book is done. The book is FINISHED. There will be no more writing of the book! Holy macaroni. If you think you might be sensing just a SMIDGE of relief, you wouldn’t be…

Any significant shift in an organization’s software engineering culture has the potential to feel tectonic, and observability (o11y for short)—or more specifically, Observability Driven Development—is no different. Leaning into observability, which calls for tool-enhanced…

Miss O11y is delighted to welcome our newest band member: Martin Thwaites! Martin has been a member of the Honeycomb user community practically since its inception. He is a UK-based consultant who specializes in…

Tracing looks like a lot of work. We already have logs. Why bother adding traces? Ah, good question!  TL;DR: Trace instead of log. Traces show connection, performance, concurrency, and causality. Logs are the original…

Honeycomb Pro is about to get even better. Starting today, all Pro accounts have access to Honeycomb Metrics and two Service Level Objectives (SLOs), previously only available to Enterprise accounts. Full disclosure: Later this…

TL;DR: startSpan is easier and measures a duration. Use it if your work won’t create any subspans. startActiveSpan requires that you pass a callback for the work in the span, and then any spans…

We know that you value collaboration. That’s why we share incident reviews and learnings—because we believe the entire community benefits by working together transparently.  In the spirit of working better together, we invited ecosystem…

I think my biggest question is: How do I introduce observability without manually weaving tracing-related code throughout my codebase since that adds a lot of noise? TL;DR: Use auto-instrumentation from OpenTelemetry. Traces will happen….

In the past, we’ve written about what instrumentation is and the insights it provides. Instrumenting your code generates telemetry that shows you how your system is performing, and whether your system is healthy. Like…

How do we bring observability to the DB world? In the SQL Server world, you can marry up perfmon and extended event traces but is that enough? What about the other DBs? Oh goody,…

What are the foundational elements of a high-performance engineering team? While there’s no silver bullet, a few common threads make up the fabric of engineering teams that set the standard for velocity, quality, and…

At Honeycomb Developer Week, I got an opportunity to walk through a couple of fun new features we’ve shipped since August and ways that we’ve been able to improve Honeycomb for you.  Hearing feedback…

Observability is a great way to understand how your system is operating in production, diagnose errors when systems fail, and find subtle gaps in logic. But there’s no reason to wait until your code…

Getting started with observability can be time consuming. It takes time to configure your apps and practice to change the way you approach troubleshooting. So it can be hard to prioritize investing time, especially…

Have you ever deep dived into the sea of your tracing data, but wanted additional context around your underlying system? For instance, it may be easy to see when/where certain users are experiencing latency,…

I have a good sense of how to use traces to understand my system’s behavior within request/response cycles. What about multi-request processes? What about async tasks spawned within a request? Is there a higher-level…

Is the lack of time holding you back from sharpening your observability (o11y) skills? Maybe you’ve dipped your toes into o11y, but you’re not sure how and where it will drastically improve your team’s…

Dear Miss O11y: It feels so overwhelming to get started with observability. I want to use Honeycomb, but it feels like I can’t justify spending the time and money without having proof of how…

This blog was co-authored by Amy Davis.  The moment of launching something new at a game studio (titles, experiences, features, subscriptions) is a blockbuster moment that hangs in the balance. The architecture—distributed and complex,…

Honeycomb sees a surge in migrations from legacy APM tools to observability as developers seek faster and more flexible ways to optimize code in complex cloud environments San Francisco, Calif., October 20, 2021 –…

Today, we announced that Honeycomb has raised $50M in Series C funding, in a round led by Insight Partners and joined by all existing investors from our Series B. We’re using this investment to…

The Query Data API is a Honeycomb Enterprise feature. With a Honeycomb Enterprise account, you can use this API today. Head over to our API docs to learn how to get access to your…

San Francisco, Calif., September 8, 2021 – Organizations using Honeycomb for observability now have a new metrics capability to quickly identify and resolve system issues. Honeycomb, which provides industry-leading observability software for understanding, troubleshooting,…

Join us for a live tour & Q&A session on Honeycomb Metrics. Ready to get hands-on? Honeycomb Metrics is already included in Enterprise subscriptions. Existing Free or Pro customers can request an Enterprise trial to try…

To dive deeper into distributed tracing and what it can do for you, download a free copy of “Distributed Tracing: A Guide for Microservices and More.” You can also try Honeycomb for yourself with a…

Rich Anakor, chief solutions architect at Vanguard, is on a small team with a big goal: Give Vanguard customers a better experience by enabling internal engineering teams to better understand their massively complex production…

Modern software services are expected to be highly available, and running a service with minimal interruptions requires a certain amount of reliability-focused engineering work. At the same time, teams also need to build new…

But it’s better than nothing… Most of the industry is racing to adopt better observability practices, and they’re discovering lots of power in being able to see and measure what their systems are doing….

New metrics feature helps customers bridge the gap between traditional debugging practices and modern systems, without compromising the powerful insights of observability. SAN FRANCISCO, June 10, 2021 – Honeycomb, which provides industry-leading observability software…

You’ve probably seen the announcement about our upcoming annual conference, o11ycon+hnycon, happening June 9–10. If you’re still not registered, here’s a list of nine reasons to attend. 1. Highly interactive content Honeycomb isn’t your…

Have you registered for o11ycon+hnycon yet? If not, now’s the time! This highly interactive virtual event is happening June 9–10 and designed to connect you with your peers to explore cutting-edge observability practices. We’ve…

In case you missed it, Honeycomb is gearing up for our conference, o11ycon. Based on your feedback, we’re also adding a new day to that event this year: hnycon. o11ycon+hnycon is a two-day virtual…

A year ago, we wrote about our experiences as early adopters of Graviton2, and how we were able to see 30% price-performance improvements on one dogfood workload from switching to the arm64 architecture. In…

This HoneyByte walks through how to get Refinery running locally to try out different configuration options and sampling methods.

San Francisco, March 2, 2021 – Honeycomb, the company that pioneered the first commercial observability solution to understand, debug, and improve distributed production systems, announced today a new solution, Refinery, to help enterprises refine…

I’m delighted to announce that Honeycomb has raised $20M in Series B funding, led by e.ventures Growth, with participation from existing investors Scale Venture Partners, Storm Ventures, Next World Capital, and Merian Ventures, and…

Developer Advocate Shelby Spees bookends 2020 with appreciation for her team and the community.

We’re here at last: the final days of 2020. Let’s take a look back at this year’s most popular Honeycomb blog posts. Observability 101 In Observability 101: Terminology and Concepts, Shelby Spees reflects on…

OpenTelemetry has evolved so much since the 2019 KubeCon North America in San Diego, where I live-demoed OpenTelemetry on the keynote stage and highlighted our alpha to the world. We’re excited to be entering…

Today, AWS announced enhancements for AWS Distro for OpenTelemetry. We’re working with AWS to build in additional support from partners. In tandem with that launch, Honeycomb is announcing support for event ingestion using OpenTelemetry…

This post is to help orient folks who want to learn more about observability but maybe feel overwhelmed by the vocabulary list. The goal is to get everyone on the same page about what these words mean so that we can focus on leveraging the tools and ideas to build better software and deliver more value!

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…

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 kickass community of “Pollinators”–this blog post is dedicated to them 💖

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.

Once again we are at the end of another year, facing into the endless potential of the next one, and thinking back on the fun and hard work behind us. Join me now in…

It’s that season, when we take time to consider what we’re grateful for and extend thanks to those we value and the experiences we treasure. One special aspect of America’s Thanksgiving holiday is the…

Observability-driven development requires both rich query capabilities and sufficient instrumentation in order to capture the nuances of developers’ intention and useful dimensions of cardinality. When our systems are running in containers, we need an…

If you’re involved in improving the performance of your application, you’ve probably heard about application performance monitoring (APM), metric analysis, and log management. But you might not understand what they are or the differences…