Business Software for Grafana Cloud

Identify and resolve performance issues and errors within your microservices architecture. Establish connections between root causes by analyzing traces, logs, and metrics. Reduce your costs associated with OpenTelemetry traces through Aspecto's integrated remote sampling feature. The way OTel data is visualized plays a crucial role in enhancing your troubleshooting efficiency. Transition seamlessly from a broad overview to intricate details using top-tier visualization tools. Link logs directly to their corresponding traces effortlessly, maintaining context to expedite issue resolution. Utilize filters, free-text searches, and grouping options to navigate your trace data swiftly and accurately locate the source of the problem. Optimize expenses by sampling only essential data, allowing for trace sampling based on programming languages, libraries, specific routes, and error occurrences. Implement data privacy measures to obscure sensitive information within traces, specific routes, or other critical areas. Moreover, integrate your everyday tools with your operational workflow, including logs, error monitoring, and external event APIs, to create a cohesive and efficient system for managing and troubleshooting issues. This holistic approach not only improves visibility but also empowers teams to tackle problems proactively.

Unify all your data sources, encompassing both relational and NoSQL databases, SaaS applications, and APIs, allowing you to query them as if they were a single data entity instantly. Process data at its source without delay, enabling you to query, cache, and merge information from various origins seamlessly. Utilize webhooks to bring in real-time streaming data from platforms like Kafka and Segment into the Peaka BI Table, moving away from the traditional nightly batch ingestion in favor of immediate data accessibility. Approach every data source as though it were a relational database, transforming any API into a table that can be integrated and joined with your other datasets. Employ familiar SQL syntax to execute queries in NoSQL environments, allowing you to access data from both SQL and NoSQL databases using the same skill set. Consolidate your data to query and refine it into new sets, which you can then expose through APIs to support other applications and systems. Streamline your data stack setup without becoming overwhelmed by scripts and logs, and remove the complexities associated with building, managing, and maintaining ETL pipelines. This approach not only enhances efficiency but also empowers teams to focus on deriving insights rather than being bogged down by technical hurdles.

We keep a close eye on your websites, APIs, cron jobs, and other scheduled tasks. Your team receives instant notifications through various channels, including email, SMS, Slack, PagerDuty, and Incident.io. You don’t need to be a tech expert to get started, as our setup is straightforward and user-friendly. Enjoy peace of mind with monitoring that helps you sleep easier at night. Checks can be performed as frequently as every 30 seconds, allowing you to identify problems that could temporarily disrupt your website. Each check can be customized with specific HTTP methods, headers, and bodies according to your needs. OnlineOrNot ensures reliability by conducting each check at least twice before notifying you, with the possibility of additional checks if required. Furthermore, OnlineOrNot monitors your SSL certificates for any impending expirations or potential issues and promptly alerts you if something goes awry. You have the option to perform uptime checks from a single region or multiple locations simultaneously. Since your customers depend on your services, keep them informed with a dynamic status page that updates automatically. You can easily add your customers as subscribers to this status page and send regular updates about any incidents via email to keep everyone in the loop. This proactive approach not only enhances customer trust but also improves overall service reliability.

Introducing a self-service development platform tailored for your applications, databases, and various tasks. You can begin with a single workload and effortlessly expand to manage hundreds, utilizing either compute or GPUs. Enhance every phase from code push to production with customizable self-service workflows, pipelines, templates, and GitOps practices. Safely launch preview, staging, and production environments while benefiting from built-in observability tools, backups, restoration capabilities, and rollback options. Northflank integrates flawlessly with your preferred tools, supporting any technology stack you choose. Regardless of whether you operate on Northflank’s secure infrastructure or utilize your own cloud account, you will enjoy the same outstanding developer experience, alongside complete control over your data residency, deployment regions, security measures, and cloud costs. By harnessing Kubernetes as its operating system, Northflank provides the advantages of a cloud-native environment without the associated complexities. Whether you opt for Northflank’s straightforward cloud or connect to your GKE, EKS, AKS, or even bare-metal setups, you can achieve a managed platform experience within minutes, thus optimizing your development workflow. This flexibility ensures that your projects can scale efficiently while maintaining robust performance across diverse environments.

Tetragon is an adaptable security observability and runtime enforcement tool designed for Kubernetes, leveraging eBPF to implement policies and filtering that minimize observation overhead while enabling the tracking of any process and real-time policy enforcement. With eBPF technology, Tetragon achieves profound observability with minimal performance impact, effectively reducing risks without the delays associated with user-space processing. Building on Cilium's architecture, Tetragon identifies workload identities, including namespace and pod metadata, offering capabilities that exceed conventional observability methods. It provides a selection of pre-defined policy libraries that facilitate quick deployment and enhance operational insights, streamlining both setup time and complexity when scaling. Furthermore, Tetragon actively prevents harmful actions at the kernel level, effectively closing off opportunities for exploitation while avoiding vulnerabilities related to TOCTOU attack vectors. The entire process of synchronous monitoring, filtering, and enforcement takes place within the kernel through the use of eBPF, ensuring a secure environment for workloads. This integrated approach not only enhances security but also optimizes performance across Kubernetes deployments.

Nango stands out as a leading product integration platform that empowers developers to implement integrations with over 300 APIs in just a matter of hours. It simplifies the complexities of API interactions through a variety of pre-built integrations, developer tools, and user interface components. By using Nango, developers maintain complete control over their code and have direct access to external APIs, enabling them to create tailored integrations that meet their customers' specific needs, much like an in-house development team would. The platform is designed with built-in support for all types of authorization and API peculiarities, presenting a unified interface that works with your own data models while ensuring smooth user interfaces for top-tier integration experiences. Each developer tool is customized for individual APIs, effectively managing pagination, rate limits, and other essential features. Furthermore, Nango includes an AI co-pilot that has been trained on a multitude of integrations to help facilitate the creation of custom solutions. For those who need additional expertise, Nango not only connects users with API specialists but also offers a service where their engineers can craft bespoke integrations tailored to specific requirements. This comprehensive approach ensures that developers have the resources and support needed to succeed in their integration projects.

Grafana Loki is a free and open-source system designed for log aggregation, focusing on the efficient collection, storage, and querying of logs from diverse sources. Unlike conventional logging solutions, Loki is specifically tailored for cloud-native applications, making it ideal for modern environments like Kubernetes that utilize containerization. It integrates smoothly with Grafana, enabling users to visualize log data alongside metrics and traces, thereby creating a cohesive observability framework. By indexing only essential metadata, including labels and timestamps, Loki minimizes data storage needs while enhancing query efficiency compared to traditional log management systems. This streamlined method not only facilitates easier scalability but also ensures more economical storage solutions. Furthermore, Loki accommodates log aggregation from a variety of sources, such as Syslog, application logs, and container logs, and works in conjunction with other observability tools, offering a comprehensive insight into system performance. Users benefit from this integration, as it allows for real-time monitoring and troubleshooting, ultimately leading to improved operational efficiency.

Revolte is an AI-native software engineering platform that helps development teams automate the complete software delivery lifecycle from initial requirements through production operations. Rather than focusing only on AI code generation, the platform executes planning, development, testing, deployment, release management, runtime monitoring, and operational workflows across the entire SDLC. Engineers define project requirements, approve outcomes, and maintain governance while Revolte handles repetitive engineering tasks through coordinated AI agents. The platform integrates with existing tools including Jira, Git, Figma, Kubernetes, Terraform, Slack, Grafana, GitLab, AWS, Google Cloud, and other engineering services, allowing organizations to adopt AI without replacing their current toolchain. Revolte supports use cases including new application development, legacy application modernization, production operations, and continuous feature evolution. Agent Harness allows teams to define platform requirements in YAML, automatically provisioning environments, infrastructure, and services needed to build and operate applications. Delivery Intelligence provides visibility into software delivery performance while runtime observability helps monitor production systems and respond to operational issues. Developer-in-the-loop workflows ensure engineers remain responsible for reviews, approvals, and deployment decisions while AI accelerates execution. By combining workflow orchestration, AI automation, and engineering governance, Revolte helps organizations release software faster, improve delivery consistency, and reduce operational overhead.

Tracetest is a powerful open-source testing framework that empowers developers to design and execute both end-to-end and integration tests by utilizing OpenTelemetry traces. This tool not only verifies the final results but also scrutinizes each stage of the workflow, guaranteeing that every part of a distributed system operates as intended. It integrates effortlessly with popular testing frameworks such as Cypress, Playwright, k6, and Postman, thus improving testability and transparency without necessitating any modifications to the existing codebase. By employing trace data, Tracetest uncovers problems like improper service interactions or performance hurdles that may go unnoticed with conventional testing approaches. Additionally, it works well with a wide range of observability platforms and can be seamlessly integrated into CI/CD pipelines to facilitate ongoing testing practices. Furthermore, Tracetest provides synthetic monitoring features, which help in the early identification of performance issues, ensuring that user experiences remain unaffected. This multifaceted tool not only enhances testing rigor but also promotes greater confidence in the reliability of distributed systems.

FriendliAI serves as an advanced generative AI infrastructure platform that delivers rapid, efficient, and dependable inference solutions tailored for production settings. The platform is equipped with an array of tools and services aimed at refining the deployment and operation of large language models (LLMs) alongside various generative AI tasks on a large scale. Among its key features is Friendli Endpoints, which empowers users to create and implement custom generative AI models, thereby reducing GPU expenses and hastening AI inference processes. Additionally, it facilitates smooth integration with well-known open-source models available on the Hugging Face Hub, ensuring exceptionally fast and high-performance inference capabilities. FriendliAI incorporates state-of-the-art technologies, including Iteration Batching, the Friendli DNN Library, Friendli TCache, and Native Quantization, all of which lead to impressive cost reductions (ranging from 50% to 90%), a significant decrease in GPU demands (up to 6 times fewer GPUs), enhanced throughput (up to 10.7 times), and a marked decrease in latency (up to 6.2 times). With its innovative approach, FriendliAI positions itself as a key player in the evolving landscape of generative AI solutions.

StarOps is a cutting-edge AI-driven workflow engine that takes the complexity out of deploying and managing cloud infrastructure by eliminating the need for manual Terraform scripting or Kubernetes management. It provides a seamless way to launch GenAI models, provision blob storage, configure virtual private clouds (VPCs), and establish observability, all automated by an intelligent system of microagents operating behind the scenes. This platform is specifically built for AI and data-heavy applications, helping teams handle the growing demands of modern cloud environments effortlessly. Application developers can rely on StarOps to provide infrastructure that “just works,” without the usual operational overhead. Machine learning engineers and data scientists can focus on delivering models without being slowed down by DevOps challenges. Platform engineers can grow their teams’ capabilities while minimizing the increase in operational complexity. StarOps bridges the gap between development and operations by automating infrastructure workflows intelligently. Its ability to simplify and scale cloud operations makes it essential for organizations adopting AI-driven technologies.

Storm MCP serves as an advanced gateway centered on the Model Context Protocol (MCP), facilitating seamless connections between AI applications and multiple verified MCP servers through a straightforward one-click deployment process. It ensures robust enterprise-level security, enhanced observability, and easy integration of tools without the need for extensive custom development. By standardizing AI connections and only exposing specific tools from each MCP server, it helps minimize token consumption and optimizes the selection of model tools. With its Lightning deployment feature, users can access over 30 secure MCP servers, while Storm efficiently manages OAuth-based access, comprehensive usage logs, rate limitations, and monitoring. This innovative solution is crafted to connect AI agents to external context sources securely, allowing developers to sidestep the complexities of building and maintaining their own MCP servers. Tailored for AI agent developers, workflow creators, and independent innovators, Storm MCP stands out as a flexible and configurable API gateway, simplifying infrastructure challenges while delivering dependable context for diverse applications. Its unique capabilities make it an essential tool for those looking to enhance their AI integration experience.

Tiger Data reimagines PostgreSQL for the modern era — powering everything from IoT and fintech to AI and Web3. As the creator of TimescaleDB, it brings native time-series, event, and analytical capabilities to the world’s most trusted database engine. Through Tiger Cloud, developers gain access to a fully managed, elastic infrastructure with auto-scaling, high availability, and point-in-time recovery. The platform introduces core innovations like Forks (copy-on-write storage branches for CI/CD and testing), Memory (durable agent context and recall), and Search (hybrid BM25 and vector retrieval). Combined with hypertables, continuous aggregates, and materialized views, Tiger delivers the speed of specialized analytical systems without sacrificing SQL simplicity. Teams use Tiger Data to unify real-time and historical analytics, build AI-driven workflows, and streamline data management at scale. It integrates seamlessly with the entire PostgreSQL ecosystem, supporting APIs, CLIs, and modern development frameworks. With over 20,000 GitHub stars and a thriving developer community, Tiger Data stands as the evolution of PostgreSQL for the intelligent data age.

Pangolin serves as an open-source platform designed for identity-aware tunneled reverse-proxying, which allows users to securely expose applications from any location without the need to open inbound ports or set up a conventional VPN. It employs a distributed system consisting of globally positioned nodes that facilitate traffic routing through encrypted WireGuard tunnels, making it possible for devices behind NATs or firewalls to publicly host applications via a centralized dashboard. This unified dashboard enables users to manage various sites and resources throughout their infrastructure while also allowing for the definition of detailed access-control rules, including options such as SSO, OIDC, PINs, geolocation, and IP restrictions, along with monitoring real-time health and usage statistics. The platform accommodates both self-hosting options, available in Community or Enterprise editions, and a managed cloud service, functioning by deploying a lightweight agent on each site while the central control server manages ingress, traffic routing, authentication, and failover processes. Additionally, Pangolin’s architecture fosters a secure and efficient environment for developers and IT teams aiming to streamline application exposure and maintain robust security protocols.

Kagent is a versatile, open-source framework specifically designed for cloud-native AI agents, allowing teams to construct, deploy, and operate autonomous agents within Kubernetes clusters to streamline complex operational processes, troubleshoot cloud-native infrastructures, and oversee workloads with minimal human oversight. This framework empowers DevOps and platform engineers to develop intelligent agents capable of comprehending natural language, planning strategically, reasoning effectively, and executing a series of actions across Kubernetes environments by utilizing integrated tools and Model Context Protocol (MCP)-compatible integrations for various functions, including metric queries, pod log displays, resource management, and service mesh interactions. Additionally, Kagent facilitates communication between agents to orchestrate intricate workflows and includes observability features that enable teams to track and assess agent performance and behavior. Furthermore, its compatibility with multiple model providers, such as OpenAI and Anthropic, enhances its versatility and adaptability within diverse operational contexts.

Sherlocks.ai operates as an autonomous AI Site Reliability Engineering (SRE) agent, tirelessly functioning around the clock to avert incidents, streamline root cause analysis, and hasten recovery processes without necessitating additional personnel. Distinct from conventional monitoring tools, Sherlocks integrates seamlessly as a cognitive ally within your Slack channels, promptly addressing alerts, and synthesizing logs, metrics, and traces from your entire infrastructure, providing context-sensitive root cause analysis in mere seconds instead of hours. Organizations utilizing Sherlocks experience a threefold increase in the speed of incident resolution, a 50% decrease in manual work, and achieve 20-30% savings on cloud expenses due to intelligent predictive scaling. The system requires no agent installation, as it effortlessly connects to your existing observability stack—such as OpenTelemetry, Prometheus, and Datadog—through a secure API. Additionally, it boasts SOC2 Type 2 certification and offers a self-hosted deployment option, ensuring comprehensive control over data management. Furthermore, the integration of Sherlocks enhances team collaboration, allowing for a more efficient response to incidents and improved operational insights.

PagerTree is a cloud-based platform for managing incidents and on-call alerts, created to assist teams in swiftly and effectively addressing operational challenges. By consolidating alerts from various monitoring tools, it ensures that the correct responders are notified automatically through customizable on-call schedules, layered escalation processes, and smart routing rules. The platform offers real-time notifications via push notifications, emails, SMS, voice calls, chatbots, and mobile applications, guaranteeing prompt delivery of incidents to the designated team members. With PagerTree, organizations can establish simple on-call rotations and enhance their systems with escalation policies while monitoring performance through integrated analytics dashboards. Its sophisticated routing and notification protocols enable teams to align alerts with specific criteria, reduce unnecessary noise, and focus on urgent incidents, which ultimately lessens alert fatigue and enhances the accuracy of responses. Moreover, PagerTree's user-friendly interface allows for easy adjustments to notification preferences, promoting a more efficient incident management workflow.

Resolve production incidents and development issues with AI that understands your code, infrastructure, and telemetry — reducing MTTR by up to 80% and boosting engineering productivity by 50%. OpsWorker helps Software Developers, SREs, and DevOps Engineers reduce MTTR, resolve complex development issues, and manage high-incident environments. Through intelligent incident correlation, code-aware troubleshooting, and deep integration into your technical ecosystem, OpsWorker delivers actionable insights and autonomous remediation — ensuring resilient, high-performance operations across Kubernetes and Cloud workloads. Built as an AI SRE platform for modern AIOps, OpsWorker leverages AI Observability to analyze incidents across distributed systems, correlating signals from metrics, logs, traces, infrastructure state, and deployments to surface the most probable root cause within minutes. Designed with an EU-first approach, OpsWorker prioritizes data sovereignty, privacy, and enterprise-grade security while enabling engineering teams to investigate incidents faster and operate complex cloud-native environments with confidence. Recent platform capabilities include Resource Topology and Service Dependency mapping, giving engineers full visibility into upstream and downstream service interactions across HTTP, TCP, and gRPC workloads. OpsWorker now integrates with Grafana Alerting contact points and supports Bring Your Own LLM, allowing organizations to use their preferred AI models for investigations. Engineers can also enrich investigations with custom operational context, enabling deeper root-cause analysis for complex incidents. To reduce alert fatigue, OpsWorker delivers a Daily Diff Summary in Slack, highlighting meaningful changes in alerts and system behavior

Struct is an innovative communication platform that leverages artificial intelligence to enhance the way teams collect, structure, and utilize insights from their conversations, effectively converting chat exchanges into an organized and searchable knowledge repository. Unlike traditional messaging systems that treat conversations as fleeting, Struct systematically categorizes discussions into coherent threads and feeds, all while developing a contextual knowledge base that retains critical insights, decisions, and shared materials. By harnessing AI capabilities, it analyzes dialogues to highlight pertinent information and link related concepts, ensuring that essential context remains intact over time and across messages. This functionality enables teams to swiftly access documents, answers, and past exchanges without the hassle of sifting through various tools or reiterating information. Furthermore, Struct prioritizes clarity and productivity by minimizing communication noise, transforming routine interactions into actionable knowledge that bolsters teamwork and informed decision-making processes. Ultimately, this approach not only streamlines collaboration but also empowers teams to work more efficiently and effectively.

Hopp is a remote pair programming tool that is open source and tailored for developers, facilitating effortless real-time collaboration as if they were on the same machine. Unlike generic meeting applications, Hopp offers a specialized experience that features ultra-low latency, high-definition screen sharing, and complete keyboard and mouse control for both users, which empowers teams to code, debug, and review their work collaboratively without any hindrance. Users can initiate a session with just one click, streamlining the process by removing the need for links or coordinating calendars, and it provides the capability to share and control the entire workspace, encompassing any visible application, such as development tools, design software, or documentation editors. Moreover, Hopp supports collaboration with up to 10 participants in a single room, making it an excellent choice for mob programming, onboarding new team members, and addressing team-wide challenges effectively. This makes Hopp not just a tool for pair programming, but a comprehensive solution for enhancing team productivity and collaboration.

Devtron serves as an AI-driven, Kubernetes-centric DevOps platform that aims to streamline and integrate the entire application delivery lifecycle, infrastructure oversight, and operational tasks within a singular control interface. By merging essential DevOps functionalities, including CI/CD, GitOps, security measures, observability, cost oversight, and debugging tools, it removes the hassle of juggling various disjointed tools and dashboards. This platform functions as a unified control layer for Kubernetes settings, empowering teams to deploy, monitor, manage, and resolve issues with applications across multi-cloud or on-premises clusters, all while ensuring comprehensive visibility and governance. Additionally, it features Kubernetes-native CI/CD pipelines with no-code workflows, orchestration across multiple environments, approval-based deployments, and reusable templates, facilitating quicker and more dependable software delivery while minimizing manual tasks. Thus, organizations can achieve greater efficiency and consistency in their development processes.

Skyhook is a developer platform built on Kubernetes that streamlines the processes teams use to create, deploy, and scale cloud applications by minimizing the intricacies associated with DevOps and infrastructure oversight. It offers a completely configured environment that is ready for production, enabling developers to quickly launch services, set up environments, and manage infrastructure in mere seconds, while seamlessly incorporating top-tier tools from the Kubernetes ecosystem, such as ArgoCD, Kyverno, and Grafana. By integrating these tools into standardized “golden paths,” Skyhook facilitates the adoption of best practices from the outset, covering aspects like monitoring, rollout strategies, temporary environments, and secure secret management without the need for manual configuration. This platform not only provides a self-service experience for developers but also ensures that governance and oversight are preserved for DevOps teams, empowering organizations to automate their workflows, uphold standards, and minimize reliance on bespoke internal tools. Consequently, Skyhook promotes efficiency and agility in cloud application development, allowing teams to focus on innovation rather than operational overhead.

Hyground serves as an AI-enhanced co-pilot for DevOps and Site Reliability Engineering (SRE), functioning as a comprehensive operational intelligence platform that integrates seamlessly within the client's Kubernetes environment without any data leaving the premises. This sophisticated agent interfaces with over 21 enterprise systems to analyze incidents through various sources such as logs, metrics, traces, and Kubernetes events. Engineers can pose questions in everyday language and receive insights tailored to their specific datasets, eliminating the need to master new query languages. The AutoRCA feature transforms alert webhooks into self-sufficient root-cause analyses, providing updates directly to platforms like Slack or Teams. The investigation process initiates immediately upon alert, rather than waiting for an engineer to respond, leading customers to experience reductions in mean time to resolution (MTTR) of up to 85%. Leveraging Google's Agent Development Kit, Hyground employs a multi-agent framework that evolves by learning from the customer's infrastructure over time. Each resolved incident enhances the knowledge base, ensuring that operational runbooks remain up to date and relevant for future challenges. By facilitating real-time insights and continuous learning, Hyground empowers teams to operate more efficiently and effectively.

Signal9 is an Alert Management, On-Call, and IT service management (ITSM) platform for IT Operations, NOC, SRE, DevOps, Platform Engineering, and Infrastructure teams. It runs the full operational lifecycle on one foundation that learns from your operation itself, so alerts, incidents, changes, problems, requests, and on-call response all share the same operational identity, memory, and understanding. Signal9 provides alert management, event correlation, incident management, problem management, change management, service request management, on-call and escalation management, knowledge management, operational analytics, automation, and collaboration in Microsoft Teams and Slack. AI agents assist on every record, from incident investigation and change preflight checks to problem root cause and request fulfillment, with the evidence and reasoning shown so your team decides what happens next. Instead of a CMDB nobody keeps current, Signal9 builds operational identity from real activity through its Identity Correlation Database (ICDB): a self-building inventory earned by evidence, not maintained by hand. By combining alert data, response behavior, ownership, correlations, and operational history, Signal9 reduces alert fatigue, improves incident response, increases visibility, and uncovers the operational patterns that traditional monitoring and observability tools often miss. It gets sharper every time you use it. Built to learn, not to be taught. Works alongside Splunk, Datadog, Grafana, Azure Monitor, CloudWatch, New Relic, Prometheus, Dynatrace, ServiceNow, Jira, Microsoft Teams, Slack, and more, complementing your existing monitoring and ITSM investments.

Dokku serves as an open-source alternative to Heroku, representing one of the most compact implementations of a Platform as a Service (PaaS) solution available. It empowers developers to create and oversee their application lifecycle—from initial construction to eventual scaling—while allowing them to utilize familiar tools and maintain control over their platform. Built on Docker, Dokku can be deployed on virtually any hardware or cost-effective cloud service and operates seamlessly on a single server of your preference. After installation, users are able to push applications that are compatible with Heroku via Git, utilizing Heroku buildpacks, Dockerfiles, or Docker images to construct and execute them within isolated containers. The platform is designed to support on-the-fly app building directly from a git push, automatically detecting the programming language using buildpacks when necessary and initiating containers from the generated images. In addition to this, Dokku manages web processes and background operations through technologies like Nginx and cron, ensuring that scheduled tasks run smoothly and efficiently. Ultimately, Dokku not only simplifies app deployment but also enhances the overall development experience by streamlining common processes.