davidmanukian commented on a change in pull request #373:
URL: https://github.com/apache/airflow-site/pull/373#discussion_r561739322
##########
File path: landing-pages/site/content/en/use-cases/plarium-krasnodar.md
##########
@@ -0,0 +1,17 @@
+---
+title: "Plarium Krasnodar"
+linkTitle: "Plarium Krasnodar"
+quote:
+ text: "Apache Airflow helps us efficiently tackle crucial game dev tasks,
such as working with churn or sorting bank offers."
+ author: "David Manukian"
+logo: "plarium-krasnodar-logo.svg"
+---
+
+##### What was the problem?
+Our Research & Development department carries out experiments that are aimed
at finding better solutions. Previously, we didn't have any suitable tools with
a sufficient number of built-in functions, and we had to orchestrate processes
manually and entirely from scratch every time. This led to difficulties with
dependencies and monitoring when building complex workflows. We needed a tool
that would provide a more centralized approach so that we could see all the
logs, the number of retries, and the task performance time. The most important
thing that we lacked was the ability to backfill historical data and restart
failed tasks.
Review comment:
@leahecole Thank you. We changed the text.
##########
File path: landing-pages/site/content/en/use-cases/plarium-krasnodar.md
##########
@@ -0,0 +1,17 @@
+---
+title: "Plarium Krasnodar"
+linkTitle: "Plarium Krasnodar"
+quote:
+ text: "Apache Airflow helps us efficiently tackle crucial game dev tasks,
such as working with churn or sorting bank offers."
+ author: "David Manukian"
+logo: "plarium-krasnodar-logo.svg"
+---
+
+##### What was the problem?
+Our Research & Development department carries out experiments that are aimed
at finding better solutions. Previously, we didn't have any suitable tools with
a sufficient number of built-in functions, and we had to orchestrate processes
manually and entirely from scratch every time. This led to difficulties with
dependencies and monitoring when building complex workflows. We needed a tool
that would provide a more centralized approach so that we could see all the
logs, the number of retries, and the task performance time. The most important
thing that we lacked was the ability to backfill historical data and restart
failed tasks.
+
+##### How did Apache Airflow help to solve this problem?
+Apache Airflow offers lots of convenient built-in solutions, including
integrative ones. The DAG model helps us avoid errors and follow general
patterns when building workflows. In addition, this platform has a large
community where we can find plenty of sensors and operators that cover 90% of
our cases. This allows us to save ourselves loads of time.
+
+##### What are the results?
+Thanks to Apache Airflow, we've managed to simplify the process of building
complex workflows. Many procedures that are so important for game development,
such as working with the churn rate, processing messages to the support team,
and sorting bank offers, run efficiently, and all issues are resolved
centrally. In addition, Apache Airflow is widely used in the industry, allowing
us to onboard new people to our team more quickly and smoothly.
Review comment:
@leahecole Thank you!
----------------------------------------------------------------
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.
For queries about this service, please contact Infrastructure at:
[email protected]
