Honeycomb announced that it is the first observability platform to launch fully-executing Natural Language Querying using generative AI for its new capability, Query Assistant.
This development dramatically scales the platform's query power and makes observability more usable for all engineering levels.
Honeycomb's new Query Assistant is a distinctly different approach to AI compared to what's been done historically by traditional APM and ops tools that apply AI to data analytics for features like automated alerting. This capability uses generative AI to enhance human intuition by allowing users, no matter how seasoned, to ask questions and get fast feedback on what's happening with their code.
Query Assistant joins Honeycomb's other human-first, machine-assisted debugging tools, such as BubbleUp. Used by engineering teams to quickly answer complex problems in their code, BubbleUp uses machine analysis to cycle through billions of high-cardinality data points (fields like userId, shoppingCartId, and orderId, etc.), visually compares problematic user experiences to healthy ones, and identifies the differences. This dramatically accelerates the debugging process by eliminating the time-consuming and error-prone legacy APM workflow of jumping from metrics dashboards to individual logs and traces to guess at problematic patterns.
"The best developer tools are increasingly going to be the ones that get out of your way and become invisible," said Charity Majors, CTO of Honeycomb. "Observability shouldn't require you to master complicated tools or languages that force you to constantly switch context and piece together clues to get answers to complex problems. The only thing observability tools should encourage you to focus on is your own curiosity about what's happening in your system."
Honeycomb believes that delivering superior user experiences is a team sport and makes significant investments in making observability usable for all. This is showcased in our unique pricing model that has no additional charge per service, host, memory, custom field, or seat as well as our collaborative team features like the ability to share query histories. With the addition of Query Assistant, anyone on the team can easily understand how their application code is behaving in the hands of real users in unpredictable and complex cloud environments. This new capability is a great first step for Honeycomb R&D to further explore how AI can be incorporated into the product to enhance the Honeycomb user experience.
Query Assistant is available to all Honeycomb users. As of today, it is an experimental feature that can be turned off by teams. No user data is passively sent to OpenAI, and no data is retained for training models.
The Latest
We're at a critical inflection point in the data landscape. In our recent survey of executive leaders in the data space — The State of Data Observability in 2024 — we found that while 92% of organizations now consider data reliability core to their strategy, most still struggle with fundamental visibility challenges ...
From the accelerating adoption of artificial intelligence (AI) and generative AI (GenAI) to the ongoing challenges of cost optimization and security, these IT leaders are navigating a complex and rapidly evolving landscape. Here's what you should know about the top priorities shaping the year ahead ...
In the heat of the holiday online shopping rush, retailers face persistent challenges such as increased web traffic or cyber threats that can lead to high-impact outages. With profit margins under high pressure, retailers are prioritizing strategic investments to help drive business value while improving the customer experience ...
In a fast-paced industry where customer service is a priority, the opportunity to use AI to personalize products and services, revolutionize delivery channels, and effectively manage peaks in demand such as Black Friday and Cyber Monday are vast. By leveraging AI to streamline demand forecasting, optimize inventory, personalize customer interactions, and adjust pricing, retailers can have a better handle on these stress points, and deliver a seamless digital experience ...
Broad proliferation of cloud infrastructure combined with continued support for remote workers is driving increased complexity and visibility challenges for network operations teams, according to new research conducted by Dimensional Research and sponsored by Broadcom ...
New research from ServiceNow and ThoughtLab reveals that less than 30% of banks feel their transformation efforts are meeting evolving customer digital needs. Additionally, 52% say they must revamp their strategy to counter competition from outside the sector. Adapting to these challenges isn't just about staying competitive — it's about staying in business ...
Leaders in the financial services sector are bullish on AI, with 95% of business and IT decision makers saying that AI is a top C-Suite priority, and 96% of respondents believing it provides their business a competitive advantage, according to Riverbed's Global AI and Digital Experience Survey ...
SLOs have long been a staple for DevOps teams to monitor the health of their applications and infrastructure ... Now, as digital trends have shifted, more and more teams are looking to adapt this model for the mobile environment. This, however, is not without its challenges ...
Modernizing IT infrastructure has become essential for organizations striving to remain competitive. This modernization extends beyond merely upgrading hardware or software; it involves strategically leveraging new technologies like AI and cloud computing to enhance operational efficiency, increase data accessibility, and improve the end-user experience ...
AI sure grew fast in popularity, but are AI apps any good? ... If companies are going to keep integrating AI applications into their tech stack at the rate they are, then they need to be aware of AI's limitations. More importantly, they need to evolve their testing regiment ...
