talatuyarer commented on code in PR #29305: URL: https://github.com/apache/beam/pull/29305#discussion_r1385508822
########## website/www/site/content/en/blog/apache-beam-flink-and-kubernetes.md: ########## @@ -0,0 +1,355 @@ +--- +title: "How to Build a Scalable Self-Managed Streaming Infrastructure with Beam and Flink" +date: 2023-11-03 09:00:00 -0400 +categories: + - blog +authors: + - talat +--- +<!-- +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at +http://www.apache.org/licenses/LICENSE-2.0 +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +--> + +In this blog series, [Talat Uyarer (Senior Principal Engineer)](https://www.linkedin.com/in/talatuyarer/), [Rishabh Kedia (Principal Engineer)](https://www.linkedin.com/in/rishabhkedia/), and [David He (Engineering Director)](https://www.linkedin.com/in/davidqhe/) will describe how we built a self managed streaming platform and our learnings by using Apache Beam and Flink. In part I, we describe why and how we built a large-scale self managed streaming infrastructure and services based on Flink, by migrating from a cloud managed streaming service, and the learnings for operational scalability and observability, performance, and cost effectiveness. We summarize useful techniques, and experience in our journey. + +<!--more--> + +# How to Build a Scalable Self Managed Streaming Infrastructure with Flink - Part 1 + +# Introduction + +Palo Alto Networks (PANW) is a leader in cybersecurity, providing products, services and solutions to our customers. Data is the center of our products and services. We stream and store exabytes of data in our data lake, with near real-time ingestion, data transformation, data insertion to data store, and forwarding data to our internal ML-based systems and external SIEM’s. We support multi-tenancy in each component so that we can isolate tenants and provide optimal performance and SLA. Streaming processing plays a critical role in the pipelines. Review Comment: In This context PANW is we. Because I am working for PANW :) -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
