Best Container Orchestration Software - Page 3

Make your Kubernetes autoscaling proactivе. From reactive scaling to proactive, with PredictKube, you’ll be able to finish autoscaling before the load rise thanks to predictions made by our AI model. Our AI model can start working with the data for 2 weeks to provide you with reliable prediction and autoscaling. The predictive Keda scaler named PredictKube helps you to minimize time-wasting on manual setup of autoscaling and gives you an automated performance. We made our KEDA scaler out of the top-notch technologies available for Kubernetes and AI. Input the data for 1+ week and get proactive autoscaling up to 6 hours horizon based on AI prediction. The right time for scaling is selected by our trained AI model that analyzes your historical data and can utilize the data of custom and public business metrics that can affect the traffic load. We’ll support free access to API in general with all basic features available to provide autoscaling possibilities.

Amazon EC2 Auto Scaling helps you maintain application availability and lets you automatically add or remove EC2 instances using scaling policies that you define. Dynamic or predictive scaling policies let you add or remove EC2 instance capacity to service established or real-time demand patterns. The fleet management features of Amazon EC2 Auto Scaling help maintain the health and availability of your fleet. Automation is vital to efficient DevOps, and getting your fleets of Amazon EC2 instances to launch, provision software, and self-heal automatically is a key challenge. Amazon EC2 Auto Scaling provides essential features for each of these instance lifecycle automation steps. Use machine learning to predict and schedule the right number of EC2 instances to anticipate approaching traffic changes.

UbiOps is an AI infrastructure platform that helps teams to quickly run their AI & ML workloads as reliable and secure microservices, without upending their existing workflows. Integrate UbiOps seamlessly into your data science workbench within minutes, and avoid the time-consuming burden of setting up and managing expensive cloud infrastructure. Whether you are a start-up looking to launch an AI product, or a data science team at a large organization. UbiOps will be there for you as a reliable backbone for any AI or ML service. Scale your AI workloads dynamically with usage without paying for idle time. Accelerate model training and inference with instant on-demand access to powerful GPUs enhanced with serverless, multi-cloud workload distribution.

Managing Kubernetes shouldn't be a headache. With Syself Autopilot, both beginners and experts can deploy and maintain enterprise-grade clusters with ease. Say goodbye to downtime and complexity—our platform ensures automated upgrades, self-healing capabilities, and GitOps compatibility. Whether you're running on bare metal or cloud infrastructure, Syself Autopilot is designed to handle your needs, all while maintaining GDPR-compliant data protection. Syself Autopilot integrates with leading DevOps and infrastructure solutions, allowing you to build and scale applications effortlessly. Our platform supports: - Argo CD, Flux (GitOps & CI/CD) - MariaDB, PostgreSQL, MySQL, MongoDB, ClickHouse (Databases) - Grafana, Istio, Redis, NATS (Monitoring & Service Mesh) Need additional solutions? Our team helps you deploy, configure, and optimize your infrastructure for peak performance.

The fundamental idea of YARN is to split up the functionalities of resource management and job scheduling/monitoring into separate daemons. The idea is to have a global ResourceManager (RM) and per-application ApplicationMaster (AM). An application is either a single job or a DAG of jobs. The ResourceManager and the NodeManager form the data-computation framework. The ResourceManager is the ultimate authority that arbitrates resources among all the applications in the system. The NodeManager is the per-machine framework agent who is responsible for containers, monitoring their resource usage (cpu, memory, disk, network) and reporting the same to the ResourceManager/Scheduler. The per-application ApplicationMaster is, in effect, a framework specific library and is tasked with negotiating resources from the ResourceManager and working with the NodeManager(s) to execute and monitor the tasks.

Test Kitchen provides a test harness to execute infrastructure code on one or more platforms in isolation. A driver plugin architecture is used to run code on various cloud providers and virtualization technologies such as Vagrant, Amazon EC2, Microsoft Azure, Google Compute Engine, Docker, and more. Many testing frameworks are supported out of the box including Chef InSpec, Serverspec, and Bats For Chef Infra workflows, cookbook dependency resolution via Berkshelf or Policyfiles is supported or include a cookbooks/ directory and Kitchen will know what to do. Test Kitchen is used by all Chef-managed community cookbooks and is the integration testing tool of choice for cookbooks.

What’s so great about azk? azk is open source software (Apache 2.0) and will always be. azk is agnostic and has a very soft learning curve. Keep using the exact same development tools you already use. It only takes a few commands. Minutes instead of hours or days. azk does its magic by executing very short and simple recipe files (Azkfile.js) that describe the environments to be installed and configured. azk is fast and your machine will barely feel it. It uses containers instead of virtual machines. Containers are like virtual machines, only with better performance and lower consumption of physical resources. azk is built with Docker, the best open source engine for managing containers. Sharing an Azkfile.js assures total parity among development environments in different programmers' machines and reduces the chances of bugs during deployment. Not sure if all the programmers in your team are using the updated version of the development environment?

Aurora runs applications and services across a shared pool of machines, and is responsible for keeping them running, forever. When machines experience failure, Aurora intelligently reschedules those jobs onto healthy machines. When updating a job, Aurora will detect the health and status of a deployment and automatically rollback if necessary. Aurora has a quota system to provide guaranteed resources for specific applications, and can support multiple users to deploy services. Services are highly-configurable via a DSL which supports templating, allowing you to establish common patterns and avoid redundant configurations. Aurora announces services to Apache ZooKeeper for discovery by clients like Finagle.

Apache ODE (Orchestration Director Engine) software executes business processes written following the WS-BPEL standard. It talks to web services, sending and receiving messages, handling data manipulation and error recovery as described by your process definition. It supports both long and short living process executions to orchestrate all the services that are part of your application. WS-BPEL (Business Process Execution Language) is an XML-based language defining several constructs to write business processes. It defines a set of basic control structures like conditions or loops as well as elements to invoke web services and receive messages from services. It relies on WSDL to express web services interfaces. Message structures can be manipulated, assigning parts or the whole of them to variables that can in turn be used to send other messages. Side-by-side support for both the WS-BPEL 2.0 OASIS standard and the legacy BPEL4WS 1.1 vendor specification.

Deploy applications quickly and confidently with Critical Stack, the open source container orchestration tool from Capital One. Critical Stack enforces the highest level of governance and security standards, enabling teams to efficiently scale containerized applications in the strictest environments. View your entire environment and deploy new services with a few simple clicks. Spend more time on development and decision making and less on maintenance. Dynamically adjust shared resources of your environment efficiently. Enforce container networking policies and controls that your teams can configure. Speed up development cycles and deployment of containerized applications. Guarantee containerized applications run according to your specifications. Deploy containerized applications confidently. Critical Stack enables application verification and powerful orchestration capabilities for your important workloads.

Better operators for enterprise apps with a full application graph and declarative integration for both Kubernetes and legacy estate. Juju operator integration allows us to keep each operator as simple as possible, then compose them to create rich application graph topologies that support complex scenarios with a simple, consistent experience and much less YAML. The UNIX philosophy of ‘doing one thing well’ applies to large-scale operations code too, and the benefits of clarity and reuse are exactly the same. Small is beautiful. Juju allows you to adopt the operator pattern for your entire estate, including legacy apps. Model-driven operations dramatically reduce maintenance and operations costs for traditional workloads without re-platforming to K8s. Once charmed, legacy apps become multi-cloud ready, too. The Juju Operator Lifecycle Manager (OLM) uniquely supports both container and machine-based apps, with seamless integration between them.

Accelerate your development by using a storage layer that works natively with your Kubernetes environment. Focus on running your application, while we make sure you have the persistent volumes that give you the scale and stability you need. Reduce complexity and increase efficiency in your app modernization journey by truly integrating stateful storage into Kubernetes. Run your database or any persistent workload in a Kubernetes environment without having to worry about managing the storage layer. Ondat gives you the ability to deliver a consistent storage layer across any platform. We give you the persistent volumes to allow you to run your own databases without paying for expensive hosted options. Take back control of your data layer in Kubernetes. Kubernetes-native storage with dynamic provisioning that works as it should. Fully API-driven, tight integration with your containerized applications.

Conductor is a workflow orchestration engine that runs in the cloud. Conductor was built to help Netflix orchestrate microservices-based process flows with the following features. A distributed server ecosystem, which stores workflow state information efficiently. Allow creation of process/business flows in which each individual task can be implemented by the same/different microservices. A DAG (Directed Acyclic Graph) based workflow definition. Workflow definitions are decoupled from the service implementations. Provide visibility and traceability to these process flows. Simple interface to connect workers, which execute the tasks in workflows. Workers are language agnostic, allowing each microservice to be written in the language most suited for the service. Full operational control over workflows with the ability to pause, resume, restart, retry and terminate. Allow greater reuse of existing microservices providing an easier path for onboarding.

No need to compromise between the convenience of a graphical user interface and the power of infrastructure as code anymore. Kubestack allows you to design your Kubernetes platform in an intuitive, graphical user interface. And then export your custom stack to Terraform code for reliable provisioning and sustainable long-term operations. Platforms designed using Kubestack Cloud are exported to a Terraform root module, that's based on the Kubestack framework. All framework modules are open-source, lowering the long-term maintenance effort and allowing easy access to continued improvements. Adapt the tried and tested pull-request and peer-review based workflow to efficiently manage changes with your team. Reduce long-term effort by minimizing the bespoke infrastructure code you have to maintain yourself.