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Despite its simplicity, “DevOps” has a profound impact on modern software development. As a seemingly innocuous phrase conceals an underlying tension between expansion and operational efficiency, which can ultimately lead to impeded dialogue and ineffective management of increasingly complex technological infrastructures. The founders of Honeycomb, an observability startup, aimed to bridge the gap in DevOps rigidity and communication that often hinders collaboration.
Around 2012, a serendipitous encounter unfolded between two enterprising minds – Christine Yen and Charity Majors – as they collaborated at Parse, a pioneering force in developing robust back-ends for mobile applications. While Yen focused on developing aspects, Majors demonstrated a strong inclination towards shaping the underlying infrastructure. Despite diverging career paths and distinct skill sets, a strong bond developed between them.
As a testament to her innate affinity for technology, she emerged from the womb clutching a pager, setting the stage for a lifelong passion that would define her career as an operations and infrastructure engineer. As a former product engineer, I had a passion for crafting innovative and memorable experiences for our customers, notes Yen. I previously undermined manufacturing confidence and inadvertently dismantled key components of the charitable organization’s foundation.
Despite advancements in 2012, persistent gaps in observability still existed. Extracting data from logs was a challenging task, becoming even more arduous as software stacks evolved from monolithic applications running on-premises to microservices-based systems operating within clouds, let alone modern serverless and stateless applications deployed in Kubernetes clusters.
In 2013, Facebook acquired Parse, unveiling Yen and Majors to a pioneering logging and metrics tool known as Scuba. Built on a robust in-memory time-series database, Scuba suddenly enabled engineers to visualize previously inaccessible “nitty-gritty” insights, including data related to specific app IDs, software development kit (SDK) versions, and app variants. Their eyes were suddenly opened to a completely novel universe of observability elements and efficiency troubleshooting opportunities.
Yen recalled that the pace was relentless, with an overwhelming influx of information prompting rapid-fire analysis: “You’d digest enormous amounts of data, generate a chart, and then instruct, ‘Dive deep into this specific application and this particular SDK framework.'” Since we operated as a platform, we were vulnerable to the possibility of a Russian relationship app emerging unexpectedly, utilizing a novel endpoint to compromise our cluster’s integrity. It was inevitable that this issue arose frequently, necessitating a thoughtful approach to overcome its impact.
Established on a foundation of extensive Scuba knowledge, Yen and Majors departed from Facebook’s constraints to launch Honeycomb in 2016. The duo proposed a novel type of observability tool designed to categorize operational concepts in developers’ terminology, aiming to bridge the gap between Development and Operations teams by introducing simplicity and understandability.
What were these reasonably understandable worlds that could potentially be grasped at an exceptionally high level where everyone had Rails applications running on five robust EC2 instances, and they were considered one’s own personal playgrounds, right? Yen, CEO of Honeycomb, notes that they attribute cute names to their problems and become increasingly anxious when any issue arises. As the rivalry between pets and cattle reaches a boiling point. Now we’re witnessing cases where we’re biking seamlessly through the cloud. “We’re transitioning away from our current five-app-server-monolith infrastructure in favor of a more scalable and dynamic architecture, leveraging microservices deployed on Kubernetes pods that seamlessly self-recover through continuous recycling.”
In 2016, Yen and Majors, Honeycomb’s chief technology officer, made a handful of pivotal decisions that ultimately steered the company’s trajectory. It was found that there wasn’t a compelling reason to fragment the three pillars of observability – logs, metrics, and traces – which are often separated by some observability providers. By consolidating logs, metrics, and traces under a single umbrella, it becomes significantly easier to identify patterns and correlations between data points, thereby expediting the resolution of complex problems.
The corporation’s second significant architectural decision was the selection of a column-oriented database to store all observability data. The new Honeycomb release exceeded expectations and received praise from critics, including Yen, who noted its superior quality.
During a recent interview at re:Invent 2024, she clarified that her company didn’t pioneer column shops and wouldn’t be the first to highlight their significance, stating, “There’s nothing particularly remarkable about column shops.” “Why didn’t we pioneer in recording key performance indicators and data points from the beginning?” Shouldn’t we explore ways to preserve their cohesion, especially when they’re discussing the same topic in a context like an application?
By eschewing the arduous task of manually integrating disparate knowledge sets for analysis, Honeycomb’s innovative design seamlessly stores them in a cohesive manner, leveraging the standardized OpenTelemetry (OTEL) format to facilitate effortless analysis. By abstracting away from the requirement for seamless data fusion, Honeycomb’s contextualization of complex metadata enables a crucial functionality: translating technical operations lingo into a business-oriented lexicon that resonates with developers.
As we collaborated on the project, I could recall occasions when you’d ask me to verify the write-throughput on a specific instance of Cassandra, and I’d have to investigate to provide accurate information. I’m actually scared,” Yen mentioned. As Christine, I found that these discussions transformed into meaningful exchanges about the performance of my Cassandra instances, specifically highlighting increased write throughput and its implications for data processing. It seems that visibly, a significant surge in traffic has been observed at this endpoint, driven by the mobile application in question. What’s happening?’
When discussing a perceived decline in performance, she would remark, “That’s a regression.” Because it’s in my realm now, I’ll just go and find out? Now you’re able to make an attempt to reproduce it in your own look at? I’m now able to explore the underlying business rules and architecture. “Now that I understand the root cause, I recognize which apps you’re referring to, and that’s exactly how our collaboration changed as an engineering team.”
That method appears to be resonating, because the San Francisco-based firm has already signed 800 paying clients, together with corporations like Vanguard, Fender Guitars, and Jack Henry & Associates. The corporation, having secured around $147 million through its Collection D round, also recently garnered an award in the category of Best Large Data Product: DataOps and Observability.
Several observability firms are revolutionizing the status quo by transforming how organizations approach monitoring and troubleshooting their digital infrastructure. Companies that have migrated their IT infrastructures to public cloud environments are grappling with overwhelming volumes of log data, performance metrics, and application trails, coupled with the significant costs associated with storing and processing such vast amounts of information, making them receptive to innovative solutions. Although the established players in the observability space retain their momentum, a fresh cohort of innovators, including up-and-coming startups like Honeycomb, are gaining traction.
Here’s an improved version: “As Honeycomb seeks to attract clients dissatisfied with traditional approaches from larger rivals in the observability space, CEO Spencer Yen notes that these clients are looking for innovative solutions to tackle today’s complex storage and processing challenges.”
“To reinvigorate software development, it’s essential to regularly question our approaches and tools, potentially reassessing decades-old methods used in conjunction with telemetry, APM, logging, and monitoring instruments.” “I think our readers appreciate our presence because we’re willing to challenge them.”
