#go #app_mesh #cloud_native #cncf #consul #control_plane #docker #envoy #gitops #golang #gsoc #hacktoberfest #infrastructure_as_code #istio #kubernetes #linkerd #management_plane #meshery #reactjs #service_mesh #visualization

https://github.com/meshery/meshery

#go #builder #buildkit #cloud_native #containers #docker #dockerfile #golang #oci #oci_image

https://github.com/moby/buildkit

#go #cloud_native #ebpf #energy_consumption #energy_efficiency #energy_monitor #kubernetes #machine_learning #prometheus #prometheus_exporter #sustainability

https://github.com/sustainable-computing-io/kepler

#go #cloud_native #kubernetes #kubernetes_operator #logging #operator

https://github.com/kube-logging/logging-operator

#java #cloud_native_java #docker #gradle_plugin #hacktoberfest #kubernetes #maven_plugin #openshift

https://github.com/eclipse/jkube

#html #blueteam #cloud_native #cloud_security #cloudsecurity #container #container_security #devsecops #docker #hacking #infrastructure #k8s #kubernetes #kubernetes_goat #kubernetes_security #owasp #pentesting #redteam #security #vulnerable_app

https://github.com/madhuakula/kubernetes-goat

#go #anns #cloud_native #distributed #embedding_database #embedding_similarity #embedding_store #faiss #golang #hnsw #image_search #llm #nearest_neighbor_search #tensor_database #vector_database #vector_search #vector_similarity #vector_store

Milvus is an open-source vector database designed for embedding similarity search and AI applications. It makes unstructured data search more accessible and provides a consistent user experience across different deployment environments. Key features include millisecond search on trillion vector datasets, simplified unstructured data management, reliable and always-on operations, high scalability, and hybrid search capabilities. Milvus is cloud-native, supports multiple SDKs, and has a strong community with extensive documentation and support channels like Discord and mailing lists. Using Milvus benefits users by enabling fast and efficient vector searches, simplifying data management, and ensuring reliability and scalability in their applications.

https://github.com/milvus-io/milvus

#java #airflow #azkaban #cloud_native #data_pipelines #job_scheduler #orchestration #powerful_data_pipelines #task_scheduler #workflow #workflow_orchestration #workflow_schedule

Apache DolphinScheduler is a powerful tool for managing data workflows. It makes it easy to create and manage complex tasks with a user-friendly interface and low-code options. You can deploy it in several ways, including standalone, cluster, Docker, and Kubernetes, making it flexible for different environments. It's highly reliable, scalable, and performs much faster than other platforms, supporting millions of tasks daily. The tool also offers features like versioning, state control of workflows, multi-tenancy support, and permission control. This helps you manage your data pipelines efficiently and reliably, saving time and effort.

https://github.com/apache/dolphinscheduler

#c_lang #bigdata #cloud_native #cluster #connected_vehicles #database #distributed #financial_analysis #industrial_iot #iot #metrics #monitoring #scalability #sql #tdengine #time_series #time_series_database #tsdb

TDengine is a powerful, open-source time-series database designed for handling large amounts of data from IoT devices, connected cars, and industrial IoT. Here are the key benefits It can handle billions of data collection points efficiently, outperforming other time-series databases in data ingestion, querying, and compression.
- **Simplified Solution** Designed for cloud environments, it supports distributed design, sharding, partitioning, and Kubernetes deployment.
- **Ease of Use** Makes data exploration and access efficient through features like super tables and pre-computation.
- **Open Source**: Available under open source licenses with an active developer community.

Using TDengine helps you manage and analyze large-scale time-series data efficiently, making it ideal for various IoT and industrial applications.

https://github.com/taosdata/TDengine

#go #ai_gateway #ai_native #api_gateway #cloud_native #envoy

Higress is a powerful API gateway that uses AI and is built on top of Envoy and Istio. It helps manage traffic for AI services, microservices, and other applications. Here are the key benefits You can start Higress with just a Docker command, making it simple for personal developers to set up and use.
- **AI Integration** It is designed for large-scale scenarios, handling tens of thousands of requests per second without disrupting the service.
- **Flexible Expansion** It includes WAF protection, multiple authentication strategies, and automatic SSL certificate management, ensuring your applications are secure.

Overall, Higress makes managing and scaling your applications easier, more efficient, and secure.

https://github.com/alibaba/higress

#cplusplus #analytics #bigquery #cloud_native #cpp #database #distributed_database #distributed_transactions #hacktoberfest #htap #mysql #mysql_compatibility #mysql_database #oceanbase #olap #oltp #paxos #scalable #sql #vector_database

OceanBase Database is a powerful, distributed relational database developed by Ant Group. It offers several key benefits It can handle large amounts of data and scale easily.
- **Fast Performance** It saves up to 90% on storage costs.
- **Real-time Analytics** It ensures zero data loss and quick recovery times.
- **MySQL Compatibility**: It is easy to migrate from MySQL databases.

You can quickly start using OceanBase with simple deployment options using commands or Docker, making it easy to get started and benefit from its advanced features.

https://github.com/oceanbase/oceanbase

#go #cloud_native #database #distributed_database #distributed_transactions #go #hacktoberfest #htap #mysql #mysql_compatibility #scale #serverless #sql #tidb

TiDB is an open-source database that combines transactional and analytical processing. It is compatible with MySQL, scalable, consistent, and highly available. This means you can handle a lot of data and queries efficiently without worrying about the database crashing. You can try it online through the TiDB Playground or start using it with a quick start guide. The community is active, so you can get help from forums, Discord, Slack, and Stack Overflow. This makes it easier to use and maintain, benefiting users by providing a reliable and powerful database solution.

https://github.com/pingcap/tidb

#go #bigdata #cloud_native #distributed_systems #filesystem #go #golang #hdfs #object_storage #posix #redis #s3 #storage

JuiceFS is a powerful file system designed for cloud environments. It allows you to use massive cloud storage as if it were local storage, without changing your code. Here are the key benefits JuiceFS offers low latency and high throughput, making it suitable for big data, machine learning, and AI applications.
- **POSIX Compatibility** Supports Kubernetes and various object storage services like Amazon S3, Google Cloud Storage, and more.
- **Strong Consistency** Ensures data security and efficiency.
- **Shared Access**: Multiple clients can read and write files simultaneously.

Using JuiceFS, you can efficiently manage large amounts of data in the cloud, making it easier to integrate with various platforms and applications.

https://github.com/juicedata/juicefs