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<\/a><\/a>\nFindings from Grafana Labs\u2019 4th Annual Observability Survey<\/a> reinforce the shift: operational complexity and overhead are now the top observability challenge, while adoption of managed\/SaaS observability continues to climb: half of organizations use managed solutions in some form (up from 43% in 2025). Exclusive SaaS use has also grown (10% in 2024 to 17% in 2026). That shift reflects growing pressure from AI workloads, which spike telemetry volume just as teams are trying to move away from fragmented, self-hosted stacks.<\/p> \nExisting customers like Harrison.ai highlight why AI-driven organizations are turning to Grafana Cloud. \u201cRunning AI in production means there\u2019s no margin for blind spots,\u201d said Graham Bucknell, Platforms Engineering Manager at Harrison.ai. \u201cGrafana Cloud gives us end-to-end visibility across our systems, so our teams can understand what\u2019s happening, act quickly, and scale safely. That transparency lets us move fast without compromising reliability or trust.\u201d<\/p> \nTeamSystem Aims to Align Observability Cost With Value<\/b><\/p> \nAs observability data volumes continue to surge, especially at the scale AI leaders like TeamSystem operate at, organizations are prioritizing more intelligent ways to manage cost without sacrificing visibility. While 90% of survey respondents<\/a> expect their observability spending to stay the same or increase next year, they are becoming far more deliberate in how that budget is allocated, with 65% now citing cost as a key factor in tool selection.<\/p> \nThis shift is driving demand for adaptive approaches that prioritize high-value signals over sheer data volume. TeamSystem is leveraging Grafana Cloud\u2019s Adaptive Telemetry<\/a> suite to reduce unnecessary data ingestion, control spend, and maintain deep visibility where it matters most. By aligning telemetry with actual usage and impact, they are improving both efficiency and performance without losing any insights.<\/p> \nZama Puts Grafana Assistant to Work<\/b><\/p> \nFor Zama<\/a>, maintaining the performance edge of its FHE libraries and Zama Protocol requires granular, continuous benchmarking. The team has integrated Grafana Cloud as the primary source of truth for its automated performance testing suites. This setup allows Zama engineers to monitor regressions across 54 unique FHE operations and blockchain transaction types in real-time. By correlating telemetry with algorithmic updates and hardware-level trade-offs, Zama uses these insights to iterate on implementation efficiency. This data-driven approach to optimization is a core component of Zama\u2019s roadmap to achieving 100 TPS on the Zama Protocol by the end of the year.<\/p> \nZama also uses Grafana Assistant<\/a> to accelerate investigation, reduce time to resolution, and make observability more accessible across engineering teams. By embedding actually useful AI directly into the observability experience, Grafana Assistant helps teams quickly understand complex systems, surface relevant insights, and onboard new engineers faster. For high-growth organizations operating at scale, this translates into faster debugging, improved productivity, and more confident decision-making.<\/p> \n7AI Migrates from OSS to Grafana Cloud<\/b><\/p> \n7AI, a fast-scaling AI company, is migrating from self-managed open source observability stacks to Grafana Cloud. At their scale, maintaining bespoke tooling competes directly with engineering capacity for core innovation. Rather than investing in infrastructure upkeep, these teams are standardizing on a managed platform that frees engineering time for product work while preserving deep visibility across production AI workloads.<\/p> \n\u201cAI companies need observability that keeps pace with them,\u201d said Anthony Woods, Co-Founder, Grafana Labs. \u201cThese organizations are running some of the most complex and fast-moving infrastructure in the world, and they've chosen Grafana Cloud because it gives them a single platform that unifies their telemetry, controls their costs, and puts AI to work in the places that matter, from root cause analysis to onboarding new engineers. This is what the next generation of observability looks like.\u201d<\/p> \nAbout Grafana Labs<\/b><\/p> \nGrafana Labs, the company behind the open observability cloud, is founded on the principles of open source, open standards, open ecosystems, and open culture. Grafana Cloud, our fully managed observability platform, is flexible and built for scale. With Grafana Cloud's actually useful AI, organizations can see, understand, and act on all their disparate data to move at the speed of their ambitions. Today, more than 35 million users and 7,000+ customers \u2013 including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce \u2013 trust Grafana Labs to ensure reliability of their applications and systems, resolve incidents quickly, and optimize their telemetry to reduce noise and cost. We are a 100% remote company with 1,400+ team members across 40+ countries, and we\u2019re 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<\/a> and follow us on LinkedIn<\/a> and X<\/a>.<\/p>