投稿時間:2023-02-02 23:27:03 RSSフィード2023-02-02 23:00 分まとめ(31件)

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AWS	lambdaタグが付けられた新着投稿 - Qiita	エンジニアインターン10日目	https://qiita.com/a27879038/items/51fbe577b271a6d63a63	beautifulsoup	2023-02-02 22:16:26
python	Pythonタグが付けられた新着投稿 - Qiita	ChatGPTに書いてもらったPythonコード集	https://qiita.com/data_mom/items/b200926f29dccf4444a3	chatgpt	2023-02-02 22:59:15
python	Pythonタグが付けられた新着投稿 - Qiita	画像から動画を生成 OpenCV	https://qiita.com/john-rocky/items/06b64f1487be83ca0683	deocvvideowriterfilepathc	2023-02-02 22:51:21
python	Pythonタグが付けられた新着投稿 - Qiita	エンジニアインターン10日目	https://qiita.com/a27879038/items/51fbe577b271a6d63a63	beautifulsoup	2023-02-02 22:16:26
js	JavaScriptタグが付けられた新着投稿 - Qiita	Video.js完全マニュアル part12 〜プラグイン〜	https://qiita.com/manzoku_bukuro/items/da39b75901e9ffa1ace5	videojs	2023-02-02 22:53:56
Ruby	Rubyタグが付けられた新着投稿 - Qiita	Ruby12	https://qiita.com/yupi/items/7f0ba24d9df55578c0c4	数字	2023-02-02 22:36:17
Docker	dockerタグが付けられた新着投稿 - Qiita	M1 MacでDocker DesktopからRancher Desktopに移行	https://qiita.com/aibazhang/items/a3fdc83b98c9557d79f6	istpriceofthedockerbusine	2023-02-02 22:40:15
Docker	dockerタグが付けられた新着投稿 - Qiita	【初心者のアウトプット記録】MAMPを使わずに、Laravel上でphpMyAdminを使えるようにしました。	https://qiita.com/FrancineH/items/cd4666f79691ef6f7124	docker	2023-02-02 22:27:40
GCP	gcpタグが付けられた新着投稿 - Qiita	Cloud SQLにある大量なテーブルをBigQueryに入れる話	https://qiita.com/aibazhang/items/5c06d70b4d8bad6b1b9b	bigquery	2023-02-02 22:42:00
海外TECH	DEV Community	FluentD vs FluentBit - Which log collector to choose?	https://dev.to/signoz/fluentd-vs-fluentbit-which-log-collector-to-choose-4md1	FluentD vs FluentBit Which log collector to choose This article was originally posted on SigNoz Blog and is written by Muskan Paliwal Tools like Fluentbit and Fluentd make log management more efficient by centralizing log data from multiple sources and providing the ability to monitor and analyze it all in one place Log management is the practice of collecting storing analyzing and monitoring log data from various systems and applications This log data can provide valuable insights for organizations such as identifying system issues troubleshooting problems detecting security threats and meeting compliance requirements In this article we will be talking about the two very famous log aggregators Fluentd and Fluent Bit Fluentd and Fluent Bit are open source log management tools that are designed to collect store and analyze log data Fluentd is a more feature rich tool with a robust plugin system written in Ruby and can process transform and forward log data to various systems Fluent Bit is a lightweight performant tool written in C and focuses on low resource usage serving highly distributed environments where limited capacity and reduced overhead memory and CPU are a huge consideration making it suitable for edge computing and IoT use cases Both tools have active communities and support a variety of integrations organizations can choose the one that fits their specific requirements Let s compare the two in depth Key Differences between Fluentd and Fluent Bit PerformancePerformance is one of the key factors that organizations consider when choosing between Fluentd and Fluentbit Both tools have different performance characteristics when it comes to latency and throughput ThroughputFluentd Fluentd can handle a high throughput of data as it can be scaled horizontally and vertically to handle large amounts of data Its plugin system allows for handling large amounts of data Fluent Bit Fluent Bit also can handle a high throughput of data It s designed to be lightweight and with low resource usage which means it can be deployed in large numbers of small instances which can help to handle a high throughput of data LatencyFluentd Latency in Fluentd is generally higher compared to Fluentbit This is due to the fact that Fluentd processes and transforms log data before forwarding it which can add to the latency Fluent Bit Fluent Bit is designed to be highly performant with low latency It is lightweight and has minimal overhead which makes it well suited for edge computing and IoT use cases where low latency is important Resources such as memory and CPU usageFluentd and Fluentbit have different resource usage characteristics when it comes to memory and CPU Fluentd uses more memory and CPU resources than Fluentbit Fluentd has a larger codebase and additional features which can increase its memory and CPU usage Fluentbit on the other hand is designed to be lightweight and with low resource usage which helps keep its memory and CPU usage low This makes Fluentbit a more suitable option for use cases where resource usage is a concern such as edge computing and IoT ScalabilityScalability is another important factor to consider when comparing Fluentd and Fluent Bit Both tools can be scaled horizontally and vertically to handle large amounts of data but they have different scalability characteristics Horizontal ScalingFluentd Fluentd can be horizontally scaled by adding more instances of Fluentd running on different machines This can be done by using a load balancer to distribute incoming data to multiple Fluentd instances Fluent Bit Fluent Bit can also be horizontally scaled by adding more instances running on different machines Fluent Bit uses a smaller footprint which means that it can be deployed in a large number of small instances which can handle a high throughput of data Vertical ScalingFluentd Fluentd can be vertically scaled by increasing the resources of a single instance such as adding more CPU and memory Fluent Bit Fluent Bit can also be vertically scaled by increasing the resources of a single instance such as adding more CPU and memory but due to its minimal overhead it might require fewer resources to handle the same amount of data compared to Fluentd Features Input and output pluginsBoth Fluentd and Fluent Bit provide a wide range of input and output plugins that allow you to collect data from various sources such as log files databases message queues and cloud services and forward them to different destinations such as files databases message queues and cloud services This allows you to collect and process data from different sources and forward it to the desired location for further analysis and storage Fluentd has around plugins and Fluent Bit has only plugins available Filter and transformation capabilitiesBoth Fluentd and Fluent Bit have filter and transformation capabilities which allow you to process and modify data before it is forwarded to its final destination This can include things like filtering out specific log levels renaming fields adding new fields and more This allows you to pre process data to make it more useful for your specific use case ExtensibilityIn terms of extensibility Fluentd has a larger community and ecosystem of plugins compared to Fluent Bit This means that there are more plugins available for Fluentd which can make it easier to add new functionality to your data collection and logging pipeline Additionally Fluentd has more advanced routing and buffering capabilities which can be useful for managing and processing large amounts of data Fluent Bit on the other hand is written in C and is more lightweight and less resource intensive compared to Fluentd This makes Fluent Bit well suited for use cases where low resource usage and high performance is needed such as in embedded systems edge computing and IoT applications Fluent Bit also has a smaller footprint and can be easily integrated into existing systems Community and support systemBoth Fluentd and Fluent Bit have strong community support and a wide range of resources available for users Fluentd has a larger and more established community with a more extensive ecosystem of plugins and integrations while Fluent Bit has a smaller but growing and focused user base with strong support systems from the company Use cases of FluentD and FluentBitLogging and monitoring Fluentd and Fluent Bit can be used to collect process and forward log data from various sources to a centralized location for analysis and storage This can be used for monitoring the performance and stability of systems as well as troubleshooting and debugging issues Data integration Fluentd and Fluent Bit can be used to collect and process data from different sources and forward it to different destinations This can be used for integrating data from different systems and applications such as databases message queues and cloud services Internet of Things IoT Fluentd and Fluent Bit can be used to collect and process data from IoT devices and forward it to a centralized location for analysis and storage Fluent Bit is particularly well suited for this use case due to its lightweight and low resource usage Cloud native Fluentd and Fluent Bit can be used to collect process and forward data in cloud environments Fluent Bit has been designed to work well in cloud native environments and can be used in the Kubernetes cluster to collect and forward logs and metrics from the containers Fluentd and Fluent Bit are versatile data collection and logging tools that can be used in a wide range of use cases such as logging and monitoring data integration stream processing IoT and cloud native environments Fluentd is more versatile and can handle more complex use cases while Fluent Bit is more suitable for resource constrained environments and cloud native use cases Choosing between FluentD and FluentBitIn conclusion Fluentd and Fluent Bit are both open source data collection and logging tools that provide powerful and flexible ways to collect process and forward data from various sources to different destinations They have similar features such as input output plugins extensibility and filter and transformation capabilities However Fluentd is more advanced in terms of routing and buffering capabilities and has a larger community and ecosystem of plugins while Fluent Bit is more lightweight and well suited for resource constrained environments such as embedded systems edge computing and IoT applications and has a smaller but growing and focused user base All in all Fluent Bit to Fluentd is more like beats to logstash a lightweight shipper that can be installed as agents on edge hosts or devices in a distributed architecture For e g in a Kubernetes environment Fluent Bit can be deployed as a DaemonSet on each node to collect and forward data to a centralized Fluentd instance acting as an aggregator processing the data and routing it to different sources based on tags providing efficient and centralized management of the data collected from all nodes in the cluster This setup allows for efficient resource utilization and flexibility in routing and processing data Fluent Bit can be used on its own of course but has far less to offer in terms of aggregation capabilities and a much smaller amount of plugins for integrating with other solutions Once the log data is collected and aggregated you will need a centralized log management tool to store and analyze the logs That s where SigNoz comes in Log Analytics with SigNozSigNoz is a full stack open source APM that can be used as a log management tool SigNoz uses a columnar database ClickHouse to store logs which is very efficient at ingesting and storing logs data Columnar databases like ClickHouse are very effective in storing log data and making it available for analysis The logs tab in SigNoz has advanced features like a log query builder search across multiple fields structured table view JSON view etc Log management in SigNozYou can also view logs in real time with live tail logging Live Tail Logging in SigNozWith advanced Log Query Builder you can filter out logs quickly with a mix and match of fields Advanced Log Query Builder in SigNoz Getting Started with SigNozSigNoz can be installed on macOS or Linux computers in just three steps by using a simple install script The install script automatically installs Docker Engine on Linux However on macOS you must manually install Docker Engine before running the install script git clone b main cd signoz deploy install shYou can visit our documentation for instructions on how to install SigNoz using Docker Swarm and Helm Charts If you liked what you read then check out our GitHub repo Related PostsSigNoz A Lightweight Open Source ELK alternativeOpenTelemetry Logs A complete introduction	2023-02-02 13:37:39
海外TECH	DEV Community	How I made a GPT-3 Chrome Extension and earned $1143 in 2 weeks	https://dev.to/serjobas/how-i-made-a-gpt-3-chrome-extension-and-earned-1143-in-2-weeks-2eg	How I made a GPT Chrome Extension and earned in weeksHey My name is Sergey Bunas and in this article I will tell about my experience of building a side project that was created in day went viral on Twitter and earned in weeks Replai so is a GPT Chrome browser extension that generates human like Twitter replies in seconds to help users grow their audience Replai s interface example of a reply in Joke tone IdeaMy fellow hustler friend had experience in creating courses on the growing an audience on Twitter he knew what hurts the people trying to grow their audience on Twitter from Pain One of the main ways to grow your audience on Twitter is to reply to tweets from more famous people In order for this method to bring results certain conditions must be met Consistency audience growth on Twitter is a long game it is very important to respond to at least tweets every day Speed you need to be among the first to respond to a tweet otherwise your answer will drown and no one will notice it Creativity the answer should be in the context of a discussion also it should contain an emotion Solution With Replai so you can generate human like replies to tweets with a single button We use GPT to reply to tweets and with the help of the Chrome extension we embed it into the Twitter page reducing friction no need to go to another site copy paste the Tweet and reply CodeI ve created the first version of the extension in hours I immediately submitted it to the Chrome Web Store for review After days our extension was approved and published to the public store The extension has two main parts Extension FrontendSingle javascript file that contains logic of detecting wether it s the Twitter page inserting buttons into the Tweeter text field when you click on the button we send the original tweet need to find it in the page and tone of response to the server insert the response from the server into the text field emulating paste event BackendSimple node js server hosted on heroku which contains logic for creating GPT prompts depending on the tone in which you want to reply REST calls to the OpenAI GPT API API keys analytics payment verification The first version of the product did not have a paywall and a limit on the number of replays we wanted to test the hypothesis as quickly as possible and let users touch the product Viral LaunchWhen the extension became available in the store my friend wrote a tweet with an example of using the extension the tweet went viral and gained k views retweets and attracted the first users to us We continued to write under the hashtag buildinpublic about the progress of the product about experience insights and mistakes These tweets gained views increased awareness and later word of mouth appeared We was featured in various Twitter AI Productivity collections And received great comments from our usersAfter days we saw that the bills for requests in OpenAI reached dollars a day we had people download our extension at that point We decided to create a pay wall and to be quick with the payments we decided to use Gumroad We created a landing page using site builder and added payments to the extensionPricing with different reply limits weeks passed after the time that we ve added payments In weeks we reached the following milestones Paying customers MRR Revenue Followers on Twitter ConclusionChatGPT GPT provides significant benefits it s easy to integrate it s cheap and it creates amazing value for customers if done right Chrome Extension provides embedding into the user s already developed habits allowing you to significantly increase retention By combining these technologies you will have fantastic opportunities to create new products	2023-02-02 13:20:40
海外TECH	Engadget	ChatGPT reportedly reached 100 million users in January	https://www.engadget.com/chatgpt-100-million-users-january-130619073.html?src=rss	ChatGPT reportedly reached million users in JanuaryChatGPT has been growing at a rate much much faster than TikTok or any other popular app or service According to a new study by analytics firm UBS via Reuters and CBS the OpenAI developed chatbot was on pace to reach over million monthly active users in January The chatbot only became available to the public on November th last year but its rise to fame has apparently been meteoric Within its first month of availability it already boasted million monthly active users the study said By January it was already being visited by around million individual users a day nbsp In comparison it took TikTok nine months after its global debut to reach million monthly users despite its popularity especially among the younger generation UBS analyst Lloyd Walmsley also pointed out that Meta s Instagram had been around for two and a half years before reaching that point It remains to be seen however if the chatbot can maintain this level of interest in the coming months quot The next question is obviously what its staying power will be There may be an element of people just coming to look quot Walmsley added ChatGPT provides users with natural sounding human like responses to queries so much so that educators are concerned that it could be used by students to cheat While it still has serious accuracy problems ー quot Models like ChatGPT have a notorious tendency to spew biased harmful and factually incorrect content quot MIT s Tech Review wrote in a piece ーthere isn t another public chatbot with comparable capabilities It has reportedly rattled Google s execs to the point that they decided to declare quot code red quot and accelerated the company s AI development The tech giant is working on a few potential ChatGPT competitors including a chatbot for search and is aiming to showcase AI products this year nbsp ChatGPT remains free to use at the moment and OpenAI doesn t seem to have any plans to completely lock access to it behind a paywall However the startup does intend to start charging for the service and has already started testing a paid ChatGPT plan for per month which offers faster response times and priority access to new features	2023-02-02 13:06:19
Cisco	Cisco Blog	Partners, join CX at Cisco Live	https://blogs.cisco.com/customerexperience/partners-join-cx-at-cisco-live	Partners join CX at Cisco LiveCisco CX partners make sure to join us at Cisco Live EMEA in Amsterdam Join our Partner Day as well to learn about how we are helping drive this Experiential economy through our Lifecycle Services	2023-02-02 13:00:54
Cisco	Cisco Blog	Building a secure and scalable multi-cloud environment with Cisco Secure Firewall Threat Defense on Alkira Cloud	https://blogs.cisco.com/security/building-a-secure-and-scalable-multi-cloud-environment-with-cisco-secure-firewall-threat-defense-on-alkira-cloud	Building a secure and scalable multi cloud environment with Cisco Secure Firewall Threat Defense on Alkira CloudCisco has partnered with Alkira to deliver a centralized security model for multi cloud architecture that is easy to deploy manage and increases visibility and control	2023-02-02 13:00:48
海外TECH	CodeProject Latest Articles	How to Check out a Remote GIT Branch, Which Doesn't Exist on Your Local Clone?	https://www.codeproject.com/Articles/5353567/How-to-Check-out-a-Remote-GIT-Branch-Which-Doesnt	local	2023-02-02 13:47:00
海外TECH	CodeProject Latest Articles	Solutions to the Rotated Binary Search Problem in C#	https://www.codeproject.com/Articles/5353546/Solutions-to-the-Rotated-Binary-Search-Problem-in	binary	2023-02-02 13:27:00
金融	金融庁ホームページ	つみたてNISA対象商品届出一覧、つみたてNISA取扱金融機関一覧を更新しました。	https://www.fsa.go.jp/policy/nisa2/about/tsumitate/target/index.html	対象商品	2023-02-02 15:00:00
ニュース	@日本経済新聞 電子版	福岡空港の免税店に列をつくる韓国人のインバウンド。「なにわの台所」は中国人客の来店が見込めず化粧水などの福袋はなく。沖縄は欧米で関心の高い「アドベンチャーツーリズム」に着目します。 https://t.co/qCFCt2hWUV	https://twitter.com/nikkei/statuses/1621141503220260864	福岡空港の免税店に列をつくる韓国人のインバウンド。	2023-02-02 13:40:28
ニュース	@日本経済新聞 電子版	5大銀行の業務純益23%増　4〜12月、海外で利ざや改善 https://t.co/XHr79YGSIr	https://twitter.com/nikkei/statuses/1621140307407679488	銀行	2023-02-02 13:35:43
ニュース	@日本経済新聞 電子版	ECB、0.5%利上げ決定　2会合連続 https://t.co/UaycTDflSi	https://twitter.com/nikkei/statuses/1621136783273783299	決定	2023-02-02 13:21:43
ニュース	@日本経済新聞 電子版	市場、米金利低下・ドル安観測強まる　1ドル120円台も https://t.co/UBznqeeajY	https://twitter.com/nikkei/statuses/1621135025835225088	金利	2023-02-02 13:14:44
ニュース	@日本経済新聞 電子版	ZHD、難路の3社合併　広告・EC低迷でLINE軸にテコ入れ https://t.co/yPr2olkbFA	https://twitter.com/nikkei/statuses/1621133766721945600	難路	2023-02-02 13:09:43
ニュース	@日本経済新聞 電子版	国内コロナ感染、新たに4万5501人　累計3265万5953人 https://t.co/ErYMwMJwnt	https://twitter.com/nikkei/statuses/1621132183779024897	累計	2023-02-02 13:03:26
ニュース	BBC News - Home	UK to see shorter recession, says Bank of England	https://www.bbc.co.uk/news/business-64487179?at_medium=RSS&at_campaign=KARANGA	englandthe	2023-02-02 13:48:15
ニュース	BBC News - Home	Omagh bombing: UK government announces independent statutory inquiry	https://www.bbc.co.uk/news/uk-northern-ireland-64495873?at_medium=RSS&at_campaign=KARANGA	investigation	2023-02-02 13:52:47
ニュース	BBC News - Home	Aidan McAnespie killing: Ex-soldier Holden avoids jail over Troubles shooting	https://www.bbc.co.uk/news/uk-northern-ireland-64499374?at_medium=RSS&at_campaign=KARANGA	troubles	2023-02-02 13:36:08
ニュース	BBC News - Home	Shell reports highest profits in 115 years	https://www.bbc.co.uk/news/uk-64489147?at_medium=RSS&at_campaign=KARANGA	record	2023-02-02 13:27:24
ニュース	BBC News - Home	US secures deal on Philippines bases to complete arc around China	https://www.bbc.co.uk/news/world-asia-64479712?at_medium=RSS&at_campaign=KARANGA	taiwan	2023-02-02 13:16:53
ニュース	BBC News - Home	Six Nations 2023: Ireland prop Finlay Bealham replaces Tadhg Furlong	https://www.bbc.co.uk/sport/rugby-union/64491698?at_medium=RSS&at_campaign=KARANGA	wales	2023-02-02 13:15:39
GCP	Google Cloud Platform Japan 公式ブログ	BigQuery による構築: Tamr が大規模なマスターデータ管理を提供する方法およびデータ プロダクト戦略に与える効果	https://cloud.google.com/blog/ja/products/data-analytics/how-tamr-delivers-master-data-management-at-scale-with-bigquery/	このようなプラットフォームを導入すれば、信頼できるデータを取得し、ビジネス上の成果を向上させることが可能となります。	2023-02-02 14:20:00
GCP	Cloud Blog JA	BigQuery による構築: Tamr が大規模なマスターデータ管理を提供する方法およびデータ プロダクト戦略に与える効果	https://cloud.google.com/blog/ja/products/data-analytics/how-tamr-delivers-master-data-management-at-scale-with-bigquery/	このようなプラットフォームを導入すれば、信頼できるデータを取得し、ビジネス上の成果を向上させることが可能となります。	2023-02-02 14:20:00