Grafana Labs announced advancements in AI/ML for observability, enhancements to the fully managed Grafana Cloud observability platform, and the launch of Grafana Labs’ new startup program.
These updates are designed to simplify observability, save time and resources, and bring sophisticated new capabilities to a broader audience.
“Today’s announcements represent a significant leap forward in making observability easier, more efficient, and more intelligent,” said Tom Wilkie, CTO of Grafana Labs. “We’re not just improving our tools; we are completely changing how DevOps teams and SREs interact with their systems and data, simplifying their everyday activities.”
Grafana Labs is announcing new enhancements to the Grafana LGTM (Loki, Grafana, Tempo, Mimir) stack designed to accelerate onboarding and streamline usability within Grafana Cloud.
■ Explore Apps: Grafana Labs is expanding its query-less experiences following positive feedback of Explore Metrics and Explore Logs, both now Generally Available to all open source and Grafana Cloud (including the free tier) users. Building on this success, Explore Traces and Explore Profiles are now available in Public Preview. These new UIs allow users to drill down and reduce the volume of data they’re sifting through without having to know query languages like PromQL, LogQL, or TraceQL, streamlining data exploration and analysis.
■ Cloud Provider Observability: In an effort to meet customers where they are, Grafana Labs is announcing the General Availability of Cloud Provider Observability — an experience for understanding workloads and usage of Amazon Web Services, Microsoft Azure, and Google Cloud services, all in Grafana Cloud. Cloud Provider Observability simplifies monitoring multi-cloud environments and provides more comprehensive insights across cloud services with a single, out-of-the-box observability solution that is easy to set up and scale.
■ Synthetic Monitoring and Load Testing: Earlier this year, Grafana Labs introduced a revamped version of Grafana Cloud Synthetic Monitoring powered by Grafana k6 to enable users to simulate the most complex transactions and user journeys. Today, the company is announcing the unification of Synthetic Monitoring and k6 and a focus on making authoring tests easy with the introduction of k6 Studio, Scripted Monitoring, and Browser Monitoring in Grafana Cloud.
- k6 studio: This new GUI-based, low-code test authoring tool enables users to create tests without hand-scripting in JavaScript. This not only accelerates the process of recording and running tests compared to manual scripting, but also generates scripts compatible with both synthetic monitoring and load testing, offering a unified experience across both products to developers and QA/Performance testers without strong programming skills. (Experimental)
- Scripted Monitoring: This feature in Grafana Cloud Synthetic Monitoring allows developers to perform comprehensive black-box synthetic monitoring of services using JavaScript, enabling complex user journey simulations, custom validations, and flexible retry policies. (Public Preview)
- Browser Testing: By running a real browser and rendering the entire web page, browser-based testing in Grafana Cloud k6 captures WebVital metrics, screenshots, and timings to validate the full frontend user experience (Generally Available). This functionality will be coming soon to Synthetic Monitoring as well.
Grafana Labs is adding several AI-powered features designed to significantly enhance efficiency and cost-effectiveness for users.
■ Adaptive Telemetry: On average, customers are seeing a 35% reduction in metrics costs with Adaptive Metrics, which lowers bills by identifying and eliminating unused metrics through aggregation. TeleTracking, an integrated healthcare operations platform provider, used Adaptive Metrics to cut its billable metrics series by 50%, reducing costs by up to 33%. Customers have grown so confident in their tailored aggregation recommendations that several have switched to applying them automatically without any human intervention. Grafana Labs is extending this “Adaptive” concept to logs and traces, leveraging AI/ML techniques to analyze observability data at a scale that wouldn’t be feasible with manual processes.
- Adaptive Logs: Generally Available as of today, Adaptive Logs helps customers lower their observability costs by reducing the volume of unnecessary logs. Adaptive Logs identifies commonly ingested log patterns and creates a set of customized sampling recommendations based on how frequently those patterns are queried, giving customers the ability to prune away low-value logs so that they only retain the important ones. As an early adopter of Adaptive Logs, TeleTracking has now also reduced its log volume by 50%. Said TeleTracking Software Engineer II Andrew Qu, who is presenting a talk at ObservabilityCON: “Without Adaptive Logs, even at lower log levels, our dev teams are still generating many logs that never get reviewed. This makes it significantly harder and longer to sift through logs and find what they’re looking for, especially when searching back over days or weeks. Adaptive Logs help reduce this noise, making it easier to spot valuable logs and ultimately saves us costs.”
- Adaptive Traces: To accelerate the development of Adaptive Traces, Grafana Labs is pleased to announce the acquisition of TailCtrl, an early-stage company founded by Sean Porter, a tenured engineer and entrepreneur who previously co-founded Sensu. Sean’s expertise aligns with our vision for Adaptive Traces, which is now in Research phase.
■ Open Source LLM Observability: As LLMs become more prevalent in customers’ day-to-day work, Grafana Labs is developing various ways to monitor and observe LLMs.
- Grafana Labs engineers have built a tool to track ML experiments and compare performance by charting model metrics (loss vs. epoch, etc) and monitoring application logs for any failures. The open source tool contains a Python library to instrument training code, a backend written in Go to store data about training runs, and a Grafana plugin to visualize data in Grafana.
- Grafana Labs engineers have also explored ways to use open source tools to observe LLMs, including the OpenLIT SDK. The SDK produces OpenTelemetry traces and metrics for the LLM calls including latency, cost, and the number of tokens generated. These metrics and traces can be sent to Grafana Cloud and visualized using the AI observability solution. The integration code is open source and available on GitHub.
- The team also built GPU monitoring using eBPF which helps AI developers get fine-grained information about their workloads without manual instrumentation and is currently available as a branch in Grafana Labs’ open source eBPF project Beyla.
■ Incident Rooms featuring Generative AI: A lot of rich context for both incident understanding and post-incident learning is hard to capture and often lost completely when responders discuss the incident on an audio or video call. To address this, Grafana Labs is investing in Incident Rooms, which provide real-time transcription for incident bridge calls. A bot transcribes conversations in the Incident Room directly into the incident timeline, using LLMs to summarize and capture critical insights that might otherwise be missed. (Experimental)
Grafana Labs also announced integration of Asserts.ai, acquired in November 2023. The company is unveiling a suite of unified workflows that connect Asserts’ technology with various Grafana Cloud solutions, which leverages AI/ML to automate the process of detecting and correlating anomalies across application and infrastructure signals. These new integrations cover a wide range of monitoring needs, including application performance, Kubernetes workload monitoring, infrastructure monitoring, real user monitoring, and simplified SLO management. By automating the correlation of anomalies and providing a more cohesive troubleshooting experience, these AI-driven inferences enable even junior engineers to more effectively understand and diagnose issues in complex systems.
To help more organizations get up and running with observability, Grafana Labs is launching a Startup Program, offering 50 eligible startups up to $100,000 in Grafana Cloud credits for 12 months or until their next funding round. This initiative aims to encourage startups to adopt Grafana Labs’ scalable, open, and composable observability solutions from the outset, avoiding future vendor lock-in. Participants will receive all products within Grafana Cloud including all enterprise plugins, Grafana support, and access to Grafana Labs’ business development team for ecosystem integration. The program targets startups with less than $10 million in funding and fewer than 25 employees, though exceptions may be considered.
“Our new Startup Program isn’t just about offering credits; it’s about equipping the next generation of tech leaders with best-in-class observability tools from the start. We’re investing in these companies’ futures, providing them with the same powerful, scalable solutions trusted by global enterprises,” said Ash Mazhari, VP of Corporate Development at Grafana Labs. “This program embodies our commitment to fostering a vibrant tech ecosystem and our belief that when startups succeed with the right tools, the entire industry moves forward. We’re excited to partner with these organizations and continually find ways to support their growth journeys.”
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