Blog written by Tom Wilkie, CTO, Grafana Labs, published April 21, 2026

From the beginning, Loki has been designed around a simple goal: make log management cost-efficient and easier to operate at scale. That focus is why teams continue to turn to the open source, horizontally scalable, and highly available log aggregation system, which also powers Grafana Cloud Logs, time and time again.

Loki is powered by a label-based indexing approach that keeps storage costs low and operations lightweight. For the majority of use cases, this design works extremely well. But at large scale, searches involving highly unique values, like request or job IDs, can become more challenging, with queries taking longer to return results. 

As our users push into larger datasets and more demanding use cases, we want to expand what Loki can do, without compromising the cost and simplicity that make it so effective.

That’s why, at GrafanaCON 2026, we’re excited to share that Grafana Labs has acquired Logline, a company specializing in the execution of “needle-in-the-haystack” queries and full text search. Logline was founded by Jason Nochlin, an entrepreneur and engineering leader who was previously CEO of Teleport Data, which was acquired by Fivetran in May 2021. By chance, Jason met Logan Smith, senior director, corporate business development here at Grafana Labs, at an industry event two years ago, and had a conversation about Loki’s growing pains that planted a seed.

“After that conversation, I started thinking about new ways to do indexing over object storage. It took awhile, but eventually I had a breakthrough and thought, ‘wow, I may be onto something here – maybe Grafana Labs will be interested,” said Jason.

With the acquisition, Logline brings a new indexing approach to Loki that’s designed specifically for high-cardinality attributes over object storage. Ultimately, this makes it much faster to find specific, highly unique values in large datasets, without changing Loki’s core design. 

“We want to drive down the time it takes to perform these searches without having to introduce techniques that are much more computationally expensive,” said Jason. “So Logline is the best of both worlds, where we can accelerate those needle-in-the-haystack searches with much simpler indexing than anything else that’s on the market today.”

Early benchmarks being shared this week at GrafanaCON show that a query for a universally unique identifier (UUID) in Loki that previously scanned 3.5 TB of data without returning a result now scans just 8GB with Logline – a 99.7% reduction in data scanned. 

These improvements, coupled with other major architectural changes coming to Loki, enable faster large-scale scans, minimize the impact of stream cardinality, and improve performance for analytical workloads.  

When it comes to Grafana Labs and Logline, the alignment goes far beyond technology. In addition to our shared commitment and appreciation for the open source community, Jason’s model for Logline mirrors our own goals of making observability easier, more accessible, and cost-effective for everyone.

“The mission of making observability ubiquitous while also keeping costs under control really stood out to me about Grafana Labs,” Jason recalls. “You don’t usually see that in this space.”

Needle-in-the-haystack log queries are available in Grafana Cloud Logs in limited private preview today; please reach out to your sales rep to learn more. We are working to make them available to Loki OSS users in the coming year with the next major release of Loki.

To learn more about needle-in-the-haystack queries and Loki’s new architecture, be sure to check out the GrafanaCON 2026 opening keynote and Loki deep dive session when they become available on demand. 

In the meantime, we welcome Jason to Grafana Labs and into our wider open source community.

Read also :