Sumo Logic adds AI tools to cut telemetry costs upstream

Sumo Logic has introduced an enhanced version of its Data Pipelines product, expanding its push into data pipeline management for security and observability teams.

The product is designed to let customers make decisions about telemetry before it is ingested, stored and analysed. Users can filter out unwanted data, transform records and route telemetry to different destinations or cost tiers from within Sumo Logic's existing platform.

The update reflects a wider issue for security and operations teams as data volumes continue to rise. Organisations are collecting more telemetry from applications, infrastructure and cloud systems, while AI is increasing both the amount of data produced and the demand for data to train and run analytical tools.

That has created a cost problem for companies that have often sent all available data into analytics platforms and decided later what to use. Sumo Logic argues that managing data further upstream can reduce storage and ingestion costs while keeping more relevant signals available for investigation and monitoring.

The company says it currently ingests and analyses nearly seven exabytes of data a day for thousands of customers. It is using that experience to move more data management functions to the point before telemetry reaches analytics systems.

Cost control

One of the main additions is a live pipeline preview, which allows teams to see the effects of filtering and routing decisions before data adds to platform charges. This can help users direct lower-value data to cheaper storage tiers or send it to external destinations instead of keeping everything in the same environment.

Sumo Logic has also added AI-assisted configuration. The feature can help write rules for filtering and transformation tasks, and flag anomalies or changes in data formats that might otherwise require manual work to identify.

Another part of the update is an assistant that recommends whether data should be routed, transformed or dropped. Human oversight remains part of that process.

Sumo Logic framed the release as part of an effort to combine data pipeline management with downstream security and observability work, including detection, investigation and response. Rather than relying on separate tools to collect, shape and analyse telemetry, the company is trying to keep those functions within one platform.

That approach also reflects pressure on software buyers to simplify technology estates. Security and operations teams have often assembled multiple specialist products to manage logs, metrics, traces and alerts, but rising volumes and tighter scrutiny of spending have increased interest in tools that can reduce overlap.

Vendor view

Keith Kuchler, Chief Product and Technology Officer, outlined the company's argument for moving those decisions earlier in the data lifecycle.

"We've spent fifteen years as experts helping customers maximize the value of their telemetry, turning exabytes of noise into actionable insights that are critical to improving enterprise security and overall performance of infrastructure and applications," said Keith Kuchler, Chief Product and Technology Officer, Sumo Logic.

"With AI exponentially increasing data volumes and costs, that expertise is even more crucial. The next generation of our AI-powered data pipeline solution moves data strategy decisions upstream, empowering teams to determine the purpose of their data so it can effectively be leveraged by responsible AI implementations and also enables them to effectively manage the economics of their data," Kuchler said.

Sumo Logic also cited industry research on the economics of observability data. In a report quoted by the company, Gartner said many organisations had defaulted to ingesting all operational data for later analysis, but that model had become less workable because of ingestion and storage costs and the growing volume of low-quality telemetry.

Broader shift

The latest changes are part of a broader platform direction that links telemetry management more closely to AI use in security and operations. As more companies look to use AI systems for automated detection, investigation and remediation, the quality of source data has become a bigger operational issue, not just a storage one.

Sumo Logic says poor-quality telemetry can weaken downstream analysis and make automated systems less useful. Its argument is that organisations need to decide earlier what data is worth keeping, where it should go and how much it should cost to manage.

While the company also outlined additional planned enhancements, the immediate update focuses on giving customers more control over data before it reaches the analytics bill. Data Pipelines is built natively into the platform rather than being offered as a separate product to deploy and integrate.

Sumo Logic says Data Pipelines now gives customers the ability to make data and cost decisions before telemetry reaches the analytics platform.