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Red Hat® OpenShift® Streams for Apache Kafka is a cloud-managed service designed to enhance the developer experience for creating, deploying, and scaling cloud-native applications, as well as for modernizing legacy systems. This service simplifies the processes of creating, discovering, and connecting to real-time data streams, regardless of their deployment location. Streams play a crucial role in the development of event-driven applications and data analytics solutions. By enabling seamless operations across distributed microservices and handling large data transfer volumes with ease, it allows teams to leverage their strengths, accelerate their time to value, and reduce operational expenses. Additionally, OpenShift Streams for Apache Kafka features a robust Kafka ecosystem and is part of a broader suite of cloud services within the Red Hat OpenShift product family, empowering users to develop a diverse array of data-driven applications. With its powerful capabilities, this service ultimately supports organizations in navigating the complexities of modern software development.

The infrastructure is fully equipped with capabilities built as microservices, which are containerized using Docker and managed through Kubernetes. It offers support for multiple protocols and remains hardware agnostic, allowing seamless connections between any device and various third-party applications. Secure connections are ensured through TLS and DTLS, alongside mutual TLS authentication that utilizes X.509 certificates. The Mainflux software stack encompasses all essential components and microservices needed for developing IoT solutions, projects, or products. This IoT platform is designed to enhance interoperability with existing enterprise applications and other IoT platforms. Furthermore, it supports bidirectional communication with a vast number of devices and gateways, employing diverse open protocols and data formats. The system normalizes messages to simplify integration with the overall infrastructure, promoting efficiency and ease of use. Ultimately, this comprehensive approach fosters a robust environment for innovative IoT applications.

Achieve limitless data retention for Apache Kafka® with Confluent, empowering you to be infrastructure-enabled rather than constrained by outdated systems. Traditional technologies often force a choice between real-time processing and scalability, but event streaming allows you to harness both advantages simultaneously, paving the way for innovation and success. Have you ever considered how your rideshare application effortlessly analyzes vast datasets from various sources to provide real-time estimated arrival times? Or how your credit card provider monitors millions of transactions worldwide, promptly alerting users to potential fraud? The key to these capabilities lies in event streaming. Transition to microservices and facilitate your hybrid approach with a reliable connection to the cloud. Eliminate silos to ensure compliance and enjoy continuous, real-time event delivery. The possibilities truly are limitless, and the potential for growth is unprecedented.

Utilizing a microservices architecture for IoT backed by Kubernetes allows for limitless scalability and the ability to adjust resources as needed, all while maintaining high performance and resilience against failures. Streamline the data flow from your IoT devices to any analytics platform through a seamlessly integrated Kafka channel, enabling you to modify device behavior based on the insights gained from processing results. The creators of this platform bring over 25 years of expertise in IoT, telecommunications, and big data, leveraging their extensive knowledge to develop an exceptional IoT solution suitable for both large enterprises and emerging startups. Your data remains secure with encryption both during transmission and while stored. Additionally, the platform offers built-in user authentication and authorization features via an open OAuth2 / UMA interface. Easily connect and manage IoT devices through a cloud-based graphical user interface or a RESTful API. Gather and visualize telemetry data using the integrated dashboard or utilize third-party tools such as Grafana for enhanced analysis and presentation of data insights. This comprehensive IoT platform ensures that you have the tools necessary to effectively handle your data and device management needs.

We developed Conduktor, a comprehensive and user-friendly interface designed to engage with the Apache Kafka ecosystem seamlessly. Manage and develop Apache Kafka with assurance using Conduktor DevTools, your all-in-one desktop client tailored for Apache Kafka, which helps streamline workflows for your entire team. Learning and utilizing Apache Kafka can be quite challenging, but as enthusiasts of Kafka, we have crafted Conduktor to deliver an exceptional user experience that resonates with developers. Beyond merely providing an interface, Conduktor empowers you and your teams to take command of your entire data pipeline through our integrations with various technologies associated with Apache Kafka. With Conduktor, you gain access to the most complete toolkit available for working with Apache Kafka, ensuring that your data management processes are efficient and effective. This means you can focus more on innovation while we handle the complexities of your data workflows.

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.

StreamNative transforms the landscape of streaming infrastructure by combining Kafka, MQ, and various other protocols into one cohesive platform, which offers unmatched flexibility and efficiency tailored for contemporary data processing requirements. This integrated solution caters to the varied demands of streaming and messaging within microservices architectures. By delivering a holistic and intelligent approach to both messaging and streaming, StreamNative equips organizations with the tools to effectively manage the challenges and scalability of today’s complex data environment. Furthermore, Apache Pulsar’s distinctive architecture separates the message serving component from the message storage segment, creating a robust cloud-native data-streaming platform. This architecture is designed to be both scalable and elastic, allowing for quick adjustments to fluctuating event traffic and evolving business needs, and it can scale up to accommodate millions of topics, ensuring that computation and storage remain decoupled for optimal performance. Ultimately, this innovative design positions StreamNative as a leader in addressing the multifaceted requirements of modern data streaming.

Event Hubs provides a fully managed service for real-time data ingestion that is easy to use, reliable, and highly scalable. It enables the streaming of millions of events every second from various sources, facilitating the creation of dynamic data pipelines that allow businesses to quickly address challenges. In times of crisis, you can continue data processing thanks to its geo-disaster recovery and geo-replication capabilities. Additionally, it integrates effortlessly with other Azure services, enabling users to derive valuable insights. Existing Apache Kafka clients can communicate with Event Hubs without requiring code alterations, offering a managed Kafka experience while eliminating the need to maintain individual clusters. Users can enjoy both real-time data ingestion and microbatching on the same stream, allowing them to concentrate on gaining insights rather than managing infrastructure. By leveraging Event Hubs, organizations can rapidly construct real-time big data pipelines and swiftly tackle business issues as they arise, enhancing their operational efficiency.

Transform your customer service interactions and conversational AI applications by utilizing the open-source Airy platform. Airy Core stands out as a fully-featured conversational platform that is ready for production use. With Airy, you are equipped to handle conversational data sourced from multiple channels effortlessly. Powered by Apache Kafka, Airy's infrastructure allows for the simultaneous processing of numerous conversations and messages, efficiently streaming pertinent data wherever needed. You can easily integrate a variety of tools, from our complimentary open-source live chat plugin to popular messaging services like Facebook Messenger and Google’s Business Messages, all connected to your Airy Core. This seamless integration is made possible through an ingestion platform that leverages Apache Kafka to manage incoming webhook data from diverse sources. By effectively interpreting this data, we transform it into contacts, conversations, and messages that work independently of their origins, enhancing the versatility and capability of your conversational engagements. Ultimately, Airy empowers you to create a cohesive communication strategy across different platforms.

Experience Apache Kafka offered as a fully managed service that avoids vendor lock-in while providing comprehensive features for constructing your streaming pipeline. You can establish a fully managed Kafka instance in under 10 minutes using our intuitive web console or programmatically through our API, CLI, Terraform provider, or Kubernetes operator. Seamlessly integrate it with your current technology infrastructure using more than 30 available connectors, and rest assured with comprehensive logs and metrics that come standard through our service integrations. This fully managed distributed data streaming platform can be deployed in any cloud environment of your choice. It’s perfectly suited for applications that rely on event-driven architectures, facilitating near-real-time data transfers and pipelines, stream analytics, and any situation where swift data movement between applications is essential. With Aiven’s hosted and expertly managed Apache Kafka, you can effortlessly set up clusters, add new nodes, transition between cloud environments, and update existing versions with just a single click, all while keeping an eye on performance through a user-friendly dashboard. Additionally, this service enables businesses to scale their data solutions efficiently as their needs evolve.

DeltaStream is an integrated serverless streaming processing platform that integrates seamlessly with streaming storage services. Imagine it as a compute layer on top your streaming storage. It offers streaming databases and streaming analytics along with other features to provide an integrated platform for managing, processing, securing and sharing streaming data. DeltaStream has a SQL-based interface that allows you to easily create stream processing apps such as streaming pipelines. It uses Apache Flink, a pluggable stream processing engine. DeltaStream is much more than a query-processing layer on top Kafka or Kinesis. It brings relational databases concepts to the world of data streaming, including namespacing, role-based access control, and enables you to securely access and process your streaming data, regardless of where it is stored.

Google Cloud's Managed Service for Apache Kafka is an efficient and scalable solution that streamlines the deployment, oversight, and upkeep of Apache Kafka clusters. By automating essential operational functions like provisioning, scaling, and patching, it allows developers to concentrate on application development without the burdens of managing infrastructure. The service guarantees high reliability and availability through data replication across various zones, thus mitigating the risks of potential outages. Additionally, it integrates effortlessly with other Google Cloud offerings, enabling the creation of comprehensive data processing workflows. Security measures are robust, featuring encryption for both stored and transmitted data, along with identity and access management, and network isolation to keep information secure. Users can choose between public and private networking setups, allowing for diverse connectivity options that cater to different requirements. This flexibility ensures that businesses can adapt the service to meet their specific operational needs efficiently.

Red Hat AMQ serves as a versatile messaging platform that ensures reliable information delivery, fostering real-time integration and enabling connectivity for the Internet of Things (IoT). Built on the foundations of open source projects such as Apache ActiveMQ and Apache Kafka, it accommodates a range of messaging patterns, allowing for the swift and effective integration of applications, endpoints, and devices, which ultimately boosts enterprise agility and responsiveness. With the ability to facilitate high-throughput and low-latency data sharing among microservices and other applications, AMQ significantly enhances operational efficiency. Furthermore, it offers connectivity options for client programs developed in various programming languages, ensuring broad compatibility. The platform also establishes an open-wire protocol for messaging interoperability, which permits businesses to implement diverse distributed messaging solutions tailored to their changing needs. Supported by the award-winning services of Red Hat, AMQ is recognized for its ability to underpin mission-critical applications, reinforcing its value in enterprise environments. Additionally, its adaptability makes it an ideal choice for organizations aiming to stay ahead in a rapidly evolving digital landscape.

Everyware Cloud (EC) is an Internet of Things (IoT) integration platform developed and maintained by Eurotech. Built on the foundation of Eclipse Kapua, Everyware Cloud features a flexible and open IoT cloud platform that utilizes a microservices architecture. It facilitates comprehensive device management, diagnostics, provisioning, remote access to IoT gateways and devices, as well as integration services for telemetry data. By enabling remote access, users can conduct maintenance and troubleshoot issues without the need for physical visits to the installation site. You can rely on your remote devices thanks to the robust enterprise-level security measures embedded within the Everyware Cloud IoT Platform. Additionally, the platform helps lower integration costs through the use of standard-based interfaces. Device connectivity is supported by the ISO-certified MQTT protocol and employs an open, language-independent data payload format. This ensures seamless communication and data exchange across diverse devices and applications. Overall, Everyware Cloud stands out as a comprehensive solution for managing IoT ecosystems efficiently and securely.

Experience a robust infrastructure for deploying and managing devices, all hosted by balena. Simply create your image, power it on, and watch as your fully set-up device appears seamlessly in your application. For quicker startup times, preload your image with your application code. Develop at web speed using tools you're already accustomed to. You have the flexibility to build your application in any language and distribution that suits your needs. Work locally for rapid feedback and make updates with a single command, ensuring your devices stay online and operational. If you're utilizing a microservices architecture, we fully support multi-container applications. Enjoy comprehensive insights into your devices' real-time status and activities. You can efficiently organize your fleet using tags and filters, and remotely configure and troubleshoot each device as needed. This streamlined approach not only saves time but also enhances overall efficiency.

We know how simple Apache Kafka®, can be when you have the right tools. kPow was created to simplify the Kafka development experience and save businesses time and money. kPow makes it easy to find the root cause of production problems in a matter of clicks and not hours. With kPow's Data Inspect and kREPL functions, you can search tens of thousands messages per second. Are you new to Kafka kPow's Kafka UI is unique and allows developers to quickly understand the core Kafka concepts. You can upskill new members of your team and increase your Kafka knowledge. kPow offers a range of Kafka management features and monitoring capabilities in a single Docker Container. You can manage multiple clusters and schema registries. Connect installs with one instance.

Concentrate on creating applications for processing data streams instead of spending time on infrastructure upkeep. The Managed Service for Apache Kafka takes care of Zookeeper brokers and clusters, handling tasks such as configuring the clusters and performing version updates. To achieve the desired level of fault tolerance, distribute your cluster brokers across multiple availability zones and set an appropriate replication factor. This service continuously monitors the metrics and health of the cluster, automatically replacing any node that fails to ensure uninterrupted service. You can customize various settings for each topic, including the replication factor, log cleanup policy, compression type, and maximum message count, optimizing the use of computing, network, and disk resources. Additionally, enhancing your cluster's performance is as simple as clicking a button to add more brokers, and you can adjust the high-availability hosts without downtime or data loss, allowing for seamless scalability. By utilizing this service, you can ensure that your applications remain efficient and resilient amidst any unforeseen challenges.

Axual provides a Kafka-as-a-Service tailored for DevOps teams, empowering them to extract insights and make informed decisions through our user-friendly Kafka platform. For enterprises seeking to effortlessly incorporate data streaming into their essential IT frameworks, Axual presents the perfect solution. Our comprehensive Kafka platform is crafted to remove the necessity for deep technical expertise, offering a ready-made service that allows users to enjoy the advantages of event streaming without complications. The Axual Platform serves as an all-encompassing solution, aimed at simplifying and improving the deployment, management, and use of real-time data streaming with Apache Kafka. With a robust suite of features designed to meet the varied demands of contemporary businesses, the Axual Platform empowers organizations to fully leverage the capabilities of data streaming while reducing complexity and minimizing operational burdens. Additionally, our platform ensures that your team can focus on innovation rather than getting bogged down by technical challenges.

WarpStream serves as a data streaming platform that is fully compatible with Apache Kafka, leveraging object storage to eliminate inter-AZ networking expenses and disk management, while offering infinite scalability within your VPC. The deployment of WarpStream occurs through a stateless, auto-scaling agent binary, which operates without the need for local disk management. This innovative approach allows agents to stream data directly to and from object storage, bypassing local disk buffering and avoiding any data tiering challenges. Users can instantly create new “virtual clusters” through our control plane, accommodating various environments, teams, or projects without the hassle of dedicated infrastructure. With its seamless protocol compatibility with Apache Kafka, WarpStream allows you to continue using your preferred tools and software without any need for application rewrites or proprietary SDKs. By simply updating the URL in your Kafka client library, you can begin streaming immediately, ensuring that you never have to compromise between reliability and cost-effectiveness again. Additionally, this flexibility fosters an environment where innovation can thrive without the constraints of traditional infrastructure.

Davra IoT empowers businesses, fleet operators, original equipment manufacturers (OEMs), municipalities, and various organizations to conceptualize, develop, and swiftly launch industrial-grade IoT applications on a dependable, secure, and scalable platform. Bring your IoT initiative to market in under 50 days, and enjoy a system that prioritizes integrations. Significantly cut your project costs by as much as 80%, while accessing comprehensive analytics that include descriptive, diagnostic, predictive, and prescriptive insights. Utilize our cloud-based streaming analytics alongside machine learning, natural language processing, and artificial intelligence capabilities directly at the network's edge. Benefit from HTML5 dashboard visualizations, sophisticated geo-mapping, and an intuitive layout manager, among other features. Gain access to a thorough developer suite that includes source control, versioning, and a full code editor. Achieve an "asset-centric view" of your IoT devices by incorporating both static and dynamic attributes into your applications. Additionally, take advantage of a fully microservice-oriented design that supports infrastructure libraries and runtime engines for enhanced efficiency and performance. This comprehensive approach ensures that your IoT solutions are not only functional but also adaptable to future technological advancements.

The Streaming service is a real-time, serverless platform for event streaming that is compatible with Apache Kafka, designed specifically for developers and data scientists. It is seamlessly integrated with Oracle Cloud Infrastructure (OCI), Database, GoldenGate, and Integration Cloud. Furthermore, the service offers ready-made integrations with numerous third-party products spanning various categories, including DevOps, databases, big data, and SaaS applications. Data engineers can effortlessly establish and manage extensive big data pipelines. Oracle takes care of all aspects of infrastructure and platform management for event streaming, which encompasses provisioning, scaling, and applying security updates. Additionally, by utilizing consumer groups, Streaming effectively manages state for thousands of consumers, making it easier for developers to create applications that can scale efficiently. This comprehensive approach not only streamlines the development process but also enhances overall operational efficiency.

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.

Keen is a fully managed event streaming platform. Our real-time data pipeline, built on Apache Kafka, makes it easy to collect large amounts of event data. Keen's powerful REST APIs and SDKs allow you to collect event data from any device connected to the internet. Our platform makes it possible to securely store your data, reducing operational and delivery risks with Keen. Apache Cassandra's storage infrastructure ensures data is completely secure by transferring it via HTTPS and TLS. The data is then stored with multilayer AES encryption. Access Keys allow you to present data in an arbitrary way without having to re-architect or re-architect the data model. Role-based Access Control allows for completely customizable permission levels, down to specific queries or data points.

Apache APISIX boasts a comprehensive suite of traffic management capabilities, including Load Balancing, Dynamic Upstream, Canary Release, Circuit Breaking, Authentication, and Observability. This open-source API Gateway is designed to effectively manage microservices, ensuring optimal performance, enhanced security, and a scalable infrastructure for all your APIs and microservices. Notably, Apache APISIX is the pioneering open-source API Gateway equipped with an integrated low-code Dashboard, offering a robust and adaptable user interface tailored for developers. The Dashboard simplifies the operation of Apache APISIX through an intuitive frontend, making it accessible for users. As an open-source project, it is continually evolving, and contributions are always welcome. Furthermore, the Apache APISIX Dashboard is highly responsive to user needs, allowing the creation of custom modules to meet specific requirements while still providing a comprehensive no-code toolchain. This adaptability ensures that users can enhance their experience while working with the platform.

Qubitro facilitates teamwork on device data and contemporary application creation. It imposes no restrictions on data ingestion or extraction, ensuring they do not impact overall usage. With built-in support for widely-used data sources, Qubitro also offers tools for seamless real-time collaboration on your initiatives alongside scalable infrastructure. To utilize Qubitro effectively, one must establish a project that organizes various data sources and platform functionalities. Additionally, enhance your startup's offerings through effective event planning and strategic marketing efforts. By leveraging these features, Qubitro empowers teams to innovate and expand their projects efficiently.

An open-source, comprehensive microservice framework offers high performance right out of the box, ensuring compatibility with widely used ecosystems and supporting multiple programming languages. It guarantees service contracts via OpenAPI and features one-click scaffolding to expedite the development of microservice applications. This solution enables the ecological extension for various programming languages, including Java, Golang, PHP, and NodeJS. Apache ServiceComb serves as a robust open-source microservices framework, comprising several components that can be tailored to diverse scenarios through strategic combinations. This guide is designed to help newcomers swiftly get acquainted with Apache ServiceComb, making it an ideal starting point for beginners. Additionally, the framework allows for a separation between programming and communication models, enabling developers to integrate any desired communication model as needed. Consequently, application developers can prioritize API development while effortlessly adapting their communication strategies during deployment. With this flexibility, the framework enhances productivity and streamlines the microservice application lifecycle.

EMR serves as a comprehensive enterprise-grade big data platform, offering cluster, job, and data management functionalities that leverage various open-source technologies, including Hadoop, Spark, Kafka, Flink, and Storm. Alibaba Cloud Elastic MapReduce (EMR) is specifically designed for big data processing within the Alibaba Cloud ecosystem. Built on Alibaba Cloud's ECS instances, EMR integrates the capabilities of open-source Apache Hadoop and Apache Spark. This platform enables users to utilize components from the Hadoop and Spark ecosystems, such as Apache Hive, Apache Kafka, Flink, Druid, and TensorFlow, for effective data analysis and processing. Users can seamlessly process data stored across multiple Alibaba Cloud storage solutions, including Object Storage Service (OSS), Log Service (SLS), and Relational Database Service (RDS). EMR also simplifies cluster creation, allowing users to establish clusters rapidly without the hassle of hardware and software configuration. Additionally, all maintenance tasks can be managed efficiently through its user-friendly web interface, making it accessible for various users regardless of their technical expertise.

Samza enables the development of stateful applications that can handle real-time data processing from various origins, such as Apache Kafka. Proven to perform effectively at scale, it offers versatile deployment choices, allowing execution on YARN or as an independent library. With the capability to deliver remarkably low latencies and high throughput, Samza provides instantaneous data analysis. It can manage multiple terabytes of state through features like incremental checkpoints and host-affinity, ensuring efficient data handling. Additionally, Samza's operational simplicity is enhanced by its deployment flexibility—whether on YARN, Kubernetes, or in standalone mode. Users can leverage the same codebase to seamlessly process both batch and streaming data, which streamlines development efforts. Furthermore, Samza integrates with a wide range of data sources, including Kafka, HDFS, AWS Kinesis, Azure Event Hubs, key-value stores, and ElasticSearch, making it a highly adaptable tool for modern data processing needs.

The engineering team at Altinity possesses extensive expertise, enabling them to implement a wide range of functionalities from essential ClickHouse features to the behavior of Kubernetes operators and enhancements for client libraries. They offer a versatile, docker-based GUI manager for ClickHouse that enables users to install clusters, manage nodes through addition, deletion, or replacement, monitor the status of clusters, and assist with troubleshooting and diagnostics. Additionally, they support various third-party tools and software integrations, including ingestion tools like Kafka and ClickTail, APIs for Python, Golang, ODBC, and Java, as well as compatibility with Kubernetes. UI tools such as Grafana, Superset, Tabix, and Graphite are also part of their ecosystem, along with database integrations for MySQL and PostgreSQL, and business intelligence tools like Tableau and many others. Altinity.Cloud draws upon its extensive experience gained from assisting numerous clients in managing ClickHouse-based analytics, ensuring it meets diverse needs. Built on a Kubernetes-based architecture, Altinity.Cloud offers both portability and flexibility regarding deployment options, allowing users to operate without fear of vendor lock-in. Recognizing that effective cost management is vital for SaaS companies, Altinity prioritizes this aspect in its offerings to support sustainable growth.

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, Apache Druid, 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.

Nutanix's Karbon Platform Services (KPS) is a multicloud Platform-as-a-Service (PaaS) built on Kubernetes, aimed at expediting the creation and deployment of applications that are based on microservices across various cloud environments. The platform boasts an extensive array of managed services, such as Container-as-a-Service for Kubernetes applications, Functions-as-a-Service for serverless functions, global data pipelines, and streaming services including Kafka-aaS and NATS-aaS. It also provides AI services like Tensorflow-aaS and Openvino-aaS, along with ingress controllers and service mesh solutions (nginx/traefik-aaS and Istio-aaS), application monitoring and alerting through Prometheus-aaS, and log forwarding capabilities. KPS streamlines multicloud operations with a SaaS model that enhances operational efficiency and ensures consistent management of applications, data, and security across different cloud platforms. This allows developers the convenience of writing their applications a single time and deploying them seamlessly across any cloud environment, simplifying the entire application lifecycle. Furthermore, KPS empowers organizations to focus on innovation while minimizing the complexity of cloud management.

The Baidu Messaging System (BMS) serves as a scalable and distributed message queue service renowned for its impressive throughput capabilities. It gathers extensive data from various sources such as websites, devices, and applications, allowing for immediate analysis of activities like user browsing behavior, clicks, and search queries. Built on the foundation of Apache Kafka, BMS leverages this robust, distributed, multi-partitioned, and multi-replica messaging platform. Producers and consumers communicate asynchronously through the message queue, enabling them to operate independently without waiting for one another. Unlike conventional messaging services, BMS simplifies the complexities of managing a Kafka cluster by offering it as a hosted solution. This means users can seamlessly integrate BMS with widely distributed applications without needing to manage cluster operations, paying only for what they use. Consequently, BMS provides an efficient and user-friendly approach to handling messaging needs in modern distributed systems.

IBM Event Streams is a comprehensive event streaming service based on Apache Kafka, aimed at assisting businesses in managing and reacting to real-time data flows. It offers features such as machine learning integration, high availability, and secure deployment in the cloud, empowering organizations to develop smart applications that respond to events in real time. The platform is designed to accommodate multi-cloud infrastructures, disaster recovery options, and geo-replication, making it particularly suitable for critical operational tasks. By facilitating the construction and scaling of real-time, event-driven solutions, IBM Event Streams ensures that data is processed with speed and efficiency, ultimately enhancing business agility and responsiveness. As a result, organizations can harness the power of real-time data to drive innovation and improve decision-making processes.

Microservices, containers, and Kubernetes empower applications to operate independently from the underlying infrastructure, allowing them to be deployed across various environments. Utilizing VMware Tanzu enables organizations to fully leverage these cloud-native architectures, streamlining the deployment of containerized applications while facilitating proactive management in live environments. The primary goal is to liberate developers, allowing them to focus on creating exceptional applications. Integrating Kubernetes into your existing infrastructure doesn't necessarily complicate matters; with VMware Tanzu, you can prepare your infrastructure for contemporary applications by implementing consistent and compliant Kubernetes across all environments. This approach not only provides a self-service and compliant experience for developers, smoothing their transition to production, but also allows for centralized management, governance, and monitoring of all clusters and applications across multiple cloud platforms. Ultimately, it simplifies the entire process, making it more efficient and effective. By embracing these strategies, organizations can enhance their operational capabilities significantly.

JHipster serves as a comprehensive development platform designed for the rapid creation, development, and deployment of contemporary web applications and microservice architectures. It accommodates a variety of frontend technologies, such as Angular, React, and Vue, and also extends support to mobile applications using Ionic and React Native. On the backend, JHipster offers compatibility with Spring Boot (utilizing either Java or Kotlin), Micronaut, Quarkus, Node.js, and .NET frameworks. When it comes to deployment, the platform adheres to cloud-native principles via Docker and Kubernetes, providing deployment options for various environments including AWS, Azure, Cloud Foundry, Google Cloud Platform, Heroku, and OpenShift. The primary objective is to produce a comprehensive and modern web application or microservice architecture equipped with a high-performance and resilient server-side stack, showcasing excellent test coverage. The user interface is designed to be sleek, modern, and mobile-first, utilizing Angular, React, or Vue along with Bootstrap for styling. Moreover, the platform incorporates a powerful workflow for application building through tools like Webpack and Maven or Gradle, ensuring a resilient microservice architecture that remains focused on cloud-native methodologies. This holistic approach ensures that developers have all the resources they need to create scalable and efficient applications.

The Apprenda Cloud Platform (ACP) equips enterprise IT with the ability to establish a Kubernetes-enabled shared service across various infrastructures, making it accessible for developers throughout different business units. This platform is designed to support the entirety of your custom application portfolio. It facilitates the swift creation, deployment, operation, and management of cloud-native, microservices, and container-based .NET and Java applications, while also allowing for the modernization of legacy workloads. ACP empowers developers with self-service access to essential tools for quick application development, all while providing IT operators with an effortless way to orchestrate environments and workflows. As a result, enterprise IT transitions into a genuine service provider role. ACP serves as a unified platform that integrates seamlessly across multiple data centers and cloud environments. Whether deployed on-premise or utilized as a managed service in the public cloud, it guarantees complete independence of infrastructure. Additionally, ACP offers policy-driven governance over the infrastructure usage and DevOps processes related to all application workloads, ensuring efficiency and compliance. This level of control not only maximizes resource utilization but also enhances collaboration between development and operations teams.

HyScale transforms agile teams' ability to deploy software to modern IT infrastructures powered with cloud, containers, and Kubernetes. It is open-source and vendor-neutral. Containerized and created apps for a microservice-based platform that minimizes delays in application delivery. A leading UK insurance company needed to migrate monolithic apps from the UK to K8s and set up a self service process in a matter of weeks. Automated CI/CD pipeline for a US-based transport management company. You should be focusing on your app and quickly implement any changes. Continuously deliver microservices via Kubernetes using self-service DevOps. Deliver apps to Kubernetes that run on multi-cloud environments. Streamline your workflow with left-shifted security and gain visibility over container sprawl.

M3 stands out as the ideal selection for Cloud Native enterprises that aim to enhance their Prometheus-based monitoring frameworks. Serving as a Prometheus Remote Storage solution, M3 boasts complete compatibility with PromQL, ensuring seamless integration. Initially created at Uber, M3 was designed to offer comprehensive insights into the company's operations, microservices, and infrastructure. Its remarkable capability to scale horizontally allows M3 to function as a unified storage solution for diverse monitoring scenarios. The system maintains data integrity through three replicas and employs quorum reads and writes for consistency. M3 has demonstrated its effectiveness in production environments, managing to ingest over one billion data points every second and facilitating more than two billion data point reads in the same timeframe. Additionally, it is open-sourced under the Apache 2 license and is supported by a vibrant and engaged community, which contributes to its ongoing development and improvement. This makes M3 not just a robust solution, but also a collaborative effort that continues to evolve.

TEM actively supports the Spring Cloud open source community and functions as a robust, scalable, and adaptable commercial platform for microservice technology based on components. This platform facilitates a seamless transition of Spring Cloud applications to an elastic microservice architecture without necessitating changes to the code, thereby significantly cutting down on both migration duration and operational expenses. TEM provides comprehensive application hosting services that oversee the complete lifecycle of cloud-native microservice applications. By leveraging TEM, users can easily create, deploy, scale, halt, deactivate, and monitor applications efficiently and securely, all while avoiding the complexities of underlying infrastructure management. Furthermore, TEM allows businesses to transition to the cloud effortlessly and swiftly, maintaining the integrity of their original code, which minimizes the learning curve, drastically lowers operational costs, and enhances overall business performance. In this way, TEM positions itself as a valuable ally for organizations looking to innovate and streamline their cloud operations.

The Wia IoT Cloud offers a secure platform and APIs designed for businesses and engineers to develop, connect, and implement Internet of Things solutions on a large scale. We manage fleet operations, allocate resources, ingest sensor data, integrate devices, automate processes, conduct real-time analyses, and provide rich visualizations, all consolidated in a single platform. By utilizing real-time data, organizations can analyze their energy usage, control consumption, lower expenses, and enhance operational effectiveness. This innovative approach enables companies to monitor electricity consumption throughout a building or an entire campus, granting access to scalable, secure, and cost-effective real-time energy data that supports efficiency and sustainability initiatives. Rather than waiting for utility bills, organizations can track their usage minute by minute, allowing them to respond promptly and implement necessary changes to optimize energy consumption. This proactive energy management can significantly contribute to a company’s overall sustainability efforts and operational excellence.

Equalum offers a unique continuous data integration and streaming platform that seamlessly accommodates real-time, batch, and ETL scenarios within a single, cohesive interface that requires no coding at all. Transition to real-time capabilities with an intuitive, fully orchestrated drag-and-drop user interface designed for ease of use. Enjoy the benefits of swift deployment, powerful data transformations, and scalable streaming data pipelines, all achievable in just minutes. With a multi-modal and robust change data capture (CDC) system, it enables efficient real-time streaming and data replication across various sources. Its design is optimized for exceptional performance regardless of the data origin, providing the advantages of open-source big data frameworks without the usual complexities. By leveraging the scalability inherent in open-source data technologies like Apache Spark and Kafka, Equalum's platform engine significantly enhances the efficiency of both streaming and batch data operations. This cutting-edge infrastructure empowers organizations to handle larger data volumes while enhancing performance and reducing the impact on their systems, ultimately facilitating better decision-making and quicker insights. Embrace the future of data integration with a solution that not only meets current demands but also adapts to evolving data challenges.

Introducing a versatile, open-source multi-cloud platform for contemporary data applications, built on Apache Cassandra™. Achieve global-scale performance with guaranteed 100% uptime while avoiding vendor lock-in. You have the flexibility to deploy on multi-cloud environments, on-premises infrastructures, or use Kubernetes. The platform is designed to be elastic and offers a pay-as-you-go pricing model to enhance total cost of ownership. Accelerate your development process with Stargate APIs, which support NoSQL, real-time interactions, reactive programming, as well as JSON, REST, and GraphQL formats. Bypass the difficulties associated with managing numerous open-source projects and APIs that lack scalability. This solution is perfect for various sectors including e-commerce, mobile applications, AI/ML, IoT, microservices, social networking, gaming, and other highly interactive applications that require dynamic scaling based on demand. Start your journey of creating modern data applications with Astra, a database-as-a-service powered by Apache Cassandra™. Leverage REST, GraphQL, and JSON alongside your preferred full-stack framework. This platform ensures that your richly interactive applications are not only elastic but also ready to gain traction from the very first day, all while offering a cost-effective Apache Cassandra DBaaS that scales seamlessly and affordably as your needs evolve. With this innovative approach, developers can focus on building rather than managing infrastructure.

Microservices architecture enables efficient streaming and batch data processing specifically designed for platforms like Cloud Foundry and Kubernetes. By utilizing Spring Cloud Data Flow, users can effectively design intricate topologies for their data pipelines, which feature Spring Boot applications developed with the Spring Cloud Stream or Spring Cloud Task frameworks. This powerful tool caters to a variety of data processing needs, encompassing areas such as ETL, data import/export, event streaming, and predictive analytics. The Spring Cloud Data Flow server leverages Spring Cloud Deployer to facilitate the deployment of these data pipelines, which consist of Spring Cloud Stream or Spring Cloud Task applications, onto contemporary infrastructures like Cloud Foundry and Kubernetes. Additionally, a curated selection of pre-built starter applications for streaming and batch tasks supports diverse data integration and processing scenarios, aiding users in their learning and experimentation endeavors. Furthermore, developers have the flexibility to create custom stream and task applications tailored to specific middleware or data services, all while adhering to the user-friendly Spring Boot programming model. This adaptability makes Spring Cloud Data Flow a valuable asset for organizations looking to optimize their data workflows.

Macaw serves as an advanced enterprise platform specifically designed to create and enhance applications suited for the digital era. It introduces a distinctive method for upgrading legacy applications, enabling them to leverage containerization and microservices technologies effectively. Additionally, Macaw presents a comprehensive solution that aids enterprises in the design, development, publication, execution, and management of microservices-based applications, all while remaining agnostic to the underlying infrastructure and cloud environments. This platform is ideal for organizations eager to expedite their modernization efforts through a hybrid-cloud approach and the adoption of cloud-native applications. With its array of integrated foundational services, operational features, and seamless Kubernetes integration, Macaw equips users with the essential runtime environment, tools, and services necessary for building, deploying, and overseeing microservices applications. Furthermore, it boasts a variety of core application services that are readily available, including database management, security protocols, messaging systems, and load balancing, facilitating quicker development cycles and streamlined operations. Ultimately, Macaw stands out as a versatile solution for enterprises aiming to thrive in a rapidly evolving technological landscape.

AWS IoT Greengrass effectively brings the capabilities of AWS to edge devices, enabling them to locally process the data they create while still leveraging the cloud for management, analysis, and reliable storage solutions. This platform allows connected devices to execute AWS Lambda functions, run Docker containers, or utilize both, enabling real-time predictions based on machine learning models, maintaining data synchronization, and ensuring secure communication among devices—even in the absence of an internet connection. With AWS IoT Greengrass, developers can utilize familiar programming languages and models to design and validate their device applications in the cloud before deploying them to the actual devices. Furthermore, this service can be configured to filter and manage device data, ensuring only essential information is sent back to AWS. Additionally, AWS IoT Greengrass offers seamless integration with third-party applications, local software solutions, and a range of AWS services through its Connectors, enhancing the overall functionality and versatility of edge computing. By incorporating these features, AWS IoT Greengrass empowers businesses to maximize the potential of their connected devices while maintaining operational efficiency.