Alternatives to UbiOps

Google Cloud is an online service that lets you create everything from simple websites to complex apps for businesses of any size. Customers who are new to the system will receive $300 in credits for testing, deploying, and running workloads. Customers can use up to 25+ products free of charge. Use Google's core data analytics and machine learning. All enterprises can use it. It is secure and fully featured. Use big data to build better products and find answers faster. You can grow from prototypes to production and even to planet-scale without worrying about reliability, capacity or performance. Virtual machines with proven performance/price advantages, to a fully-managed app development platform. High performance, scalable, resilient object storage and databases. Google's private fibre network offers the latest software-defined networking solutions. Fully managed data warehousing and data exploration, Hadoop/Spark and messaging.

Compute Engine (IaaS), a platform from Google that allows organizations to create and manage cloud-based virtual machines, is an infrastructure as a services (IaaS). Computing infrastructure in predefined sizes or custom machine shapes to accelerate cloud transformation. General purpose machines (E2, N1,N2,N2D) offer a good compromise between price and performance. Compute optimized machines (C2) offer high-end performance vCPUs for compute-intensive workloads. Memory optimized (M2) systems offer the highest amount of memory and are ideal for in-memory database applications. Accelerator optimized machines (A2) are based on A100 GPUs, and are designed for high-demanding applications. Integrate Compute services with other Google Cloud Services, such as AI/ML or data analytics. Reservations can help you ensure that your applications will have the capacity needed as they scale. You can save money by running Compute using the sustained-use discount, and you can even save more when you use the committed-use discount.

StarTree Cloud is a fully-managed real-time analytics platform designed for OLAP at massive speed and scale for user-facing applications. Powered by Apache Pinot, StarTree Cloud provides enterprise-grade reliability and advanced capabilities such as tiered storage, scalable upserts, plus additional indexes and connectors. It integrates seamlessly with transactional databases and event streaming platforms, ingesting data at millions of events per second and indexing it for lightning-fast query responses. StarTree Cloud is available on your favorite public cloud or for private SaaS deployment. StarTree Cloud includes StarTree Data Manager, which allows you to ingest data from both real-time sources such as Amazon Kinesis, Apache Kafka, Apache Pulsar, or Redpanda, as well as batch data sources such as data warehouses like Snowflake, Delta Lake or Google BigQuery, or object stores like Amazon S3, Apache Flink, Apache Hadoop, or Apache Spark. StarTree ThirdEye is an add-on anomaly detection system running on top of StarTree Cloud that observes your business-critical metrics, alerting you and allowing you to perform root-cause analysis — all in real-time.

SaltStack is an intelligent IT automation platform that can manage, secure, and optimize any infrastructure--on-prem, in the cloud, or at the edge. It is built on an event-driven automation engine that detects and responds intelligently to any system. This makes it a powerful solution for managing complex environments. SaltStack's new SecOps offering can detect security flaws and mis-configured systems. This powerful automation can detect and fix any issue quickly, allowing you and your team to keep your infrastructure secure, compliant, and up to date. Comply and Protect are both part of the SecOps suite. Comply scans for compliance with CIS, DISA, STIG, NIST and PCI standards. Also, scan your operating system for vulnerabilities and update it with patches and patches.

You can use your favorite debugging software to locally troubleshoot your Kubernetes services. Telepresence, an open-source tool, allows you to run one service locally and connect it to a remote Kubernetes cluster. Telepresence was initially developed by Ambassador Labs, which creates open-source development tools for Kubernetes such as Ambassador and Forge. We welcome all contributions from the community. You can help us by submitting an issue, pull request or reporting a bug. Join our active Slack group to ask questions or inquire about paid support plans. Telepresence is currently under active development. Register to receive updates and announcements. You can quickly debug locally without waiting for a container to be built/push/deployed. Ability to use their favorite local tools such as debugger, IDE, etc. Ability to run large-scale programs that aren't possible locally.

Kubernetes (K8s), an open-source software that automates deployment, scaling and management of containerized apps, is available as an open-source project. It organizes containers that make up an app into logical units, which makes it easy to manage and discover. Kubernetes is based on 15 years of Google's experience in running production workloads. It also incorporates best-of-breed practices and ideas from the community. Kubernetes is built on the same principles that allow Google to run billions upon billions of containers per week. It can scale without increasing your operations team. Kubernetes flexibility allows you to deliver applications consistently and efficiently, no matter how complex they are, whether you're testing locally or working in a global enterprise. Kubernetes is an open-source project that allows you to use hybrid, on-premises, and public cloud infrastructures. This allows you to move workloads where they are most important.

The AI Knowledge Platform. The Pinecone Database, Inference, and Assistant make building high-performance vector search apps easy. Fully managed and developer-friendly, the database is easily scalable without any infrastructure problems. Once you have vector embeddings created, you can search and manage them in Pinecone to power semantic searches, recommenders, or other applications that rely upon relevant information retrieval. Even with billions of items, ultra-low query latency Provide a great user experience. You can add, edit, and delete data via live index updates. Your data is available immediately. For more relevant and quicker results, combine vector search with metadata filters. Our API makes it easy to launch, use, scale, and scale your vector searching service without worrying about infrastructure. It will run smoothly and securely.

Launch GPU-accelerated instances that are highly configurable for your AI workload and budget. Reserve thousands of GPUs for training and inference in a next generation AI data center. The AI world is moving to GPU clouds in order to build and launch groundbreaking models without having the hassle of managing infrastructure or scarcity of resources. AI-centric cloud providers are outperforming traditional hyperscalers in terms of availability, compute costs, and scaling GPU utilization for complex AI workloads. Ori has a large pool with different GPU types that are tailored to meet different processing needs. This ensures that a greater concentration of powerful GPUs are readily available to be allocated compared to general purpose clouds. Ori offers more competitive pricing, whether it's for dedicated servers or on-demand instances. Our GPU compute costs are significantly lower than the per-hour and per-use pricing of legacy cloud services.

Xosphere Instance Orchestrator performs automatic spot optimization using AWS Spot instances. This optimizes the cost of your infrastructure, while maintaining the same reliability as on-demand instance. Spot instances have been diversified by family, size and availability zone in order to minimize the impact of reclaiming Spot instances. Spot instances will not replace instances that use reservations. Respond automatically to Spot termination notifications. EBS volumes can configured to be attached new replacement instances, enabling stateful apps to work seamlessly.

Amazon EC2 Auto Scaling allows you to maintain application availability by adding or removing EC2 instances automatically using scaling policies you define. Dynamic or predictive policies allow you to add or remove EC2 instances capacity in response to real-time or established demand patterns. The fleet management features in Amazon EC2 Auto Scaling maintain the health and availability your fleet. Automating DevOps is essential, and getting your fleets to automatically launch, provision software and self-heal is a major challenge. Amazon EC2 Auto Scaling offers essential features to automate each of these steps in the instance lifecycle. Use machine learning to predict the number of EC2 instance to be used to anticipate traffic changes.

Horay.ai offers out-of-the box large model inference services, bringing an efficient user experience to generative AI applications. Horay.ai, a cutting edge cloud service platform, primarily offers APIs for large open-source models. Our platform provides a wide range of models, guarantees fast updates, and offers services at competitive rates. This allows developers to easily integrate advanced multimodal capabilities, natural language processing, and image generation into their applications. Horay.ai infrastructure allows developers to focus on innovation, rather than the complexity of model deployment and maintenance. Horay.ai was founded in 2024 by a team of AI experts. We are focused on serving generative AI developer, improving service quality and the user experience. Horay.ai offers reliable solutions for both startups and large enterprises to help them grow rapidly.

Nscale is a hyperscaler that is engineered for AI. It offers high-performance computing optimized to train, fine-tune, and handle intensive workloads. Vertically integrated across Europe, from our data centers to software stack, to deliver unparalleled performance, efficiency and sustainability. Our AI cloud platform allows you to access thousands of GPUs that are tailored to your needs. A fully integrated platform will help you reduce costs, increase revenue, and run AI workloads more efficiently. Our platform simplifies the journey from development through to production, whether you use Nscale's AI/ML tools built-in or your own. The Nscale Marketplace provides users with access to a variety of AI/ML resources and tools, allowing for efficient and scalable model deployment and development. Serverless allows for seamless, scalable AI without the need to manage any infrastructure. It automatically scales up to meet demand and ensures low latency, cost-effective inference, for popular generative AI model.

Here is where the future of AI development begins. Modular is a composable, integrated suite of tools which simplifies your AI infrastructure, allowing your team to develop, deploy and innovate faster. Modular's inference engines unify AI industry frameworks with hardware. This allows you to deploy into any cloud or on-prem environments with minimal code changes, unlocking unmatched portability, performance and usability. Move your workloads seamlessly to the best hardware without rewriting your models or recompiling them. Avoid lock-in, and take advantage of cloud performance and price improvements without migration costs.

Create your first AI automation in 60 seconds. Inferable seamlessly integrates into your existing infrastructure and codebase, allowing you create powerful AI automation while maintaining control and security. Work with your existing codebase. Integrates with existing services via opt-in. Source code can be used to enforce determinism. Automate and manage automation programmatically. You own your computer and infrastructure. Inferable comes with delightful DX that will kickstart your AI automation journey. We bring you the best vertically integrated LLM Orchestration. You bring your domain and product expertise. Inferable's core is a distributed messaging queue that ensures AI automation is reliable and scalable. It ensures that your automations are executed correctly and that errors are handled gracefully. Decorators can be used to make your existing functions, REST endpoints, or GraphQL APIs require human approval.

Software-defined load balancers and container ingress services simplify application delivery for any application, in any datacenter and cloud. Simplify administration by implementing centralized policies that ensure operational consistency in hybrid clouds and on-premises datacenters, including VMware Cloud, AWS, Azure and Google Cloud. Self-service enables DevOps to free infrastructure teams from manual tasks. The toolkits for application delivery automation include Python SDKs, RESTful APIs and Terraform and Ansible integrations. With real-time monitoring of application performance, closed-loop analysis and deep machine-learning, you can gain unprecedented insights into network, end-users and security.

GMI GPU Cloud allows you to create generative AI applications within minutes. GMI Cloud offers more than just bare metal. Train, fine-tune and infer the latest models. Our clusters come preconfigured with popular ML frameworks and scalable GPU containers. Instantly access the latest GPUs to power your AI workloads. We can provide you with flexible GPUs on-demand or dedicated private cloud instances. Our turnkey Kubernetes solution maximizes GPU resources. Our advanced orchestration tools make it easy to allocate, deploy and monitor GPUs or other nodes. Create AI applications based on your data by customizing and serving models. GMI Cloud allows you to deploy any GPU workload quickly, so that you can focus on running your ML models and not managing infrastructure. Launch pre-configured environment and save time building container images, downloading models, installing software and configuring variables. You can also create your own Docker images to suit your needs.

Nebula enables you to scale and deploy your AI projects quickly and easily2 on a highly robust GPU infrastructure. Nebula Cloud powered by Nvidia GPUs on demand allows you to train and infer models easily and securely. You can also create and manage containerized workloads using Nebula's easy-to-use orchestration layer. Access Nebula’s MLOps, low-code/no code engines and AI-powered applications to quickly and seamlessly deploy AI-powered apps for business teams. Choose from the Nebula containerized AI Cloud, your on-prem or any cloud. The Nebula Unify platform allows you to build and scale AI-enabled use cases for business in a matter weeks, not months.

The perfect public cloud is available to handle all your workloads! SaaS solutions are cost-effective, eCommerce applications work well even under peak load, and CPU-intensive rendering tasks can be completed efficiently. Data archives and backups are redundantly stored. The Compute Engine is the perfect choice for you, whether you want to mix on-site applications with public clouds into a hybrid cloud or need a real alternative to multi-cloud strategies. It has transparent prices, maximum privacy in certified data centers and unbeatable backbone connections, a simple user interface thanks to the Data Center Designer, Cloud REST API and reliable vertical scaling. We protect all your business-critical data. It is stored in dual redundancy in our data centers in Europe and the United States. The Compute Engine increases flexibility by allowing your company to respond quickly to market changes and making low investments.

It is a simple and flexible task orchestrator that deploys and manages containers and non-containerized apps across on-prem as well as cloud environments. One 35MB binary that can be integrated into existing infrastructure. It is easy to use on-prem and in the cloud with minimal overhead. You can orchestrate any type of application, not just containers. First-class support for Docker and Windows, Java, VMs, VMs, and other technologies. Orchestration benefits can be added to existing services. Zero downtime deployments, increased resilience, higher resource utilization, as well as greater resilience can all be achieved without containerization. Multi-region, multicloud federation - single command Nomad is a single control plane that allows you to deploy applications worldwide to any region. One workflow to deploy to cloud or bare metal environments. Multi-cloud applications can be enabled with ease. Nomad seamlessly integrates with Terraform Consul and Vault for provisioning and service networking. Secrets management is also possible.

A desktop application that allows users to deploy and self-host AI models from open-source without exposing sensitive information to third parties. OpenAI's API allows you to easily implement machine learning models using an intuitive interface. Avoid the complexity of inference optimizations. Prem has you covered. In just minutes, you can create, test and deploy your models. Learn how to get the most out of Prem by diving into our extensive resources. Make payments using Bitcoin and Cryptocurrency. It's an infrastructure designed for you, without permission. We encrypt your keys and models from end-to-end.

Azure Kubernetes Services (AKS), a fully managed service that manages containerized applications, makes it easy to deploy and manage them. It provides serverless Kubernetes and integrated continuous integration/continuous delivery (CI/CD), as well as enterprise-grade security, governance, and governance. You can quickly build, deliver, scale and scale applications using confidence by bringing together your operations and development teams. You can easily provision additional capacity by using elastic provisioning without having to manage the infrastructure. KEDA allows for event-driven autoscaling. Azure Dev Spaces allows for faster end-to-end development, including integration with Visual Studio Code Kubernetes tools and Azure DevOps. Azure Policy allows for advanced identity and access management, as well as dynamic rules enforcement across multiple clusters. More regions are available than any other cloud provider.

CAST AI significantly reduces your compute costs with automated cost management and optimization. Within minutes, you can quickly optimize your GKE clusters thanks to real-time autoscaling up and down, rightsizing, spot instance automation, selection of most cost-efficient instances, and more. What you see is what you get – you can find out what your savings will look like with the Savings Report available in the free plan with K8s cost monitoring. Enabling the automation will deliver reported savings to you within minutes and keep the cluster optimized. The platform understands what your application needs at any given time and uses that to implement real-time changes for best cost and performance. It isn’t just a recommendation engine. CAST AI uses automation to reduce the operational costs of cloud services and enables you to focus on building great products instead of worrying about the cloud infrastructure. Companies that use CAST AI benefit from higher profit margins without any additional work thanks to the efficient use of engineering resources and greater control of cloud environments. As a direct result of optimization, CAST AI clients save an average of 63% on their Kubernetes cloud bills.

Pepperdata autonomous, application-level cost optimization delivers 30-47% greater cost savings for data-intensive workloads such as Apache Spark on Amazon EMR and Amazon EKS with no application changes. Using patented algorithms, Pepperdata Capacity Optimizer autonomously optimizes CPU and memory in real time with no application code changes. Pepperdata automatically analyzes resource usage in real time, identifying where more work can be done, enabling the scheduler to add tasks to nodes with available resources and spin up new nodes only when existing nodes are fully utilized. The result: CPU and memory are autonomously and continuously optimized, without delay and without the need for recommendations to be applied, and the need for ongoing manual tuning is safely eliminated. Pepperdata pays for itself, immediately decreasing instance hours/waste, increasing Spark utilization, and freeing developers from manual tuning to focus on innovation.

Microservices, containers, and Kubernetes allow apps to run anywhere and everywhere. VMware Tanzu allows you to make the most out of cloud native patterns, automate containerized workload delivery, and proactively manage production apps. It's all about allowing developers to do what they love: create great apps. Kubernetes don't need to be complicated. VMware Tanzu makes it easy to prepare your infrastructure for modern apps by using consistent, conformant Kubernetes wherever you go. Developers can access a self-service, compliant environment that makes it easy to get to production. Centrally manage, govern, and monitor all apps and clusters across clouds. It's that easy.

You can run containers without having to manage servers Azure Container Instances allows you to focus on the design and building of your applications, rather than managing the infrastructure. Containers on demand increase agility With one command, deploy containers to the cloud with unrivalled speed and simplicity. ACI can be used to provision additional compute for your most demanding workloads whenever you require. ACI can be used to elastically burst your Azure Kubernetes Service cluster (AKS) when traffic spikes. Secure applications with hypervisor isolation You can use virtual machines to secure your container workloads while still using lightweight containers. ACI provides hypervisor isolation to each container group so containers can run in isolation and not share a kernel.

D2iQ Enterprise Kubernetes Platform (DKP) Enterprise Kubernetes Platform: Run Kubernetes Workloads at Scale D2iQ Kubernetes Platform (DKP): Adopt, expand, and enable advanced workloads across any infrastructure, whether on-prem, on the cloud, in air-gapped environments, or at the edge. Solve the Toughest Enterprise Kubernetes Challenges Accelerate the journey to production at scale, DKP provides a single, centralized point of control to build, run, and manage applications across any infrastructure. * Enable Day 2 Readiness Out-of-the-Box Without Lock-In * Simplify and Accelerate Kubernetes Adoption * Ensure Consistency, Security, and Performance * Expand Kubernetes Across Distributed Environments * Ensure Fast, Simple Deployment of ML and Fast Data Pipeline * Leverage Cloud Native Expertise

mogenius is a platform that combines visibility, automation, and observability in one place for Kubernetes management. Connect and visualize Kubernetes workloads and clusters. Visibility for the whole team. Identify misconfigurations in your workloads. Take action within the mogenius platform. Automate K8s operations using service catalogs, developer-self-service and ephemeral environment. Leverage developer self-service to simplify deployments for your developers. Standardized and automated workflows can optimize resource allocation and prevent configuration drift. Service catalogs eliminate duplicate work and encourage reuse. Get complete visibility into your Kubernetes configuration. Deploy an operator that is cloud-agnostic to get a complete view of your clusters and workloads. In a few clicks, you can provide developers with ephemeral and local testing environments that mimic your production setup.

NetApp AIPod is an advanced AI infrastructure solution designed to simplify the deployment and management of artificial intelligence workflows. Combining NVIDIA-validated systems like DGX BasePOD™ with NetApp’s cloud-connected all-flash storage, it offers a unified platform for analytics, training, and inference. This scalable solution enables organizations to accelerate AI adoption, streamline data workflows, and ensure seamless integration across hybrid cloud environments. With preconfigured, optimized infrastructure, AIPod reduces operational complexity and helps businesses gain insights faster while maintaining robust data security and management capabilities.

Ridge is a flexible cloud that’s anywhere you need to be. Through one API, Ridge converts any underlying infrastructure into a cloud-native platform. Whether you need to deploy in a private data center, on-prem server, edge micro-center, or even in an multi-facility hybrid environment, Ridge expands your footprint without limits.

JAAS offers Juju as a service. JAAS allows you to quickly design and deploy cloud-based applications. With a fully managed Juju infrastructure, you can focus on your software and solutions. Canonical, in partnership with Google, delivers a 'pure' K8s experience. It has been tested across many clouds and is integrated with modern metrics. The Charmed Kubernetes can be used in full production. Start using Kubernetes today. JAAS will deploy your workload to the cloud of your choice. To allow JAAS access to virtual machines and create them for you, you must provide your cloud credentials. We recommend that users create a new set for JAAS using the public cloud's IAM tool. You can find hundreds of cloud-oriented applications, such as Kubernetes and Apache Hadoop, Big Data solutions, OpenStack, and many others in the store as charms or bundles. They are constantly updated and added to the store.

Enterprise apps will have better operators thanks to a full application graph, declarative integration for legacy estate and Kubernetes, and a full app graph. Juju operator integration allows us keep each operator as simple and consistent as possible, then we compose them to create rich topologies for complex scenarios that support complex scenarios with less YAML. Large-scale operations code can also be governed by the UNIX philosophy of "doing one thing right". The benefits of clarity as well as reuse are the same. It is important to be small. Juju allows you the option to use the same operator pattern across your entire estate, even legacy apps. Model-driven operations significantly reduce maintenance and operation costs for traditional workloads, without the need to re-platform to K8s. Once mastered, legacy apps can be made multi-cloud-ready. The Juju Operator Lifecycle Manager, (OLM), uniquely supports both machine-based and container-based apps with seamless integration.

Self-service platform for developers to create apps, databases and jobs. Scale up from one workload to hundreds of workloads on compute or GPUs. GitOps, self-service workflows and templates, pipelines and templates that are highly configurable, will accelerate every step, from push to production. With observability tools, backups and restores, rollbacks, and a rollback feature, you can deploy preview, staging and production environments securely. Northflank integrates seamlessly with your preferred tools and can accommodate any technology stack. You can deploy on Northflank’s secure infrastructure, or on your own account. Either way, you will get the same developer experience and have total control over your data, deployment regions, security and cloud expenses. Northflank uses Kubernetes to deliver the best of cloud native without the overhead. Northflank offers a cloud deployment option for maximum simplicity. You can also connect your GKE or EKS to Northflank to get a managed platform in minutes.

OpenAI compatible, fast, lightweight, portable and powered by rust. We work with cloud providers to support microservices in web apps, especially edge cloud/CDN computing providers. Use cases include AI inferences, database accesses, CRM, ecommerce and workflow management. We work with streaming frameworks, databases and data to support embedded functions for data filtering. The serverless functions may be database UDFs. They could be embedded into data ingest streams or query results. Write once and run anywhere. Take full advantage of GPUs. In just 5 minutes, you can get started with the Llama 2 models on your device. Retrieval - Argumented Generation (RAG) has become a popular way to build AI agents using external knowledge bases. Create an HTTP microservice to classify images. It runs YOLO models and Mediapipe models natively at GPU speed.

Virtualization Software for AI Infrastructure. Increase GPU utilization by having visibility and control over AI workloads. Run:AI has created the first virtualization layer in the world for deep learning training models. Run:AI abstracts workloads from the underlying infrastructure and creates a pool of resources that can dynamically provisioned. This allows for full utilization of costly GPU resources. You can control the allocation of costly GPU resources. The scheduling mechanism in Run:AI allows IT to manage, prioritize and align data science computing requirements with business goals. IT has full control over GPU utilization thanks to Run:AI's advanced monitoring tools and queueing mechanisms. IT leaders can visualize their entire infrastructure capacity and utilization across sites by creating a flexible virtual pool of compute resources.

Fully managed infrastructure, tools and workflows allow you to build, train and deploy models faster. Scale inference and deploy custom AI & LLMs in seconds on any infrastructure. Schedule batch jobs to handle your most demanding tasks, and only pay per second. Optimize costs by utilizing GPUs, spot instances, and automatic failover. YAML simplifies complex infrastructure setups by allowing you to train with a single command. Automate the scaling up of workers during periods of high traffic, and scaling down to zero when inactive. Deploy cutting edge models with persistent endpoints within a serverless environment to optimize resource usage. Monitor system and inference metrics, including worker counts, GPU utilization, throughput, and latency in real-time. Split traffic between multiple models to evaluate.

We have the infrastructure to meet all your computing needs, whether you need one or thousands GPUs or one vCPU or tens of thousand vCPUs. Our resources are available whenever you need them. Our platform makes switching between GPU and CPU instances a breeze. You can easily deploy, modify and rescale instances to meet your needs. You can get outstanding machine learning performance without breaking your bank. The latest technology for a much lower price. Modern GPUs are built to meet your workload demands. Get access to computing resources that are tailored for your models. Our OblivusAI OS allows you to access libraries and leverage our infrastructure for large-scale inference. Use our robust infrastructure to unleash the full potential of gaming by playing games in settings of your choosing.

Fully serverless platform Cloud Build scales up or down according to load. There is no need to pre-provision servers and pay in advance for additional capacity. Only pay for what you use. Flexibility Enterprises can easily integrate their legacy or home-grown tools into their build process with pre-created extensions to third-party apps and custom build steps. Security and compliance Vulnerability scanning can help you protect your software supply chain from security threats. DevSecOps policies can be used to block the deployment of vulnerable images.

CentML speeds up Machine Learning workloads by optimising models to use hardware accelerators like GPUs and TPUs more efficiently without affecting model accuracy. Our technology increases training and inference speed, lowers computation costs, increases product margins using AI-powered products, and boosts the productivity of your engineering team. Software is only as good as the team that built it. Our team includes world-class machine learning, system researchers, and engineers. Our technology will ensure that your AI products are optimized for performance and cost-effectiveness.

Instead of focusing on building applications and business logic you can let Azure solve hard distributed system problems like reliability, scalability and management. Service Fabric is an open-source project that powers core Azure infrastructure and other Microsoft services like Intune, Skype for Business, Intune and Azure Event Hubs. It also powers Azure Data Factory, Azure Cosmos DB and Azure SQL Database. Dynamics 365 and Cortana are all powered by Service Fabric. Azure Service Fabric is designed to deliver high-availability and durable services at cloud scale. It automatically understands the infrastructure and resource requirements of applications. This allows for automatic scaling, rolling upgrades, and self healing from faults that occur. Without the need to write additional code to address issues such as reliability, scalability or management, you can focus on adding business value to your application.

There is no need to compromise between the convenience and power of infrastructure as a code. Kubestack lets you design your Kubernetes platform using an intuitive, graphical user interface. Export your custom stack to Terraform code to ensure reliable provisioning and long-term sustainability. Platforms built with Kubestack Cloud can be exported to a Terraform root Module, which is based on Kubestack framework. Framework modules are all open-source, which reduces the long-term maintenance effort as well as allowing for easy access to future improvements. To efficiently manage changes with your team, adapt the tried-and-trued pull-request and peer review based workflow. You can reduce the amount of bespoke infrastructure code that you need to maintain and save time in the long-term.

Nendo, the AI audio tool suite, allows you to easily develop and use audio apps. This will increase efficiency and creativity in all aspects of audio production. Machine learning and audio processing codes are no longer a problem. AI is a game-changer for audio production. It amplifies efficiency and creativity across industries that rely on audio. But creating custom AI Audio solutions is difficult and operating them at a large scale is even more challenging. Nendo Cloud empowers developers and business to deploy Nendo apps, use premium AI audio models via APIs, and manage workloads efficiently at scale. Nendo Cloud is the solution for batch processing, model inference, training, and more.

NVIDIA Triton™, an inference server, delivers fast and scalable AI production-ready. Open-source inference server software, Triton inference servers streamlines AI inference. It allows teams to deploy trained AI models from any framework (TensorFlow or NVIDIA TensorRT®, PyTorch or ONNX, XGBoost or Python, custom, and more on any GPU or CPU-based infrastructure (cloud or data center, edge, or edge). Triton supports concurrent models on GPUs to maximize throughput. It also supports x86 CPU-based inferencing and ARM CPUs. Triton is a tool that developers can use to deliver high-performance inference. It integrates with Kubernetes to orchestrate and scale, exports Prometheus metrics and supports live model updates. Triton helps standardize model deployment in production.

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.

Your offline data can be used to make real-time predictions, without the need for custom pipelines. Data consistency is achieved between offline training and online prediction, eliminating train-serve bias. Standardize data engineering workflows within a consistent framework. Feast is used by teams to build their internal ML platforms. Feast doesn't require dedicated infrastructure to be deployed and managed. Feast reuses existing infrastructure and creates new resources as needed. You don't want a managed solution, and you are happy to manage your own implementation. Feast is supported by engineers who can help with its implementation and management. You are looking to build pipelines that convert raw data into features and integrate with another system. You have specific requirements and want to use an open-source solution.

Zyphra, an artificial intelligence company with offices in Palo Alto and Montreal, is growing in London. We're developing MaiaOS, an agent system that combines advanced research in next-gen neuronal network architectures (SSM-hybrids), long-term memories & reinforcement learning. We believe that the future of AGI is a combination of cloud-based and on-device strategies, with an increasing shift towards local inference. MaiaOS was built around a deployment platform that maximizes the efficiency of inference for real-time Intelligence. Our AI and product teams are drawn from top organizations and institutions, including Google DeepMind and Anthropic. They also come from Qualcomm, Neuralink and Apple. We have deep expertise across AI models, learning algorithms, and systems/infrastructure with a focus on inference efficiency and AI silicon performance. The Zyphra team is dedicated to democratizing advanced artificial intelligence systems.

Cloud-hosted AI packages that are managed and cloud-hosted will make it easier to ship AI faster. GPT-4 support is fully integrated. API tokens do not need to be used. Use our low-code framework to build. All major models can be integrated. Get an instant API by deploying. Scale and share your API without having to manage infrastructure. Make prompts, prompt chains, basic Python, and managed APIs. A clever prompt can be turned into a publicly available API that you can share. Python allows you to add logic and routing smarts. Steamship connects with your favorite models and services, so you don't need to learn a different API for each provider. Steamship maintains model output in a standard format. Consolidate training and inference, vector search, endpoint hosting. Import, transcribe or generate text. It can run all the models that you need. ShipQL allows you to query across all the results. Packages are fully-stack, cloud-hosted AI applications. Each instance you create gives you an API and private data workspace.

Tenstorrent DevCloud was created to allow people to test their models on our servers, without having to purchase our hardware. Tenstorrent AI is being built in the cloud to allow programmers to test our AI solutions. After logging in, your first login is free. You can then connect with our team to better assess your needs. Tenstorrent is a group of motivated and competent people who have come together to create the best computing platform for AI/software 2.0. Tenstorrent is a new-generation computing company that aims to address the rapidly increasing computing needs for software 2.0. Tenstorrent is based in Toronto, Canada. It brings together experts in the fields of computer architecture, basic design and neural network compilers. ur processors have been optimized for neural network training and inference. They can also perform other types of parallel computation. Tenstorrent processors are made up of a grid consisting of Tensix cores.

The complete LLM Platform with a superior developer's experience and robust infrastructure. Build, deploy and manage trusted, hyper-personalized and streamlined generative AI applications. Langbase is a new AI tool and inference engine for any LLM. It's an OpenAI alternative that's open-source. The most "developer friendly" LLM platform that can ship hyper-personalized AI applications in seconds.

A system that can scale to millions of users, without requiring an engineering team. Create, customize and deploy your chat-based AI. Finance chatbot. xFinance is a 13-billion-parameter model fine-tuned using LoRA. Our goal was show that impressive results can be achieved in financial NLP without breaking the bank. Your own AI assistant to chat with documents. Single or multiple documents. Simple or complex questions. Easy-to-use deep learning platform, hardware efficient algorithms that speed up inference and lower costs. Real-time monitoring and logging of resource usage and cloud costs for deployed models. xTuring, an open-source AI software for personalization, is a powerful tool. xTuring provides a simple interface for personalizing LLMs based on your data and application.

NVIDIA Picasso, a cloud service that allows you to build generative AI-powered visual apps, is available. Software creators, service providers, and enterprises can run inference on models, train NVIDIA Edify foundation model models on proprietary data, and start from pre-trained models to create image, video, or 3D content from text prompts. The Picasso service is optimized for GPUs. It streamlines optimization, training, and inference on NVIDIA DGX Cloud. Developers and organizations can train NVIDIA Edify models using their own data, or use models pre-trained by our premier partners. Expert denoising network to create photorealistic 4K images The novel video denoiser and temporal layers generate high-fidelity videos with consistent temporality. A novel optimization framework to generate 3D objects and meshes of high-quality geometry. Cloud service to build and deploy generative AI-powered image and video applications.