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PostgreSQL their latest version (PostgreSQL 14) on September 30th, which includes a bunch of features like pipeline API, gathering statistics on replication slots, query parallelism improvements and so on. While the of PostgreSQL can be traced back to 1986, it has been in active development for the past 30 years. Tons of companies, agnostic of the type and size, have trusted Postgres over the years and their tagline “The world's most advanced open-source relational database” is hardly an overstatement. announced origin In a typical, non-trivial system, there is more than one database server, and the data is often copied across multiple servers. A fairly common notion in a distributed system, this copying of data across multiple server nodes is known as replication. Replication processes are often abstracted from the consumers of the database, so most of the application layers are transparent to which node serves the data and if you’re an app developer like me, we expect things to “just work”. However, what goes behind the scenes of some of the most sophisticated databases of the world is often a fascinating reading and learning experience. In this post, we will start diving into the internals of Postgres to understand how replication works and data integrity is ensured using WAL (Write-Ahead Logging). We will then steer towards interesting concepts like logical decoding and output plugins. Finally, we will start hacking some code to write our own plugin that can send push notifications! I know this sounds a bit contrarian to the common approach of sending notifications from application servers, but hey what's the fun in doing common boring things! Let's dive right in :) Replication at a high level is the process of transferring data from a primary server to a replica server. In Postgres lingo, servers can either be primary or stand-by. Primary servers are the ones that send data, while standbys are the receivers of replicated data. In certain settings, standbys can also act as senders. Replica or standby servers can take over if the primary fails which is the crux of how database systems manage fault tolerance. https://www.enterprisedb.com/postgres-tutorials/postgresql-replication-and-automatic-failover-tutorial#replication WAL (Write-Ahead Logging) is the standard method to ensure data integrity in Postgres. Systems are bound to fail and database servers are not excused from that. At the application layer, it's comparatively easier to retry and manage failures without typically resulting in data loss, however, when we go deep in the stack, especially at the data layer, persistence is doubtlessly super critical. When consumers make a write operation to the database, before the database is acted-upon, the changes are written to the server’s file system. This by design ensures data persistence and recovery in the cases of operating system crashes or hardware failures. Consumers are (obviously) abstracted from these internal mechanisms and applications connected to the Database expect things to work out of the box. The log entry we talked about above is known as the Write-Ahead Log record while the process is called Write-Ahead Logging. Each record has a Sequence number which is used for checkpointing periodically after logs are synchronized to the database. In cases of system crashes, this checkpoint is used to re-read and synchronize. WAL, being a reliable method for synchronizing or recreating the ordered state of the database, is used for replication across multiple servers. WAL can replicate the data using either a File based approach or a Streaming approach where both approaches have their own pros and cons. Streaming replication, although is typically in an asynchronous mode, can be tuned to be synchronous. https://hevodata.com/learn/postgres-wal-replication/ WAL records being representative of the internal state of the Database system, are not easy to be fed into or understood by an external system/consumer. Logical Decoding to the rescue! “ is the process of extracting all persistent changes to a database's tables into a coherent, easy to understand format which can be interpreted without detailed knowledge of the database's internal state.” Using logical decoding, replication solutions and auditing can be achieved much easily. Logical decoding The following diagram depicts the logical decoding process. Source: https://techcommunity.microsoft.com/t5/azure-database-for-postgresql/change-data-capture-in-postgres-how-to-use-logical-decoding-and/ba-p/1396421 In order to enable the logical decoding, you need to make some configuration changes to the Postgres instance - wal_level = logical # default value is `replica`
max_replication_slots = 1 # good enough for a sample project
max_wal_senders = 1 # default is 10 Ref: and for details on tuning the configuration https://www.postgresql.org/docs/current/runtime-config-replication.html https://www.postgresql.org/docs/current/runtime-config-wal.html Once we have the configuration up and running, record changes are passed to the Output Plugin which does the key step of transformation from the WAL format to the format specified in the plugin (eg. JSON). These changes are made available on the replication slot(s) and consumer applications can receive the stream of updates as and when those occur. Some output plugins and consumer apps out there - Output Plugin that converts WAL output to JSON objects [Open Source] Postgres app that can consume update stream [Out-of-the-box with Postgres]
decoderbufs Output Plugin that delivers data as protobuf [Open Source, Used in ] wal2json pg_recvlogical Debezium We can write a consumer from scratch or use battle-tested tools built to achieve this at scale. Debezium is one of the most widely used solutions out there. Netflix open sourced their in-house tool for CDC called DBLog - is a fantastic read on it. https://netflixtechblog.com/dblog-a-generic-change-data-capture-framework-69351fb9099b What are we building? Let’s keep this simple - whenever a new user entry is made to Postgres table, we will consume replication logs and send a welcome email to the user. Let’s hack some code! We will be using a Go package which is a Postgres logical replication library. https://github.com/jackc/pglogrepl Step 1: Follow Logical replication instructions README has step-by-step instructions to configure logical replication in your local Postgres Instance. https://github.com/jackc/pglogrepl Step 2: Try out the demo in the repo Give a try - it demos how the library works under the hood https://github.com/jackc/pglogrepl/tree/master/example/pglogrepl_demo Step 3: Update the demo code to log new email inserts To keep it simple for this blog post, let's add some code that prints out a specific email that was inserted on the new row. A.  Look for inserts and print the WAL data if logicalMsg.Type() == 'I' {
   // `I` stands for Insert
   log.Println(string(xld.WALData))
   // this logs the complete entry
   // however it would require a little more cleanup
} For example, a new entry with ID 5 and email shows up as I@Nt5ttejas@courier.com tejas@courier.com B. Clean up the internal WAL representation and derive email // find the second column
  walData := xld.WALData[5:]
  pos := bytes.Index(walData, []byte("t"))

  email := walData[pos+1:]
  pos = bytes.Index(email, []byte("t"))

  email = email[pos+1:]
  emailStr := string(email) C. Send a welcome email to the user We will be creating a new template by configuring an email integration supported by Courier. messageID, err := client.Send(context.Background(), "VDPE8SWN1K4BWMP8RJ101YRZTF3J", "user-id", 
courier.SendBody{
   	Profile: profile{
   	   Email: emailStr,
   	},
   	Data: data{
   	   Foo: "bar",
   	},
})

if err != nil {
  log.Fatalln(err) 
}

log.Println(messageID) Find the modified code at Here’s a quick of how things work. https://github.com/tk26/pglogrepl loom video Now that we have configured Postgres to send emails by listening to replication logs, changing it to send a push notification would be as simple as changing a configuration in the Courier Studio. Thanks for reading! Reach out to us if you have any questions or comments or you know, just say Hi! @trycourier

Hacking PostgreSQL Internals to Deliver Push Notifications

If you’re seeing this interview draft, it means you’ve recently published on HackerNoon . For this reason, we would like to help the community get to know you better as well as find out some writing tips from you. a story that the community found interesting and/or valuable While this template is automatic, our interest in the answers below is genuine and our human editors (and some cyborg wannabes) will review it before publishing. So let’s start! Tell us a bit about yourself. For example, name, profession, and personal interests. Maria Delgado. Interesting! What was your latest Hackernoon Top story about? My latest was on the unsung hero, data. Latam startups are at a disadvantage, experiencing a sharp decline in investment compared to last year and Q over Q. Therefore tools such as TheVentureCity’s Growth Scanner have helped LatAm startups leverage user data to ensure product-led growth, market fit, and build strong relationships with investors. Do you usually write on similar topics? If not, what do you usually write about? I usually write about tech innovations, LatAm startups, UFC, and beer brewing (my hobbies). Great! What is your usual writing routine like (if you have one?) I usually focus on the story behind startups and their solutions. Why are they relevant, what are they solving, and why would people be interested in reading about them? Being a writer in tech can be a challenge. It’s not often our main role, but an addition to another one. What is the biggest challenge you have when it comes to writing? Sharing a unique story can be a challenge when there’s a hot topic and tons of articles about the same thing. Therefore, looking for your secret sauce and a differentiating factor can make a difference. What is the next thing you hope to achieve in your career? I hope to continue writing about tech solutions pertinent to emerging markets to help build a global market and uplift their quality of life. Aside from that, I’m happy to share stories about my hobbies and spread that passion with like-minded readers. Wow, that’s admirable. Now, something more casual: What is your guilty pleasure of choice? I’m not really into entertainment news, following celebrities, etc., but I do admire how they are looking to branch out, investing in startups, and actively seeking out advice from VCs. I feel like even those reality stars can help leave a mark and positive effect on today’s market. Do you have a non-tech-related hobby? If yes, what is it? I am an avid beer brewer and boxer. I enjoy betting on UFC and NFL and am actively helping to share this passion and knowledge with latAm culture. What can the Hacker Noon community expect to read from you next? I will continue highlighting the benefits of investing in LatAm startups and what makes their product innovative and resilient. Many of these solutions can be scaled to reach greater regions, and now is the best time to continue investing in Latin America. What’s your opinion on HackerNoon as a platform for writers? Hackernoon is a great platform to help share stories that drive action. I’ve seen how many connections are made among businesses and entrepreneurs that would otherwise take longer without the exposure Hackernoon provides to top stories. Thanks for taking time to join our “ ” series. It was a pleasure. Do you have any closing words? Meet the writer I look forward to sharing more stories showcasing how LatAm truly is building resilience for the future.

Meet the Writer: Hacker Noon's Contributor Maria Delgado on LatAm Startups, Writing, and More

Designing Neural Nets for the Human Intuition Challenge

Learn how to build your own JSON speaking REST API using the asynchronous Tornado networking library. It wouldn’t be an overstatement to say that REST APIs power the web. Everything from social networks to the apps that help you order pizza is powered by REST APIs. In fact, mobile apps, enterprise applications, and even games need to talk to servers once in a (very short) while. There’s no point in limiting REST API tutorials to just web developers. Tornado & Motor Tornado is a mature, battle-tested web framework written in Python. Motor is an async driver for MongoDB that integrates really well with Tornado. These are going to be the two main tools we will be working as we create our superhero API. Prerequisites and initial setup Before we begin, please ensure that you have: python>=3.6 installed on your machine. The venv module along with pip installed. mongodb up and running at localhost:27017. A decent text editor or IDE. On Ubuntu and similar systems, venv and pip can be easily installed using: $ sudo apt install python3-pip python3-venv Create a virtual environment for our new project. $ mkdir heroes
$ cd heros
$ python3 -m venv env Install the project dependencies. $ source env/bin/activate
$ pip install tornado motor Initial App Configuration Create a folder named heroes inside the project folder (which is confusingly also named heroes but this is how things are!). This folder will contain our .py files. In the app.py file, we create an instance of tornado.web.Application and make the tornado.httpserver.HTTPServer serve it. The handlers.py file contains the request handlers that inherit from tornado.web.RequestHandler. The HomeHandler implements the get method so that it can handle GET requests. Tornado automatically sends the response as JSON when a dictionary is passed as a parameter to the write method. The ErrorHandler implements the prepare method which is called before the get or any other method. In this case, we send back an error message and finish the response. <a href="https://medium.com/media/a0c952eb27c148b1efdb683e15a6774f/href">https://medium.com/media/a0c952eb27c148b1efdb683e15a6774f/href</a> Firing up the Motor Connecting the MongoDB driver to Tornado is simpler than most web frameworks. Attach an instance of the MotorClient to the Application object. Use the heroes database. Refactor the handlers to inherit from a BaseHandler. This step is not required, but it will save us from a lot of duplicate code in the future. Thank you for these awesome ! Pycharm Git Diffs If you prefer to copy, you can find the updated files . here An API for Super Heroes Add a /heroes endpoint that allows CRUD operations for the hero resource. Add the /heroes routes to the Application instance in app.py. Add the prepare method in the BaseHandler that automatically parses the request body as JSON for POST and PUT requests. Add the HeroesHandler class with get, put, delete, and post methods. Git Diff for app.py file Two routes are added to the app. One for the /heroes endpoint and another for the /heroes/<hero_id> endpoint. While the former is the general endpoint for the resource, the latter is used for operations on a single item. The changes in handlers.py are too many to show in a diff. Please check the complete source code listing below. <a href="https://medium.com/media/1df1e23340cccf404cd22d1a8770b05b/href">https://medium.com/media/1df1e23340cccf404cd22d1a8770b05b/href</a> The get method returns all the heroes for the /heroes route. For the /heroes/<hero_id> route, the details of a single hero are returned. The get method also implements a basic form of paging. The post method creates a new hero in the database. The name is required while the other fields are optional. The put method is used to replace an existing hero with a different one. Also, note the use of async/await syntax for asynchronous database operations. Final Project Structure A tree view of the heroes project folder. heroes
├── heroes
│   ├── app.py
│   ├── handlers.py
│   └── __pycache__
└── env
    ├── bin
    ├── include
    ├── lib
    ├── lib64 -> lib
    └── pyvenv.cfg

7 directories, 3 files Running the Application Ensure that the mongod process is running at localhost:27017. Open a terminal in the project root folder and run: $ source env/bin/activate
$ export PORT=8080
$ export MONGO_CONNECT_URI=mongodb://localhost:27017
$ python3 -m heroes.app The API server should now be up and running. Let’s hit the endpoints and check the results. Consuming the REST API httpie is a great library for consuming APIs from the command line. You can install it using: $ pip install httpie What next? We have built a really cool REST API but it is far from being production-ready. Our API can be a lot more robust and user-friendly. If you want to learn more, Check out this article on by . Restful API Design Mahesh Haldar Skim through the documentation of . Tornado Keep an eye out for by me! more Python tutorials Thanks for reading, drop a few claps if you enjoyed it. Check out some other posts I’ve written, follow and reach out to me on . Linkedin Ramit Mittal.

Tutorial: Writing a REST API with Tornado & Motor

These are the 100+ Companies Hiring Data Scientists Now

One excellent way to build is by scraping the web. It becomes especially relevant when sources like Common Crawl or official APIs fail to meet your project’s requirements (for example, the data isn’t recent enough or Twitter prices you out). However, web scraping comes with its own challenges like and geo-restrictions. This is where our hero — proxies — enter the scene. datasets CAPTCHAs A proxy server is another computer (a server, phone, or even IoT device) that lets you access the web through itself. This way, you get a new IP address from an optionally different location. Proxies are much like VPNs — the difference is that you can use many of them at once instead of just one or two connections. Proxy servers are becoming more and more necessary as websites implement rate limiting and more sophisticated restrictions to prevent automated access. Sometimes, for good reasons, though often it’s to protect their commercial interests or monopolize data. Proxies won’t solve all your problems; but aside from basic hygiene, such as using realistic user-agents, they’re the most effective way to keep your web scraper running. This guide will give you a strong understanding of proxy servers in the context of web scraping. It comes with theoretical knowledge together with some practical data we collected for our annual . proxy market research First things first: you most likely don’t want to use free proxies When web scrapers (the people) encounter a need for proxies, their first impulse is to try out a free proxy list. These lists are publicly available online; most of the proxies in them come from vulnerable or mismanaged servers. One big problem with free proxy lists is that you never know who runs them. The operator may have malicious intentions, which can manifest in ad injection, traffic logging, and other nasty things. This sounds scary, but it’s unlikely to affect you much as a data scientist: you probably won’t configure proxies on the operating system level or use them to access your bank account. A more boring — though realistic — issue is that free proxies are simply unreliable. They rarely stay online for long; the ones that do run are unbearably slow because they have hundreds of tenants; and because they have hundreds of tenants, such proxies very quickly strike themselves out with any relevant website. Not a great tool to work with. For this reason, I strongly recommend paying for a commercial proxy service. Types of proxy servers out there Proxy servers are most often categorized by the IP source. For web scraping purposes, you’ll most likely choose between three types: datacenter, residential, or ISP (also called static residential) proxies. Datacenter proxies These proxies are hosted on servers in data centers. They can be instances of Amazon Cloud Services (AWS) or come from any other cloud hosting provider. IP databases see datacenter proxies as belonging to or ranges. hosting datacenter Datacenter proxies typically run on powerful hardware and internet connection, so you can scrape a lot of data fast. They can be a very efficient choice for targets that don’t monitor IP reputation but struggle with websites that do. Residential proxies These proxies come from the residential devices of real people (hence the name). For example, they can run on a Windows laptop, Android phone, or a smart fridge on Wi-Fi. IP databases classify residential proxies as or connections. landline mobile Residential proxies always come in large pools of addresses from around the world. They’re less predictable than datacenter IPs because they rely on the connection quality and availability of the host device. However, this very feature makes residential proxies very effective with all kinds of websites, as they look like regular visitors. ISP proxies These proxies are hosted on servers in data centers registered under consumer internet service providers like Verizon. This is achieved by signing a contract with an ISP and getting it to announce IPs on its network. Ideally, IP databases should identify such proxies as or connections. Sometimes, though, smaller regional ISPs are still classified as data centers. but landline mobile ISP proxies retain the qualities of datacenter proxies but are able to scrape more effectively due to a better IP reputation. How proxies are sourced and whether they’re legal At this point, you may be thinking, “Woah, wait a minute! Android phones? Sounds awfully like a botnet! Is that even legal?” This is a good question to ask, and it shows that you care. Many don’t. The fact is that there’s a fine line between a commercial proxy server and a botnet. It applies less to datacenter proxies where the supply chain is pretty much clear: a cloud host buys IPs, puts them on a server, and rents the addresses to a proxy provider. But the question of ethics becomes very relevant with residential proxy networks. Without delving too deep into the topic, residential proxies can be sourced in several ways. The most popular method is via SDKs in desktop and mobile applications. gives concrete examples of what that looks like. This video https://www.youtube.com/watch?v=1-Lbgd4BYHI&embedable=true Another way is to exchange traffic directly for a service (such as a free VPN, see BrightVPN) or money (using bandwidth-sharing apps like Honeygain). In any case, the onus falls on the proxy provider to ensure that the IP source is aware of the arrangement and consents to it. You should be able to find information about proxy sourcing and usage approaches on the provider’s website. This significantly reduces the chance that you’ll be using a botnet. Proxy server configurations Proxy servers may have different configurations based on and . tenancy rotation The first criterion describes how many people can use the same proxy server at once. All free proxy lists have potentially hundreds of tenants, while commercial proxy providers impose limits. In the market lingo, or means you’ll use the same proxy server with several other people (often one to four). or means that you alone will use the proxies for all or particular domains. shared semi-shared Private dedicated The ability to choose tenancy is a feature of datacenter and ISP proxies, as providers have full ownership over them. It’s unavailable with residential proxies but also less relevant — residential users have more natural browsing patterns and are less likely to overload websites with requests. The second criterion, rotation, shows whether proxy servers switch automatically. The ones that don’t often come in proxy lists formatted as IP:Port (1). The ones that do take the format of endpoint:port (2): 192.168.0.1:10000 en.proxyprovider.net:10000 The endpoint functions as a gateway to the provider’s proxy pool. It automatically routes your requests through different addresses in the backend. Even when an IP address changes, the endpoint remains the same. Rotating proxies are very convenient for web scraping, as you get access to an effectively infinite number of IPs (thousands to millions). However, such services often charge for traffic expenditure, while static proxy lists tend to offer unlimited traffic. Comparing the different proxy types Let’s compare the discussed proxy types based on their various characteristics. Affordability In the case of rotating proxy networks, residential proxies cost around eight to 10 times more than datacenter addresses and a little less than rotating ISP proxy networks. Static proxy networks usually charge per IP address. Compared to ISP proxies, datacenter proxy servers cost two to three times less, depending on how much you buy. Infrastructure performance Despite routing traffic through unpredictable end-user devices, major residential proxy networks work very well. For web scraping purposes (when the IP rotates with each connection request), they transfer data almost as well as datacenter proxies: We also failed to see a big difference in latency. Below are response times for requests made to the nearest server of a global CDN (the response size is several kilobytes) and Amazon (around 1 MB response size): One area where datacenter and ISP proxies dominate is throughput. They have wider pipes for transferring data. Some residential proxies can be very fast, but you can just as well encounter servers that fail to reach 1 Mbps. There’s much less predictability. IP Uptime Datacenter and ISP proxies can stay up nearly 24/7, going offline only when an outage or maintenance occurs. The uptime of a residential proxy depends on various factors, such as whether it comes from a Windows or Android device. In any case, it’s much shorter and less dependable compared to server-based proxies. We wrote a script that pinged an IP database every 20 seconds to see how often a residential IP address would change. Here are some results: 43 seconds IP #1: Over an hour IP #2: 3 minutes, 33 seconds IP #3: 8 minutes, 31 seconds IP #4: Over an hour IP #5: Scraping effectiveness Datacenter proxies struggle against protected or highly popular websites like Google or social media. This can be somewhat mitigated by choosing dedicated IPs with a cleaner usage history. Sometimes, connecting from a datacenter IP range is enough for websites not to let you in. In such cases, the only recourse is to use a different proxy type. ISP proxies have a better IP reputation by default, so they face less initial scrutiny. However, they still have less realistic browsing patterns compared to a true residential address. Residential proxy servers form large pools, are very diverse, and share browsing history with real people. These qualities make them very hard to distinguish from the website’s broader audience. Location variety Datacenter and ISP proxies are hosted in data centers, and the number of available datacenters is limited. The most frequent location is probably Ashburn, though major providers can get you datacenter IPs from dozens of countries. However, if you need addresses in smaller locales, and especially their non-capital cities, you’ll be out of luck. Residential proxies have no such restrictions — as long as there’s a device and a willing participant, anyone from anywhere can join. Consequently, major providers can offer IPs in all countries with city, ASN, and sometimes even ZIP code targeting. Popularity Based on our survey of major proxy providers, most chose residential proxies as their most popular product. Only two providers specified datacenter proxy servers, and none ISP proxies. Datacenter proxies have been falling off in recent years, as major targets like Amazon, Google, LinkedIn, and others tightened their security systems. ISP proxies have the capacity to take their place, but their uptake is hindered by sourcing difficulties — it’s hard to get reputable ISPs onboard. Recommendations for your projects But enough theory. How can you apply this knowledge to your project? I’ve modeled multiple scenarios with proxy server suggestions. To keep this article free from commercial interests, I won’t mention particular providers. If you’d like some recommendations, we compare major providers (Disclaimer: we’re in an affiliate relationship with most of those companies. However, this has no impact on our market reports.) on our website Scraping websites without advanced protection Scraping a minor news portal, e-commerce website, or even non-Google search engine. Example: Rotating datacenter proxies. You can get access to a pool of 2,000–100,000 rotating IPs for $0.7/GB or less. You won’t have to worry about replacing blocked IPs, and the cost of traffic is low enough for some serious data extraction. Recommendation: Downloading multimedia content Downloading videos off a streaming service or pictures from an image aggregator for archiving purposes. Example: Static datacenter or ISP proxies. They are fast and don’t count traffic expenditure. Go for datacenter proxies when the website allows it and ISP proxies otherwise. Recommendation: Crawling many different websites Searching for brand mentions throughout the web. Example: Static datacenter or ISP proxies. Crawling requires a lot of data, so it’s best to choose a proxy type that doesn’t use traffic as the main metric. Also, even a finite number of IPs will take you far when you switch targets. Recommendation: Scraping large popular targets Extracting job ads from LinkedIn, company information from G2, or hashtagged posts from a social media network. Example: Residential proxies. With an effectively infinite number of IPs, you won’t risk banning out your proxies. In addition, you’ll experience a higher success rate compared to other proxy types. Recommendation: Collecting real-time data Tracking stock price movements. Example: Datacenter proxies if the website allows them; else, ISP proxies**.** Their fast connection speed ensures that you’ll extract data as it appears. Recommendations: Accessing hyper-localized pages Monitoring search engine page positions for localized Google queries. Example: Residential proxies, as they support city-level IP filtering. Recommendation: Conclusion This article gave you a brief introduction to proxy servers for web scraping purposes. After reading it, you should be able to distinguish between the main proxy types, configurations, and which setup would benefit your data science project the most.

Proxy Servers for Your Data Science Project: A Comprehensive Guide

আপনার ডেটা বিজ্ঞান প্রকল্পের জন্য প্রক্সি সার্ভার: একটি ব্যাপক নির্দেশিকা

Proxyserver für Ihr Data-Science-Projekt: Ein umfassender Leitfaden

Servidores proxy para su proyecto de ciencia de datos: una guía

Serveurs proxy pour votre projet de science des données : un guide

आपके डेटा साइंस प्रोजेक्ट के लिए प्रॉक्सी सर्वर: एक गाइड

データ サイエンス プロジェクトのプロキシ サーバー: ガイド

데이터 과학 프로젝트를 위한 프록시 서버: 종합 가이드

Servidores proxy para seu projeto de ciência de dados: um guia

Veri Bilimi Projeniz için Proxy Sunucuları: Kapsamlı Bir Kılavuz

Máy chủ proxy cho Dự án khoa học dữ liệu của bạn: Hướng dẫn

数据科学项目的代理服务器：指南

Windows 10 operating system designed and built with tons of microtask to macro modules features, just imagine like an electron bombarded in an “Atom”. Alright, let’s get to the business cut the blah blah story. ★ You may or may not noticed that The Microsoft Compatibility Telemetry module occupies your computer “ ” & “ ” and “ ” at certain points. CPU memory Power usage Usage trend When you turn on your PC, right away go to the “ ”, you will find the lab rat “ ”. Quick Tip: Task Manager Microsoft Compatibility Telemetry module What it’s the purpose: ★ It’s a compatibility feature enabled by default in the Microsoft operating system after (windows 8.1 successors), it helps to gather information about the user telemetry data (Applications installed, Device driver types, unknown application data), and the other software function together and forward that statistics to Microsoft center( Unknown locations). If you know about the locations, let us know in the comment sections. They use it to improve the user experience program and improve the Windows 10 services such as security, OS enhancement, compatibility improvement. ★ In this post, we will discuss a few methods to the “Microsoft Compatibility Telemetry” on Windows 10 regardless of the windows 10 version. It would work on any versions. get rid of It’s 2020, who knows who will turn their back on, I mean, you may be surprised to see the disabled “ ” module could when you are to the next version. I will keep an eye on this matter, if I caught them in the act, I will update this post until then don’t whisper it to the Microsoft R&D team haha. Note: Microsoft Compatibility Telemetry re-appear updating the current Win10 versions Windows 10 introduced “ ”, they are categorized into Telemetry Requirements four types Complete set of data available to access including other levels as well. 1. Full- Used to identify and understand the device platform to interconnect dots( issues). 2. Basic- -Used to collect how the user is accessing Applications on the device. 3. Enhanced - used for Enterprise Threat Detection service. 4. Security ★ The Telemetry Full and Basic are visible to the users in the settings, and other remaining types of security, enhancement is not visible in settings, and they can be found in the Group Policy or REgistry programs. How Microsoft handles diagnostic data, you may wonder, aren’t you? Again it depends on the type of “diagnostic data” settings and controls enabled on your device, all the diagnostic data can be collected via the following methods: Data collection: It Contains data events, Operated by the User Experiences and Telemetry Modules. Small payloads: logs from the device for additional troubleshooting and operation purpose. Diagnostic logs: In the event of a crash or a Dump occurrence, this built-in tool collects the crash files and reports them together. Windows Error Reporting: ★ In the next post, I will tell you how these different types of diagnostic data are collected and processed. It will enlighten your knowledge trust me, bro. ✓ Data transmission: ★ To make sure your data is safer on Air, All types of diagnostic data are encrypted using TLS and Applied certificate pinning feature during the transfer from your windows 10 device to the Microsoft data management services. ✓ Endpoints: ★ In this section, you are the Hero. You can control, manage, data collection, and diagnostic data. Figure 1. Windows Endpoint- Data & Diagnostic control. ✓ They store and keep it as long as it’s needed. Data Retention period: Final Solutions: In this post, we will learn how to resolve these issues with five different options. Using TaskScheduler. (I) Option I- Diagnostic service. (ii) Option II- Using command Prompt. (iii) Option III- Group Policy Editor (GPE). (iv) Option IV- (v) Diagnostics & Feedback — ->How to control your diagnostics and feedback data. Option V- Registry Editor. (vi) Option VI - Using TaskScheduler Option I - ★ To disable/Turn of this service, please ensure to follow the given below steps : In the search box type “Task Scheduler App”, and then click on it. 2. To get to the “Application Experience folder window” navigate to the path as shown in Figure 2: Figure 2. Task Scheduler App-Navigate to this path. 3. Inside the Application Experience folder, Click on the first option “Microsoft Compatibility Appraiser”. 4. Just Right-click on it, select “Disable” as shown in Figure.3. Figure 3. Microsoft Compatibility Appraiser- Disable it. 5. Close the “Task Scheduler App”, and verify in the “task scheduler” if these issues persist. Diagnostic service Option II - ★ By disabling this Feedback service can also improve the system performance. Once you disabled it, you may not participate in the feedback process. In the search box type “Services”, and then click on it as shown in Figure 4. Figure 4. Search Services in the start menu. 2. To get to the “Application Experience folder window” navigate to the path. 3. Right-click and click properties. Now, choose Disabled from the Startup type. Figure 5. Startup type- Choose Disabled. 4. Click “Apply” first and then click “Ok”. Using command Prompt Option III - ★ All of our options objectives are to disable the “Microsoft Compatibility Telemetry”. In this CMD, we enter a couple of commands and keep entering it. Press key + R to open a “Run module”, then Enter “cmd” in the search box and continue as Administrator. Windows Figure 6. Open a command prompt. 2. To run the “cmd” as an administrator, follow the steps as shown in Figure 7. Right-click on the cmd and choose Run as an administrator. Figure 7. Run as an Administrator. 3. Now, feed each command and pressing the Enter button at the end of the command. one by one sc delete DiagTrack

sc delete dmwappushservice

echo “” > C: rogramData icrosoft iagnosis TLLogs utoLogger utoLogger-DiagTrack-Listener.etl

red add “HKLM OFTWARE olicies Microsoft indows ataCollection”/v AllowTelemtery/t REG_DWORD/d 0 /f \P \M \D \E \A \A \S \P \\ \W \D Group Policy Editor (GPE) Option IV- ★ (GPE) It’s is a built-in Windows administration tool, allows you to configure important settings on their computers or networks. One can perform operations like configuring the password requirements, startup programs, and define what applications or settings users can invoke on their own. Group Policy Editor Introduction: The final option seems to be a quick fix for the High usage caused by the “ ”. We gonna use Group Policy Editor (GPR) to disable the compatelrunner.exe. Let's begin the adventure! CPU Microsoft Compatibility Telemetry To open a Run command Press the key + R to open the Now, start typing and enter OK, as shown in Figure 8. Windows “Run Module”. gpedit.msc Figure 8. opening a GPE. 3. Now navigate to (GPE) as shown in this Tree map. Group Policy Editor Figure 9. navigate to (GPE) Telemetry properties. Group Policy Editor 4. Now, it's time to Double-click Allow Telemetry. 5. Select “Disabled”, then click Apply “OK”. 6) On your keyboard, press (all together) to open your Task Manager, check to see if using up a normal disk usage. Ctrl + Alt + Esc keys “Microsoft Compatibility Telemetry” ✓ Option V — Diagnostics & Feedback — >How to control your diagnostics and feedback data? To open settings click on menu> > > Start Settings Privacy Diagnostics & feedback. Figure 10. opening a Diagnostics & feedback. Figure 11. choosing Required Diagnostic data. 2. Now, If your computer has chosen optional diagnostic data, unselect it, and choose Required Diagnostic data as shown in Figure 11. To change the setting of the Inking and Typing, Tailored experience, Diagnostic Data all together just unselect it as shown in Figure 12. Go to , then select > > . Start Settings Privacy Diagnostics & feedback 2. Now, click Under , choose the setting you’d prefer. Tailored experiences Figure 12. Go to , then select > > . Inking and Typing, Tailored experience, Diagnostic Data- Disable it. Start Settings Privacy Diagnostics & feedback 2. Make sure that the setting is turned and then select . Diagnostic data viewer On Diagnostic Data Viewer To delete your diagnostic data ★ Under , you can delete diagnostic data for your device. Delete diagnostic data Figure 13. Delete Diagnostic data from your computer. Deleting the data here is not synchronized with your user account, nor does it stop your diagnostic data from being sent to Microsoft. So, they still got away around your back to get the data haha. Note: ✓ Registry Editor Option VI - if the registry is modified incorrectly, you may end up reinstalling or restoring your OS. I warned you prior. Modify the Registry at your own risk. Option V Warning: Life is what you make it Quote of the day: — English Proverb Explanation: Simple words but ones that are so true. Your attitude, how you see your world, will depend on the happiness and contentment in your life. And, we are the ones who control our attitude. How we react to any situation is up to us. Thanks for reading! Previously published at https://gtmars.medium.com/how-can-i-permanently-turn-off-or-disable-the-microsoft-compatibility-telemetry-task-to-prevent-aa9f0a264295

5 Simple Ways To Get Rid Of High CPU Usage Troubles on Windows

Raw data coming in from various sources is often inherently dirty data, rife with factual errors, typos and inaccuracies. Left unattended, this data becomes a nightmare. Imagine having to pull a report only to realize it has duplicated data – not to mention half of them don’t even have valid phone numbers or addresses. Your boss is not going to be happy. Correcting this faulty and inaccurate data, fixing typos, and punctuation issues, deleting duplicate information and bringing the data into a consistent format is necessary. And that’s where you’d need to implement a data scrubbing process. Tell Me Something New, Isn’t it Obvious I Need Clean Data? Actually, despite being an, ‘obvious,’ thing, most companies often end up neglecting the importance of clean data. In fact, data is not even considered part of a business process and is often wrongly assumed as an IT process. Most business users, managers and leaders are not even aware of the problems with their data until a key initiative fails. It’s even more challenging for IT managers when they are tasked with the mundane responsibility of manually sorting through data, when they could easily have an automated data scrubbing solution. In an age of digital technology, AI, automation and what not, you’ll still find employees in large organizations using manual data matching and Excel filters to clean data. If anything, this is counter-productive. Data today is so complex, it’s impossible to fix it manually on Excel sheets. Even for data experts, cleaning data manually is not a preferred task. Saving the Day With a Data Scrubbing Solution Apart from being hailed as a hero to fix your company’s data flaws, a data scrubbing solution can literally save your company hundreds of thousands of dollars and prevent them from making costly mistakes. Something that would take IT teams or data experts days and months to accomplish, would take a software just a few minutes (hours?). Also, a software gives you better results, promises accuracy and lets you breathe a sigh of relief as it processes millions of rows of data. Here are a few key benefits that you can use to convince your CEO, your CMO, your COO to invest in a powerful solution. Better Analysis Bringing data quality at par is simply good business sense. of companies state that their marketing, BI and CRM departments name untidy data as their biggest challenge. Low-quality data is the cause of inaccurate analysis, leading to decisions that can prove costlier in the long run. More than that, a clean data can give you better business insight and reveal hidden opportunities that may not have been visible before (really, bad data makes it impossible to see sense!) More than 40% Increasing Operational Efficiency Imagine all the time you’d have if you performed tasks that are of value if you weren’t busy fixing data. This is the greatest benefit of using an automated solution – you, your team and your company can improve their processes which in turn will impact their efficiency. For example, your company could save hundreds of dollars on return mails if the contact information in your database has verified and validated addresses. Data Matching Becomes a Breeze There is a crisis in your company. Sales are down. Customers are unhappy. Your company executives want reports from multiple departments in the company to determine a course of action. Guess what happens if you have bad data? You’d have to first fix data then manually match it. But there are millions of records from disparate data sources. How do you do that? You run a common data matching algorithm to consolidate data, only to realize your data is complex and way too messed up. Last course of action? You’d have to clean data first, make sure all errors are fixed before you can run an exact match. Well, luckily, most data scrubbing solutions come with allowing you to clean data and quickly match then *without* increasing your stress meter. data matching With all these major benefits in place, some experts also recommend data scrubbing as an ongoing background function carried out at businesses which are largely data-driven, to avoid any dirty data related hiccup. Ok, You Got Me. What’s Next? What’s next is deciding on the right data scrubbing solution. There are literally dozens of software solutions out there and depending on your business size, budget and requirements you can choose any that meets your criteria. Whatever you choose though, make sure that the solution does the following: Helps with Data Governance So ideally, you want a solution that helps you maintain a standard – meaning, you don’t want your data to have the same mistakes over and over again. Once you understand the problems plaguing your data, you’d want to make sure they don’t keep occurring. An enterprise-level data scrubbing solution does more than just cleans data – it helps you sets standards, which you might not even have thought about before. For example, you might not have known that your web form allows for the entering of phone numbers with punctuations (dashes or commas). When you want to match data, most of your phone numbers are not being matched simply because they have dashes or commas. When you start scrubbing this data to remove dashes and commas, you vow to yourself to implement a web parameter that STOPS the use of dashes. Uses a Combination of Algorithms to Ensure Accuracy Various algorithms have been devised to clean data which was previously done manually by the IT team, costing companies valuable time and resources; not to mention compromised accuracy as manual tasks are highly prone to human error. You wouldn’t want that on your hands! Machine matching and cleaning is always better. Everything is automated and there is very little chance to miss a field or a list. Because a good data scrubbing software will be using multiple matching algorithms to match data and highlight duplicates. Data is so complex these days that it takes a darn smart machine to identify that or may be the same person with different nicks. Bill and Billy Cat and Cath Does All the Boring Nitty Gritty Jobs for You A standard data cleaning software will perform some basic tasks like standardization, transforming unclean data into good data by removing errors and typos and normalizing numbers between a set minimum and maximum limit, finding hidden patterns and filling in missing values, removing irrelevant and duplicate data and assembling relevant data under correct formats for easy access – you know all the boring, redundant work that you want to get rid of ASAP! Often an Overlooked, Underrepresented Problem that Turns Into a Crisis This needs to be said! Although companies are running after the data bandwagon and want to be considered as a “data-driven” organization, they are the most reluctant in buying the right tool or solution to fix their problems. They’d rather make the lives of IT experts and data experts miserable with redundant activities than invest in a solution that can resolve the matter once and for all. Little do they realize that delaying the data cleaning job can result in a crisis in no time. Imagine what would happen if a segment of your customers accidentally receive an email that wasn’t meant for them. Or a data leak waiting to happen. Or a fine waiting to be imposed because your organization didn’t take its GDPR policies seriously.  Gathering relevant data is simply not enough; it is the clean data that produces clear insights. It is an investment into the company, and eventually, in making sure the company doesn’t become a victim to a small typo error.

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