beam
kubernetes
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beam | kubernetes | |
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30 | 657 | |
7,508 | 106,778 | |
1.5% | 1.3% | |
10.0 | 10.0 | |
6 days ago | 1 day ago | |
Java | Go | |
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.
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.
kubernetes
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My Favorite DevTools to Build AI/ML Applications!
Deploying AI models into production requires tools that can package applications and manage them at scale. Docker simplifies the deployment of AI applications by containerizing them, ensuring that the application runs smoothly in any environment. Kubernetes, an orchestration system for Docker containers, allows for the automated deployment, scaling, and management of containerized applications, essential for AI applications that need to scale across multiple servers or cloud environments.
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Building Scalable GraphQL Microservices With Node.js and Docker: A Comprehensive Guide
To learn more, you can start by exploring the official Kubernetes documentation.
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Building Llama as a Service (LaaS)
With the containerized Node.js/Express API, I could run multiple containers, scaling to handle more traffic. Using a tool called minikube, we can easily spin up a local Kubernetes cluster to horizontally scale Docker containers. It was possible to keep one shared instance of the database, and many APIs were routed with an internal Kubernetes load balancer.
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The power of the CLI with Golang and Cobra CLI
This package is widely used for powerful CLI builds, it is used for example for Kubernetes CLI and GitHub CLI, in addition to offering some cool features such as automatic completion of shell, automatic recognition of flags (the tags) , and you can use -h or -help for example, among other facilities.
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Upgrading Hundreds of Kubernetes Clusters
We closely monitor Kubernetes and cloud providers' updates by following official changelogsand using RSS feeds, allowing us to anticipate potential issues and adapt our infrastructure proactively.
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Kubernetes and back – Why I don't run distributed systems
"You are holding it wrong", huh?
From the homepage https://kubernetes.io/:
"Kubernetes, also known as K8s, is an open-source system for automating deployment, scaling, and management of containerized applications."
Do you see "not recommended for smaller-scale applications" anywhere? Including on the entire home page? Looking for "small", "big" and "large" also yields nothing.
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Open Source Ascendant: The Transformation of Software Development in 2024
Open Source and Cloud Computing: A Match Made in Heaven The cloud is accelerating OSS adoption. Cloud-native technologies like Kubernetes [https://kubernetes.io/] and Istio [https://istio.io/], both open-source projects, are revolutionizing how applications are built and deployed across cloud platforms.
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Get a specific apiVersion manifest from k8s
If you do kubectl explain deployment than (surprise!) you'll get a description for extensions/v1beta1. Because kubectl explain works the same way, just like kubectl get:
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Open source at Fastly is getting opener
Through the Fast Forward program, we give free services and support to open source projects and the nonprofits that support them. We support many of the world’s top programming languages (like Python, Rust, Ruby, and the wonderful Scratch), foundational technologies (cURL, the Linux kernel, Kubernetes, OpenStreetMap), and projects that make the internet better and more fun for everyone (Inkscape, Mastodon, Electronic Frontier Foundation, Terms of Service; Didn’t Read).
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Experience Continuous Integration with Jenkins | Ansible | Artifactory | SonarQube | PHP
In this project, you will understand and get hands on experience around the entire concept around CI/CD from applications perspective. To fully gain real expertise around this idea, it is best to see it in action across different programming languages and from the platform perspective too. From the application perspective, we will be focusing on PHP here; there are more projects ahead that are based on Java, Node.js, .Net and Python. By the time you start working on Terraform, Docker and Kubernetes projects, you will get to see the platform perspective of CI/CD in action.
What are some alternatives?
Apache Arrow - Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing
Apache ZooKeeper - Apache ZooKeeper
Apache Hadoop - Apache Hadoop
bosun - Time Series Alerting Framework
Scio - A Scala API for Apache Beam and Google Cloud Dataflow.
Rundeck - Enable Self-Service Operations: Give specific users access to your existing tools, services, and scripts
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
kine - Run Kubernetes on MySQL, Postgres, sqlite, dqlite, not etcd.
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
BOSH - Cloud Foundry BOSH is an open source tool chain for release engineering, deployment and lifecycle management of large scale distributed services.
Apache Hive - Apache Hive
Juju - Orchestration engine that enables the deployment, integration and lifecycle management of applications at any scale, on any infrastructure (Kubernetes or otherwise).