Prometheus Integrations

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.

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.

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.

Dopamine is a user-friendly AI agent platform that allows individuals to create, implement, and oversee intelligent AI agents tailored for specific tasks and workflows with ease and efficiency. By focusing on rapid deployment and straightforward processes, it enables users to develop operational AI "team members" in a matter of minutes instead of weeks, utilizing a visual agent builder, personalized instructions, and integrated connections to real-time data sources for immediate action. Users have the flexibility to merge various agents into cohesive workflows, adjust each agent's cognitive and behavioral parameters, and collaborate with colleagues or communities by sharing agents. This versatility makes Dopamine ideal for tasks such as information summarization, automating tedious processes, generating and modifying content, and managing tasks. The platform is designed to eliminate the common challenges and complexities associated with other agent and workflow builders, delivering tangible productivity improvements from the outset while enhancing collaborative efforts across different projects and minimizing the demand for intricate engineering solutions. In essence, Dopamine seeks to empower users by streamlining the process of leveraging AI for everyday tasks.

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.

WunderGraph Hub serves as a comprehensive platform that empowers development teams to collaboratively design, manage, and enhance APIs within a well-defined workflow. Acting as a unifying layer for API development, it facilitates cooperation among teams working on distributed services, enabling them to design schemas, suggest modifications, and agree on API functionalities prior to the start of implementation. The platform features a visual design canvas that allows developers, API owners, and consumers to outline capabilities, model schema architectures, and engage in discussions about requirements in a collaborative environment. After a design is established, Hub automatically creates schema proposals and collects feedback from stakeholders through controlled workflows, guaranteeing that any proposed changes to the API undergo thorough review, approval, and documentation before deployment. This method fosters a transition from casual communication and disjointed documentation to a more organized collaboration process that emphasizes clear and traceable decision-making. Ultimately, WunderGraph Hub enhances the efficiency of API development by ensuring that all team members are aligned and informed throughout the project lifecycle.

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

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.

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.

Vision Agents is a versatile open-source Python framework designed for developing low-latency voice and video AI agents utilizing any model. This framework empowers developers to integrate large language models, speech recognition, and vision models from over 25 different providers, enabling the creation of real-time agents for applications such as telehealth, voice assistance, live coaching, video analysis, interactive avatars, security surveillance, sports commentary, and a variety of other multimodal uses. Its architecture is tailored to facilitate the development of agents capable of listening, speaking, seeing, processing media, accessing tools, and providing instant responses, all while operating on Stream's expansive global edge network, which ensures latency below 500ms. With just a minimal Python setup, developers can quickly create their first agent by leveraging platforms like Gemini Realtime, OpenAI, Deepgram, ElevenLabs, Stream, or other compatible providers. Furthermore, Vision Agents accommodates both real-time speech-to-speech models and tailored speech-to-text, language processing, and text-to-speech pipelines, allowing teams to either rapidly deploy a functional voice agent or exercise complete control over the components involved in speech recognition, language reasoning, and text-to-speech functionalities. Overall, this framework not only simplifies the process of building sophisticated AI agents but also enhances flexibility and performance across diverse applications.

root9 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. root9 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, root9 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, root9 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.

Verdonz is an advanced platform for business intelligence and AI analytics tailored for teams analyzing company performance and data. The platform seamlessly integrates with various data warehouses, databases, query engines, monitoring systems, and knowledge repositories, systematically organizing metrics, entities, relationships, and access guidelines within a unified semantic model. Users can pose questions in natural language, delve into metric definitions and the SQL queries that underpin responses, and navigate through dashboards, reports, and alerts linked to governed metrics. AI agents that can be configured engage with connected data and knowledge either on demand, according to a set schedule, or in response to alerts; external assistants can retrieve authorized context via the read-only Model Context Protocol (MCP) server or through API access. Additionally, embedded analytics allow for the integration of saved queries across other applications, enhancing usability. Verdonz offers flexibility in deployment, as it can be accessed as hosted SaaS, via a dedicated instance or customer-specific cloud, and can also be utilized as self-hosted software for organizations requiring greater control over their infrastructure. This versatility makes Verdonz a compelling choice for businesses seeking to leverage data analytics effectively.

Gradify serves as a platform for the issuance and verification of credentials for universities, employers, businesses, and public sector entities. It enables teams to generate academic records, certificates, badges, identity documents, and various signed records using templates, allowing for issuance either one at a time or in bulk via CSV uploads or through an API. These credentials are securely anchored to a permissionless blockchain, with their metadata stored on IPFS, facilitating verification through a public verifier via QR codes or credential IDs. The system is compatible with W3C Verifiable Credentials, decentralized identifiers, and Open Badges, while also offering tools for document extraction, anomaly detection, revocation processes, activity reporting, and audit documentation. Additionally, it integrates with educational registries and wallets such as NAD, ABC, and DigiLocker, and can seamlessly connect with institutional ERP or student information systems. Gradify is available as either managed cloud software or for deployment on-premises, providing flexibility for diverse organizational needs. This versatility allows institutions to enhance their credentialing processes while ensuring security and accessibility.

Cisco ThousandEyes is an innovative platform for network intelligence that equips organizations with profound insights into digital interactions across various environments, including the internet, cloud, and enterprise networks. Utilizing sophisticated monitoring and analytics capabilities, ThousandEyes enables businesses to identify, troubleshoot, and rectify performance challenges that affect essential applications, websites, and services. Its extensive array of tools delivers valuable information regarding network performance, application delivery, and user engagement, allowing organizations to maintain uninterrupted connectivity and enhance user experiences. This platform is widely embraced by Fortune 500 companies and SaaS providers alike, establishing itself as a reliable solution for navigating the intricacies of contemporary hybrid and multi-cloud landscapes. Additionally, ThousandEyes empowers IT teams by equipping them with the tools needed to proactively manage, optimize, and refine their digital infrastructures for improved operational efficiency.

D2iQ Enterprise Kubernetes Platform (DKP) Enterprise Kubernetes Platform: Run Kubernetes Workloads at Scale D2iQ Kubernetes Platform (DKP): Adopt, expand, and enable advanced workloads across any infrastructure, whether on-prem, on the cloud, in air-gapped environments, or at the edge. Solve the Toughest Enterprise Kubernetes Challenges Accelerate the journey to production at scale, DKP provides a single, centralized point of control to build, run, and manage applications across any infrastructure. * Enable Day 2 Readiness Out-of-the-Box Without Lock-In * Simplify and Accelerate Kubernetes Adoption * Ensure Consistency, Security, and Performance * Expand Kubernetes Across Distributed Environments * Ensure Fast, Simple Deployment of ML and Fast Data Pipeline * Leverage Cloud Native Expertise

Kubernetes, cloud, and container security that closes loop from source to finish Find vulnerabilities and prioritize them; detect and respond appropriately to threats and anomalies; manage configurations, permissions and compliance. All activity across cloud, containers, and hosts can be viewed. Runtime intelligence can be used to prioritize security alerts, and eliminate guesswork. Guided remediation using a simple pull request at source can reduce time to resolution. Any activity in any app or service, by any user, across clouds, containers and hosts, can be viewed. Risk Spotlight can reduce vulnerability noise by up 95% with runtime context. ToDo allows you to prioritize the security issues that are most urgent. Map production misconfigurations and excessive privileges to infrastructure as code (IaC), manifest. A guided remediation workflow opens a pull request directly at source.

HAProxy Enterprise, the industry's most trusted software load balancer, is HAProxy Enterprise. It powers modern application delivery at all scales and in any environment. It provides the highest performance, observability, and security. Load balance can be determined by round robin or least connections, URI, IP addresses, and other hashing methods. Advanced decisions can be made based on any TCP/IP information, or HTTP attribute. Full logical operator support is available. Send requests to specific application groups based on URL, file extension, client IP, client address, health status of backends and number of active connections. Lua scripts can be used to extend and customize HAProxy. TCP/IP information and any property of the HTTP request (cookies headers, URIs, etc.) can be used to maintain users' sessions.

Meet the Galileo Suite: a better way to monitor and measure the health of your environment. It automatically visualizes your asset relationships, analyzes your device health, and displays it in a single view so you can quickly remediate issues and get on with your day. Join the smart IT teams that rely on the Galileo Suite to make smarter, faster decisions to keep their systems running optimally and their business growing. Full-Stack Monitoring and Visibility. Reimagined. From basic monitoring to immersive 3D exploration, identify and resolve your IT issues faster than ever with the Galileo Suite. Try Galileo for 🆓 FREE 🆓 today.

Coralogix is the most popular stateful streaming platform, providing engineering teams with real-time insight and long-term trend analysis without relying on storage or indexing. To manage, monitor, alert, and manage your applications, you can import data from any source. Coralogix automatically narrows the data from millions of events to common patterns, allowing for faster troubleshooting and deeper insights. Machine learning algorithms constantly monitor data patterns and flows among system components and trigger dynamic alarms to let you know when a pattern is out of the norm without the need for static thresholds or pre-configurations. Connect any data in any format and view your insights anywhere, including our purpose-built UI and Kibana, Grafana as well as SQL clients and Tableau. You can also use our CLI and full API support. Coralogix has successfully completed the relevant privacy and security compliances by BDO, including SOC 2, PCI and GDPR.

DevSecOps Next Generation - Securing Your Binaries. Identify security flaws and license violations early in development and block builds that have security issues before deployment. Automated and continuous auditing and governance of software artifacts throughout the software development cycle, from code to production. Additional functionalities include: - Deep recursive scanning components, drilling down to analyze all artifacts/dependencies and creating a graph showing the relationships between software components. - On-Prem or Cloud, Hybrid, Multi-Cloud Solution - An impact analysis of how one issue in a component affects all dependent parts with a display chain displaying the impacts in a component dependency diagram. - JFrog's vulnerability database is continuously updated with new component vulnerabilities data. VulnDB is the industry's most comprehensive security database.

Enhance the engagement of your online learners with BigBlueButton, a robust web conferencing platform specifically tailored for virtual education. If you are in search of a reliable solution to facilitate remote teaching, BigBlueButton enables instantaneous sharing of audio, video, slides, chat, and screen content. The platform fosters student interaction through features like emoji sharing, polling, and breakout rooms, creating a dynamic learning environment. It’s essential that synchronous learning tools seamlessly integrate with your learning management system (LMS). Notably, platforms like Instructure, Schoology, Jenzabar, and D2L come equipped with native BigBlueButton integration, while Moodle and Sakai offer plugins for enhanced compatibility. Additionally, BigBlueButton adheres to learning tools interoperability (LTI) 1.0 standards, ensuring broad usability across various educational settings. Supported by a global community of developers and commercial entities, BigBlueButton is committed to providing an exceptional web conferencing experience for online education, making it a top choice for educators worldwide. Thus, whether you are teaching a small group or a large class, BigBlueButton is equipped to meet your online teaching needs effectively.

ScyllaDB serves as an ideal database solution for applications that demand high performance and minimal latency, catering specifically to data-intensive needs. It empowers teams to fully utilize the growing computing capabilities of modern infrastructures, effectively removing obstacles to scaling as data volumes expand. Distinct from other database systems, ScyllaDB stands out as a distributed NoSQL database that is completely compatible with both Apache Cassandra and Amazon DynamoDB, while incorporating significant architectural innovations that deliver outstanding user experiences at significantly reduced costs. Over 400 transformative companies, including Disney+ Hotstar, Expedia, FireEye, Discord, Zillow, Starbucks, Comcast, and Samsung, rely on ScyllaDB to tackle their most challenging database requirements. Furthermore, ScyllaDB is offered in various formats, including a free open-source version, a fully-supported enterprise solution, and a fully managed database-as-a-service (DBaaS) available across multiple cloud platforms, ensuring flexibility for diverse user needs. This versatility makes it an attractive choice for organizations looking to optimize their database performance.

Massive amounts data can be moved as messages between services, applications and systems at any one time. If an application isn’t available or a service interruption occurs, messages and transactions may be lost or duplicated. This can cost businesses time and money. IBM has refined IBM MQ over the past 25 years. MQ allows you to hold a message in a queue until it is delivered. MQ moves data once, even file data, to avoid competitors delivering messages twice or not at the right time. MQ will never lose a message. IBM MQ can be run on your mainframe, in containers, in public or private clouds or in containers. IBM offers an IBM-managed cloud service (IBM MQ Cloud), hosted on Amazon Web Services or IBM Cloud, as well as a purpose-built Appliance (IBM MQ Appliance), to simplify deployment and maintenance.

Establishing a cohesive logging framework is essential for ensuring that log data is both accessible and functional. Unfortunately, many current solutions are inadequate; traditional tools do not cater to the demands of modern cloud APIs and microservices, and they are not evolving at a sufficient pace. Fluentd, developed by Treasure Data, effectively tackles the issues associated with creating a unified logging framework through its modular design, extensible plugin system, and performance-enhanced engine. Beyond these capabilities, Fluentd Enterprise also fulfills the needs of large organizations by providing features such as Trusted Packaging, robust security measures, Certified Enterprise Connectors, comprehensive management and monitoring tools, as well as SLA-based support and consulting services tailored for enterprise clients. This combination of features makes Fluentd a compelling choice for businesses looking to enhance their logging infrastructure.

Do you struggle with providing access to large data sets that are rapidly growing or enabling distributed content-based uses? Tape is cost-effective, but data is not always available and tape can be difficult to manage. Public cloud can present the challenge of unpredictable, compounding recurring costs and inability to meet privacy and performance requirements. DataCore Swarm is an on-premises object storage system that simplifies the process of managing, storing, and protecting data. It also allows S3/HTTP access for any application, device, and end-user. Swarm transforms your data archive to a flexible, immediately accessible content library that allows remote workflows, on demand access, and massive scaling.

Marathon serves as a robust container orchestration platform that integrates seamlessly with Mesosphere’s Datacenter Operating System (DC/OS) and Apache Mesos, ensuring high availability through its active/passive clustering and leader election mechanism, which guarantees continuous uptime. It supports multiple container runtimes, offering first-class integration for Mesos containers utilizing cgroups as well as Docker, making it adaptable to various development environments. Additionally, Marathon facilitates the deployment of stateful applications by allowing persistent storage volumes to be linked to your apps, which is particularly beneficial for running databases such as MySQL and Postgres with storage managed by Mesos. The platform boasts an intuitive and powerful user interface, along with a range of service discovery and load balancing options to suit diverse needs. Health checks are implemented to monitor application performance via HTTP or TCP checks, ensuring reliability. Users can also set up event subscriptions by providing an HTTP endpoint to receive notifications, which can aid in integrating with external load balancers. Lastly, metrics can be queried in JSON format at the /metrics endpoint, while also being capable of integration with popular systems like Graphite, StatsD, DataDog, or scraped using Prometheus, allowing for comprehensive monitoring and analysis of application performance. This combination of features positions Marathon as a versatile tool for managing containerized applications effectively.

Nobl9 Service level objectives platform converts your reliability goals into automatic action. Nobl9 is a platform that helps organizations set and understand their reliability goals. You can ensure reliable and balanced performance by monitoring the performance of your systems. The platform gathers metrics from all your existing monitoring systems and calculates the performance. SLOs can be defined in an expressive SLOs as-code language to enable automated actions when they are at risk. Nobl9 facilitates cross-team collaboration between various stakeholders to improve and maintain the reliability and efficiency of your service. Nobl9 historical and real-time reports provide clear data-driven solutions to critical questions such as "should we concentrate on features or technical debt?" or "are we wasting too much money on cloud resources?" By using the shared language SLOs, you can achieve the right balance between speed, safety, spend, and speed.

Empower individuals to explore and analyze streaming data effectively. By sharing, documenting, and organizing your data, you can boost productivity by as much as 95%. Once you have your data, you can create applications tailored for real-world use cases. Implement a security model focused on data to address the vulnerabilities associated with open source technologies, ensuring data privacy is prioritized. Additionally, offer secure and low-code data pipeline functionalities that enhance usability. Illuminate all hidden aspects and provide unmatched visibility into data and applications. Integrate your data mesh and technological assets, ensuring you can confidently utilize open-source solutions in production environments. Lenses has been recognized as the premier product for real-time stream analytics, based on independent third-party evaluations. With insights gathered from our community and countless hours of engineering, we have developed features that allow you to concentrate on what generates value from your real-time data. Moreover, you can deploy and operate SQL-based real-time applications seamlessly over any Kafka Connect or Kubernetes infrastructure, including AWS EKS, making it easier than ever to harness the power of your data. By doing so, you will not only streamline operations but also unlock new opportunities for innovation.

Achieve precise visibility and policy application across every data endpoint in your system. This solution is tailored to facilitate your infrastructure-as-code processes and orchestration seamlessly. It possesses the ability to dynamically adjust to your workloads while maintaining sub-millisecond response times. Integration with your existing tools is effortless and requires no modifications to your applications. Strengthen your cloud security by implementing detailed data access policies and extending a Zero Trust approach to the data cloud. Safeguard your organization against potential data breaches, thereby enhancing customer trust and delivering reassurance. Designed to address the specific performance, deployment, and availability hurdles associated with the data cloud, Cyral provides a comprehensive view of your data ecosystem. Cyral’s lightweight, stateless data cloud sidecar acts as an interception service that offers real-time insights into all activities within the data cloud and ensures detailed access controls. Its high performance and scalability allow for efficient interception, effectively preventing threats and unauthorized access to your data that might otherwise remain unnoticed. In a rapidly evolving digital landscape, having such robust security measures in place is crucial for maintaining the integrity of your organization's data.

Using OpenEBS in conjunction with Kubera is the optimal solution for storage needs in Kubernetes environments. OpenEBS stands out as the leading open source storage option for Kubernetes, recognized for its speed and efficiency. Kubera enhances OpenEBS Mayastor by providing a user-friendly graphical interface, along with APIs, automatic checks, configuration options, Active Directory authentication, built-in performance benchmarks, and additional operators to streamline upgrades and various other scenarios. Available at no cost, Kubera is offered by MayaData, which also provides round-the-clock support to help customers minimize operational expenses and simplify management. Kubera Propel, a cloud-native declarative data plane crafted in Rust, is built upon the foundational OpenEBS Mayastor technology. This innovative platform integrates cutting-edge technologies such as NVMe, SPDK, and new storage capabilities emerging within the Linux kernel. Independent benchmarks have demonstrated that OpenEBS, when governed by Kubera Propel, achieves remarkably low latency performance for databases and various workloads on Kubernetes, making it an excellent choice for developers and organizations alike. This combination not only enhances performance but also addresses the increasing demand for efficient and reliable storage solutions in modern computing environments.

Reduce your cloud expenses, enhance security, and boost developer efficiency. Why waste funds on cloud providers? Our solution allows you to monitor your expenditures and implement straightforward, machine learning-driven strategies to cut costs. Explore our assortment of over 60 applications available in the AWS Marketplace, designed for easy deployment at the most competitive prices. Safeguard your cloud infrastructure and efficiently manage EC2 instance updates across various regions through a unified interface. Our intuitive dashboard enables you to analyze and optimize your AWS spending thoroughly. It automatically identifies and eliminates unused AWS resources to help lower costs. Benefit from ongoing machine learning assessments to continually minimize cloud expenses. Instead of focusing on building complex application stacks, utilize our pre-configured, secure images available right off the shelf. This way, you can focus more on coding rather than getting caught up in operations. Additionally, our solution scans your AWS environment for security vulnerabilities, providing assistance in mitigating risks. With the capability to patch servers across multiple regions from one centralized dashboard, managing your cloud infrastructure has never been easier.

StackPulse streamlines and enhances the processes of incident response and management, fostering a seamless commitment to the reliability of software services. It equips Site Reliability Engineers, developers, and on-call personnel with the essential context and authority to effectively analyze, address, and resolve incidents throughout the entire stack, regardless of scale. By revolutionizing how engineering and operations teams handle software and infrastructure services, StackPulse introduces a collaborative platform filled with various incident management tools. Users can effortlessly initiate teamwork through automated war room setups, efficient data collection, and auto-generated postmortem reports. The insights gathered during incidents pave the way for tailored recommendations on playbooks and triggers, leading to remarkable decreases in Mean Time to Recovery (MTTR) and enhanced adherence to Service Level Objectives (SLOs). Additionally, StackPulse identifies risks by analyzing unique patterns within an organization’s monitoring, infrastructure, and operational data, offering customized automated playbooks that suit specific organizational needs. This approach not only mitigates risks but also empowers teams to better manage their operational challenges.

OpsLevel is the most flexible Internal Developer Portal, helping teams streamline service ownership, automate catalog maintenance, and drive engineering excellence. With AI-powered insights, automation, and self-service workflows, OpsLevel eliminates bottlenecks—so developers can focus on building, not bureaucracy. Unlike fragmented spreadsheets or homegrown solutions, OpsLevel brings clarity to complex architectures, ensuring teams can enforce best practices, reduce incidents, and accelerate deployments. From onboarding to security, OpsLevel makes software delivery faster, more reliable, and more scalable.

The enterprise database for time series, documents, and vectors. Store any type data and combine the simplicity and scalability NoSQL with SQL. CrateDB is a distributed database that runs queries in milliseconds regardless of the complexity, volume, and velocity.

Beats serves as a free and accessible platform designed specifically for single-purpose data shippers that transport data from numerous machines and systems to Logstash or Elasticsearch. These open-source data shippers are installed as agents on your servers, enabling the seamless transfer of operational data to Elasticsearch. Elastic offers Beats to facilitate the collection of data and event logs efficiently. Data can be directed to Elasticsearch or routed through Logstash, allowing for additional processing and enhancement before visualization in Kibana. If you're eager to start monitoring infrastructure metrics and centralizing log analytics swiftly, the Metrics app and Logs app in Kibana are excellent resources to explore. For comprehensive guidance, refer to Analyze metrics and Monitor logs. Filebeat simplifies the process of collecting data from various sources, including security devices, cloud environments, containers, and hosts, by providing a lightweight solution to forward and centralize logs and files. This flexibility ensures that you can maintain an organized and efficient data pipeline regardless of the complexity of your infrastructure.

Cortex is an innovative open-source solution that enhances horizontal scalability. While Prometheus is capable of handling up to 1 million samples per second on a single machine, Cortex enables a virtually limitless level of horizontal scaling. In an ever-evolving landscape, it is essential to adopt alternative strategies for monitoring individual virtual machines or servers. Prometheus features a service-discovery-driven, pull-based metrics system that caters to the dynamic characteristics of microservices. This capability allows for seamless monitoring of your entire ecosystem, regardless of the number of components involved. You can instrument your application to generate tailored metrics using the standard Prometheus client libraries, or you can leverage the vast array of Prometheus Exporters that gather data from existing software like MySQL, Redis, Java, ElasticSearch, and many others. By adopting these tools, organizations can ensure they maintain visibility and control over their complex infrastructures. This flexibility is particularly valuable in today's fast-paced, continuously changing technological environments.

Harness is a software development and delivery platform designed to help engineering organizations automate application releases, manage infrastructure, and maintain security controls. Its continuous integration capabilities enable developers to build, test, and publish software through configurable pipelines. Continuous delivery tools support automated deployments across cloud and on-premises environments using strategies such as rolling updates, canary releases, and blue-green deployments. Harness includes infrastructure as code management for provisioning resources, enforcing policies, and detecting configuration drift. The platform provides application security testing, software composition analysis, and supply chain security capabilities to identify vulnerabilities during development and deployment. AI-powered agents assist with pipeline configuration, deployment troubleshooting, infrastructure operations, and other software delivery tasks. Cloud and AI cost management tools help organizations monitor resource consumption, identify unnecessary spending, and allocate costs across teams and services. Engineering analytics provide visibility into delivery performance, development activity, and operational efficiency through dashboards and reports. Harness connects with source code repositories, cloud platforms, monitoring systems, and enterprise applications while supporting role-based access controls, approval workflows, and audit trails.

Enhance both your production and staging environments by integrating logs, metrics, and traces in real-time and on-demand directly from your IDE or command line interface. With Lightrun, you can significantly improve productivity and achieve complete code-level visibility. You can add logs and metrics instantly while services are operational, making it easier to debug complex architectures like monoliths, microservices, Kubernetes, Docker Swarm, ECS, and serverless applications. Quickly insert any missing log lines, instrument necessary metrics, or establish snapshots as needed without the hassle of recreating the production setup or redeploying. When you invoke instrumentation, the resulting data gets sent to your log analysis platform, IDE, or preferred APM tool. This allows for thorough analysis of code behavior to identify bottlenecks and errors without interrupting the running application. You can seamlessly incorporate extensive logs, snapshots, counters, timers, function durations, and much more without risking system stability. This streamlined approach lets you focus on coding rather than getting bogged down in debugging, eliminating the need for constant restarts or redeployments when troubleshooting. Ultimately, this results in a more efficient development workflow, allowing you to maintain momentum on your projects.

Shoreline is the only cloud reliability platform that allows DevOps engineers to build automations in a matter of minutes and fix problems forever. Shoreline’s modern “Operations at the Edge” architecture runs efficient agents in the background of all monitored hosts. Agents run as a DaemonSet on Kubernetes or an installed package on VMs (apt, yum). The Shoreline backend is hosted by Shoreline in AWS, or deployed in your AWS virtual private cloud. Debugging and repairing issues is easy with advanced tooling for your best SREs, Jupyter style notebooks for the broader team, and a platform that makes building automations 30X faster by allowing operators to manage their entire fleet as if it were a single box. Shoreline does the heavy lifting, setting up monitors and building repair scripts, so that customers only need to configure them for their environment.