Search Results for "teams"
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Showing 34 open source projects for "teams"
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Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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DataHub
The Metadata Platform for your Data and AI Stack
...A modern web UI and search layer make it easy for analysts, engineers, and stewards to find assets, read documentation, and see context such as usage, schema history, and downstream impacts. Governance features such as glossaries, tags, ownership, and policies bring order and accountability without blocking day-to-day work. APIs and SDKs enable teams to integrate DataHub into catalogs, CI pipelines, and automation so metadata becomes part of the development lifecycle rather than an afterthought. -
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Apache DevLake
Apache DevLake is an open-source dev data platform
...From DORA to scrum retros, DevLake implements metrics effortlessly with prebuilt dashboards supporting common frameworks and goals. DevLake fits teams of all shapes and sizes, and can be readily extended to support new data sources, metrics, and dashboards, with a flexible framework for data collection and transformation. -
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Airbyte
Data integration platform for ELT pipelines from APIs, databases
...Airbyte already provides the largest catalog of 300+ connectors for APIs, databases, data warehouses, and data lakes. Moving critical data with Airbyte is as easy and reliable as flipping on a switch. Our teams process more than 300 billion rows each month for ambitious businesses of all sizes. Enable your data engineering teams to focus on projects that are more valuable to your business. Building and maintaining custom connectors have become 5x easier with Airbyte. With an average response rate of 10 minutes or less and a Customer Satisfaction score of 96/100, our team is ready to support your data integration journey all over the world. -
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Architecture as a code
Visualize, collaborate, and evolve the software architecture
...The project includes command-line tooling, IDE integrations, live preview servers, and diagram exporters, letting developers instantly see architectural diagrams update as the model evolves. By treating architecture as code, teams benefit from version control, live collaboration, consistency across diagrams, and the ability to treat architectural change with the same tooling and workflows used for code. -
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5
Backstage
Backstage is an open platform for building developer portals
Powered by a centralized software catalog, Backstage restores order to your infrastructure and enables your product teams to ship high-quality code quickly, without compromising autonomy. At Spotify, we've always believed in the speed and ingenuity that comes from having autonomous development teams. But as we learned firsthand, the faster you grow, the more fragmented and complex your software ecosystem becomes. And then everything slows down again. -
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Zingg
Scalable master data management and identity resolution
...It uses machine learning to learn how records should be compared, reducing the need for brittle hand-written matching rules. The project is designed for data engineering and analytics teams working on customer 360, supplier 360, deduplication, fuzzy matching, data quality, and golden record workflows. Zingg runs on Apache Spark and can scale to large data lake, warehouse, and cloud platform environments. It supports configuration-driven pipelines where users define input data, match fields, training data, models, and output destinations. ... -
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Great Expectations
Always know what to expect from your data
Great Expectations helps data teams eliminate pipeline debt, through data testing, documentation, and profiling. Software developers have long known that testing and documentation are essential for managing complex codebases. Great Expectations brings the same confidence, integrity, and acceleration to data science and data engineering teams. Expectations are assertions for data. -
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Rackula
Drag and drop rack visualizer
...The tool emphasizes clarity and ease of use so that both hobbyists and professionals can plan wiring, sizing, and space allocation before physically committing to changes. It also supports exporting and sharing of layouts, which is useful for documentation or collaboration across teams. Community contributions focus on persistent storage, self-hosting guides, and UI improvements that make Rackula more adaptable for different environments. -
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Timesketch
Collaborative forensic timeline analysis
...Powerful search, aggregations, and saved views help you pivot quickly, highlight anomalies, and preserve investigative steps for later review. The system supports tagging, sketch notes, and story building so teams can annotate findings and share context without losing the raw data trail. Integrations with popular DFIR pipelines make ingestion repeatable, while role-based access and audit logs support enterprise workflows. By combining scale, collaboration, and reproducibility, Timesketch moves incident response beyond ad-hoc spreadsheets to a durable, team-oriented investigation record. -
Paessler: Easy to Use With Enterprise Power. Free TrialYou shouldn't have to choose between a monitoring tool that's easy to use and one that's powerful enough for a complex environment. PRTG's low-code interface lets any admin build dashboards, set alerts and monitor devices without scripting, while custom sensors and full API access are there when your team needs deeper control. One platform, no compromise. Download a free 30-day trial now.
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Amazon SageMaker Examples
Jupyter notebooks that demonstrate how to build models using SageMaker
...It uses the familiar JupyterLab interface and has seamless integration with a variety of deep learning and data science environments and scalable compute resources for training, inference, and other ML operations. Studio offers teams and companies easy on-boarding for their team members, freeing them up from complex systems admin and security processes. Administrators control data access and resource provisioning for their users. Notebook Instances are another option. They have the familiar Jupyter and JuypterLab interfaces that work well for single users, or small teams where users are also administrators. ... -
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FossFLOW
Make beautiful isometric infrastructure diagrams
...Because it runs fully client-side with offline support, users can design diagrams without sending data to external servers. FossFLOW focuses on usability through drag-and-drop components, connector tools, and automatic saving capabilities. Overall, it serves engineers and technical teams who want a modern, open alternative to traditional diagramming tools with a strong visual infrastructure focus. -
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Checkmate
Checkmate is an open-source, self-hosted tool
...The system is designed to scale, having been stress-tested with more than a thousand active monitors without major performance issues. Checkmate also includes incident tracking and notification capabilities so teams can quickly respond to outages or anomalies. Overall, the platform serves as a comprehensive, developer-friendly alternative to commercial uptime and infrastructure monitoring tools. -
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Koito
Koito is a modern, themeable scrobbler
Koito is a lightweight, self-hostable collaborative knowledge base and note-taking platform designed to help teams and individuals capture, organize, and link ideas with the reliability of a local or private server rather than relying on managed SaaS tools. It combines concepts from wikis, Zettelkasten systems, and modern note apps by letting you create interconnected notes, bidirectional links, and structured collections that mirror how knowledge naturally grows. -
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Pyper
Concurrent Python made simple
...Unlike heavier platforms like Airflow, Pyper aims to remain lean, modular, and developer-friendly, embracing Pythonic conventions and minimizing boilerplate. It focuses on local development ergonomics and seamless transition to production environments, making it ideal for small teams and individuals needing a programmable and flexible orchestration solution without the overhead of enterprise systems. -
15
nw_wrld
nw_wrld is an event-driven sequencer for triggering visuals
...It also includes utilities to derive metadata from worlds, such as climate distributions, strategic points of interest, and navigable paths, which can be consumed by gameplay systems or AI agents. For teams building games or simulations, nw_wrld provides a reusable foundation that reduces upfront world design costs while enabling endless variety. -
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rudderstack
Privacy and Security focused Segment-alternative, in Golang
...Our complete toolset makes it easy to level-up your customer data stack. Spare your data engineers the headache. Our 180+ integrations, along with custom webhook sources and destinations, save data teams hundred of hours. Say goodbye to different versions of the truth. Our SDKs track anonymous and known users at the source and reconcile users in your warehouse and SaaS tools. Go beyond event streaming and control all of your customer data on your own terms. Learn how we can help you build a customer data platform. RudderStack treats your data warehouse as a first-class citizen among destinations, with advanced features and configurable, near real-time sync. ... -
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ClearML
Streamline your ML workflow
ClearML is an open source platform that automates and simplifies developing and managing machine learning solutions for thousands of data science teams all over the world. It is designed as an end-to-end MLOps suite allowing you to focus on developing your ML code & automation, while ClearML ensures your work is reproducible and scalable. The ClearML Python Package for integrating ClearML into your existing scripts by adding just two lines of code, and optionally extending your experiments and other workflows with ClearML powerful and versatile set of classes and methods. ... -
18
Kubernetes History Inspector
A log viewer for Kubernetes troubleshooting
...The project aligns with Google Cloud’s broader ecosystem of tools that help developers build scalable, containerized applications while maintaining visibility into system behavior. It often emphasizes integration with Kubernetes clusters, cloud-native APIs, and modern DevOps practices, allowing teams to manage complex workloads more efficiently. Although not a beginner-oriented repository, it provides valuable components and reference implementations for advanced users building production systems. -
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Blueprint MCP
Diagram generation for understanding codebases and system architecture
Blueprint MCP is a modular control plane designed for managing and orchestrating multiple game-server clusters in real time, giving operators fine-grained control over scaling, configuration, and deployment workflows across distributed infrastructure. It provides a central management REST API and dashboard where teams can view cluster health, adjust instance fleets, set auto-scaling policies, and monitor usage metrics in a unified interface. Blueprint-MCP also supports templated server configurations so game environments can be versioned, replicated, and deployed consistently across regions or cloud providers. The control plane includes hooks for event-driven automation, allowing rules like “scale up at peak hours” or “restart unhealthy nodes automatically” to be codified and managed without manual intervention. ... -
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Jitsu
Jitsu is an open-source Segment alternative
Jitsu is a fully-scriptable data ingestion engine for modern data teams. Set-up a real-time data pipeline in minutes, not days. Installing Jitsu is a matter of selecting your framework and adding few lines of code to your app. Jitsu is built to be framework agnostic, so regardless of your stack, we have a solution that'll work for your team. Connect data warehouse (Snowflake, Clickhouse, BigQuery, S3, Redshift ot Postgres) and query your data instantly. -
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Searchkick
Intelligent search made easy
...It integrates with Rails scopes and authorization patterns, making it straightforward to return only records the user can see. By wrapping complex search infrastructure in a clean Ruby interface, Searchkick lets teams deliver fast, relevant search experiences without becoming experts. -
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Ridgepole
Ridgepole is a tool to manage DB schema. It defines DB schema
...This diff-and-apply approach makes schema changes repeatable and reviewable, avoiding hand-written migrations for routine structural edits. It supports multiple environments and options to ignore benign differences (such as auto-generated defaults), reducing churn in teams and CI pipelines. Dumps can be generated from an existing database, making it easy to adopt the tool on legacy systems and then evolve via code reviews. Used alongside application frameworks or standalone, Ridgepole offers a tidy workflow for versioning and promoting schema changes safely across development, staging, and production. -
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ODD Platform
First open-source data discovery and observability platform
Unlock the power of big data with OpenDataDiscovery Platform. Experience seamless end-to-end insights, powered by unprecedented observability and trust - from ingestion to production - while building your ideal tech stack! Democratize data and accelerate insights. Find data that fits your use case and discover hints left by your peers to leverage existing knowledge. Explore tags, ownership details, links to other sources and other information to shorten and simplify data discovery phase.... -
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Dagster
An orchestration platform for the development, production
...Dagster as a robust orchestration engine: Put your pipelines into production with a robust multi-tenant, multi-tool engine that scales technically and organizationally. Dagster as a unified control plane: The ‘single plane of glass’ data teams love to use. Rein in the chaos and maintain control over your data as the complexity scales. Centralize your metadata in one tool with built-in observability, diagnostics, cataloging, and lineage. Spot any issues and identify performance improvement opportunities. -
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CPQ Metrics & KPI Dictionary
Standard CPQ metrics for quote speed, approvals and commercial control
...Includes an Excel workbook, CSV and JSON dictionaries, JSON Schema, dashboard specification, data requirements, implementation checklist and fictional examples. For pricing, sales operations, revenue operations, deal desk, CPQ, BI and analytics teams. No industry benchmarks, KPI targets or recommended thresholds are provided. Published by Configure to WIN: https://configure.win/ https://configure.win/resources/cpq-metrics
