NetBrain, founded in 2004, provides a powerful no-code automation platform for hybrid network observability, allowing organizations to enhance their operational efficiency through automated workflows. The platform applies automation across three key workflows: troubleshooting, change management, and assessment.
Get network-wide and contextualized analysis across your multi-vendor, multi-cloud network
Visualize and document the entire hybrid network using dynamic network maps and end-to-end paths
Automate network discovery and ensure data accuracy for a single source of truth
Auto-discover and decode your network's golden configurations, discover day 1 issues, and automate configuration drift prevention
Automate pre- and post-validations for network changes with application performance context understanding
Automate collaborative troubleshooting from human to machine
For every network troubleshooting idea, create a map, apply automation from your own library
Build. Test. Automate.
Empower your whole team to build and maintain automated tests, not just developers.
Meet your testing demands fast. Get full test coverage in days, not months.
Our natural-language tests are extremely stable to code changes. When tests break our AI will repair it in minutes.
Go Agile/DevOps by setting up Continuous Testing. Push features in production the same day.
Boozang supports the following test approaches:
- Codeless Record/Replay interface
- BDD / Cucumber
- API testing
- Model-based testing
- HTML Canvas testing
The following features makes your testing a breeze
- In-browser console debugging
- Screenshots to show where test fails
- Integrate to any CI server
- Test with unlimited parallel workers to speed up tests
- Root-cause analysis reports
- Trend reports to track failures and performance over time
- Test management integration (Xray / Jira)
Continuous performance testing software to automate API and application load testing. Design code-less performance tests for complex applications. Script performance tests <as:code /> within automated pipelines for API testing. Design, maintain and run performance tests as code and analyze results within continuous integration pipelines using pre-packaged plugins for CI/CD tools and the NeoLoad API. Create test scripts quickly for large, complex applications using a graphical user interface and skip the complexity of hand coding new and updated tests. Define SLAs based on built-in monitoring metrics. Put pressure on the app and compare SLAs to server-level statistics to determine performance. Automate pass/fail triggers based on SLAs. Contributes to root cause analysis. Update test scripts faster with automatic test script updates. Update only the part of the test that’s changed and re-use the rest for easy test maintenance.
Edge Delta is a new way to do observability that helps developers and operations teams monitor datasets and create telemetry pipelines. We process your log data as it's created and give you the freedom to route it anywhere.
Our primary differentiator is our distributed architecture. We are the only observability provider that pushes data processing upstream to the infrastructure level, enabling users to process their logs and metrics as soon as they’re created at the source.
We combine our distributed approach with a column-oriented backend to help users store and analyze massive data volumes without impacting performance or cost.
By using Edge Delta, customers can reduce observability costs without sacrificing visibility. Additionally, they can surface insights and trigger alerts before data leaves their environment.
Cloud-based observability solution that helps businesses track and manage workload and performance on a unified dashboard.
Monitor everything you run in your cloud without compromising on cost, granularity, or scale. groundcover is a full stack cloud-native APM platform designed to make observability effortless so that you can focus on building world-class products. By leveraging our proprietary sensor, groundcover unlocks unprecedented granularity on all your applications, eliminating the need for costly code changes and development cycles to ensure monitoring continuity.
100% visibility, all the time.
Cover your entire Kubernetes stack instantly, with no code changes using the superpowers of eBPF instrumentation.
Take control of your data, all in-cloud.
groundcover’s unique inCloud architecture keeps your data private, secured and under your control without ever leaving your cloud premises.
There are an estimated 25 million engineers in the world across dozens of distinct functions. As every company becomes a software company, engineers are using New Relic to gather real-time insights and trending data about the performance of their software so they can be more resilient and deliver exceptional customer experiences. Only New Relic provides an all-in-one platform that is built and sold as a unified experience. With New Relic, customers get access to a secure telemetry cloud for all metrics, events, logs, and traces; powerful full-stack analysis tools; and simple, transparent usage-based pricing with only 2 key metrics. New Relic has also curated one of the industry’s largest ecosystems of open source integrations, making it easy for every engineer to get started with observability and use New Relic alongside their other favorite applications.
The training data platform for AI teams. A machine learning model is only as good as its training data. Labelbox is an end-to-end platform to create and manage high-quality training data all in one place, while supporting your production pipeline with powerful APIs. Powerful image labeling tool for image classification, object detection and segmentation. When every pixel matters, you need accurate and intuitive image segmentation tools. Customize the tools to support your specific use case, including instances, custom attributes and much more. Performant video labeling editor for cutting-edge computer vision. Label directly on the video up to 30 FPS with frame level. Additionally, Labelbox provides per frame label feature analytics enabling you to create better models faster. Creating training data for natural language intelligence has never been easier. Label text strings, conversations, paragraphs, and documents with fast & customizable classification.
Build, deploy, and scale machine learning (ML) models faster, with fully managed ML tools for any use case.
Through Vertex AI Workbench, Vertex AI is natively integrated with BigQuery, Dataproc, and Spark. You can use BigQuery ML to create and execute machine learning models in BigQuery using standard SQL queries on existing business intelligence tools and spreadsheets, or you can export datasets from BigQuery directly into Vertex AI Workbench and run your models from there. Use Vertex Data Labeling to generate highly accurate labels for your data collection.
Statseeker is a fully-featured network performance monitoring solution. It's highly scalable and delivers fast real-time performance data from a minimal server footprint.
Statseeker can be up and running within minutes, and discovering your entire network in less than an hour, without any significant effect on your bandwidth availability.
Statseeker monitors networks of any size, polling up to one million interfaces every 60 seconds, collecting network data such as SNMP, ping, NetFlow (sFlow and J-Flow), syslog and trap messages and API data, as well as SDN configuration and health metrics.
Your network performance data is never averaged or rolled up. This removes the guesswork in identifying over- and underutilized infrastructure, conducting root cause analysis, or capacity planning.
Statseeker's out-of-the-box dashboards and reports give you the contextual data needed to proactively monitor your network and fix problems before users are aware.
Derive insights from your images in the cloud or at the edge with AutoML Vision or use pre-trained Vision API models to detect emotion, understand text, and more. Google Cloud offers two computer vision products that use machine learning to help you understand your images with industry-leading prediction accuracy. Automate the training of your own custom machine learning models. Simply upload images and train custom image models with AutoML Vision’s easy-to-use graphical interface; optimize your models for accuracy, latency, and size; and export them to your application in the cloud, or to an array of devices at the edge. Google Cloud’s Vision API offers powerful pre-trained machine learning models through REST and RPC APIs. Assign labels to images and quickly classify them into millions of predefined categories. Detect objects and faces, read printed and handwritten text, and build valuable metadata into your image catalog.