Alternatives to Nextflow

Fully managed compute platform to deploy and scale containerized applications securely and quickly. You can write code in your favorite languages, including Go, Python, Java Ruby, Node.js and other languages. For a simple developer experience, we abstract away all infrastructure management. It is built upon the open standard Knative which allows for portability of your applications. You can write code the way you want by deploying any container that listens to events or requests. You can create applications in your preferred language with your favorite dependencies, tools, and deploy them within seconds. Cloud Run abstracts away all infrastructure management by automatically scaling up and down from zero almost instantaneously--depending on traffic. Cloud Run only charges for the resources you use. Cloud Run makes app development and deployment easier and more efficient. Cloud Run is fully integrated with Cloud Code and Cloud Build, Cloud Monitoring and Cloud Logging to provide a better developer experience.

Rivery’s ETL platform consolidates, transforms, and manages all of a company’s internal and external data sources in the cloud. Key Features: Pre-built Data Models: Rivery comes with an extensive library of pre-built data models that enable data teams to instantly create powerful data pipelines. Fully managed: A no-code, auto-scalable, and hassle-free platform. Rivery takes care of the back end, allowing teams to spend time on mission-critical priorities rather than maintenance. Multiple Environments: Rivery enables teams to construct and clone custom environments for specific teams or projects. Reverse ETL: Allows companies to automatically send data from cloud warehouses to business applications, marketing clouds, CPD’s, and more.

Portainer Business makes managing containers easy. It is designed to be deployed from the data centre to the edge and works with Docker, Swarm and Kubernetes. It is trusted by more than 500K users. With its super-simple GUI and its comprehensive Kube-compatible API, Portainer Business makes it easy for anyone to deploy and manage container-based applications, triage container-related issues, set up automate Git-based workflows and build CaaS environments that end users love to use. Portainer Business works with all K8s distros and can be deployed on prem and/or in the cloud. It is designed to be used in team environments where there are multiple users and multiple clusters. The product incorporates a range of security features - including RBAC, OAuth integration and logging, which makes it suitable for use in large, complex production environments. For platform managers responsible for delivering a self-service CaaS environment, Portainer includes a suite of features that help control what users can / can't do and significantly reduces the risks associated with running containers in prod. Portainer Business is fully supported and includes a comprehensive onboarding experience that ensures you get up and running.

Amazon Elastic Kubernetes Service (EKS) is a comprehensive Kubernetes management solution that operates entirely under AWS's management. High-profile clients like Intel, Snap, Intuit, GoDaddy, and Autodesk rely on EKS to host their most critical applications, benefiting from its robust security, dependability, and ability to scale efficiently. EKS stands out as the premier platform for running Kubernetes for multiple reasons. One key advantage is the option to deploy EKS clusters using AWS Fargate, which offers serverless computing tailored for containers. This feature eliminates the need to handle server provisioning and management, allows users to allocate and pay for resources on an application-by-application basis, and enhances security through inherent application isolation. Furthermore, EKS seamlessly integrates with various Amazon services, including CloudWatch, Auto Scaling Groups, IAM, and VPC, ensuring an effortless experience for monitoring, scaling, and load balancing applications. This level of integration simplifies operations, enabling developers to focus more on building their applications rather than managing infrastructure.

Amazon Elastic Container Service (ECS) is a comprehensive container orchestration platform that is fully managed. Notable clients like Duolingo, Samsung, GE, and Cook Pad rely on ECS to operate their critical applications due to its robust security, dependability, and ability to scale. There are multiple advantages to utilizing ECS for container management. For one, users can deploy their ECS clusters using AWS Fargate, which provides serverless computing specifically designed for containerized applications. By leveraging Fargate, customers eliminate the need for server provisioning and management, allowing them to allocate costs based on their application's resource needs while enhancing security through inherent application isolation. Additionally, ECS plays a vital role in Amazon’s own infrastructure, powering essential services such as Amazon SageMaker, AWS Batch, Amazon Lex, and the recommendation system for Amazon.com, which demonstrates ECS’s extensive testing and reliability in terms of security and availability. This makes ECS not only a practical option but a proven choice for organizations looking to optimize their container operations efficiently.

Airflow is a community-driven platform designed for the programmatic creation, scheduling, and monitoring of workflows. It features a flexible architecture and employs a message queue to manage a potentially unlimited number of workers. With its capability to scale infinitely, Airflow pipelines are crafted using Python, which enables the dynamic creation of these workflows. This dynamic pipeline generation empowers developers to write code that can instantiate workflows on the fly. You have the ability to easily define custom operators and enhance libraries to meet the specific abstraction level required for your setting. The design of Airflow pipelines is straightforward and clear, incorporating core parametrization through the advanced Jinja templating engine. Gone are the days of obscure command-line instructions or convoluted XML configurations! Airflow allows the use of standard Python features for workflow creation, such as date and time formatting for scheduling and loops for generating tasks dynamically. This ensures that you maintain maximum flexibility while constructing your workflows. Moreover, this adaptability makes Airflow an excellent choice for diverse use cases across various industries.

Kubernetes (K8s) is a powerful open-source platform designed to automate the deployment, scaling, and management of applications that are containerized. By organizing containers into manageable groups, it simplifies the processes of application management and discovery. Drawing from over 15 years of experience in handling production workloads at Google, Kubernetes also incorporates the best practices and innovative ideas from the wider community. Built on the same foundational principles that enable Google to efficiently manage billions of containers weekly, it allows for scaling without necessitating an increase in operational personnel. Whether you are developing locally or operating a large-scale enterprise, Kubernetes adapts to your needs, providing reliable and seamless application delivery regardless of complexity. Moreover, being open-source, Kubernetes offers the flexibility to leverage on-premises, hybrid, or public cloud environments, facilitating easy migration of workloads to the most suitable infrastructure. This adaptability not only enhances operational efficiency but also empowers organizations to respond swiftly to changing demands in their environments.

Conductor serves as a cloud-based workflow orchestration engine designed to assist Netflix in managing process flows that rely on microservices. It boasts a number of key features, including an efficient distributed server ecosystem that maintains workflow state information. Users can create business processes where individual tasks may be handled by either the same or different microservices. The system utilizes a Directed Acyclic Graph (DAG) for workflow definitions, ensuring that these definitions remain separate from the actual service implementations. It also offers enhanced visibility and traceability for the various process flows involved. A user-friendly interface facilitates the connection of workers responsible for executing tasks within these workflows. Notably, workers are language-agnostic, meaning each microservice can be developed in the programming language best suited for its purposes. Conductor grants users total operational control over workflows, allowing them to pause, resume, restart, retry, or terminate processes as needed. Ultimately, it promotes the reuse of existing microservices, making the onboarding process significantly more straightforward and efficient for developers.

Harpoon is an intuitive drag-and-drop tool designed for Kubernetes that allows users to deploy software within seconds. Whether you are just starting your journey with Kubernetes or seeking an efficient way to master it, Harpoon equips you with all the necessary features for effective deployment and configuration of your applications using this leading container orchestration platform, all without writing any code. The platform's visual interface makes it accessible for anyone to launch production-ready software effortlessly. You can easily manage simple or advanced enterprise-level cloud deployments, enabling you to deploy and configure software while autoscaling Kubernetes without the need for code or configuration scripts. With a single click, you can swiftly search for and find any commercial or open-source software available and deploy it to the cloud. Moreover, before launching any applications or services, Harpoon conducts automated security scripts to safeguard your cloud provider account. You can seamlessly connect Harpoon to your source code repository from anywhere and establish an automated deployment pipeline, ensuring a smooth development workflow. This streamlined process not only saves time but also enhances productivity, making Harpoon an essential tool for developers.

Tenzir is a business located in 2017 in Germany that's known for a software product called Tenzir. Tenzir includes training via documentation and live online. Tenzir is SaaS software. Tenzir includes online support. Tenzir is a type of data pipeline software. Alternative software products to Tenzir are Onum, VirtualMetric, and Crux.

Leverage Reactive Programming on the back-end without the hassle of using specialized languages or complex frameworks. With the help of Triggers, Actors, and Event Collections, it becomes straightforward to create data pipelines and manage data streams through an intuitive SQL-like syntax, effectively simplifying the challenges associated with distributed system development. A standout aspect is the Extensible Data Modeling feature, which enables rich semantics and schema definitions to accurately represent real-world entities. The implementation of on-the-fly validation and data shaping rules accommodates various formats, including XML and JSON, making it effortless to articulate and adapt your schema in line with evolving business needs. If you can articulate it, we have the capability to query it. If you're familiar with SQL and JavaScript, you're already equipped to navigate the data engine. No matter the format, a robust query language allows for immediate testing of logic expressions and functions, which accelerates development and streamlines deployment, resulting in exceptional data agility and responsiveness to changing circumstances. This adaptability not only enhances productivity but also fosters innovation within teams.

Mesos operates on principles similar to those of the Linux kernel, but it functions at a higher level of abstraction. Its kernel is deployed across all machines, facilitating applications such as Hadoop, Spark, Kafka, and Elasticsearch by offering APIs that manage resources and schedules throughout entire data centers and cloud infrastructures. Additionally, Mesos includes native capabilities for launching containers using Docker and AppC images. It enables both cloud-native and legacy applications to run within the same cluster while allowing for customizable scheduling policies. Users benefit from HTTP APIs designed for the development of new distributed applications, as well as tools for cluster management and monitoring. Furthermore, there is a built-in Web UI that allows users to observe the state of the cluster and navigate through container sandboxes, enhancing overall operability and visibility. This comprehensive approach makes Mesos a versatile option for managing complex application deployments effectively.

JFrog Pipelines enables software development teams to accelerate the delivery of updates by automating their DevOps workflows in a secure and efficient manner across all tools and teams involved. It incorporates functions such as continuous integration (CI), continuous delivery (CD), and infrastructure management, automating the entire journey from code development to production deployment. This solution is seamlessly integrated with the JFrog Platform and is offered in both cloud-based and on-premises subscription models. It can scale horizontally, providing a centralized management system capable of handling thousands of users and pipelines within a high-availability (HA) setup. With pre-built declarative steps that require no scripting, users can easily construct intricate pipelines, including those that link multiple teams together. Furthermore, it works in conjunction with a wide array of DevOps tools, and the various steps within a single pipeline can operate on diverse operating systems and architectures, thus minimizing the necessity for multiple CI/CD solutions. This versatility makes JFrog Pipelines a powerful asset for teams aiming to enhance their software delivery processes.

Our platform allows you create distributed coding and data science processes with contractors, freelancers, and developers located anywhere. They work on their own devices, while auditing your data and ensuring data security. Strong Network has created a multi-cloud platform we call Virtual Workspace Infrastructure. It allows companies to securely unify their access to their global data science and coding processes via a simple web browser. The VWI platform is an integral component of their DevSecOps process. It doesn't require integration with existing CI/CD pipelines. Process security is focused on data, code, and other critical resources. The platform automates the principles and implementation of Zero-Trust Architecture, protecting the most valuable IP assets of the company.

The Nebula container orchestrator is designed to empower developers and operations teams to manage IoT devices similarly to distributed Docker applications. Its primary goal is to serve as a Docker orchestrator not only for IoT devices but also for distributed services like CDN or edge computing, potentially spanning thousands or even millions of devices globally, all while being fully open-source and free to use. As an open-source initiative focused on Docker orchestration, Nebula efficiently manages extensive clusters by enabling each component of the project to scale according to demand. This innovative project facilitates the simultaneous updating of tens of thousands of IoT devices around the world with just a single API call, reinforcing its mission to treat IoT devices like their Dockerized counterparts. Furthermore, the versatility and scalability of Nebula make it a promising solution for the evolving landscape of IoT and distributed computing.

Introducing a self-service development platform tailored for your applications, databases, and various tasks. You can begin with a single workload and effortlessly expand to manage hundreds, utilizing either compute or GPUs. Enhance every phase from code push to production with customizable self-service workflows, pipelines, templates, and GitOps practices. Safely launch preview, staging, and production environments while benefiting from built-in observability tools, backups, restoration capabilities, and rollback options. Northflank integrates flawlessly with your preferred tools, supporting any technology stack you choose. Regardless of whether you operate on Northflank’s secure infrastructure or utilize your own cloud account, you will enjoy the same outstanding developer experience, alongside complete control over your data residency, deployment regions, security measures, and cloud costs. By harnessing Kubernetes as its operating system, Northflank provides the advantages of a cloud-native environment without the associated complexities. Whether you opt for Northflank’s straightforward cloud or connect to your GKE, EKS, AKS, or even bare-metal setups, you can achieve a managed platform experience within minutes, thus optimizing your development workflow. This flexibility ensures that your projects can scale efficiently while maintaining robust performance across diverse environments.

A versatile and straightforward workload orchestrator designed to deploy and oversee both containerized and non-containerized applications seamlessly across on-premises and cloud environments at scale. This efficient tool comes as a single 35MB binary that effortlessly fits into your existing infrastructure. It provides an easy operational experience whether on-prem or in the cloud, maintaining minimal overhead. Capable of orchestrating various types of applications—not limited to just containers—it offers top-notch support for Docker, Windows, Java, VMs, and more. By introducing orchestration advantages, it helps enhance existing services. Users can achieve zero downtime deployments, increased resilience, and improved resource utilization without the need for containerization. A single command allows for multi-region, multi-cloud federation, enabling global application deployment to any region using Nomad as a cohesive control plane. This results in a streamlined workflow for deploying applications to either bare metal or cloud environments. Additionally, Nomad facilitates the development of multi-cloud applications with remarkable ease and integrates smoothly with Terraform, Consul, and Vault for efficient provisioning, service networking, and secrets management, making it an indispensable tool in modern application management.

Test Kitchen serves as a testing framework that allows the execution of infrastructure code in a controlled environment across multiple platforms. It employs a driver plugin system to facilitate code execution on a variety of cloud services and virtualization options, including Vagrant, Amazon EC2, Microsoft Azure, Google Compute Engine, and Docker, among others. The tool comes pre-configured with support for several testing frameworks such as Chef InSpec, Serverspec, and Bats. In addition, it offers compatibility with Chef Infra workflows, allowing for cookbook dependency management through Berkshelf or Policyfiles, or even by simply including a cookbooks/ directory for automatic recognition. As a result, Test Kitchen is widely adopted by community cookbooks managed by Chef and has become the preferred tool for integration testing in the cookbook ecosystem. This widespread usage underscores its importance in ensuring that infrastructure code is robust and reliable across diverse environments.

Enhanced operators for enterprise applications feature a comprehensive application graph and declarative integration that caters to both Kubernetes environments and legacy systems. Through Juju operator integration, we can simplify each operator, enabling their composition to form intricate application graph topologies that handle complex scenarios while providing a user-friendly experience with significantly reduced YAML requirements. The UNIX principle of ‘doing one thing well’ is equally applicable in the realm of large-scale operational code, yielding similar advantages in clarity and reusability. The charm of small-scale design is evident here: Juju empowers organizations to implement the operator pattern across their entire infrastructure, including older applications. Model-driven operations lead to substantial savings in maintenance and operational expenses for traditional workloads, all without necessitating a shift to Kubernetes. Once integrated with Juju, legacy applications also gain the ability to operate across multiple cloud environments. Furthermore, the Juju Operator Lifecycle Manager (OLM) uniquely accommodates both containerized and machine-based applications, ensuring smooth interoperability between the two. This innovative approach allows for a more cohesive and efficient management of diverse application ecosystems.

GlassFlow is an innovative, serverless platform for building event-driven data pipelines, specifically tailored for developers working with Python. It allows users to create real-time data workflows without the complexities associated with traditional infrastructure solutions like Kafka or Flink. Developers can simply write Python functions to specify data transformations, while GlassFlow takes care of the infrastructure, providing benefits such as automatic scaling, low latency, and efficient data retention. The platform seamlessly integrates with a variety of data sources and destinations, including Google Pub/Sub, AWS Kinesis, and OpenAI, utilizing its Python SDK and managed connectors. With a low-code interface, users can rapidly set up and deploy their data pipelines in a matter of minutes. Additionally, GlassFlow includes functionalities such as serverless function execution, real-time API connections, as well as alerting and reprocessing features. This combination of capabilities makes GlassFlow an ideal choice for Python developers looking to streamline the development and management of event-driven data pipelines, ultimately enhancing their productivity and efficiency. As the data landscape continues to evolve, GlassFlow positions itself as a pivotal tool in simplifying data processing workflows.

Pliant offers a robust solution for IT Process Automation that simplifies, enhances, and secures the way teams create and implement automation. By minimizing human errors, ensuring compliance, and boosting overall efficiency, Pliant serves as an invaluable resource. Users can easily incorporate existing automation or develop new workflows through a unified orchestration interface. The platform provides reliable governance that maintains compliance through practical, built-in features. By abstracting thousands of vendor APIs, Pliant creates intelligent action blocks that empower users to simply drag and drop, eliminating the need for repetitive coding. Citizen developers can seamlessly construct effective and uniform automation across various platforms, services, and applications within minutes, thereby maximizing the value of their entire technology ecosystem from a single interface. Furthermore, with the capability to integrate new APIs in just 15 business days, Pliant ensures that any non-standard requirements will be addressed in a leading timeframe, keeping your automation capabilities up to date. This efficiency allows teams to remain agile and responsive in a rapidly changing technological landscape.

Dagster is the cloud-native open-source orchestrator for the whole development lifecycle, with integrated lineage and observability, a declarative programming model, and best-in-class testability. It is the platform of choice data teams responsible for the development, production, and observation of data assets. With Dagster, you can focus on running tasks, or you can identify the key assets you need to create using a declarative approach. Embrace CI/CD best practices from the get-go: build reusable components, spot data quality issues, and flag bugs early.

AWS Data Pipeline is a robust web service designed to facilitate the reliable processing and movement of data across various AWS compute and storage services, as well as from on-premises data sources, according to defined schedules. This service enables you to consistently access data in its storage location, perform large-scale transformations and processing, and seamlessly transfer the outcomes to AWS services like Amazon S3, Amazon RDS, Amazon DynamoDB, and Amazon EMR. With AWS Data Pipeline, you can effortlessly construct intricate data processing workflows that are resilient, repeatable, and highly available. You can rest assured knowing that you do not need to manage resource availability, address inter-task dependencies, handle transient failures or timeouts during individual tasks, or set up a failure notification system. Additionally, AWS Data Pipeline provides the capability to access and process data that was previously confined within on-premises data silos, expanding your data processing possibilities significantly. This service ultimately streamlines the data management process and enhances operational efficiency across your organization.

You determine the cluster size, node specifications, and a range of services, while Yandex Data Proc effortlessly sets up and configures Spark, Hadoop clusters, and additional components. Collaboration is enhanced through the use of Zeppelin notebooks and various web applications via a user interface proxy. You maintain complete control over your cluster with root access for every virtual machine. Moreover, you can install your own software and libraries on active clusters without needing to restart them. Yandex Data Proc employs instance groups to automatically adjust computing resources of compute subclusters in response to CPU usage metrics. Additionally, Data Proc facilitates the creation of managed Hive clusters, which helps minimize the risk of failures and data loss due to metadata issues. This service streamlines the process of constructing ETL pipelines and developing models, as well as managing other iterative operations. Furthermore, the Data Proc operator is natively integrated into Apache Airflow, allowing for seamless orchestration of data workflows. This means that users can leverage the full potential of their data processing capabilities with minimal overhead and maximum efficiency.

Kestra is a free, open-source orchestrator based on events that simplifies data operations while improving collaboration between engineers and users. Kestra brings Infrastructure as Code to data pipelines. This allows you to build reliable workflows with confidence. The declarative YAML interface allows anyone who wants to benefit from analytics to participate in the creation of the data pipeline. The UI automatically updates the YAML definition whenever you make changes to a work flow via the UI or an API call. The orchestration logic can be defined in code declaratively, even if certain workflow components are modified.

Metrolink offers a high-performance unified platform that seamlessly integrates with any existing infrastructure to facilitate effortless onboarding. Its user-friendly design empowers organizations to take control of their data integration processes, providing sophisticated manipulation tools that enhance the handling of diverse and complex data, redirect valuable human resources, and reduce unnecessary overhead. Organizations often struggle with an influx of complex, multi-source streaming data, leading to a misallocation of talent away from core business functions. With Metrolink, businesses can efficiently design and manage their data pipelines in accordance with their specific requirements. The platform features an intuitive user interface and advanced capabilities that maximize data value, ensuring that all data functions are optimized while maintaining stringent data privacy standards. This approach not only improves operational efficiency but also enhances the ability to adapt to rapidly evolving use cases in the data landscape.

The managed features of Cloud Composer, along with its compatibility with Apache Airflow, enable you to concentrate on crafting, scheduling, and overseeing your workflows rather than worrying about resource provisioning. Its seamless integration with various Google Cloud products such as BigQuery, Dataflow, Dataproc, Datastore, Cloud Storage, Pub/Sub, and AI Platform empowers users to orchestrate their data pipelines effectively. You can manage your workflows from a single orchestration tool, regardless of whether your pipeline operates on-premises, in multiple clouds, or entirely within Google Cloud. This solution simplifies your transition to the cloud and supports a hybrid data environment by allowing you to orchestrate workflows that span both on-premises setups and the public cloud. By creating workflows that interconnect data, processing, and services across different cloud platforms, you can establish a cohesive data ecosystem that enhances efficiency and collaboration. Additionally, this unified approach not only streamlines operations but also optimizes resource utilization across various environments.

Consolidate offline data, import various files, and meticulously process and refine the information. With just a single click, you can export everything to a live database, thereby optimizing your data workflows. Centralize offline information, ensuring that your team can easily access it. Transfer offline files to Dropbase in multiple formats, accommodating any preferences you may have. Process and format your data seamlessly, allowing for additions, edits, reordering, and deletions of processing steps as needed. Enjoy the convenience of 1-click exports, whether to a database, endpoints, or downloadable code. Gain instant REST API access to securely query your Dropbase data using REST API access keys. Onboard your data wherever necessary, and combine multiple datasets to fit your required format or data model without needing to write any code. Manage your data pipelines effortlessly through a user-friendly spreadsheet interface, tracking every step of the process. Benefit from flexibility by utilizing a library of pre-built processing functions or by creating your own as you see fit. With 1-click exports, you can easily manage databases and credentials, ensuring a smooth and efficient data management experience. This system empowers teams to work more collaboratively and efficiently, transforming how they handle data.

Experience robust data engineering processes free from the challenges of infrastructure management. By utilizing straightforward, modular Python, you can define intricate streaming, scheduling, and data backfill pipelines with ease. Transition from traditional ETL methods and access your data instantly, regardless of its complexity. Seamlessly blend deep learning and large language models with structured business datasets to enhance decision-making. Improve forecasting accuracy using up-to-date information, eliminate the costs associated with vendor data pre-fetching, and conduct timely queries for online predictions. Test your ideas in Jupyter notebooks before moving them to a live environment. Avoid discrepancies between training and serving data while developing new workflows in mere milliseconds. Monitor all of your data operations in real-time to effortlessly track usage and maintain data integrity. Have full visibility into everything you've processed and the ability to replay data as needed. Easily integrate with existing tools and deploy on your infrastructure, while setting and enforcing withdrawal limits with tailored hold periods. With such capabilities, you can not only enhance productivity but also ensure streamlined operations across your data ecosystem.

Centurion is a deployment tool specifically designed for Docker, facilitating the retrieval of containers from a Docker registry to deploy them across a network of hosts while ensuring the appropriate environment variables, host volume mappings, and port configurations are in place. It inherently supports rolling deployments, simplifying the process of delivering applications to Docker servers within our production infrastructure. The tool operates through a two-stage deployment framework, where the initial build process pushes a container to the registry, followed by Centurion transferring the container from the registry to the Docker fleet. Integration with the registry is managed via the Docker command line tools, allowing compatibility with any existing solutions they support through conventional registry methods. For those unfamiliar with registries, it is advisable to familiarize yourself with their functionality prior to deploying with Centurion. The development of this tool is conducted openly, welcoming community feedback through issues and pull requests, and is actively maintained by a dedicated team at New Relic. Additionally, this collaborative approach ensures continuous improvement and responsiveness to user needs.

TrueFoundry is a cloud-native platform-as-a-service for machine learning training and deployment built on Kubernetes, designed to empower machine learning teams to train and launch models with the efficiency and reliability typically associated with major tech companies, all while ensuring scalability to reduce costs and speed up production release. By abstracting the complexities of Kubernetes, it allows data scientists to work in a familiar environment without the overhead of managing infrastructure. Additionally, it facilitates the seamless deployment and fine-tuning of large language models, prioritizing security and cost-effectiveness throughout the process. TrueFoundry features an open-ended, API-driven architecture that integrates smoothly with internal systems, enables deployment on a company's existing infrastructure, and upholds stringent data privacy and DevSecOps standards, ensuring that teams can innovate without compromising on security. This comprehensive approach not only streamlines workflows but also fosters collaboration among teams, ultimately driving faster and more efficient model deployment.

Manage, oversee, control, and safeguard the applications, data, and IT resources essential for your business, spanning from edge to cloud. HPE Ezmeral propels digital transformation efforts by reallocating time and resources away from IT maintenance towards innovation. Update your applications, streamline your operations, and leverage data to transition from insights to impactful actions. Accelerate your time-to-value by implementing Kubernetes at scale, complete with integrated persistent data storage for modernizing applications, whether on bare metal, virtual machines, within your data center, on any cloud, or at the edge. By operationalizing the comprehensive process of constructing data pipelines, you can extract insights more rapidly. Introduce DevOps agility into the machine learning lifecycle while delivering a cohesive data fabric. Enhance efficiency and agility in IT operations through automation and cutting-edge artificial intelligence, all while ensuring robust security and control that mitigate risks and lower expenses. The HPE Ezmeral Container Platform offers a robust, enterprise-grade solution for deploying Kubernetes at scale, accommodating a diverse array of use cases and business needs. This comprehensive approach not only maximizes operational efficiency but also positions your organization for future growth and innovation.

Apache Brooklyn is a versatile software solution designed for overseeing cloud applications, enabling you to manage your applications seamlessly across various environments, including public clouds, private clouds, and bare metal servers. With Brooklyn, you can create blueprints that outline your application architecture and store them as text files in version control, ensuring your components are automatically configured and integrated across multiple machines. It supports over 20 public cloud platforms as well as Docker containers, allowing for efficient monitoring of critical application metrics while scaling resources to accommodate demand. Additionally, you can easily restart or replace any failed components, and you have the option to view and modify your applications through a user-friendly web console or automate processes via the REST API for greater efficiency. This flexibility offers organizations the ability to streamline their operations and enhance their cloud management capabilities.

Mirantis Kubernetes Engine (formerly Docker Enterprise) gives you the power to build, run, and scale cloud native applications—the way that works for you. Increase developer efficiency and release frequency while reducing cost. Deploy Kubernetes and Swarm clusters out of the box and manage them via API, CLI, or web interface. Kubernetes, Swarm, or both Different apps—and different teams—have different container orchestration needs. Use Kubernetes, Swarm, or both depending on your specific requirements. Simplified cluster management Get up and running right out of the box—then manage clusters easily and apply updates with zero downtime using a simple web UI, CLI, or API. Integrated role-based access control (RBAC) Fine-grained security access control across your platform ensures effective separation of duties, and helps drive a security strategy built on the principle of least privilege. Identity management Easily integrate with your existing identity management solution and enable two-factor authentication to provide peace of mind that only authorized users are accessing your platform. Mirantis Kubernetes Engine works with Mirantis Container Runtime and Mirantis Secure Registry to provide security compliance.

Rapidly create applications without the hassle of overseeing virtual machines or learning unfamiliar tools—simply deploy your app in a cloud-based container. By utilizing Azure Container Instances (ACI), your attention can shift towards the creative aspects of application development instead of the underlying infrastructure management. Experience an unmatched level of simplicity and speed in deploying containers to the cloud, achievable with just one command. ACI allows for the quick provisioning of extra compute resources for high-demand workloads as needed. For instance, with the aid of the Virtual Kubelet, you can seamlessly scale your Azure Kubernetes Service (AKS) cluster to accommodate sudden traffic surges. Enjoy the robust security that virtual machines provide for your containerized applications while maintaining the lightweight efficiency of containers. ACI offers hypervisor-level isolation for each container group, ensuring that each container operates independently without kernel sharing, which enhances security and performance. This innovative approach to application deployment simplifies the process, allowing developers to focus on building exceptional software rather than getting bogged down by infrastructure concerns.

Oracle's Container Engine for Kubernetes (OKE) serves as a managed container orchestration solution that significantly minimizes both the time and expenses associated with developing contemporary cloud-native applications. In a departure from many competitors, Oracle Cloud Infrastructure offers OKE as a complimentary service that operates on high-performance and cost-efficient compute shapes. DevOps teams benefit from the ability to utilize unaltered, open-source Kubernetes, enhancing application workload portability while streamlining operations through automated updates and patch management. Users can initiate the deployment of Kubernetes clusters along with essential components like virtual cloud networks, internet gateways, and NAT gateways with just a single click. Furthermore, the platform allows for the automation of Kubernetes tasks via a web-based REST API and a command-line interface (CLI), covering all aspects from cluster creation to scaling and maintenance. Notably, Oracle does not impose any fees for managing clusters, making it an attractive option for developers. Additionally, users can effortlessly and swiftly upgrade their container clusters without experiencing any downtime, ensuring they remain aligned with the latest stable Kubernetes version. This combination of features positions Oracle's offering as a robust solution for organizations looking to optimize their cloud-native development processes.

What makes azk stand out? Azk is open source software (Apache 2.0) and will remain that way indefinitely. It offers an agnostic approach with an exceptionally gentle learning curve, allowing you to continue utilizing the same development tools you are accustomed to. With just a few commands, you can transition from hours or days of setup to a matter of minutes. The magic of azk lies in its ability to execute concise and straightforward recipe files (Azkfile.js), which specify the environments to be installed and configured. Its performance is impressively efficient, ensuring your machine hardly notices its presence. By utilizing containers rather than virtual machines, azk provides superior performance while consuming fewer physical resources. Built on Docker, the leading open-source engine for container management, azk ensures that sharing an Azkfile.js guarantees complete consistency across different development environments, minimizing the risk of bugs during deployment. Are you unsure whether all the developers on your team are running the most current version of the development environment? With azk, you can easily verify and maintain synchronization across all machines.

Helios serves as a Docker orchestration platform designed for the deployment and management of containers across a wide array of servers. It offers both an HTTP API and a command-line interface, enabling users to interact seamlessly with the servers that host their containers. In addition, Helios maintains a record of significant events within your cluster, capturing details such as deployments, restarts, and version updates. The binary version of Helios is specifically compiled for Ubuntu 14.04.1 LTS, though it is also compatible with any platform that supports at least Java 8 and a current version of Maven 3. Users can utilize helios-solo to set up a local environment featuring both a Helios master and agent. Helios adopts a pragmatic approach; while it may not aim to address every problem at once, it is committed to delivering solid performance with the features it currently offers. Consequently, certain functionalities, like resource limits and dynamic scheduling, are not yet implemented. At this stage, the focus is primarily on solidifying CI/CD use cases and the related tools, but there are plans to eventually incorporate dynamic scheduling, composite jobs, and other advanced features in the future. The evolution of Helios reflects its dedication to continuous improvement and responsiveness to user needs.

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.

You can accelerate your development by using a storage platform that integrates with Kubernetes. While you focus on running your application we ensure that you have the persistent volumes you need to give you the stability and scale you require. Integrating stateful storage into Kubernetes will simplify your app modernization process and increase efficiency. You can run your database or any other persistent workload in a Kubernetes-based environment without worrying about managing the storage layer. Ondat allows you to provide a consistent storage layer across all platforms. We provide persistent volumes that allow you to run your own databases, without having to pay for expensive hosted options. Kubernetes data layer management is yours to take back. Kubernetes-native storage that supports dynamic provisioning. It works exactly as it should. API-driven, tight integration to your containerized applications.

IBM Cloud® Kubernetes Service offers a certified and managed Kubernetes platform designed for the deployment and management of containerized applications on IBM Cloud®. This service includes features like intelligent scheduling, self-healing capabilities, and horizontal scaling, all while ensuring secure management of the necessary resources for rapid deployment, updating, and scaling of applications. By handling the master management, IBM Cloud Kubernetes Service liberates users from the responsibilities of overseeing the host operating system, the container runtime, and the updates for the Kubernetes version. This allows developers to focus more on building and innovating their applications rather than getting bogged down by infrastructure management. Furthermore, the service’s robust architecture promotes efficient resource utilization, enhancing overall performance and reliability.

YARN's core concept revolves around decentralizing resource management and job scheduling/monitoring by utilizing distinct daemons for each function. It employs a centralized ResourceManager (RM) alongside individual ApplicationMasters (AM) for each application, which may consist of either a solitary job or a Directed Acyclic Graph (DAG) of jobs. Together, the ResourceManager and NodeManager create the computational framework necessary for data processing. The ResourceManager serves as the main governing body that allocates resources across all applications within the system. Meanwhile, the NodeManager acts as the agent on each machine, handling containers, tracking their resource utilization (such as CPU, memory, disk, and network), and relaying this information to the ResourceManager/Scheduler. Additionally, the ApplicationMaster functions as a specialized library for each application, responsible for negotiating resource allocation with the ResourceManager and collaborating with the NodeManagers to execute and oversee the tasks efficiently. This division of responsibilities enhances the overall efficiency and scalability of the resource management process.

Alibaba Cloud's Container Service for Kubernetes (ACK) is a comprehensive managed offering that integrates various services, including virtualization, storage, networking, and security, to deliver a high-performance and scalable environment for running containerized applications. As a Kubernetes Certified Service Provider (KCSP), ACK is also certified under the Certified Kubernetes Conformance Program, guaranteeing a reliable Kubernetes experience and enabling workload portability across different environments. This certification ensures that users benefit from a consistent Kubernetes experience while leveraging enterprise-class cloud-native capabilities. Additionally, ACK emphasizes security with end-to-end application protection and fine-grained access control, allowing users to swiftly set up Kubernetes clusters. Moreover, the service facilitates efficient container-based management of applications throughout their entire lifecycle, enhancing operational agility and performance.

It is the only Kubernetes distribution which is simple, solid, and certified. It works on any infrastructure, including bare metal, on-premises or private clouds, edge, IoT or public clouds. It's free and open source. Zero Friction – k0s dramatically reduces the complexity involved in installing and running Kubernetes. Bootstrapping new kube clusters takes only minutes. Developer friction is zero, making it easy for anyone to get started, even if they don't have any special skills. Zero Deps: k0s comes as a single binary that has no host OS dependencies other than the kernel of the host OS. It works with any OS without additional software packages. Any security vulnerabilities or performance problems can be fixed directly within the k0s Distribution. Zero Cost - K0s is free for commercial or personal use and will always be. The source code can be found on GitHub, under Apache 2 license.

Apache ODE, known as the Orchestration Director Engine, is designed to execute business processes that adhere to the WS-BPEL standard. It effectively communicates with web services by transmitting and receiving messages while also managing data operations and error handling as outlined in your defined processes. This software accommodates both short-lived and long-running process executions, allowing for the orchestration of all services involved in your application. WS-BPEL, or Business Process Execution Language, is an XML-based format that provides various constructs for creating business processes. It outlines essential control structures such as conditions and loops, along with elements for invoking web services and receiving messages. The language depends on WSDL to characterize the interfaces of web services. Furthermore, message structures can be manipulated, enabling the assignment of specific parts or entire messages to variables that can then be utilized for sending additional messages. Additionally, Apache ODE supports both the WS-BPEL 2.0 OASIS standard and the older BPEL4WS 1.1 vendor specification, ensuring compatibility across different versions. This dual support allows developers to transition smoothly between standards while maintaining functionality.

Lightbend offers innovative technology that empowers developers to create applications centered around data, facilitating the development of demanding, globally distributed systems and streaming data pipelines. Businesses across the globe rely on Lightbend to address the complexities associated with real-time, distributed data, which is essential for their most critical business endeavors. The Akka Platform provides essential components that simplify the process for organizations to construct, deploy, and manage large-scale applications that drive digital transformation. By leveraging reactive microservices, companies can significantly speed up their time-to-value while minimizing expenses related to infrastructure and cloud services, all while ensuring resilience against failures and maintaining efficiency at any scale. With built-in features for encryption, data shredding, TLS enforcement, and adherence to GDPR standards, it ensures secure data handling. Additionally, the framework supports rapid development, deployment, and oversight of streaming data pipelines, making it a comprehensive solution for modern data challenges. This versatility positions companies to fully harness the potential of their data, ultimately propelling them forward in an increasingly competitive landscape.

The need to choose between the ease of a graphical user interface and the robustness of infrastructure as code is now a thing of the past. With Kubestack, you can effortlessly create your Kubernetes platform using an intuitive graphical user interface and subsequently export your tailored stack into Terraform code, ensuring dependable provisioning and ongoing operational sustainability. Platforms built with Kubestack Cloud are transitioned into a Terraform root module grounded in the Kubestack framework. All components of this framework are open-source, significantly reducing long-term maintenance burdens while facilitating continuous enhancements. You can implement a proven pull-request and peer-review workflow to streamline change management within your team. By minimizing the amount of custom infrastructure code required, you can effectively lessen the long-term maintenance workload, allowing your team to focus on innovation and growth. This approach ultimately leads to increased efficiency and collaboration among team members, fostering a more productive development environment.

Dataplane's goal is to make it faster and easier to create a data mesh. It has robust data pipelines and automated workflows that can be used by businesses and teams of any size. Dataplane is more user-friendly and places a greater emphasis on performance, security, resilience, and scaling.

Construct your data pipelines akin to assembling Lego blocks using Data Taps. Integrate fresh metrics layers, delve deeper, and conduct inquiries using real-time streaming SQL capabilities. Collaborate with peers, disseminate, and access data on a global scale. Enhance and modify your setup effortlessly. Employ various models and schemas while evolving your schema. Designed for scalability, it leverages the power of AWS Lambda and S3 for optimal performance. This flexibility allows teams to adapt quickly to changing data needs.

Implement robust change data capture pipelines for large-scale, real-time data replication effortlessly, without writing a single line of code. Experience the enhanced capabilities of Change Data Capture with Arcion’s distributed CDC solution. Benefit from automatic schema transformations, seamless end-to-end replication, and flexible deployment options. Arcion’s architecture ensures zero data loss, guaranteeing consistent data flow through built-in checkpointing and more, all without the need for custom coding. Say goodbye to worries about scalability and performance as you take advantage of a highly distributed and parallel architecture that achieves data replication speeds up to ten times faster. Minimize DevOps challenges with Arcion Cloud, the sole fully-managed CDC solution available. With features like autoscaling, high availability, and a monitoring console, you can streamline your operations. Furthermore, the platform simplifies and standardizes your data pipeline architecture, facilitating seamless workload migration from on-premises systems to the cloud without any downtime. With such a comprehensive solution, you can focus on leveraging your data rather than managing the complexities of its movement.