OllyGarden Raises $4 Million to Help Companies Control Growing Software Data Costs
As businesses expand their cloud operations and adopt AI-powered development tools, the amount of data generated by their software systems is growing rapidly.
That creates a problem for engineering teams: more data does not necessarily mean better visibility.
European software observability startup OllyGarden has raised $4 million in venture funding to help organisations improve the quality of the data they use to monitor software performance.
The funding announcement, published by Tech.eu on October 9, will support the company’s efforts to develop its platform and help engineering teams make more reliable decisions.
What is software observability?
Modern applications generate information about their performance and behaviour. This information, commonly called telemetry, can include logs, metrics and traces.
Engineers use it to investigate software failures, monitor response times and understand how requests move through complex systems.
For example, when an online store becomes slow, telemetry can help a developer determine whether the problem comes from a database, an external service or an application component.
But collecting and storing large quantities of telemetry can become expensive. Poorly configured systems may generate repetitive, incomplete or irrelevant information, making it harder for engineers to identify the signals that actually matter.
How OllyGarden approaches the problem
OllyGarden develops tools designed to assess telemetry quality and help engineering teams improve how their applications are monitored.
The company says its platform can identify problems in existing instrumentation and help address them at their source, reducing the amount of unnecessary data sent to observability systems.
According to Tech.eu, OllyGarden has helped organisations identify opportunities to reduce log volumes by as much as 85%.
The company has also introduced a capability called Minimum Viable Instrumentation, which aims to identify where monitoring information is missing and guide teams towards establishing an appropriate baseline.
Its AI OpenTelemetry Engineer, named Rose, is designed to assist with this process.
The underlying idea is that effective monitoring requires the right information rather than simply collecting everything available.
Source: Tech.eu — OllyGarden raises $4 million.
Who backed the startup?
The funding round was backed by Next Frontier Capital, Grand Ventures and ACTAI Ventures, with existing investor DIG Ventures participating.
Observability companies Datadog, Grafana Labs and Dash0 also made strategic investments.
The involvement of companies in the observability ecosystem highlights the commercial importance of improving the data used to monitor software systems.
As businesses adopt more cloud services and distribute applications across different environments, maintaining reliable visibility becomes increasingly complicated.
AI-generated code creates another challenge
AI coding tools can help developers generate software more quickly, but faster code production can also increase the amount of work required to maintain consistent monitoring.
When new features and services are added without appropriate instrumentation, engineers may struggle to understand how those systems behave in production.
OllyGarden’s approach aims to help teams identify gaps and maintain more consistent monitoring practices.
This is particularly relevant for businesses running large applications with multiple development teams and frequent releases.
However, automated recommendations still need to be evaluated against an organisation’s operational requirements. Excessive monitoring can increase costs, while insufficient monitoring can leave critical problems undetected.
Why this matters for European software companies
European technology companies compete in a market where operational efficiency can influence both profitability and customer satisfaction.
Reducing unnecessary data processing could help businesses control infrastructure costs while improving the quality of information available to their engineers.
For a growing startup, these savings may be particularly valuable as its software becomes more complex.
OllyGarden’s funding reflects investor interest in the tools that support AI-assisted software development, rather than only the applications built directly on top of AI models.
The bottom line: As software systems generate more data, the ability to identify what is useful — and eliminate what is not — is becoming an important engineering advantage.
