Prometheus Integrations

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.

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.

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 comprehensive AI-native software delivery platform designed to modernize DevOps practices by automating continuous integration, continuous delivery, and GitOps workflows across multi-cloud and multi-service environments. It empowers engineering teams to build faster, deploy confidently, and manage infrastructure as code with automated error reduction and cost control. The platform integrates new capabilities like database DevOps, artifact registries, and on-demand cloud development environments to simplify complex operations. Harness also enhances software quality through AI-driven test automation, chaos engineering, and predictive incident response that minimize downtime. Feature management and experimentation tools allow controlled releases and data-driven decision-making. Security and compliance are strengthened with automated vulnerability scanning, runtime protection, and supply chain security. Harness offers deep insights into engineering productivity and cloud spend, helping teams optimize resources. With over 100 integrations and trusted by top companies, Harness unifies AI and DevOps to accelerate innovation and developer productivity.

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.

Craft personalized monitoring solutions for your machine learning models using our incredibly intuitive monitor builder, which alerts you to problems such as concept drift, declines in model performance, and bias, among other issues. Aporia effortlessly integrates with any machine learning infrastructure, whether you're utilizing a FastAPI server on Kubernetes, an open-source deployment solution like MLFlow, or a comprehensive machine learning platform such as AWS Sagemaker. Dive into specific data segments to meticulously observe your model's behavior. Detect unforeseen bias, suboptimal performance, drifting features, and issues related to data integrity. When challenges arise with your ML models in a production environment, having the right tools at your disposal is essential for swiftly identifying the root cause. Additionally, expand your capabilities beyond standard model monitoring with our investigation toolbox, which allows for an in-depth analysis of model performance, specific data segments, statistics, and distributions, ensuring you maintain optimal model functionality and integrity.

The NGINX Service Mesh, which is always available for free, transitions effortlessly from open source projects to a robust, secure, and scalable enterprise-grade solution. With NGINX Service Mesh, you can effectively manage your Kubernetes environment, utilizing a cohesive data plane for both ingress and egress, all through a singular configuration. The standout feature of the NGINX Service Mesh is its fully integrated, high-performance data plane, designed to harness the capabilities of NGINX Plus in managing highly available and scalable containerized ecosystems. This data plane delivers unmatched enterprise-level traffic management, performance, and scalability, outshining other sidecar solutions in the market. It incorporates essential features such as seamless load balancing, reverse proxying, traffic routing, identity management, and encryption, which are crucial for deploying production-grade service meshes. Additionally, when used in conjunction with the NGINX Plus-based version of the NGINX Ingress Controller, it creates a unified data plane that simplifies management through a single configuration, enhancing both efficiency and control. Ultimately, this combination empowers organizations to achieve higher performance and reliability in their service mesh deployments.

Traefik Mesh is a user-friendly and easily configurable service mesh that facilitates the visibility and management of traffic flows within any Kubernetes cluster. By enhancing monitoring, logging, and visibility while also implementing access controls, it enables administrators to swiftly and effectively bolster the security of their clusters. This capability allows for the monitoring and tracing of application communications in a Kubernetes environment, which in turn empowers administrators to optimize internal communications and enhance overall application performance. The streamlined learning curve, installation process, and configuration requirements significantly reduce the time needed for implementation, allowing for quicker realization of value from the effort invested. Furthermore, this means that administrators can dedicate more attention to their core business applications. Being an open-source solution, Traefik Mesh ensures that there is no vendor lock-in, as it is designed to be opt-in, promoting flexibility and adaptability in deployments. This combination of features makes Traefik Mesh an appealing choice for organizations looking to improve their Kubernetes environments.

Discovering in-depth insights into your Kubernetes setup has never been easier, thanks to Sysdig Monitor's managed Prometheus service, which is fully compatible with Prometheus. This service allows you to access all pertinent Kubernetes information in a single location, enabling you to resolve errors in your Kubernetes environment up to ten times faster. With a managed Prometheus offering, scaling your monitoring capabilities is straightforward, featuring pre-built dashboards, alerts, and seamless integrations. Not only can you cut down on unnecessary expenses by an average of 40%, but you can also benefit from affordable custom metrics. Additionally, our service enhances your troubleshooting process by providing a prioritized listing of issues, detailed pod information, live logs, and actionable remediation steps, ultimately saving you valuable time. Leverage our scalable data storage, automatic service discovery, and streamlined integration deployment to maximize efficiency. You can maintain your existing PromQL and Grafana dashboards, with out-of-the-box options available and the flexibility to customize any dashboard to fit your specific needs. Furthermore, our alerts are highly adaptable, ensuring easy integration into your existing alert management system for improved operational performance.

Uptrace is an observability platform built on OpenTelemetry that enables users to track, comprehend, and enhance intricate distributed systems effectively. With a single, streamlined dashboard, you can oversee your entire application stack efficiently. This setup provides a swift view of all services, hosts, and systems in one place. The distributed tracing feature allows you to follow the journey of a request as it flows through various services and components, highlighting the timing of each operation along with any logs and errors that arise in real-time. Through metrics, you can swiftly gauge, visualize, and monitor a variety of operations using tools such as percentiles, heatmaps, and histograms. By receiving alerts when your application experiences downtime or when a performance issue is detected, you can respond to incidents more promptly. Moreover, the platform allows you to monitor all aspects—spans, logs, errors, and metrics—using a unified query language, simplifying the observability process further. This comprehensive approach ensures that you have all the necessary insights to maintain optimal performance in your distributed systems.

Easily access dedicated machines equipped with pre-configured professional AI development tools from reliable data centers at competitive rates. Apolo offers everything from high-performance computing resources to a comprehensive AI platform featuring an integrated machine learning development toolkit. It can be implemented in various configurations, including distributed architectures, dedicated enterprise clusters, or multi-tenant white-label solutions to cater to specialized instances or self-service cloud environments. Instantly, Apolo sets up a robust AI-focused development environment, providing you with all essential tools readily accessible. The platform efficiently manages and automates both infrastructure and processes, ensuring successful AI development at scale. Apolo’s AI-driven services effectively connect your on-premises and cloud resources, streamline deployment pipelines, and synchronize both open-source and commercial development tools. By equipping enterprises with the necessary resources and tools, Apolo facilitates significant advancements in AI innovation. With its user-friendly interface and powerful capabilities, Apolo stands out as a premier choice for organizations looking to enhance their AI initiatives.

All-in-one tracking system for maximum optimization, insights and visibility. Automation. Monitoring the location and movement your assets with our end-toend solution is not only simple, but also profitable. Our easy-to-use solution will ensure that you never again lose track of your assets, whether you manage a fleet of transport vehicles, waste containers, valuable machinery, or a complicated supply chain. Monitor the use of your assets, identify bottlenecks and predict delays. Sensolus gives you the insight to maximize your assets. You can manage your inventory levels with confidence, knowing that you will always have the optimal stock available. Automating your inventory management will reduce the risk of excess stock and underused assets. Our automated activity log will lift the veil of doubt. You can use customizable alerts to ensure that third parties are held accountable for delivery times and locations, as well as the proper use of assets.