投稿時間:2023-08-24 07:15:44 RSSフィード2023-08-24 07:00 分まとめ(17件)

カテゴリー等	サイト名等	記事タイトル・トレンドワード等	リンクURL	頻出ワード・要約等/検索ボリューム	登録日
IT	ITmedia 総合記事一覧	[ITmedia ビジネスオンライン] 「Amazonプライム」会費、きょうから値上げ　年額4900円→5900円に	https://www.itmedia.co.jp/business/articles/2308/24/news056.html	itmedia	2023-08-24 06:30:00
AWS	AWS Big Data Blog	Amazon OpenSearch Service H1 2023 in review	https://aws.amazon.com/blogs/big-data/amazon-opensearch-service-h1-2023-in-review/	Amazon OpenSearch Service H in reviewSince its release in January the OpenSearch project has released versions through June Amazon OpenSearch Service supports the latest versions of OpenSearch up to version OpenSearch Service provides two configuration options to deploy and operate OpenSearch at scale in the cloud With OpenSearch Service managed domains you specify a hardware configuration …	2023-08-23 21:47:05
AWS	AWS Management Tools Blog	Ingesting activity events from non-AWS sources to AWS CloudTrail Lake	https://aws.amazon.com/blogs/mt/ingesting-activity-events-from-non-aws-sources-to-aws-cloudtrail-lake/	Ingesting activity events from non AWS sources to AWS CloudTrail LakeAWS CloudTrail Lake is a managed data lake for capturing storing accessing and analyzing user and API activity on AWS for audit security and operational purposes You can aggregate and immutably store your activity events and run SQL based queries for search and analysis In Jan AWS announced the support of ingestion for activity events …	2023-08-23 21:16:10
AWS	AWS	Using ACM certificates with Apache on EC2 Nitro Enclaves instances | Amazon Web Services	https://www.youtube.com/watch?v=N0q1ximaMkc	Using ACM certificates with Apache on EC Nitro Enclaves instances Amazon Web ServicesThis demonstration illustrates how to use certificates from AWS Certificate Manager ACM with Apache web servers on Amazon Elastic Compute Cloud EC Nitro Enclaves instances ACM for Nitro Enclaves allows you to use public and private SSL TLS certificates with your web applications and servers running on Amazon EC instances with AWS Nitro Enclaves Nitro Enclaves is an EC capability that enables the creation of isolated compute environments to protect and securely process highly sensitive data such as SSL TLS private keys In addition to NGINX webservers you can use ACM for Nitro Enclaves with Apache HTTP webservers Links Registering a domain with Route Installing and configuring ACM for Nitro Enclaves Nitro instance types nitro instance typesTroubleshooting ACM DNS validation IAM role permissions for EC instance add policyLearn more at Subscribe More AWS videos More AWS events videos Do you have technical AWS questions Ask the community of experts on AWS re Post ABOUT AWSAmazon Web Services AWS is the world s most comprehensive and broadly adopted cloud platform offering over fully featured services from data centers globally Millions of customers ーincluding the fastest growing startups largest enterprises and leading government agencies ーare using AWS to lower costs become more agile and innovate faster AWSCertificateManager AmazonEC AWSNitroEnclaves ApacheHTTPWebservers DistributingSSLTLSCertificates ManagingCertificateRenewals AWSSecurityServicesFeatureDemos AWS AmazonWebServices CloudComputing	2023-08-23 21:28:43
Linux	Ubuntuタグが付けられた新着投稿 - Qiita	【SSH】パスワード認証から公開鍵認証に移行する	https://qiita.com/teyama3/items/17190f1da05d9ed06958	linux	2023-08-24 06:59:35
技術ブログ	Developers.IO	[アップデート] コスト配分タグで最終更新日と最終使用月が確認出来るようになったので、メタデータを参考にコスト配分タグの棚卸しが出来るようになりました	https://dev.classmethod.jp/articles/cost-allocation-tags-updated-used-timestamps/	billing	2023-08-23 21:33:47
海外TECH	MakeUseOf	6 Best Online SQL Playgrounds to Test Your Queries	https://www.makeuseof.com/online-sql-playground/	interactive	2023-08-23 21:00:28
海外TECH	DEV Community	Implementing Vector Database for AI	https://dev.to/alakkadshaw/implementing-vector-database-for-ai-5a61	Implementing Vector Database for AIWhat are vector databasesWhy are vector databases important to AICore concepts of a vector databaseFactors to consider when choosing a vector databasePopular Vector Databases for your considerationStep by Step guide to implementing a Vector databaseStep Installing MilvusStep Creating a Milvus ClientStep Create a collectionStep Inserting data into the CollectionStep Create an IndexStep Sample searching for similar vectorsBonus How to prepare your data for Vector databaseConclusion What are vector databasesVector Databases are used for data storage and retrieval like all databases but these are designed to handle high dimensional vector data which are mathematical representations of features or attributesVector databases do Similarity Search Which is to find similar vectors in a database for the given search query Similarity search is achieved through algorithms that reduce space and time complexity when compared to traditional databases like SQL Why Vector Databases are important in AIVector databases are very important in AI This is because they process large scale multimedia data natural language processing and neural networksVector databases enable resource efficient and time efficient storage and retrieval of high dimensional vector data High dimensional vector data includes feature vectors and  embeddings these data capture complex patterns and data relationshipsIn AI there is a need for searches like nearest neighbor search Clustering and classification These types of searches are resource intensive and hence there is a need for specialized databases for the sameVector databases provide fast and accurate similarity search thus improving the performance and scalability of AI apps Core Concepts of a Vector DatabaseAs we have already seen that Vector database handles high dimensional vector dataIndexing Vector databases use k d trees ball trees and other such techniques to perform high dimensional vector searches like nearest neighbour or clustering searchesScalability These databases are designed to handle huge amounts of data and the databases can be scaled with multiple machines running in parallel Distance metrics  Vector databases compute similarity between vectors such as cosine similarity Euclidean distance and Manhatten distance to figure how similar vectors are from one another and then cluster them togetherPerformance Optimization Query latency and memory usage optimization are critical for AI applications and thus is what the vector databases are designed to do Factors to consider when choosing a Vector DatabaseWhen considering a vector database first consider what are the requirements of your project There are many vector databases available in the market today From lightweight to high performance and scalable databasesThere are paid versions available as well There are some which are self hosted and others you can just purchase as a SaaS productHere are the factors that you need to consider when choosing the right vector database for your projectScalabilityPerformanceCommunity SupportCompatibilityLet us look at these individually ScalabilityWhat is the model size you are dealing with you can choose a lightweight database as well if your data size is smallIf you have a large dataset determine if the database can be scaled over multiple machines or notConsider if the database can be scaled over multiple data centers if the project is a large scale PerformancePerformance can be thought of through the metrics of the followingQuery latencymemory usageindexing timeHardware acceleration is also quite essential nowadays most vector databases can run on GPUs instead of CPU giving a boost to performanceIn many cases when considering databases you can choose which one suits your purpose for a given amount of performance per dollar you can choose a database optimized for speed vs accuracy CompatibilityDifferent databases work well with different programming languages this is especially true when working with vector databasesCheck if the database you are considering works with the programming language used in your projectWhat are the distance metrics and indexing techniques that you are using in your project Is the database compatible with thatDoes the database offer APIs libraries and connectors that integrate with your project Community SupportWhat is the level of community support around a particular database This is important because of community support there is a lot of support available to the developer like the support of stack overflow articles on how to achieve something or set up the database for a particular purpose etcHaving Community support also means access to tutorials detailed docs and articles on how to implement thingsDatabases having large communities are also well maintained and receive regular support in the form of bug fixes new features and security updates Popular Vector Databases for your considerationHere are of the most popular vector databases available in the market todayFAISS Developed by Facebook a large scale vector database model It is popular for its performance and flexibility in running AI applications It also supports GPU acceleration is which a great add on It is primarily compatible with pythonMilvus Advertised as the most popular vector database for enterprise users Milvus can be used in applications like computer vision machine learning and natural language processing and it is Open source as well It is compatible with most programs in AI and has support for multiple indexing techniques and also offers GPU hardware acceleration and distributed deploymentAnnoy This is a C library developed by Spotify that is open source and lightweight It searches points in space that are close to a given point Weaviate Weaviate is an open source database that provides HNSW that is Hierarchical Navigable Small World which is a graph based technique often used in vector databases It offers a balance between accuracy and speed and you can specify which is more preferable to you This technique may require more ram than other techniques Step by Step guide to implementing a Vector databaseFor this guide we will be using one of the most popular vector databases out there Milvus Step Installing MilvusYou can install Milvus in a docker container as well There are minimal hardware requirements for installing milvus you can check them out on the milvus websitethis article is brought to you by DeadSimpleChat Chat API for your website and appto install download the milvus YAML file wget O docker compose ymlAfter downloading the YAML file start the MILVUS with the below commandsudo docker compose up dCreating milvus etcd doneCreating milvus minio doneCreating milvus standalone donethen you can check whether the milvus is up and running by sudo docker compose psyou will get something like Name Command State Ports milvus etcd etcd advertise client url Up tcp tcpmilvus minio usr bin docker entrypoint Up healthy tcpmilvus standalone tini milvus run standalone Up gt tcp gt tcp Connect to MilvusCheck the local port where Milvus is running and replace the container name with a custom namedocker port milvus standalone tcpThis command will return a local Ip address and port number and you can connect to it Stop MilvusYou can stop Milvus using the following commandsudo docker compose down Creating the NodeJs ProjectLet us create a new directory and cd into itmkdir milvus nodejcd milvus nodejsnext let us initialize the project like sonpm init ythen we will install the milvus and other dependenciesnpm install milvus savenpm install Step Creating a Milvus Clienta Create a new file named index js and import the Milvus sdk likeconst MilvusClient require milvus Step Create a collectionNow let us define a collection schema and include the data fields and data typesconst collectionSchema collection name test collection fields field name vector data type FloatVector type params dim field name id data type Int auto id true Now let us create a collection using the Milvus clientasync function createCollection const response await milvusClient createCollection collectionSchema console log Collection has been created response createCollection Step Inserting Data into the Collectiona Preparing the data to be insertedconst vectors id vector Array from length gt Math random id vector Array from length gt Math random b inserting the data into the collectionasync function insertData const response await milvusClient insert collection name test collection fields data vectors console log Data has been added to the collection response insertData Step Create an IndexLet us define the parameters such as the index and metric typesconst indexParams collection name test collection field name vector index type IVF FLAT metric type L type params nlist Now using the Milvus CLient we will create an indexasync function createIndex const response await milvusClient createIndex indexParams console log A new index has been created response createIndex Step Sample searching for similar vectorsconst searchParams collection name test collection field name vector top k search params anns field vector metric type L query records Array from length gt Math random round decimal Now let us do a sample search query into our database For this we will need to define some search parameters such as top k results and search radius which we have done aboveasync function search const response await milvusClient search searchParams console log Results response search Thus we have implemented the Milvus client in our node js project Bonus How to prepare your Data for the Vector database Data Pre Processing and Feature extraction in Vector databasesIn vector databases there are methods we use for Data preprocessing and these areNormalizationDimensionality reductionFeature selectionLet us consider all these in detail NormalizationNormalization includes adjusting the dataset values such that they are in a common scale We do this because we do not want a single feature to dominate the model dues to the differences in the magnitude of values steps involvedThe features that need to be normalized are numerical features that have different scales and units of measurementsThere are a number of methods used for thisMin Max scaling Scaling all the values in the range of Z score standardization In this method we scale the values using statistics All the values are based on the mean average standard deviation how far do these values go from the meanApply whatever method you prefer but always use the same scaling params for training and test sets to avoid data leakage Dimensionality ReductionThis involves reducing the number of features in our data set but retaining the important features With reduced dimensions the model runs fast computational complexity decreases and the data is simplified Here are some of the steps Steps involvedSet aside the number of dimensions and the amount of variance that we want in our reduced dataset then choose a reduction technique accordinglyPrincipal Component Analysis this technique maximizes variance and uses a linear method to project data into a lower dimensional spacet Distributed Stochastic Neighbor Embedding It preserves local structures in data and is a nonlinear method of reducing the dimensionality of a dataset Feature SelectionIn Feature selection we select the most relevant features and discard the ones that are not relevant to our use case This helps to reduce noise makes the model more interpretable and decreases the training time steps involvedFilter method This involves ranking the features based on the criterion involved Such as co relation mutual information and selecting the top k featuresWrapper methods Using a specific machine learning model to evaluate features and iteratively removing the ones that are not relevant to our use caseEmbedded methods Methods such as LASSO and Ridge regression apply regularization which reduces the impact of features that are not important this method involves feature selection along with model training Apply whatever method you deep best to your dataset and choose the top k features and discard the other features Need Chat API for your website or appDeadSimpleChat is a Chat API providerAdd Scalable Chat to your app in minutes Million Online Concurrent users UptimeModeration features ChatGroup ChatFully CustomizableChat API and SDKPre Built Chat ConclusionIn this article we discussed about vector databases and how you can implement a vector databaseI hope you liked the article Thank you for reading	2023-08-23 21:44:15
海外TECH	DEV Community	Automated Updates Made Easy: Unveiling Docker Compose File Watch 🐳	https://dev.to/docker/automated-updates-made-easy-unveiling-docker-compose-file-watch-4jgc	Automated Updates Made Easy Unveiling Docker Compose File Watch Introduction Overview of Docker Compose FileContainerized development has revolutionized the way software is built and deployed offering unparalleled flexibility and scalability However this progress hasn t come without its challenges Docker Compose File Watch emerges as a promising solution to one of the most persistent obstacles faced by developers in this realm the need for seamless and automatic updates to service containers during the development process In essence Docker Compose File Watch aims to bridge the gap between coding and deployment by introducing a dynamic mechanism that ensures your service containers stay in sync with your evolving codebase It promises to eliminate the tedium of manual container updates freeing developers to focus on what truly matters writing code and crafting innovative solutions Importance of Automated Updates in Development The modern development landscape is marked by agility and rapid iteration Developers continuously refine their code responding to changing requirements and addressing bugs However in the containerized world every code modification often necessitates a corresponding container update disrupting the flow and impeding productivity Picture this you re feverishly coding bringing your brilliant ideas to life Suddenly you need to modify a configuration file triggering a series of manual steps to synchronize your changes with the container The rhythm is lost and your focus shifts from innovation to maintenance This is where Docker Compose File Watch steps in promising to liberate developers from these shackles of manual synchronization and container management Benefits of Streamlining Containerized Development At the heart of Docker Compose File Watch lies the aspiration to optimize the development process By automating the synchronization of code changes with container instances developers gain the luxury of uninterrupted focus on their codebase This newfound efficiency translates into faster development cycles quicker bug fixes and a more responsive development environment Beyond individual productivity gains Docker Compose File Watch holds the potential to foster collaboration within development teams With manual synchronization largely relegated to the past teams can work harmoniously on shared projects without constant disruptions This collaborative synergy can lead to enhanced creativity improved code quality and accelerated project timelines Understanding the Problem Challenges Faced by Developers in Containerized Development While containerization offers a plethora of advantages it isn t without its challenges especially when it comes to maintaining a fluid development experience Time Complexity in Manually Updating Containers Iterative Code Test Update Cycles In the realm of software development iteration is key Developers constantly iterate through a cycle of coding testing and refining However in a containerized environment the iteration process is often hampered by the need to manually update containers This introduces a significant time overhead disrupting the seamless flow of development Consider a scenario where you re working on a microservice architecture Each tweak to your codebase necessitates an update to the respective container The manual nature of this process introduces a time complexity that accumulates with each iteration The result Valuable time and energy diverted from coding to administrative tasks Cumbersome Restart Processes Containerized applications thrive on their ability to be lightweight and nimble Containers can be started stopped and scaled with remarkable speed However this agility often contrasts with the manual steps required to restart containers after code changes The need to halt modify and restart services introduces friction into the development process Imagine you re collaborating with team members each working on different parts of the application As code changes are integrated and services are updated the constant need to restart containers can create a disjointed development experience The more complex your architecture becomes the more pronounced this challenge becomes Shift in Focus from Development to Maintenance Impact on Creativity and Innovation Software development is a creative endeavor requiring unfettered focus and imagination Yet the burden of manual container updates can derail this creative flow Developers find themselves pulled away from the art of coding and into the realm of maintenance stifling the very creativity that drives innovation In the midst of crafting elegant algorithms or designing intuitive user interfaces the interruption caused by manual updates can lead to loss of context fragmented thoughts and a reduced capacity for innovation The cognitive shift from development to maintenance is a disruption that hampers the very essence of what developers do best innovate Mitigating Development Momentum Momentum is a powerful force in development When you re deeply engaged in coding you ride a wave of inspiration and insight However the need to frequently pause this momentum to attend to container updates can be jarring The mental shift required to transition from coding to container management disrupts the development rhythm Imagine a scenario where you re meticulously crafting intricate logic for a complex feature Suddenly you re required to switch gears update containers and ensure everything is in sync The mental context switching introduces a cognitive load that erodes the fluidity of the development process As a developer your energy is best spent on coding not on managing container states Balancing Act Development vs Maintenance Balancing development with maintenance is a delicate act While maintenance is an essential part of software engineering it should not overshadow the creative process of coding Docker Compose File Watch aspires to recalibrate this balance enabling developers to focus on development while the tool handles the intricate task of container synchronization In the sections that follow we ll delve into the mechanics of Docker Compose File Watch exploring how it tackles these challenges head on We ll uncover the inner workings of this experimental feature delve into real world scenarios and equip you with the knowledge to integrate it seamlessly into your development workflow Please note that this is a brief and simplified version of the content You should expand on each point provide more in depth explanations and include relevant examples anecdotes and insights to create a comprehensive and engaging article You can follow a similar approach for the rest of the sections in your article Introducing the Solution How Docker Compose File Watch Addresses the Developer Problem Docker Compose File Watch emerges as a beacon of hope for developers grappling with the complexities of manual container updates At its core this experimental feature embodies the principle of automation the art of simplifying and streamlining tasks that were once labor intensive When you integrate Docker Compose File Watch into your development workflow the arduous process of manual container updates becomes a thing of the past Instead of toggling between your code editor and terminal initiating container restarts and meticulously synchronizing changes you can trust Docker Compose to handle these intricacies seamlessly This feature introduces an x develop section in your Compose yaml file acting as a command center for orchestrating automatic updates By configuring watch paths and associated actions you empower Docker Compose to monitor specific files or directories for changes and trigger predefined actions accordingly The result A development environment that remains in lockstep with your codebase freeing you to channel your energy into coding rather than container management Getting Started Installation and Setup of Docker Compose Before we embark on our exploration of Docker Compose File Watch it s imperative to ensure that you have the necessary tools at your disposal Installing Docker and Docker Compose If you re new to Docker fear not The installation process is straightforward and well documented Head over to the official Docker website and follow the installation instructions tailored to your operating system Additionally Docker Compose an essential companion must be installed to orchestrate multi container applications effortlessly Ensuring Compatibility with Your Project As with any new tool compatibility is key Take a moment to assess whether your project aligns with the prerequisites of Docker Compose File Watch While the feature promises a smoother development experience confirming compatibility upfront ensures a seamless integration Basics of Compose yaml Configuration Docker Compose operates on the premise of declarative configuration At its core is the Compose yaml file a blueprint that outlines the composition and behavior of your containerized application Defining Services Networks and Volumes The Compose yaml file provides a canvas to define your services networks and volumes Services encapsulate the individual components of your application while networks facilitate communication between services Volumes on the other hand enable data persistence and sharing between containers Building the Foundation for Automated Updates To harness the power of Docker Compose File Watch it s essential to establish a strong foundation The Compose yaml file serves as the canvas on which we ll introduce the x develop extension transforming it into a dynamic control center for automated updates Enabling the x develop Section for Watch The key to unlocking the potential of Docker Compose File Watch lies in the introduction of the x develop section within your Compose yaml file Introducing the x develop Extension The x develop extension is a mechanism to extend the capabilities of Compose yaml It empowers you to define watch paths and associated actions laying the groundwork for automatic container updates Understanding the structure and syntax of this extension is crucial as we venture into the heart of automated updates Integrating File Watch in Your Project Setup Armed with the knowledge of the x develop extension you ll seamlessly integrate Docker Compose File Watch into your project By strategically configuring watch paths and actions you ll orchestrate a symphony of automated updates ensuring your containers are always in sync with your code Configuring Watch Paths and Actions Exploring the x develop Configuration Options At the heart of Docker Compose File Watch lies the power to configure watch paths and define corresponding actions This intricate dance between watching and acting is what enables the seamless synchronization of code changes and container updates Understanding Watch Paths and Glob Patterns Watch paths define the locations in your project s file structure that Docker Compose will monitor for changes By specifying these paths you dictate which components of your codebase trigger automated updates The use of glob patterns offers flexibility in selecting files and directories allowing you to be as granular or comprehensive as necessary Defining Actions Sync Rebuild and More Actions define how Docker Compose responds to changes detected in the specified watch paths The two primary actions at your disposal are synchronization and rebuild Synchronization ensures that modified files are copied into the corresponding container paths ensuring real time consistency Rebuild on the other hand triggers the rebuilding of container images and subsequent service updates Specifying Paths to Watch for Changes The art of configuring watch paths is rooted in strategic selection While the temptation might be to monitor every corner of your project a more refined approach yields greater efficiency Selecting Relevant Project Files and Folders Begin by identifying the files and folders that hold the greatest impact on your application s behavior These could include source code files configuration files or data assets By focusing on the critical components you ensure that Docker Compose File Watch expends its resources judiciously Optimizing Path Selection for Development Needs Customization is key Consider tailoring your watch paths to suit your development needs For instance if a specific feature module undergoes frequent changes targeting its directory for watch can enhance responsiveness The goal is to strike a balance between comprehensive coverage and targeted efficiency Working of Docker Compose File Watch ‍ Behind the Scenes How File Watch Mechanism Operates The allure of Docker Compose File Watch lies not only in its results but also in its elegant inner workings To truly grasp its power let s venture behind the scenes and understand how this dynamic mechanism operates Monitoring File System Events At its core Docker Compose File Watch acts as a vigilant sentry monitoring file system events with precision It keeps a watchful eye on the paths you ve configured detecting changes such as file creations modifications or deletions Communication Between Host and Containers When a file system event is detected Docker Compose orchestrates a seamless communication dance between the host and the relevant containers This dance ensures that changes are propagated swiftly maintaining a real time synchronization that mirrors your development efforts Handling Synchronization and Image Rebuilds Docker Compose File Watch s prowess extends beyond mere synchronization It has the ability to orchestrate intricate image rebuilds ensuring your services encapsulate the latest updates Understanding the Synchronization Workflow When a file is modified in a watched path Docker Compose swings into action It orchestrates the transfer of the updated file into the corresponding container ensuring that your changes are seamlessly integrated Rebuilding Images Efficiently with Cached Layers Certain changes such as modifications to package dependency files warrant more than just synchronization In such cases Docker Compose can trigger a systematic image rebuild Leveraging its understanding of cached layers Docker Compose optimizes the rebuild process minimizing unnecessary overhead Benefits and Considerations Developer Productivity and Time Savings The most tangible benefit of Docker Compose File Watch lies in its ability to amplify developer productivity By eliminating the need for manual container updates you re free to invest your time and energy where it matters most writing code The resulting acceleration in development cycles translates to quicker feature delivery faster bug fixes and an overall smoother development experience Potential Impact on Build and Deployment Pipelines The integration of Docker Compose File Watch extends its influence beyond development It can potentially impact your build and deployment pipelines by streamlining the synchronization between development testing and deployment stages Containers that remain in sync with your codebase from the outset are more likely to exhibit consistent behavior reducing discrepancies between development and production environments Known Issues and Limitations of the Experimental Feature While Docker Compose File Watch holds immense promise it s important to acknowledge its experimental nature Like any technology in its infancy there may be bugs limitations or scenarios that require manual intervention Keeping abreast of Docker s official documentation and community discussions is crucial to understanding potential pitfalls and workarounds Balancing Automation with Manual Control Docker Compose File Watch is a powerful ally but it s not the sole commander of your development landscape Striking a balance between automation and manual control is key There might be instances where nuanced adjustments or specific requirements demand a more hands on approach As you harness the power of Docker Compose File Watch ensure that you retain the flexibility to intervene when necessary Future Enhancements ️ Roadmap for Docker Compose File Watch Improvements The world of technology is ever evolving and Docker Compose File Watch is no exception The Docker Compose team is actively engaged in refining the feature based on user feedback and evolving development paradigms As you embark on your journey with Docker Compose File Watch keep an eye on the official roadmap to anticipate upcoming enhancements and refinements Community Feedback and Collaboration The strength of any tool lies in its community Docker Compose File Watch thrives on user feedback suggestions and collaborative efforts Engaging with the Docker community participating in discussions and sharing your experiences can contribute to the feature s evolution Your insights could potentially shape the direction of future updates and improvements Upcoming Features and Integrations The beauty of the software ecosystem is its relentless pursuit of improvement Docker Compose File Watch is likely to evolve in tandem with the broader container landscape Anticipate updates that might enhance its capabilities introduce new features or facilitate integrations with complementary tools Staying informed about upcoming features equips you to make informed decisions about its integration into your workflow Getting Started with Docker Compose File Watch Step by Step Integration Guide Now that you ve gained a comprehensive understanding of Docker Compose File Watch it s time to embark on your journey of integration Follow this step by step guide to get started Install Docker and Docker Compose If you haven t already ensure that Docker and Docker Compose are installed on your development environment Head to the official Docker website and follow the installation instructions for your specific operating system Create or Navigate to Your Project Directory Whether you re starting a new project or integrating Docker Compose File Watch into an existing one navigate to the root directory of your project in your terminal Compose yaml Configuration Open your project s Compose yaml file If you don t have one create a new file and define your services networks and volumes following Docker Compose s declarative syntax Introduce the x develop Extension Within your Compose yaml file introduce the x develop extension under the service for which you want to enable automated updates Define the watch paths and associated actions within this extension Configure Watch Paths and Actions Specify the paths you want Docker Compose to watch for changes These paths can encompass critical code files configuration files or other components that require synchronization Determine the appropriate actions to take upon changes whether it s synchronization or triggering image rebuilds Save and Validate Save your Compose yaml file and validate its syntax using the docker compose config command Ensure that your configuration is error free and ready for deployment Launch Your Services Run docker compose up to launch your services Docker Compose will now monitor the specified watch paths and execute the defined actions when changes occur Observe Automatic Updates As you make changes to the watched paths observe how Docker Compose File Watch springs into action It will synchronize changes or trigger image rebuilds as configured maintaining a real time connection between your code and containers Iterate and Enhance With Docker Compose File Watch seamlessly integrated into your workflow iterate on your development process with newfound efficiency Focus on coding testing and refining knowing that container updates are no longer a manual burden Congratulations You ve successfully integrated Docker Compose File Watch into your development workflow Embrace the enhanced productivity streamlined collaboration and accelerated iterations that this powerful feature brings to your containerized projects In the realm of software development time is of the essence By harnessing the capabilities of Docker Compose File Watch you ve unlocked a valuable tool that empowers you to devote more time to innovation and less to administrative tasks As you continue your journey explore additional nuances experiment with various configurations and share your experiences with the thriving Docker community Demo Projects ️Embarking on our journey we present a captivating demo project that breathes life into the concept of file watch This hands on demonstration offers a vivid showcase of Docker Compose File Watch in action allowing you to witness firsthand how it transforms the development landscape Through this engaging demo you ll unlock the potential of automated updates and seamless synchronization breathing new life into your coding endeavors So without further ado let s delve into the world of file watch and unveil the magic it brings to your development process Demo Project Todo List Application Step Clone the repositoryBegin your journey by cloning the repository for our Todo List Application In your terminal execute the following command git clone Step Examining the Compose fileDive into the heart of the Compose file that powers our Todo List Application The Compose yaml file orchestrates the interplay between services and introduces the magic of Docker Compose File Watch services app build x develop watch action rebuild path command sh c yarn install amp amp yarn run dev ports working dir app volumes app environment MYSQL HOST mysql MYSQL USER root MYSQL PASSWORD secret MYSQL DB todos mysql image mysql ports volumes todo mysql data var lib mysql environment MYSQL ROOT PASSWORD secret MYSQL DATABASE todosvolumes todo mysql data This compose file defines two services web and mysql and a volume named todo mysql data similar to the original file However the web service now includes an x develop section which enables the experimental watch mode for this service The watch section contains two actions sync and rebuild The sync action specifies a path to watch for changes in the host file system and a corresponding target path inside the container to synchronize changes to The rebuild action specifies a path to watch for changes in the host file system and triggers a rebuild of the container when changes are detected The web service maps port of the container to port of the host sets the working directory inside the container to app and mounts the current directory on the host to app inside the container The mysql service uses the official MySQL Docker image maps port of the container to port of the host and creates a volume named todo mysql data to persist the MySQL data Step Starting the container servicesdocker compose psNAME IMAGE COMMAND SERVICE CREATED STATUS PORTSapp app app app docker entrypoint s… app seconds ago Up seconds gt tcpapp mysql mysql docker entrypoint s… mysql days ago Up seconds gt tcp tcp Step Accessing the appOpen http localhost to access the app Step Testing the Compose Watch FeatureTo test the watch mode in the Docker Compose file you can make some changes to the source code files that are being watched and see if the changes are automatically synchronized and or trigger a rebuild of the container Run the below command to start monitoring for file edits within your project and keep the terminal open docker compose alpha watchIn the src index js file update the line to use the new empty text app listen gt console log Listening on port app listen gt console log Listen on port Step Verifying the effectchange detected on src index jschange detected on src index jsIf you make changes to the index js under the app directory the changes should be automatically synchronized to the corresponding files inside the container and you should see the changes in your results Note that the watch mode is still an experimental feature so there may be some issues or limitations that you encounter during testing Compose Watch also allows you to specify the name of directories For example this Docker Compose file defines a service called web which is built from the current directory and includes an experimental feature called x develop The x develop section includes a list of actions to be taken when changes are detected in certain directories or files In this case there are two actions defined sync This action will synchronize any changes made to the web directory on the host machine to the app web directory inside the container running the web service This ensures that any changes made to the web application code are immediately available inside the container rebuild This action will trigger a rebuild of the web service container if changes are detected in the package json file This ensures that any changes to the application s dependencies are automatically installed and available inside the container services web build x develop watch action sync path web target app web action rebuild path package jsonIn nutshell if you modify package json such as by installing a new npm package Compose will rebuild the image and replace the existing service with an updated version Refer to the next section to see it in action Conclusion In the dynamic landscape of containerized development Docker Compose File Watch emerges as a beacon of efficiency and innovation This experimental feature liberates developers from the chore of manual container updates unleashing a new era of productivity and collaboration By seamlessly synchronizing code changes with container instances Docker Compose File Watch empowers developers to channel their energy into coding refining and creating fostering an environment where ideas flourish As you embark on your containerized development journey remember that while technology propels progress it s your insights and creativity that shape the future of software Embrace Docker Compose File Watch enhance your workflow and embark on a seamless development journey like never before Thanks for reading this If you enjoyed this article make sure to leave a and if you need any other information or want to request a topic I should cover feel free to drop a comment below You can also follow me on LinkedIn	2023-08-23 21:34:51
Apple	AppleInsider - Frontpage News	Apple voices official support for California SB 244 right to repair bill	https://appleinsider.com/articles/23/08/23/apple-voices-official-support-for-california-sb-244-right-to-repair-bill?utm_medium=rss	Apple voices official support for California SB right to repair billAs California s SB right to repair bill is routed through the capitol Apple has voiced its support in a surprise move from the company Apple supports right to repair billRight to repair has become an increasing issue in Silicon Valley as lobbyists fight to keep repair control under mega corps like Apple and Google Bills like SB have been openly opposed by Apple in the past but this one has gotten the official stamp of approval per a letter sent by Apple s legal team Read more	2023-08-23 21:22:29
海外TECH	Engadget	Facebook’s ‘state-controlled media’ labels appear to reduce engagement	https://www.engadget.com/facebooks-state-controlled-media-labels-appear-to-reduce-engagement-212703277.html?src=rss	Facebook s state controlled media labels appear to reduce engagementFacebook s “state controlled media labels appear to reduce engagement with content from authoritarian nations A new study reveals that with the added tags users engagement decreased when they noticed content labeled as originating from Chinese and Russian government run media However the labels also appeared to boost user favorability of posts from Canadian state media suggesting broader perceptions of the country play into the tags effectiveness Researchers with Carnegie Mellon University Indiana University and the University of Texas at Austin conducted the set of studies which “explored the causal impact of these labels on users intentions to engage with Facebook content When users noticed the label they tended to reduce their engagement with it when it was a country they perceived negatively The first experiment studied people with US based Facebook accounts ーwith and without state controlled media labels Although their engagement with posts originating from Russia and China went down it only had that effect if they “actively noticed the label A second test in the series observed US Facebook users to determine that their behavior was “tied to public sentiment toward the country listed on the label In other words they responded positively to media labeled as Canadian state controlled and negatively toward Chinese and Russian government run content MetaFinally a third experiment examined how broadly Facebook users interacted with state controlled media before and after the platform added the labels They concluded the change had a “significant effect as the sharing of labeled posts dropped by percent after the shift and user likes of tagged posts fell by percent The paper s authors also noted that training users on the labels “notifying them of their presence and testing them on their meaning significantly boosted their odds of noticing them “Our three studies suggest that state controlled media labels reduced the spread of misinformation and propaganda on Facebook depending on which countries were labelled Patricia L Moravec the study s lead wrote in the paper s summary However the studies ran into some limitations in determining correlation vs causation The authors say they couldn t fully verify whether their results were caused by the labels or Facebook s nontransparent newsfeed algorithms which downlink labeled posts and make related third party research exceedingly difficult in broader terms The paper s authors also note that the experiments measured online users “beliefs intentions to share and intentions to like pages but not their actual behavior The researchers unsurprisingly given the results recommend social companies “clearly alert and inform users of labeling policy changes explain what they mean and display the labels in ways that users notice As the world grapples with online misinformation and propaganda the study s leads urge Facebook and other social platforms to do more “Although efforts are being made to reduce the spread of misinformation on social media platforms efforts to reduce the influence of propaganda may be less successful suggests co author Nicholas Wolczynski “Given that Facebook debuted the new labels quietly without informing users many likely did not notice the labels reducing their efficacy dramatically This article originally appeared on Engadget at	2023-08-23 21:27:03
海外TECH	Engadget	BioWare cuts around 50 jobs to become a 'more agile and focused studio'	https://www.engadget.com/bioware-cuts-around-50-jobs-to-become-a-more-agile-and-focused-studio-211513365.html?src=rss	BioWare cuts around jobs to become a x more agile and focused studio x Mass Effect and Dragon Age studio BioWare is eliminating approximately positions as parent Electronic Arts attempts to turn it into a quot more agile and focused studio quot The reorganization was “unavoidable according to BioWare general manager Gary McKay as it was necessary in order to meet the studio s evolving needs quot After much consideration and careful planning we have built a long term vision that will preserve the health of the studio and better enable us to do what we do best create exceptional story driven single player experiences filled with vast worlds and rich characters quot McKay wrote in the announcement quot This vision balances the current needs of the studio ーnamely ensuring Dragon Age Dreadwolf is an outstanding game ーwith its future including the success of the next Mass Effect quot McKay noted that BioWare is quot committed to supporting quot affected staff adding that quot we ve chosen to act now in part to provide our impacted colleagues with as many internal opportunities as possible quot The affected roles align with similar positions at other EA studios and workers will be provided with professional assistance if they apply for any While they will still be credited for their work on Dragon Age Dreadwolf McKay wrote that it s quot unlikely quot that everyone affected will be able to find a new position at EA The next Mass Effect game which was announced in is still in pre production with a team led by Mass Effect Andromeda nbsp producer Mike Gamble McKay wrote that the studio s dedication to Dragon Age Dreadwolf which will be the first game in the series since quot has never wavered quot and that BioWare is quot confident quot of having enough time to make sure the next entry quot reaches its full potential quot The cuts are related to an announcement that EA CEO Andrew Wilson made in March Wilson said the company would lay off around percent of its workforce of its nearly employees and reduce its office space footprint BioWare is said to have around workers Along with news of the job cuts it emerged that EA is severing ties with game services company Keywords which was working with BioWare on Dreadwolf EA was unable to reach a new agreement with Keywords an spokesperson told GamesBeat and the existing contract comes to an end on September th Among other things Keywords provides playtesting services A group of quality assurance contractors in that part of the company voted to form the first video game labor union in Canada last year EA has reportedly renewed contracts with Keywords since the June union vote but it was unable to agree terms this time around amid the BioWare changes This article originally appeared on Engadget at	2023-08-23 21:15:13
ニュース	BBC News - Home	GCSE results set to drop close to pre-Covid levels	https://www.bbc.co.uk/news/education-66476072?at_medium=RSS&at_campaign=KARANGA	england	2023-08-23 21:43:33
ニュース	BBC News - Home	PM failed to correctly declare wife's shares, says watchdog	https://www.bbc.co.uk/news/uk-politics-66596319?at_medium=RSS&at_campaign=KARANGA	financial	2023-08-23 21:31:33
ニュース	BBC News - Home	World Championships 2023: Britain's Josh Kerr stuns Jakob Ingebrigtsen to take gold	https://www.bbc.co.uk/sport/athletics/66595349?at_medium=RSS&at_campaign=KARANGA	World Championships Britain x s Josh Kerr stuns Jakob Ingebrigtsen to take goldBritain s Josh Kerr stuns Olympic champion Jakob Ingebrigtsen to win m gold at the World Championships in Budapest	2023-08-23 21:09:48
ニュース	BBC News - Home	World Championships 2023: Katie Moon and Nina Kennedy share pole vault gold medal in Budapest	https://www.bbc.co.uk/sport/athletics/66600733?at_medium=RSS&at_campaign=KARANGA	World Championships Katie Moon and Nina Kennedy share pole vault gold medal in BudapestKatie Moon and Nina Kennedy decide to share their pole vault gold medal in a touching moment at the World Championships in Budapest	2023-08-23 21:05:56
ニュース	BBC News - Home	Hermoso's union says Rubiales kiss should 'not go unpunished'	https://www.bbc.co.uk/sport/football/66598539?at_medium=RSS&at_campaign=KARANGA	Hermoso x s union says Rubiales kiss should x not go unpunished x A union representing Spain forward Jennifer Hermoso who was kissed on the lips by Spanish football federation president Luis Rubiales says the incident should not go unpunished	2023-08-23 21:26:57