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Posted to commits@airflow.apache.org by GitBox <gi...@apache.org> on 2021/01/15 15:11:10 UTC
[GitHub] [airflow-site] davidmanukian opened a new pull request #373: Add Plarium-Krasnodar use case
davidmanukian opened a new pull request #373:
URL: https://github.com/apache/airflow-site/pull/373
Plarium Krasnodar use case
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[GitHub] [airflow-site] leahecole commented on pull request #373: Add Plarium-Krasnodar use case
Posted by GitBox <gi...@apache.org>.
leahecole commented on pull request #373:
URL: https://github.com/apache/airflow-site/pull/373#issuecomment-764963574
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[GitHub] [airflow-site] leahecole commented on pull request #373: Add Plarium-Krasnodar use case
Posted by GitBox <gi...@apache.org>.
leahecole commented on pull request #373:
URL: https://github.com/apache/airflow-site/pull/373#issuecomment-764963574
LGTM!
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[GitHub] [airflow-site] leahecole commented on a change in pull request #373: Add Plarium-Krasnodar use case
Posted by GitBox <gi...@apache.org>.
leahecole commented on a change in pull request #373:
URL: https://github.com/apache/airflow-site/pull/373#discussion_r560392953
##########
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:
"...aimed at finding better solutions." <- this first sentence may be stronger if you expand on this point by giving either some general types of solutions or a specific one. For example (I'm totally making these up, they may have nothing to do with your use case 😄 )
- "better solutions to our customer's data analytics problems"
- "better solutions to slow, manual data pipelines"
- "better solutions to solve the problems our developers encounter daily."
- "alternatives to ..." (instead of solutions)
##########
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.
Review comment:
😍 for the Airflow community shoutout
##########
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:
```suggestion
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, now 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.
```
I just added "now" here to help with this big sentence. You could retool the sentence a little bit, but I'm not sure if it would be worth it. It might just be one of those cases where I don't like this sentence because the English language is the worst and not because I don't like how you wrote it 😁
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[GitHub] [airflow-site] davidmanukian commented on a change in pull request #373: Add Plarium-Krasnodar use case
Posted by GitBox <gi...@apache.org>.
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!
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[GitHub] [airflow-site] mik-laj merged pull request #373: Add Plarium-Krasnodar use case
Posted by GitBox <gi...@apache.org>.
mik-laj merged pull request #373:
URL: https://github.com/apache/airflow-site/pull/373
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[GitHub] [airflow-site] davidmanukian commented on pull request #373: Add Plarium-Krasnodar use case
Posted by GitBox <gi...@apache.org>.
davidmanukian commented on pull request #373:
URL: https://github.com/apache/airflow-site/pull/373#issuecomment-770628266
I see we have all three green checks. Are we ready to merge?
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[GitHub] [airflow-site] rachael-ds commented on a change in pull request #373: Add Plarium-Krasnodar use case
Posted by GitBox <gi...@apache.org>.
rachael-ds commented on a change in pull request #373:
URL: https://github.com/apache/airflow-site/pull/373#discussion_r562770626
##########
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 various experiments, and in all of them, we need to create workflow orchestrations for solving tasks in game dev. 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.
Review comment:
This is awesome - from my experience, not everyone gets what operators are/why are they useful until they start using them. This is such a minor point on the last sentence, feel free to ignore :)
_This saves us time by reducing the amount code we need to write and maintain._
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[GitHub] [airflow-site] mik-laj commented on pull request #373: Add Plarium-Krasnodar use case
Posted by GitBox <gi...@apache.org>.
mik-laj commented on pull request #373:
URL: https://github.com/apache/airflow-site/pull/373#issuecomment-761696886
@mschickensoup @leahecole Can you look at it?
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[GitHub] [airflow-site] leahecole commented on pull request #373: Add Plarium-Krasnodar use case
Posted by GitBox <gi...@apache.org>.
leahecole commented on pull request #373:
URL: https://github.com/apache/airflow-site/pull/373#issuecomment-764963698
@ryw @aijamalnk any objections?
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[GitHub] [airflow-site] davidmanukian commented on a change in pull request #373: Add Plarium-Krasnodar use case
Posted by GitBox <gi...@apache.org>.
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.
----------------------------------------------------------------
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[GitHub] [airflow-site] davidmanukian commented on a change in pull request #373: Add Plarium-Krasnodar use case
Posted by GitBox <gi...@apache.org>.
davidmanukian commented on a change in pull request #373:
URL: https://github.com/apache/airflow-site/pull/373#discussion_r561745231
##########
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!
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