esp-v2
beam
esp-v2 | beam | |
---|---|---|
7 | 30 | |
260 | 7,519 | |
0.8% | 0.9% | |
7.3 | 10.0 | |
3 days ago | 8 days ago | |
Go | Java | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
esp-v2
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Serverless Security Best Practices
Moreover, integrating rate limiting can thwart DDoS attacks, and schema validation can prevent malformed requests, ensuring only legitimate and well-formed traffic reaches your serverless functions. Tools like Amazon API Gateway, Azure API Management, and Google Cloud Endpoints offer these capabilities, allowing you to set up custom authorization workflows and request validation rules that align with your security requirements.
- GCP ESP JWT authentication bypass via `X-HTTP-Method-Override` header
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API Gateway VS API Endpoints VS Apigee
AFAIK, API Gateway is just managed Cloud Endpoints, which are just ESPv2 containers. Cloud Endpoints are still a thing but I would agree that they are a bit dead, as they don't support OpenAPI v3, which was released in 2016. See this support ticket from 2018: https://issuetracker.google.com/issues/78271318?pli=1
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Google Cloud Reference
Cloud Endpoints: Cloud API gateway 🔗Link
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Any grpc tutorial or github repo that contains best practices to develop production services.
We use the ESPv2 gateway (https://github.com/GoogleCloudPlatform/esp-v2) to transcode between REST/JSON and gRPC/protobuf for client-to-backend communication.
beam
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Ask HN: Does (or why does) anyone use MapReduce anymore?
The "streaming systems" book answers your question and more: https://www.oreilly.com/library/view/streaming-systems/97814.... It gives you a history of how batch processing started with MapReduce, and how attempts at scaling by moving towards streaming systems gave us all the subsequent frameworks (Spark, Beam, etc.).
As for the framework called MapReduce, it isn't used much, but its descendant https://beam.apache.org very much is. Nowadays people often use "map reduce" as a shorthand for whatever batch processing system they're building on top of.
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beam VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
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How do Streaming Aggregation Pipelines work?
Apache Beam is one of many tools that you can use
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Releasing Temporian, a Python library for processing temporal data, built together with Google
Flexible runtime ☁️: Temporian programs can run seamlessly in-process in Python, on large datasets using Apache Beam.
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Kafka cluster loses or duplicates messages
To perform the tests I'm using a Kafka cluster on Kubernetes from the Beam repo (here).
- Apache Beam
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Real Time Data Infra Stack
Apache Beam: Streaming framework which can be run on several runner such as Apache Flink and GCP Dataflow
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Google Cloud Reference
Apache Beam: Batch/streaming data processing 🔗Link
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Composer out of resources - "INFO Task exited with return code Negsignal.SIGKILL"
What you are looking for is Dataflow. It can be a bit tricky to wrap your head around at first, but I highly suggest leaning into this technology for most of your data engineering needs. It's based on the open source Apache Beam framework that originated at Google. We use an internal version of this system at Google for virtually all of our pipeline tasks, from a few GB, to Exabyte scale systems -- it can do it all.
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Pub/Sub parallel processing best practices
That being said, there is a learning curve in understanding how Apache Beam works. Take a look at the beam website for more information.
What are some alternatives?
goku_lite - A Powerful HTTP API Gateway in pure golang!Goku API Gateway (中文名:悟空 API 网关)是一个基于 Golang开发的微服务网关,能够实现高性能 HTTP API 转发、服务编排、多租户管理、API 访问权限控制等目的,拥有强大的自定义插件系统可以自行扩展,并且提供友好的图形化配置界面,能够快速帮助企业进行 API 服务治理、提高 API 服务的稳定性和安全性。
Apache Arrow - Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing
grpcstreams - An example of using grpc Server side streaming
Apache Hadoop - Apache Hadoop
iam-go - An opinionated Open Source implementation of the google.iam APIs on top of Cloud Spanner.
Scio - A Scala API for Apache Beam and Google Cloud Dataflow.
protoc-gen-typescript-http - Generate types and service clients from protobuf definitions annotated with http rules.
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
aip-go - Go SDK for implementing resource-oriented gRPC APIs.
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
social - social network in GRPC, Go, mysql, and vuejs,
Apache Hive - Apache Hive