Superwise Integrations

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.

Around 25 million engineers work across dozens of distinct functions. Engineers are using New Relic as every company is becoming a software company to gather real-time insight and trending data on the performance of their software. This allows them to be more resilient and provide exceptional customer experiences. New Relic is the only platform that offers an all-in one solution. New Relic offers customers a secure cloud for all metrics and events, powerful full-stack analytics tools, and simple, transparent pricing based on usage. New Relic also has curated the largest open source ecosystem in the industry, making it simple for engineers to get started using observability.

monday.com Work OS is a no-code work management platform that helps teams manage projects and workflows more efficiently. This software provides fully customizable solutions for a wide range of use-cases such as marketing, sales, operations, IT, HR, and many more. With monday.com you can easily plan, manage, and track every project in one place, with the help of time-saving and easy-to-use features such as automations, time tracking, document sharing, real-time collaboration, and more. Multiple visual board views such as Gantt, Kanban, and Cards help you prioritize, structure, and navigate tasks and projects the way that suits you and your team’s needs, while dashboards give a high-level overview of your progress and help you make data-driven decisions. In addition, integrations with apps such as Outlook, Microsoft Teams, Gmail, and Excel, allow you to easily continue working with your favorite tools directly within the platform. monday.com also offers dedicated solutions, such as monday dev and monday sales CRM, designed to answer the needs of specific industries.

Open source platform for machine learning. TensorFlow is a machine learning platform that is open-source and available to all. It offers a flexible, comprehensive ecosystem of tools, libraries, and community resources that allows researchers to push the boundaries of machine learning. Developers can easily create and deploy ML-powered applications using its tools. Easy ML model training and development using high-level APIs such as Keras. This allows for quick model iteration and debugging. No matter what language you choose, you can easily train and deploy models in cloud, browser, on-prem, or on-device. It is a simple and flexible architecture that allows you to quickly take new ideas from concept to code to state-of the-art models and publication. TensorFlow makes it easy to build, deploy, and test.

Keras is an API that is designed for humans, not machines. Keras follows best practices to reduce cognitive load. It offers consistent and simple APIs, minimizes the number required for common use cases, provides clear and actionable error messages, as well as providing clear and actionable error messages. It also includes extensive documentation and developer guides. Keras is the most popular deep learning framework among top-5 Kaggle winning teams. Keras makes it easy to run experiments and allows you to test more ideas than your competitors, faster. This is how you win. Keras, built on top of TensorFlow2.0, is an industry-strength platform that can scale to large clusters (or entire TPU pods) of GPUs. It's possible and easy. TensorFlow's full deployment capabilities are available to you. Keras models can be exported to JavaScript to run in the browser or to TF Lite for embedded devices on iOS, Android and embedded devices. Keras models can also be served via a web API.

TorchScript allows you to seamlessly switch between graph and eager modes. TorchServe accelerates the path to production. The torch-distributed backend allows for distributed training and performance optimization in production and research. PyTorch is supported by a rich ecosystem of libraries and tools that supports NLP, computer vision, and other areas. PyTorch is well-supported on major cloud platforms, allowing for frictionless development and easy scaling. Select your preferences, then run the install command. Stable is the most current supported and tested version of PyTorch. This version should be compatible with many users. Preview is available for those who want the latest, but not fully tested, and supported 1.10 builds that are generated every night. Please ensure you have met the prerequisites, such as numpy, depending on which package manager you use. Anaconda is our preferred package manager, as it installs all dependencies.

Datadog is the cloud-age monitoring, security, and analytics platform for developers, IT operation teams, security engineers, and business users. Our SaaS platform integrates monitoring of infrastructure, application performance monitoring, and log management to provide unified and real-time monitoring of all our customers' technology stacks. Datadog is used by companies of all sizes and in many industries to enable digital transformation, cloud migration, collaboration among development, operations and security teams, accelerate time-to-market for applications, reduce the time it takes to solve problems, secure applications and infrastructure and understand user behavior to track key business metrics.

AWS offers a wide range of services, including database storage, compute power, content delivery, and other functionality. This allows you to build complex applications with greater flexibility, scalability, and reliability. Amazon Web Services (AWS), the world's largest and most widely used cloud platform, offers over 175 fully featured services from more than 150 data centers worldwide. AWS is used by millions of customers, including the fastest-growing startups, large enterprises, and top government agencies, to reduce costs, be more agile, and innovate faster. AWS offers more services and features than any other cloud provider, including infrastructure technologies such as storage and databases, and emerging technologies such as machine learning, artificial intelligence, data lakes, analytics, and the Internet of Things. It is now easier, cheaper, and faster to move your existing apps to the cloud.

Slack, a cloud-based project collaboration software solution that facilitates communication between teams, is designed to seamlessly integrate with other organizations. Slack offers powerful tools and services all integrated into one platform. It provides private channels for interaction within smaller teams, direct channels for sending messages to colleagues, as well as public channels that allow members to start conversations across organizations. Slack is available on Mac, Windows and Android as well as iOS apps. It offers a variety of features including chat, file sharing and collaboration, real-time notifications and two-way audio/video, screen sharing, document imaging and activity tracking and logging.

Jira is a project management tool that allows you to plan and track the work of your entire team. Atlassian's Jira is the #1 tool for software development teams to plan and build great products. Jira is trusted by thousands of teams. It offers a range of tools to help plan, track, and release world-class software. It also allows you to capture and organize issues, assign work, and follow team activity. It integrates with leading developer software for end-toend traceability. Jira can help you break down big ideas into manageable steps, whether they are small projects or large cross-functional programs. Organize your work, create milestones and dependencies, and more. Linking work to goals allows everyone to see how their work contributes towards company objectives, and to stay aligned with what's important. Your next step, suggested by AI. Atlassian Intelligence automatically suggests tasks to help you get your big ideas done.

Keep track of all Ops and Dev incidents and take control. Notify the right people, reduce response times, and avoid alert fatigue. Opsgenie is a modern, incident management platform that ensures critical events are not missed and the right people take the appropriate actions in the shortest time possible. Opsgenie can receive alerts from custom applications and monitoring systems, and will categorize each alert according to importance and timing. On-call schedules ensure that the right people get notified via multiple communication channels, including voice calls, SMS, email, and push messages on mobile phones. Opsgenie automatically escalates any alert that is not acknowledged. This ensures that the incident receives the appropriate attention. Register now for a free trial.

Vertex software allows tax determination, compliance and reporting, tax data and management, as well as document management. It also integrates with core business applications to provide powerful integrations. Vertex combines the best of technology innovation, tax process expertise, and industry partnerships to create a global indirect tax solution. This reduces audit exposure and allows tax departments to add more value to their companies.

Amazon SageMaker, a fully managed service, provides data scientists and developers with the ability to quickly build, train, deploy, and deploy machine-learning (ML) models. SageMaker takes the hard work out of each step in the machine learning process, making it easier to create high-quality models. Traditional ML development can be complex, costly, and iterative. This is made worse by the lack of integrated tools to support the entire machine learning workflow. It is tedious and error-prone to combine tools and workflows. SageMaker solves the problem by combining all components needed for machine learning into a single toolset. This allows models to be produced faster and with less effort. Amazon SageMaker Studio is a web-based visual interface that allows you to perform all ML development tasks. SageMaker Studio allows you to have complete control over each step and gives you visibility.

R is a language and environment that allows for statistical computing and graphics. It is a GNU project that is very similar to the S language environment and environment, which were developed at Bell Laboratories (formerly AT&T now Lucent Technologies) in John Chambers and his colleagues. R can be seen as a different implementation to S. However, most code written for S runs without modification under R. R offers a wide range of statistical (linear, nonlinear modelling and classical statistical tests, time series analysis, classification, clustering and graphic techniques and is extensible. Research in statistical methodology is often done using the S language. R offers an Open Source way to participate in this activity. R's strength is its ability to produce well-designed publications-quality plots, including formulae and mathematical symbols.

Accelerate the entire machine learning lifecycle. Developers and data scientists can have more productive experiences building, training, and deploying machine-learning models faster by empowering them. Accelerate time-to-market and foster collaboration with industry-leading MLOps -DevOps machine learning. Innovate on a trusted platform that is secure and trustworthy, which is designed for responsible ML. Productivity for all levels, code-first and drag and drop designer, and automated machine-learning. Robust MLOps capabilities integrate with existing DevOps processes to help manage the entire ML lifecycle. Responsible ML capabilities – understand models with interpretability, fairness, and protect data with differential privacy, confidential computing, as well as control the ML cycle with datasheets and audit trials. Open-source languages and frameworks supported by the best in class, including MLflow and Kubeflow, ONNX and PyTorch. TensorFlow and Python are also supported.

Data scientists are able to build, improve, or operate end-to–end workflows independently. This allows them to deliver data science projects that are successful. Metaflow can be used with your favorite data science libraries such as SciKit Learn or Tensorflow. You can write your models in idiomatic Python codes with little to no learning. Metaflow also supports R language. Metaflow allows you to design your workflow, scale it, and then deploy it to production. It automatically tracks and versions all your data and experiments. It allows you to easily inspect the results in notebooks. Metaflow comes pre-installed with the tutorials so it's easy to get started. Metaflow allows you to make duplicates of all tutorials in your current directory by using the command line interface.

H2O.ai, the open-source leader in AI and machinelearning, has a mission to democratize AI. Our enterprise-ready platforms, which are industry-leading, are used by thousands of data scientists from over 20,000 organizations worldwide. Every company can become an AI company in financial, insurance, healthcare and retail. We also empower them to deliver real value and transform businesses.

AI Cloud is a new approach that addresses the challenges and opportunities presented by AI today. A single system of records that accelerates the delivery of AI to production in every organization. All users can collaborate in a single environment that optimizes the entire AI lifecycle. The AI Catalog facilitates seamlessly finding, sharing and tagging data. This helps to increase collaboration and speed up time to production. The catalog makes it easy to find the data you need to solve a business problem. It also ensures security, compliance, consistency, and consistency. Contact Support if your database is protected by a network rule that allows connections only from certain IP addresses. An administrator will need to add addresses to your whitelist.

Enterprise plugins such as Splunk, ServiceNow and Datadog allow you to view all your data in one place. Collaboration features built-in allow teams to collaborate from one dashboard. Advanced security and compliance features ensure that your data remains secure. Access to Prometheus, Grafite, Grafana experts, and hands-on support. Other vendors will try and sell you an "everything is in my database" mentality. Grafana Labs has a different approach. We want to help with your observation, not own it. Grafana Enterprise gives you access to enterprise plugins. These plugins allow you to import your data sources into Grafana. This allows you to visualize all data in a more efficient and effective manner, allowing you to get the most out of expensive and complex monitoring systems.

MLflow is an open-source platform that manages the ML lifecycle. It includes experimentation, reproducibility and deployment. There is also a central model registry. MLflow currently has four components. Record and query experiments: data, code, config, results. Data science code can be packaged in a format that can be reproduced on any platform. Machine learning models can be deployed in a variety of environments. A central repository can store, annotate and discover models, as well as manage them. The MLflow Tracking component provides an API and UI to log parameters, code versions and metrics. It can also be used to visualize the results later. MLflow Tracking allows you to log and query experiments using Python REST, R API, Java API APIs, and REST. An MLflow Project is a way to package data science code in a reusable, reproducible manner. It is based primarily upon conventions. The Projects component also includes an API and command line tools to run projects.

Kubeflow is a project that makes machine learning (ML), workflows on Kubernetes portable, scalable, and easy to deploy. Our goal is not create new services, but to make it easy to deploy the best-of-breed open source systems for ML to different infrastructures. Kubeflow can be run anywhere Kubernetes is running. Kubeflow offers a custom TensorFlow job operator that can be used to train your ML model. Kubeflow's job manager can handle distributed TensorFlow training jobs. You can configure the training controller to use GPUs or CPUs, and to adapt to different cluster sizes. Kubeflow provides services to create and manage interactive Jupyter Notebooks. You can adjust your notebook deployment and compute resources to meet your data science requirements. You can experiment with your workflows locally and then move them to the cloud when you are ready.

Software is what transforms a vehicle into a smart machine. Open source software stack NVIDIA DRIVE™, enables developers to quickly build and deploy a variety state-of the-art AV applications. This includes perception, localization, mapping, driver monitoring, planning and control, driver monitoring and natural language processing. DRIVE OS, the foundation of the DRIVE SoftwareStack, is the first secure operating system for accelerated computation. It includes NvMedia to process sensor input, NVIDIACUDA®, libraries for parallel computing implementations that are efficient, NVIDIA TensorRT™ for real time AI inference, as well as other tools and modules for accessing hardware engines. NVIDIA DriveWorks®, a SDK that provides middleware functions over DRIVE OS, is essential for autonomous vehicle development. These include the sensor abstraction layer (SAL), sensor plugins, data recorder and vehicle I/O support.