This document provides information about an AWS webinar on AWS Step Functions hosted by Yuta Imamura from Amazon Web Services Japan. The agenda includes an overview of Step Functions, state machines, data input and output, describing states, checking execution status, and additional details. Step Functions allows orchestrating distributed applications and microservices using state machines defined in Amazon States Language (ASL). States can pass data and parameters between each other to synchronize processes.
AWS Japan YouTube 公式チャンネルでライブ配信された 2022年4月26日の AWS Developer Live Show 「Infrastructure as Code 談議 2022」 の資料となります。 当日の配信はこちら からご確認いただけます。
https://youtu.be/ed35fEbpyIE
In the first half, we give an introduction to modern serialization systems, Protocol Buffers, Apache Thrift and Apache Avro. Which one does meet your needs?
In the second half, we show an example of data ingestion system architecture using Apache Avro.
This document summarizes a microservices meetup hosted by @mosa_siru. Key points include:
1. @mosa_siru is an engineer at DeNA and CTO of Gunosy.
2. The meetup covered Gunosy's architecture with over 45 GitHub repositories, 30 stacks, 10 Go APIs, and 10 Python batch processes using AWS services like Kinesis, Lambda, SQS and API Gateway.
3. Challenges discussed were managing 30 microservices, ensuring API latency below 50ms across availability zones, and handling 10 requests per second with nginx load balancing across 20 servers.
2017/9/7 db tech showcase Tokyo 2017(JPOUG in 15 minutes)にて発表した内容です。
SQL大量発行に伴う処理遅延は、ミッションクリティカルシステムでありがちな性能問題のひとつです。
SQLをまとめて発行したり、処理の多重度を上げることができれば高速化可能です。ですが・・・
AP設計に起因する性能問題のため、開発工程の終盤においては対処が難しいことが多々あります。
そのような状況において、どのような改善手段があるのか、Oracleを例に解説します。
This document provides an overview and agenda for an AWS webinar on AWS Glue. It introduces AWS Glue as a fully managed and serverless ETL service that can manage metadata for various data sources. The webinar will cover the background of AWS Glue, its key features including being serverless and enabling secure development in notebooks, use cases, pricing, and a conclusion. It also provides details on the components and functions of AWS Glue like the data catalog, orchestration, and serverless engines.
This document provides information about an AWS webinar on AWS Step Functions hosted by Yuta Imamura from Amazon Web Services Japan. The agenda includes an overview of Step Functions, state machines, data input and output, describing states, checking execution status, and additional details. Step Functions allows orchestrating distributed applications and microservices using state machines defined in Amazon States Language (ASL). States can pass data and parameters between each other to synchronize processes.
AWS Japan YouTube 公式チャンネルでライブ配信された 2022年4月26日の AWS Developer Live Show 「Infrastructure as Code 談議 2022」 の資料となります。 当日の配信はこちら からご確認いただけます。
https://youtu.be/ed35fEbpyIE
In the first half, we give an introduction to modern serialization systems, Protocol Buffers, Apache Thrift and Apache Avro. Which one does meet your needs?
In the second half, we show an example of data ingestion system architecture using Apache Avro.
This document summarizes a microservices meetup hosted by @mosa_siru. Key points include:
1. @mosa_siru is an engineer at DeNA and CTO of Gunosy.
2. The meetup covered Gunosy's architecture with over 45 GitHub repositories, 30 stacks, 10 Go APIs, and 10 Python batch processes using AWS services like Kinesis, Lambda, SQS and API Gateway.
3. Challenges discussed were managing 30 microservices, ensuring API latency below 50ms across availability zones, and handling 10 requests per second with nginx load balancing across 20 servers.
2017/9/7 db tech showcase Tokyo 2017(JPOUG in 15 minutes)にて発表した内容です。
SQL大量発行に伴う処理遅延は、ミッションクリティカルシステムでありがちな性能問題のひとつです。
SQLをまとめて発行したり、処理の多重度を上げることができれば高速化可能です。ですが・・・
AP設計に起因する性能問題のため、開発工程の終盤においては対処が難しいことが多々あります。
そのような状況において、どのような改善手段があるのか、Oracleを例に解説します。
This document provides an overview and agenda for an AWS webinar on AWS Glue. It introduces AWS Glue as a fully managed and serverless ETL service that can manage metadata for various data sources. The webinar will cover the background of AWS Glue, its key features including being serverless and enabling secure development in notebooks, use cases, pricing, and a conclusion. It also provides details on the components and functions of AWS Glue like the data catalog, orchestration, and serverless engines.
Redis is an in-memory key-value store that can be used as a cache or database. It supports a variety of data structures like strings, lists, sets, hashes and sorted sets. Redis has persistence options and is very fast due to being an in-memory store. It is compatible with many programming languages and is useful for tasks like caching, real-time rankings and generating temporary access tokens.
Redis is an in-memory key-value store that can be used as a cache or database. It supports varied data structures like Strings, Lists, Sets, Hashes and Sorted Sets. While it stores data in memory for high speed, it can also optionally write data to disk for persistence. Redis is useful for caching, real-time analytics or any use case requiring fast access to structured data.
12. StringString
redis python
> SET hoge fugafuga
OK
> GET hoge
"fugafuga"
> SET point 10
OK
> GET point
"10"
> INCR point
(integer) 11
> GET point
"11"
from redis import Redis
redis = Redis()
redis.set('hoge', 'fugafuga')
print(redis.get('hoge'))
#=> b'fugafuga'
redis.set('point', 10)
print(redis.get('point'))
#=> b'10'
redis.incr('point')
print(redis.get('point'))
#=> b'11'