Business Software for Prometheus

Kubernetes is an open-source platform that provides developers and DevOps with an end-to-end security solution. This includes security compliance, risk analysis, security compliance and RBAC visualizer. It also scans images for vulnerabilities. Kubescape scans K8s clusters, Kubernetes manifest files (YAML files, and HELM charts), code repositories, container registries and images, detecting misconfigurations according to multiple frameworks (such as the NSA-CISA, MITRE ATT&CK®), finding software vulnerabilities, and showing RBAC (role-based-access-control) violations at early stages of the CI/CD pipeline. It instantly calculates risk scores and displays risk trends over time. Kubescape is one of the most popular Kubernetes security compliance tools for developers. Its easy-to-use interface, flexible output formats and automated scanning capabilities have made Kubescape one of the fastest growing Kubernetes tools. This has saved Kubernetes admins and users precious time, effort and resources.

InsightFinder Unified Intelligence Engine platform (UIE) provides human-centered AI solutions to identify root causes of incidents and prevent them from happening. InsightFinder uses patented self-tuning, unsupervised machine learning to continuously learn from logs, traces and triage threads of DevOps Engineers and SREs to identify root causes and predict future incidents. Companies of all sizes have adopted the platform and found that they can predict business-impacting incidents hours ahead of time with clearly identified root causes. You can get a complete overview of your IT Ops environment, including trends and patterns as well as team activities. You can also view calculations that show overall downtime savings, cost-of-labor savings, and the number of incidents solved.

Helidon is an open-source suite of Java libraries tailored for developing microservices, utilizing a high-performance web core that is driven by Netty. The introduction of Helidon Níma marks the first Java microservices framework that leverages virtual threads to enhance performance. With a focus on user-friendliness, Helidon offers comprehensive tooling and a variety of examples to facilitate a swift onboarding process. Since it is essentially a collection of Java libraries operating on a rapid Netty core, Helidon avoids unnecessary overhead or bloat. It fully supports MicroProfile and includes well-known APIs such as JAX-RS, CDI, and JSON-P/B. The Helidon Reactive WebServer serves as the backbone for our implementation, boasting a contemporary functional programming model that sits atop Netty. This lightweight, adaptable, and reactive web server provides an efficient and straightforward base for your microservices. In addition, Helidon comes equipped with essential features like health checks, metrics, tracing, and fault tolerance, ensuring you have all the necessary tools to build cloud-ready applications that seamlessly integrate with systems like Prometheus and Jaeger/Zipkin. Overall, Helidon's capabilities and performance make it an ideal choice for developers looking to create efficient and scalable cloud-native applications.

Zenduty offers a comprehensive platform for incident alerting, on-call management, and response orchestration that integrates reliability into your production operations seamlessly. It provides a unified view of the health status across all production activities, allowing teams to respond to incidents with a 90% faster turnaround and resolve issues in 60% less time. With the ability to implement customized, data-driven on-call schedules, you can maintain round-the-clock coverage for significant incidents. The platform facilitates the application of industry-leading incident response protocols, enabling quicker resolution through effective task delegation and collaborative triaging efforts. Furthermore, it automatically integrates your playbooks into each incident, ensuring a structured approach to each situation. You can also log incident-related tasks and action items to enhance the quality of postmortems and prepare for future occurrences effectively. By suppressing unnecessary alerts, your engineering and support teams can concentrate on the notifications that truly matter. Additionally, Zenduty boasts over 100 integrations with various tools such as application performance management (APM), log monitoring, error tracking, server monitoring, IT service management (ITSM), support systems, and security services, thereby enhancing the overall operational efficiency. This extensive connectivity ensures that teams can utilize their existing tools while streamlining their incident management processes.

Uffizzi empowers teams to create internal developer platforms in a matter of minutes rather than months, offering ready-to-use Kubernetes multi-tenancy, cluster virtualization, and adaptable templating options. This solution allows you to streamline your workflows while ensuring that every developer has access to self-service, temporary environments suitable for development, testing, pull requests, staging, and additional use cases. Whether you choose to utilize your own infrastructure or ours, Uffizzi seamlessly integrates into your existing setup for a smooth experience. With Uffizzi, teams can enhance collaboration and efficiency across development processes.

Streamline your performance testing, analysis, and reporting processes to eliminate the tedious manual tasks that developers dislike. By doing so, you can uphold product quality while minimizing the cognitive strain on your development team, which is essential in agile environments. This solution is crafted to accommodate numerous teams operating within intricate agile frameworks, allowing for effective performance management with a limited number of performance engineers. It promotes a standardized approach to performance testing across the entire organization. Additionally, it facilitates the sharing of performance testing expertise among any team, engaged in any project, at any moment—thereby integrating performance testing into the culture of your developers and enhancing the quality of websites and services. Perfana empowers teams to assess their software’s performance not only prior to production but also with each build, all with ease. Our plugin seamlessly integrates with well-known CI servers, enabling every team to verify performance with each build or release, ensuring a continuous commitment to quality throughout the development process. This comprehensive approach not only enhances productivity but also fosters a culture of collaboration and continuous improvement.

Aiden by OpsVerse is an AI-driven DevOps assistant designed to help teams optimize their workflows and improve operational efficiency. It uses agentic AI to learn from team behaviors, tailor responses to specific environments, and take proactive actions such as scaling infrastructure or resolving deployment failures. Aiden integrates seamlessly with existing DevOps processes, offering real-time insights and automating repetitive tasks. With a privacy-first approach, Aiden complies with data security policies and offers flexible deployment options, ensuring security and compliance at all stages of DevOps management.

Our experiment editor streamlines your path to reliability, making it quicker and more straightforward, with all necessary tools readily accessible and granting complete authority over your experiments. Each feature is designed to assist you in reaching your objectives while safely implementing chaos engineering at scale within your organization. You can effortlessly introduce new targets, attacks, and checks through the use of extensions available in Steadybit. The innovative discovery and selection process simplifies the target-picking experience. Enhance collaboration between teams by minimizing obstacles, and easily export and import experiments using JSON or YAML formats. Steadybit's landscape provides a comprehensive view of your software's dependencies and the interconnectedness of components, serving as an excellent foundation to initiate your chaos engineering efforts. Additionally, with the robust query language, you can categorize your system(s) into various environments based on consistent information applicable across your setup, while also clearly designating specific environments to selected users and teams to mitigate the risk of unintended damage. This comprehensive approach ensures that your chaos engineering practice is not only effective but also secure and well-organized.

Polar Signals Cloud is a continuous profiling solution that operates continuously without the need for instrumentation, aimed at enhancing performance, comprehending incidents, and reducing infrastructure expenses. By executing a single command and following an exceptionally straightforward onboarding guide, you can commence cost savings and performance optimization for your infrastructure almost instantly. The capability to analyze past incidents allows users to trace and address issues effectively. The profiling data generated offers unparalleled insights into the execution of processes over time, enabling you to confidently identify the most critical areas for optimization based on statistical analysis. Many companies find that 20-30% of their resources are squandered on inefficient code paths that could be readily improved. By utilizing a remarkable combination of technologies, Polar Signals Cloud provides a profiling toolkit that meets the demands of modern infrastructure and applications. Thanks to its zero-instrumentation approach, you can implement it right away and start benefiting from actionable observability data that drives better decision-making. With ongoing use, organizations can continually refine their performance strategies and maximize resource allocation.

Receive tailored AI suggestions for your alerts that align with the chosen persona. Parny AI offers three distinct personas: DevOps engineer, senior developer, and database administrator, each designed to deliver optimal alert recommendations. You can effortlessly include your colleagues in the on-call roster, ensuring that the appropriate individuals are notified promptly. Distribute on-call duties among team members using scheduled shifts and automated escalations to enhance responsiveness. Our platform empowers engineering teams to adopt a proactive stance, enabling quicker incident resolutions and a smoother operational experience. Additionally, you can access personalized analytics tailored to your organization, teams, services, and users. This ensures that you remain informed about your performance metrics, fostering continuous improvement in your organization's overall efficiency. With these tools at your disposal, your team can work collaboratively and effectively in managing alerts and incidents.

OpenCost is an open-source initiative that is vendor-neutral, designed to measure and allocate costs associated with cloud infrastructure and containers in real-time. Developed by experts in Kubernetes and backed by practitioners in the field, OpenCost brings transparency to the often opaque spending patterns associated with Kubernetes. It offers flexible and customizable options for cost allocation and monitoring of cloud resources, facilitating accurate showback, chargeback, and continuous reporting. The tool provides real-time cost allocation that can be examined down to individual containers, ensuring precise tracking of expenses. It effectively allocates costs for in-cluster resources, including CPU, GPU, memory, load balancers, and persistent volumes. Additionally, OpenCost features dynamic asset pricing by integrating with billing APIs from AWS, Azure, and GCP, while also accommodating on-premises Kubernetes clusters with tailored pricing solutions. Beyond the Kubernetes cluster, it can monitor expenses from cloud providers related to resources such as object storage and databases, as well as other managed services. Furthermore, it seamlessly integrates with other open-source tools, allowing for convenient exports of pricing data to platforms like Prometheus, enhancing its utility in cost management. This makes OpenCost a comprehensive solution for organizations seeking to maintain control over their cloud spending effectively.

OpenLIT serves as an observability tool that is fully integrated with OpenTelemetry, specifically tailored for application monitoring. It simplifies the integration of observability into AI projects, requiring only a single line of code for setup. This tool is compatible with leading LLM libraries, such as those from OpenAI and HuggingFace, making its implementation feel both easy and intuitive. Users can monitor LLM and GPU performance, along with associated costs, to optimize efficiency and scalability effectively. The platform streams data for visualization, enabling rapid decision-making and adjustments without compromising application performance. OpenLIT's user interface is designed to provide a clear view of LLM expenses, token usage, performance metrics, and user interactions. Additionally, it facilitates seamless connections to widely-used observability platforms like Datadog and Grafana Cloud for automatic data export. This comprehensive approach ensures that your applications are consistently monitored, allowing for proactive management of resources and performance. With OpenLIT, developers can focus on enhancing their AI models while the tool manages observability seamlessly.

Healthchecks.io serves as a straightforward yet powerful tool for monitoring cron jobs, providing alerts to users when their scheduled tasks, including backups and reports, fail to complete on time. Each background job can be assigned a unique ping URL, and the platform promptly notifies users if a job does not ping within the designated timeframe. The service allows for 20 free cron job monitors and features an intuitive dashboard where users can easily name, tag, and manage their tasks. With adjustable period and grace time settings, users can monitor tasks across different statuses, such as "up," "late," or "down," according to ping timing. Additionally, Healthchecks.io supports cron syntax, maintains an event history log, and provides status badges for public viewing. Users can receive notifications through a variety of integrations, which include email, webhooks, Slack, and Discord, as well as incident management solutions like PagerDuty and Opsgenie. This service is particularly well-suited for monitoring a range of processes, from cron jobs and server tasks to database backups and SSL certificate renewals, ensuring a comprehensive approach to task management. As a result, health checks become an essential part of maintaining the reliability of critical operations.

The Stackable data platform was crafted with a focus on flexibility and openness. It offers a carefully selected range of top-notch open source data applications, including Apache Kafka, OpenSearch, Trino, and Apache Spark. Unlike many competitors that either promote their proprietary solutions or enhance vendor dependence, Stackable embraces a more innovative strategy. All data applications are designed to integrate effortlessly and can be added or removed with remarkable speed. Built on Kubernetes, it is capable of operating in any environment, whether on-premises or in the cloud. To initiate your first Stackable data platform, all you require is stackablectl along with a Kubernetes cluster. In just a few minutes, you will be poised to begin working with your data. You can set up your one-line startup command right here. Much like kubectl, stackablectl is tailored for seamless interaction with the Stackable Data Platform. Utilize this command line tool for deploying and managing stackable data applications on Kubernetes. With stackablectl, you have the ability to create, delete, and update components efficiently, ensuring a smooth operational experience for your data management needs. The versatility and ease of use make it an excellent choice for developers and data engineers alike.

Diffusion stands at the forefront of real-time data streaming and messaging innovations. Established to address the challenges of real-time systems, application connectivity, and data distribution faced by businesses globally, the company boasts a diverse team of professionals in both business and technology. Its premier product, the Diffusion data platform, streamlines the process of consuming, enriching, and reliably delivering data. Organizations can swiftly leverage both existing and new data sources, as the platform is specifically designed for straightforward event-driven, real-time application development, allowing for the rapid addition of new functionalities while keeping development costs low. It adeptly manages any data size, format, or speed and features a versatile hierarchical data model that organizes incoming event data into a multi-level topic tree. Furthermore, Diffusion is highly scalable, accommodating millions of topics and facilitating the transformation of event data through the platform's low-code capabilities. Users can subscribe to event data with remarkable precision, fostering hyper-personalization and enhancing the user experience. This robust platform not only meets current demands but also anticipates future needs in data management.

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.

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.

Windmill serves as an open-source platform for developers, functioning as a workflow engine that converts scripts into automatically generated user interfaces, APIs, and cron jobs. This innovative tool simplifies the creation of workflows and data pipelines, making it easier to construct complex applications that handle large volumes of data. Windmill supports multiple programming languages, allowing developers to write and deploy applications significantly faster, up to ten times quicker, while ensuring high reliability and observability through its self-hosted job orchestrator. Among its features are auto-generated user interfaces tailored to script parameters, a low-code application editor for crafting custom UIs, and a flow editor that utilizes a drag-and-drop approach to workflow design. Additionally, Windmill automatically manages dependencies, incorporates strong permission controls, and offers comprehensive monitoring capabilities. Users can trigger workflows using various methods, such as webhooks, scheduled tasks, CLI commands, Slack messages, or emails. Furthermore, developers have the flexibility to write their scripts in their preferred local code editors, allowing them to preview and seamlessly deploy their work using the command line interface, streamlining the overall development process. This robust platform ultimately empowers users to create sophisticated applications with minimal effort.

OpsVerse's ObserveNow is an all-in-one observability platform that seamlessly combines logs, metrics, distributed traces, and application performance monitoring into one cohesive service. Leveraging open-source technologies, ObserveNow facilitates quick implementation, enabling users to monitor their infrastructure in mere minutes without requiring extensive engineering resources. It is adaptable for deployment in various settings, whether on public clouds, private clouds, or on-premises environments, and it prioritizes data compliance by allowing users to keep their data securely within their own network. The platform features user-friendly pre-configured dashboards, alerts, advanced anomaly detection, and automated workflows for remediation, all designed to minimize the mean time to detect and resolve issues effectively. Furthermore, ObserveNow offers a private SaaS solution, allowing organizations to enjoy the advantages of SaaS while maintaining control over their data within their own cloud or network. This innovative platform not only enhances operational efficiency but also operates at a significantly lower cost compared to conventional observability solutions available in the market today.

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.

Dash0 serves as a comprehensive observability platform rooted in OpenTelemetry, amalgamating metrics, logs, traces, and resources into a single, user-friendly interface that facilitates swift and context-aware monitoring while avoiding vendor lock-in. It consolidates metrics from Prometheus and OpenTelemetry, offering robust filtering options for high-cardinality attributes, alongside heatmap drilldowns and intricate trace visualizations to help identify errors and bottlenecks immediately. Users can take advantage of fully customizable dashboards powered by Perses, featuring code-based configuration and the ability to import from Grafana, in addition to smooth integration with pre-established alerts, checks, and PromQL queries. The platform's AI-driven tools, including Log AI for automated severity inference and pattern extraction, enhance telemetry data seamlessly, allowing users to benefit from sophisticated analytics without noticing the underlying AI processes. These artificial intelligence features facilitate log classification, grouping, inferred severity tagging, and efficient triage workflows using the SIFT framework, ultimately improving the overall monitoring experience. Additionally, Dash0 empowers teams to respond proactively to system issues, ensuring optimal performance and reliability across their applications.

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.

WunderGraph is a cutting-edge, open-source API platform that streamlines the integration and management of various APIs from heterogeneous backends like REST, gRPC, Kafka, and GraphQL, allowing developers to create a cohesive, type-safe, and high-performance API interface for modern applications. It features Cosmo, a comprehensive API management solution for federated GraphQL, which encompasses essential functionalities such as schema registry, composition validation, routing, analytics, metrics, tracing, and observability, all of which can be handled through code integrated into existing development workflows instead of relying on separate dashboards. By enabling teams to specify how multiple services should be combined into a single API, WunderGraph simplifies the automatic generation of type-safe client libraries and facilitates the management of authentication, authorization, and API requests through built-in tools that align seamlessly with CI/CD and Git-centered processes. This innovative approach not only enhances productivity but also ensures that developers can focus on building robust applications without being bogged down by the complexities of API integration.

NudgeBee is an enterprise-grade AI Agents and Agentic Workflow platform purpose-built for SRE, CloudOps, DevOps, and platform engineering teams running complex cloud-native environments. The platform ships pre-built AI Assistants that work on day one, no model training, no prompt engineering. The AI SRE Agent handles incident triage, alert enrichment, root cause analysis, and remediation guidance. The AI FinOps Assistant delivers continuous Kubernetes and cloud cost optimization with right-sizing, spot instance, and abandoned resource recommendations. The AI K8sOps Agent provides natural-language interaction with clusters for workload checks, upgrade guidance, and maintenance operations. Alongside these, NudgeBee's visual no-code Workflow Builder lets teams automate any custom operational process. It supports 20+ action categories including native AWS, Azure, and GCP CLI nodes, kubectl execution, database queries, LLM-powered nodes, Agent-to-Agent (A2A) calls, and MCP server integration, all with built-in approval gates and audit logging. Key technical differentiators: NudgeBee uses a live semantic Knowledge Graph to ground AI answers in real infrastructure topology. It queries observability data in place, zero data ingestion, zero egress cost. A single workflow can span multiple clouds, Kubernetes clusters, ticketing tools, and communication channels. 49+ integrations across Kubernetes, AWS, Azure, GCP, Prometheus, Datadog, Dynatrace, Jira, ServiceNow, Slack, GitHub, ArgoCD, and more. Enterprise-ready: RBAC, MFA, immutable audit trails, BYOM (GPT, Claude, Gemini, Bedrock, Ollama), self-hosted deployment, SOC-2 Type II, and ISO 27001 certified.