groundcover
Cloud-based solution for observability that helps businesses manage and track workload and performance through a single dashboard.
Monitor all the services you run on your cloud without compromising cost, granularity or scale. Groundcover is a cloud-native APM solution that makes observability easy so you can focus on creating world-class products. Groundcover's proprietary sensor unlocks unprecedented granularity for all your applications. This eliminates the need for costly changes in code and development cycles, ensuring monitoring continuity.
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HiveMQ
The HiveMQ Platform provides a scalable, reliable data backbone with an event-driven MQTT architecture. Here are a few highlights:
1. MQTT Broker: At the heart of the HiveMQ platform is a fully MQTT-compliant broker purpose-built for fast, reliable, bi-directional data movement between IoT devices and enterprise systems.
2. Edge Data Integration: HiveMQ Edge seamlessly integrates edge data by converting industrial protocols into standardized MQTT, enabling an interoperable IIoT infrastructure.
3. IoT Streaming Governance: Data Hub transforms data in flight, passing only the most relevant, contextualized data to cloud and enterprise systems.
4. UNS & IT/OT convergence Enabler: Commonly used as the backbone for Unified Namespace architectures and seamlessly connects OT devices with IT systems for full visibility and interoperability.
5. Distributed Data Intelligence: HiveMQ Pulse unifies and contextualizes data across the enterprise for smarter decisions exactly where they matter most.
6. Maximum Interoperability: Runs anywhere on-premises or in public or private clouds. Efficiently connects to streaming applications, databases and data lakes with a Java SDK to build your own
7. Scalability to Support Growth: Elastic scaling with automatic data balancing and smart message distribution. Proven benchmark of up to 200M active clients with 1.8B messages/hour
8. Business Critical Reliability: Zero message loss with persistence to disk and offline queuing. No single point of failure due to masterless cluster architecture and zero downtime upgrades
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Amazon MSK
Amazon Managed Streaming for Apache Kafka (Amazon MSK) simplifies the process of creating and operating applications that leverage Apache Kafka for handling streaming data. As an open-source framework, Apache Kafka enables the construction of real-time data pipelines and applications. Utilizing Amazon MSK allows you to harness the native APIs of Apache Kafka for various tasks, such as populating data lakes, facilitating data exchange between databases, and fueling machine learning and analytical solutions. However, managing Apache Kafka clusters independently can be quite complex, requiring tasks like server provisioning, manual configuration, and handling server failures. Additionally, you must orchestrate updates and patches, design the cluster to ensure high availability, secure and durably store data, establish monitoring systems, and strategically plan for scaling to accommodate fluctuating workloads. By utilizing Amazon MSK, you can alleviate many of these burdens and focus more on developing your applications rather than managing the underlying infrastructure.
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Apache Kafka
Apache Kafka® is a robust, open-source platform designed for distributed streaming. It can scale production environments to accommodate up to a thousand brokers, handling trillions of messages daily and managing petabytes of data with hundreds of thousands of partitions. The system allows for elastic growth and reduction of both storage and processing capabilities. Furthermore, it enables efficient cluster expansion across availability zones or facilitates the interconnection of distinct clusters across various geographic locations. Users can process event streams through features such as joins, aggregations, filters, transformations, and more, all while utilizing event-time and exactly-once processing guarantees. Kafka's built-in Connect interface seamlessly integrates with a wide range of event sources and sinks, including Postgres, JMS, Elasticsearch, AWS S3, among others. Additionally, developers can read, write, and manipulate event streams using a diverse selection of programming languages, enhancing the platform's versatility and accessibility. This extensive support for various integrations and programming environments makes Kafka a powerful tool for modern data architectures.
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