Dabble transitions from self-hosted Grafana to fully managed Grafana Cloud, adding Adaptive Telemetry to control observability costs as it scales across Australia, the US, and the UK.
SYDNEY–(BUSINESS WIRE)–Grafana Labs, the company behind the open observability cloud, today announced that Dabble, an Australian-founded social sports betting platform with a growing global footprint, has selected Grafana Cloud as its observability platform. Dabble is using Grafana Cloud to give its SRE, Cloud, and Engineering teams a single view across metrics, logs, and traces as it scales its operations across Australia, the US, and UK.
Dabble came to Grafana Cloud as an existing Grafana open source user actively building out its SRE function. As the team grew, the limitations of a self-managed stack became clear: visibility gaps between tools made it harder to correlate signals during incidents, and the operational overhead of maintaining self-hosted infrastructure was pulling engineering time away from product. According to Grafana Labs’ 2026 Observability Survey, 38% of organizations cite complexity and overhead as their top observability concern ahead of cost and signal-to-noise challenges, and 30% say alert fatigue is the single biggest obstacle to faster incident response.
By moving to Grafana Cloud, Dabble’s teams can now correlate metrics, logs, and traces in a single interface, replacing the fragmented visibility that previously created gaps during incidents. The managed infrastructure meant Dabble could deprecate its self-hosted stack without carrying the operational overhead, freeing the team to focus on building out its SRE function rather than maintaining the platform underneath it.
- Faster investigation with Grafana Assistant: Grafana Assistant gives Dabble’s on-call engineers an AI-powered layer directly inside their observability workflow. Rather than manually querying across dashboards during an incident, engineers can ask natural language questions, get correlated answers grounded in their actual telemetry, and surface root cause faster without context-switching to separate tools or documentation. In a live sports betting environment where incidents during peak events carry real business cost, the reduction in investigation time matters directly to the product.
- Intelligent data management with Adaptive Telemetry: As Dabble’s infrastructure grows across three markets, so does the volume of telemetry it generates. Adaptive Telemetry lets the team control what data is retained and at what resolution, automatically reducing the cost of storing signals that aren’t actionable, without sacrificing coverage on the data that is. This gives Dabble a path to scale their observability footprint alongside their market expansion without telemetry costs scaling linearly with infrastructure.
- Reduce MTTR through correlated signals: Dabble is using Grafana Cloud’s unified alerting and correlated signal views to improve alert fidelity and cut mean time to resolution. Rather than pivoting between tools to reconstruct what happened, on-call engineers can trace an incident from alert to root cause within a single pane of glass.
- Cross-team visibility at scale: Grafana Cloud gives Dabble’s SRE, Cloud, and Engineering teams shared context across their infrastructure, reducing the coordination overhead that comes with siloed observability. As Dabble expands into US and UK markets over the next 12–18 months, that shared foundation becomes critical.
“Our platform is our product, and as we expand into new markets, the reliability of that platform isn’t a back-office concern; it’s a commercial one,” said Andrei Goutnik, General Manager Technology at Dabble. “We were already building on Grafana open source, but running our own stack meant our SRE team was spending time on infrastructure that wasn’t theirs to own. Moving to Grafana Cloud gave us the managed foundation we needed, and Grafana Assistant has changed how our engineers actually work through an incident. Instead of pivoting across tools, they’re getting answers faster and getting back to the product faster.”
“What stands out about Dabble is that they’re treating observability as a strategic foundation for growth,” said James Hayward, Regional Sales Director, ANZ at Grafana Labs. “As they expand across Australia, the US, and the UK, platform reliability directly shapes the customer experience. Dabble also understands the opportunity AI brings to observability – helping engineers make sense of complex telemetry, identify root causes faster, and reduce the manual work involved in resolving incidents. Their move from open source to Grafana Cloud gives them a scalable, managed foundation that can support both their teams and their ambitions as they grow globally.”
Resources:
- Learn more about Grafana Cloud at grafana.com/cloud.
About Dabble
Dabble is a social-first sports betting platform founded in Australia, with operations across Australia, the United States, and the United Kingdom. The company’s mobile app blends wagering with social features — helping recreational punters follow friends, copy trending bets, and engage with sports in real time. Learn more at dabble.com.au.
About Grafana Labs
Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X.
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