Apache Mesos Integrations

Keep a close eye on your servers, containers, and applications with high-resolution, real-time monitoring. Netdata gathers metrics every second and showcases them through stunning low-latency dashboards. It is built to operate across all your physical and virtual servers, cloud environments, Kubernetes clusters, and edge/IoT devices, providing comprehensive insights into your systems, containers, and applications. The platform is capable of scaling effortlessly from just one server to thousands, even in intricate multi/mixed/hybrid cloud setups, and can retain metrics for years if sufficient disk space is available. KEY FEATURES: - Gathers metrics from over 800 integrations - Real-Time, Low-Latency, High-Resolution - Unsupervised Anomaly Detection - Robust Visualization - Built-In Alerts - systemd Journal Logs Explorer - Minimal Maintenance Required - Open and Extensible Framework Identify slowdowns and anomalies in your infrastructure using thousands of metrics collected per second, paired with meaningful visualizations and insightful health alerts, all without needing any configuration. Netdata stands out by offering real-time data collection and visualization along with infinite scalability integrated into its architecture. Its design is both flexible and highly modular, ready for immediate troubleshooting with no prior knowledge or setup needed. This unique approach makes it an invaluable tool for maintaining optimal performance across diverse environments.

Docker simplifies complex configuration tasks and is employed throughout the entire software development lifecycle, enabling rapid, straightforward, and portable application development on desktop and cloud environments. This comprehensive platform offers various features, including user interfaces, command-line utilities, application programming interfaces, and integrated security, which all work harmoniously to enhance the application delivery process. You can kickstart your programming projects by leveraging Docker images to create unique applications compatible with both Windows and Mac operating systems. With the capabilities of Docker Compose, constructing multi-container applications becomes a breeze. In addition, Docker seamlessly integrates with familiar tools in your development toolkit, such as Visual Studio Code, CircleCI, and GitHub, enhancing your workflow. You can easily package your applications into portable container images, guaranteeing consistent performance across diverse environments, whether on on-premises Kubernetes or cloud services like AWS ECS, Azure ACI, or Google GKE. Furthermore, Docker provides access to a rich repository of trusted assets, including official images and those from verified vendors, ensuring that your application development is both reliable and high-quality. Its adaptability and integration capabilities position Docker as an essential tool for developers striving to boost their productivity and streamline their processes, making it indispensable in modern software development. This ensures that developers can focus more on innovation and less on configuration management.

Pliant provides a comprehensive solution for IT Process Automation that streamlines, improves, and secures the automation creation and implementation process for teams. By reducing the potential for human error, ensuring compliance, and enhancing overall productivity, Pliant proves to be an essential tool. Users can effortlessly integrate existing automation or create new workflows through a centralized orchestration interface. The platform ensures reliable governance while maintaining compliance through its practical, built-in features. Pliant simplifies the process by abstracting numerous vendor APIs into intelligent action blocks, allowing users to utilize a drag-and-drop functionality, which removes the need for repetitive coding tasks. Citizen developers can efficiently build consistent and effective automation across multiple platforms, services, and applications within minutes, thus maximizing the value of their entire technology ecosystem from one interface. Moreover, with the ability to incorporate new APIs in as little as 15 business days, Pliant guarantees that any unique requirements will be met promptly, ensuring your automation capabilities remain current. This level of efficiency not only empowers teams to adapt quickly but also fosters innovation in a fast-evolving tech environment. Additionally, the platform's user-friendly design encourages collaboration among team members, further enhancing productivity and streamlining workflows.

AppOptics™, developed by SolarWinds®, functions as a software-as-a-service (SaaS) tool designed for monitoring both infrastructure and applications across custom-built on-premises, hybrid, and cloud environments. By facilitating rapid detection of performance bottlenecks throughout the entire stack—from applications to the foundational infrastructure and even to the specific lines of code—AppOptics effectively minimizes mean time to recovery (MTTR). Created with user-friendliness in mind, IT professionals can easily set up and utilize the tool. Its robust features automatically pinpoint performance challenges, thereby removing uncertainty and significantly shortening the troubleshooting duration. Additionally, AppOptics enables organizations to harmonize their performance metrics and infrastructure goals with overarching business objectives, fostering a more integrated approach to operational success. Through this alignment, businesses can ensure that their technical capabilities directly support their strategic aims.

Fidelis Halo is a cloud security platform that leverages SaaS to streamline the automation of security controls in cloud computing. It ensures compliance across various environments such as containers, servers, and IaaS, whether in public, private, or hybrid clouds. With its robust automation features, Halo facilitates quicker workflows between InfoSec (DevOps) teams and the platform itself, offering more than 20,000 pre-set policies and over 150 templates tailored to standards including PCI, CIS, and HIPAA. Furthermore, the comprehensive Halo API, SDK, and toolkit enhance the automation of security and compliance processes within your DevOps workflow, enabling the identification and remediation of critical vulnerabilities prior to production deployment. Additionally, the free edition of Halo Cloud Secure grants complete access to the Halo Cloud Secure CSPM Service for up to 10 cloud service accounts across a combination of AWS and Azure. Start your journey towards automated cloud security today and experience the peace of mind that comes with comprehensive protection!

Kapacitor acts as a specialized data processing engine tailored for InfluxDB 1.x and plays a crucial role in the InfluxDB 2.0 architecture. This robust tool is adept at managing both real-time stream data and batch processing, delivering immediate responses through its distinctive programming language known as TICKscript. In today's technological landscape, simply relying on dashboards and operator alerts falls short; there is an increasing demand for automation and capabilities that trigger actions automatically. Utilizing a publish-subscribe model for its alerting mechanism, Kapacitor publishes alerts to designated topics, with handlers subscribing to these topics to receive the latest updates. This adaptable pub/sub framework, coupled with the capacity to run User Defined Functions, positions Kapacitor as a central control hub within various systems, capable of performing tasks such as auto-scaling, inventory management, and orchestrating IoT devices. Furthermore, the intuitive plugin architecture of Kapacitor facilitates easy integration with numerous anomaly detection tools, thereby amplifying its utility and effectiveness in the realm of data processing. Ultimately, Kapacitor's comprehensive functionality ensures that users can implement sophisticated data-driven operations with ease.

Riak® TS is a robust NoSQL Time Series Database tailored for handling IoT and Time Series data effectively. It excels at ingesting, transforming, storing, and analyzing vast quantities of time series information. Designed to outperform Cassandra, Riak TS utilizes a masterless architecture that allows for uninterrupted data read and write operations, even in the event of network partitions or hardware malfunctions. Data is systematically distributed across the Riak ring, with three copies of each dataset maintained by default to ensure at least one is available for access. This distributed system operates without a central coordinator, offering a seamless setup and user experience. The ability to easily add or remove nodes from the cluster enhances its flexibility, while the masterless architecture ensures this process is straightforward. Furthermore, incorporating nodes made from standard hardware can facilitate predictable and nearly linear scaling, making Riak TS an ideal choice for organizations looking to manage substantial time series datasets efficiently.

Marathon is a powerful container orchestration tool that works in harmony with Mesosphere’s Datacenter Operating System (DC/OS) and Apache Mesos to provide exceptional high availability through its active/passive clustering and leader election strategies, ensuring uninterrupted service. It is compatible with multiple container runtimes, offering seamless integration for Mesos containers that utilize cgroups and Docker, making it suitable for a variety of development ecosystems. Furthermore, Marathon enables the deployment of stateful applications by allowing users to attach persistent storage volumes to their applications, which proves advantageous for running data-driven databases like MySQL and Postgres under Mesos management. The platform features a user-friendly and robust interface, alongside an array of service discovery and load balancing solutions tailored to meet different requirements. Health checks are conducted to assess application performance through HTTP or TCP protocols, thereby enhancing reliability. Additionally, users can establish event subscriptions by supplying an HTTP endpoint to receive notifications, facilitating integration with external load balancers. Metrics can be accessed in JSON format at the /metrics endpoint and can also be integrated with popular monitoring systems such as Graphite, StatsD, DataDog, or scraped by Prometheus, thereby allowing for thorough monitoring and evaluation of application performance. This array of capabilities makes Marathon an adaptable and effective solution for managing containerized applications, ensuring that developers have the tools they need for efficient orchestration and management. Ultimately, its features not only streamline operational processes but also enhance the overall deployment experience for various applications.

Apache Spark™ is a powerful analytics platform crafted for large-scale data processing endeavors. It excels in both batch and streaming tasks by employing an advanced Directed Acyclic Graph (DAG) scheduler, a highly effective query optimizer, and a streamlined physical execution engine. With more than 80 high-level operators at its disposal, Spark greatly facilitates the creation of parallel applications. Users can engage with the framework through a variety of shells, including Scala, Python, R, and SQL. Spark also boasts a rich ecosystem of libraries—such as SQL and DataFrames, MLlib for machine learning, GraphX for graph analysis, and Spark Streaming for processing real-time data—which can be effortlessly woven together in a single application. This platform's versatility allows it to operate across different environments, including Hadoop, Apache Mesos, Kubernetes, standalone systems, or cloud platforms. Additionally, it can interface with numerous data sources, granting access to information stored in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and many other systems, thereby offering the flexibility to accommodate a wide range of data processing requirements. Such a comprehensive array of functionalities makes Spark a vital resource for both data engineers and analysts, who rely on it for efficient data management and analysis. The combination of its capabilities ensures that users can tackle complex data challenges with greater ease and speed.

Witboost is a versatile, rapid, and efficient data management platform crafted to empower businesses in adopting a data-centric strategy while reducing time-to-market, IT expenditures, and operational expenses. The system is composed of multiple modules, each serving as a functional component that can function autonomously to address specific issues or be combined to create a holistic data management framework customized to meet the unique needs of your organization. These modules enhance particular data engineering tasks, enabling a seamless integration that guarantees quick deployment and significantly reduces time-to-market and time-to-value, which in turn lowers the overall cost of ownership of your data ecosystem. As cities develop, the concept of smart cities increasingly incorporates digital twins to anticipate requirements and address potential challenges by utilizing data from numerous sources and managing complex telematics systems. This methodology not only promotes improved decision-making but also equips urban areas to swiftly adapt to ever-evolving demands, ensuring a more resilient and responsive infrastructure for the future. In this way, Witboost emerges as a crucial asset for organizations looking to thrive in a data-driven landscape.

Tackle the difficulties posed by intricate tools and overwhelming workloads by adopting an all-in-one networking and security solution. Streamlining your toolset allows for a significant reduction in time wasted on disruptive context shifts, effectively alleviating the fatigue often associated with constant toggling between applications. TF stands out for its exceptional plugin integration, frequently surpassing the basic functionalities found in many other SDN plugins to deliver advanced features. It promotes smooth network interactions, ensuring that your infrastructure operates as a cohesive unit by adhering to well-established open protocol standards in both the control and data planes. The open-source framework of TF encourages ongoing innovation from a diverse group of contributors, providing the versatility to customize outcomes according to your unique requirements or to work alongside reliable vendors. Additionally, it offers the ability to implement namespace isolation and micro-segmentation tailored to individual microservices, enabling the creation of specific security policies and configurations for different tenants. This level of customization and flexibility not only enhances network security but also streamlines operational processes, making TF an indispensable asset for organizations aiming to improve their overall efficiency and security posture. As the landscape of networking and security evolves, leveraging such a comprehensive solution becomes increasingly essential for staying competitive.

OES is designed with high availability and scalability, making it ideal for handling increasing deployment workloads while being flexible enough to integrate smoothly with diverse SDLC toolchains. The platform offers an intuitive interface that enables users to define custom stages for executing multiple deployments simultaneously, which greatly minimizes the time required for deployment tasks. Users can easily perform actions such as rolling back, advancing, or pausing all concurrent deployments with just a click, simplifying the management process. Furthermore, OES facilitates the automation of repetitive tasks within the SDLC by allowing the creation of multiple child pipelines that can be initiated from a parent pipeline. Its modular design and API-driven architecture enable OES to serve as a central Continuous Delivery (CD) tool for many organizations. This adaptability also allows developers from different teams to effortlessly link external services with Spinnaker, leading to improved deployment orchestration and enhanced collaboration. Ultimately, OES emerges as a robust solution for refining deployment procedures across a variety of environments, ensuring that teams can respond swiftly to changes in their workflows and project demands. The platform's capability to streamline processes not only boosts productivity but also fosters a more integrated development environment.

MLlib, the machine learning component of Apache Spark, is crafted for exceptional scalability and seamlessly integrates with Spark's diverse APIs, supporting programming languages such as Java, Scala, Python, and R. It boasts a comprehensive array of algorithms and utilities that cover various tasks including classification, regression, clustering, collaborative filtering, and the construction of machine learning pipelines. By leveraging Spark's iterative computation capabilities, MLlib can deliver performance enhancements that surpass traditional MapReduce techniques by up to 100 times. Additionally, it is designed to operate across multiple environments, whether on Hadoop, Apache Mesos, Kubernetes, standalone clusters, or within cloud settings, while also providing access to various data sources like HDFS, HBase, and local files. This adaptability not only boosts its practical application but also positions MLlib as a formidable tool for conducting scalable and efficient machine learning tasks within the Apache Spark ecosystem. The combination of its speed, versatility, and extensive feature set makes MLlib an indispensable asset for data scientists and engineers striving for excellence in their projects. With its robust capabilities, MLlib continues to evolve, reinforcing its significance in the rapidly advancing field of machine learning.

Apache OpenWhisk is a versatile, distributed Serverless framework that initiates function execution in response to various events, effectively managing workloads of all sizes. By abstracting the complexities of infrastructure, server management, and scaling through the use of Docker containers, it allows developers to focus on building innovative and efficient applications. The platform utilizes a programming model where developers create functional components called Actions in a range of supported programming languages, which can be triggered dynamically from external event sources (Feeds) or through HTTP requests (Triggers). Furthermore, OpenWhisk includes a Command Line Interface (CLI) based on REST APIs and various tools that assist in service packaging, cataloging, and integration with popular container deployment solutions. Its container-centric architecture offers flexibility for multiple deployment scenarios, whether on local machines or in cloud environments. This adaptability extends to compatibility with leading container frameworks, ensuring that developers can tailor their solutions to meet a wide array of requirements. Consequently, Apache OpenWhisk stands out as a robust option for teams looking to streamline their serverless application development process.

Aurora manages applications and services across a network of machines, ensuring they operate continuously without any interruptions. When machine failures occur, it intelligently reallocates tasks to the operational machines. For job updates, Aurora evaluates the health and current status of the deployment, allowing it to revert to a previous version if necessary. The system features a quota mechanism that ensures resource availability for specific applications while supporting multiple users who deploy various services. Customization is achieved through a domain-specific language (DSL) that offers templating capabilities, which helps users maintain consistent configurations and minimize redundancy. Additionally, Aurora informs Apache ZooKeeper about service availability, which aids in client discovery through frameworks like Finagle. This architecture not only improves reliability but also enhances resource management efficiency across a range of applications. Overall, Aurora's design emphasizes flexibility and responsiveness in a dynamic computing environment.

Apache Flink is a robust framework and distributed processing engine designed for executing stateful computations on both continuous and finite data streams. It has been specifically developed to function effortlessly across different cluster settings, providing computations with remarkable in-memory speed and the ability to scale. Data in various forms is produced as a steady stream of events, which includes credit card transactions, sensor readings, machine logs, and user activities on websites or mobile applications. The strengths of Apache Flink become especially apparent in its ability to manage both unbounded and bounded data sets effectively. Its sophisticated handling of time and state enables Flink's runtime to cater to a diverse array of applications that work with unbounded streams. When it comes to bounded streams, Flink utilizes tailored algorithms and data structures that are optimized for fixed-size data collections, ensuring exceptional performance. In addition, Flink's capability to integrate with various resource managers adds to its adaptability across different computing platforms. As a result, Flink proves to be an invaluable resource for developers in pursuit of efficient and dependable solutions for stream processing, making it a go-to choice in the data engineering landscape.