What do Apple, Google, and Amazon all have in common? Well, plenty of things if we’re being honest. It’s easier to list the things that they don’t share. But one thing that people don’t usually associate with any of these big tech companies is how deeply involved they are with an increasingly relevant sector in technology: video gaming. Apple, Google, and Amazon Gaming Ventures It’s true; last year, both Apple launched their own gaming-related service with Apple Arcade—a Netflix-like subscription service that offers a huge number of selected games from the App Store, playable completely ad-free. Earlier this year, Google Stadia came out of beta, and brought cloud-based gaming to Google Chromecast-powered TVs, supported Android phones, and any computer that can run the Chrome browser. Amazon first started making headway into the gaming sector with their 2014 acquisition of Twitch.tv, the Internet’s most popular game streaming website, and is also rumored to soon be launching their own game subscription service. Why now? The question should be, “Why not?” Matthew Ball, former head of strategy at Amazon Studios, wrote in his blog post entitled “ ” the following: “It used to be ‘what to watch’ and now it’s ‘whether to watch’ –, and the answer is increasingly ‘no, I’m going to play a game’.” 7 Reasons Why Video Gaming Will Take Over The numbers support his observations as well. With generated last year and predictions of it shooting up to $200 billion by 2022; more people watched the 2019 League of Legends World Championship with a record-breaking , which was a larger turn-out than the telecast of the Super Bowl; and projections for next year show that —a third of the global population—will be classified as gamers. $120 billion in revenue 100 million viewers 2.7 billion people It’s also not just the companies feeling the pressure by gamers (and yes, Netflix is scared too, with CEO Reed Hastings considering to his company than HBO Go). Of course, there are the usual suspects with Sony, Microsoft, and Nintendo working on improving their online platforms. FAANG Fortnite as a bigger threat Sony has had PS Now, a game streaming service that allows players to run their favorite PlayStation games on PCs, for a few years now. Nintendo launched their Nintendo Online subscription service which brings not only multiplayer connectivity to supported games on the Nintendo Switch, but classic virtual console titles from the NES and SNES as well. And Microsoft, perhaps the most ambitious of the bunch, just launched their Project xCloud service which, like Google Stadia and Nvidia GeForce Now, allows customers to stream live, full Xbox-quality gameplay straight to their mobile phones. WalMart So far, that all makes sense. After all, Apple, Google, and Amazon have been known to experiment in tech for years. And gaming companies will make gaming things, of course. But following the footsteps of the above-mentioned companies is another unexpected player: , who is looking into launching their own cloud gaming service. Walmart Intel And before you assume that all this gamer-catering be limited to one digital gaming platform after another, here’s another digestive for you to chew on. What was looking to be a rather mundane Architecture Day 2020 was suddenly electrified as " became headline news in the tech world that morning. “Intel announces Xe-HPG Everybody is aware of Intel as the 800lb CPU-manufacturing gorilla, but less known is the fact that they haven’t really competed in the enthusiast graphics card market since the extremely disappointing i740, i750, and i752 AGP cards back in 1998. Since then, they tried discrete graphics once again with their ultimately cancelled project, but other than that, they’ve preferred instead to develop their integrated graphics architecture. Larrabee That Intel is not just making announcements but of their Xe-HPG architecture is no small thing. showing benchmarks Let's put everything we currently know about their new pillar of Xe together: 1. Confirmation that the HPG series will support hardware-accelerated raytracing, which is a marquee feature of competing high-end video cards by NVIDIA and AMD. Further emphasizing the role of ray tracing are the upcoming console launches by Sony and Microsoft, which both feature the technology. Finally, its inclusion in the DirectX 12 Ultimate graphics driver standard all but secures its place as a critical component in next-gen graphics processing. 2. Opting to use GDDR6 instead of HBM for their memory configuration, which ensures the memory bandwidth needs of high-performance graphics processing are met without incurring the excessive costs of HBM memory—a problem suffered by AMD with their previous generation of flagship cards. Xe-HPG will be the only member of its family that will receive this treatment, with all other Xe products utilizing HBM memory instead. 3. Partnering with an external fabricator to manufacture specifically their HPG series of chips whilst all other Xe chips remain in-house. This is a company first, and it will be extremely interesting to see which major fab Intel partnered with—whether TSMC or Samsung, both of which have had experience manufacturing cores for both Nvidia and AMD in the past. When one considers all that, it really seems that this is truly going to be a gamer-first (and perhaps even gamer-only) dedicated graphics card from Intel. They will soon join Nvidia and AMD to compete for the hearts, minds, and wallets of gamers in the PC-building world. It’s clear, when accounting for the pivots and movements of these trendsetting companies, that they are reacting to the sudden explosion in video gaming. The timing is perfect; next-gen consoles are due to be launched this year, next-gen graphics cards from Nvidia and AMD are just around the corner with the former already having been announced, and widespread adoption of fiber internet as well as the continuing rollout of 5G mobile data is making cloud-based game streaming more viable than ever. It’s time to start paying attention to the gamers. They’ll soon be calling the shots.

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The birth of Bitcoin (BTC) over a decade ago has opened doors to many other cryptocurrencies. Although it still reigns as the most popular and largest cryptocurrency by market capitalization, Ethereum is trailing behind steadily while Dai is also rising in popularity. In this simple guide to Ethereum and Dai, we’ll take a closer look to understand both cryptocurrencies better. Currently, Ethereum is the second most popular cryptocurrency. Despite the exciting growth of cryptocurrencies, they’re highly volatile, and the price can fluctuate wildly. The unpredictability of cryptocurrencies prevented them from being adopted widely as a reliable currency that people can use daily. As a response to the volatility of cryptocurrencies, come stablecoins. Which virtually, cryptocurrencies value are pegged to a currency such as the US dollar. Some examples include Tether (USDT) and USD Coin (USDC). By pegging to a currency, stablecoins aim to reduce the unpredictability of cryptocurrencies. One of the fastest-growing stablecoins is Dai, launched by MakerDao, and pegged to the US dollar. What is Ethereum (ETH)? Launched in 2015, Ethereum is a decentralized software platform used for Ether, its cryptocurrency. The blockchain-based platform allows smart contracts and distributed applications to be built and run without downtime or control from a third party. As a decentralized system, it is not controlled by any governing entity. Without any central point of failure, Ethereum is autonomous and run by volunteer computers worldwide, which will never go offline. For Ethereum to run, it needs a currency to pay for the computational resources running the program. That’s where Ether comes into the picture. Ether is the digital bearer asset that operates as a currency and as sustenance for the decentralized apps within the Ethereum network. Compared to Bitcoin with a hard cap of 21 million, Ethereum has a potentially endless supply. Furthermore, Bitcoin’s average block mining time is 10 minutes, whereas Ethereum only takes about 12 seconds for confirmations. Another good thing about Ethereum is that it uses proof-of-work algorithms and encourages decentralized mining by individuals instead of large-scale mining farms as such used by Bitcoin. How Does Ethereum Work? Using the blockchain technology, Ethereum consists of secure public records linked together that are difficult to modify. The reason is that these records are stamped with user data, time and date, and changes that must be approved by all parties. Ethereum is trustless, meaning that anyone can create a financial contract or ownership registries and keep debt without a trust officer’s need. This is perhaps the most significant advantage of Ethereum. It’s utterly immune to third party interventions and can’t be controlled by anyone. Besides, the decentralized nature of the Ethereum network makes it well protected against hacking and fraud. Since smart contracts are essentially a set of codes written by people, there’s always room for human error. When the mistake happens, it’s easy for the network to be exploited. For example, in April 2016, by a hacker who used a “recursive call bug” that resulted in Ether’s value falling from over $20 to under $13. 3.5 million ether was stolen You can buy and sell ETH in exchanges such as , , or . To gain yield from your Ethereum, you can hodl it in such as , giving you 6.7% APY (annual percentage yield). Coinbase Gemini Kraken crypto lending platforms Hodlnaut What is Dai (DAI)? Dai is an ERC20 token, a stablecoin created by , a smart contract platform that controls and sells the cryptocurrency. Similar to Ethereum, Dai is trustless and decentralized while being pegged to the US dollar. The value of 1 Dai will always be approximately $1 USD. Maker DAO And since it’s built on the Ethereum network and backed by Ether, it’s completely decentralized because it relies on a set of smart contracts which does not rely on banks or centralized third party. Furthermore, Dai is suitable for payments, savings, or collateral because of its stable nature and can be easily transferred within the Ethereum wallets. Dai is the product of MakerDAO, which was founded in 2017 on the Maker Protocol by Rune Christensen, who’s also the current CEO. How Does Dai Work? Dai is key to MakerDAO’s lending system. When a loan is taken out on MakerDAO, a Dai is created and automatically becomes the currency that users use to borrow and pay. To maintain price stability, Dai is managed through a system of lending in the Ethereum network. For a Dai to be created, a user with Ether would deposit their asset into some kind of vault that’s called “collateralized debt position.” As a result of depositing ether as collateral, Dai is generated into the Ethereum network. The mechanism of how Dai generated is unique. When the Dai holders unlocked their ETH, they pay back Dai and a stability fee, which will be increased if Dai’s value drops below $1. This results in Dai loans being more expensive, which led to fewer loans and retracting the supply, driving up the price. Consequently, if Dai values more than $1, the stability fee will be lowered to make the loans cheaper, resulting in increased supply and lower market prices. As of now, Dai has remained stable for two years, with no significant price fluctuations from its $1 price peg. You can buy Dai at centralized exchanges like Kraken, Coinbase, and Bitfinex. In Conclusion Bitcoin is not the only cryptocurrency worth investing in. The emergence of other cryptos and stablecoins has proven that things will only keep evolving in the cryptocurrency world. Ethereum and Dai are two of the most popular cryptocurrencies that embody the decentralized and trustless principles that fiat currencies lack.

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In a world where everything is connected to the internet, and yes I mean (NSFW), the threat of being hacked is always present. The most recent notable security leak was with Robinhood. everything Bloomberg reported that "Almost 2,000 Robinhood Market accounts were compromised in a recent hacking spree that siphoned off customer funds, a sign that the attacks were more widespread than was previously known" ( ). There seems to be a newsworthy cyber hack or data leak almost every week. Source Fortunately, there are a number of easy safeguards that you can implement to provide more protection. Here are a few that I would recommend, listed from easiest to implement to hardest. Note: This article may contain affiliate links 1. Block your Camera Every time you finish a video chat with a friend or a Zoom call at work, you need to block the camera lens on your computer. According to the FBI, "There’s a thriving market for illicitly obtained stills and video". The former FBI director, James Comey, recommended that we all should cover our webcams for security reasons ( ). This could easily be accomplished by tape, a post-it note, or one of these . Source plastic camera blockers 2. Mute your Laptop Mic Hackers don't always need video to find something useful. There are also opportunities to capture audio. Because of this threat, you should always have your computer's mic muted when you are not on a video call. 3. Limit your Public Data You would be surprised how many people have zero privacy restrictions on their Facebook profile and publish their entire employee and education history on LinkedIn. This information is a gold mine for hackers. You could be providing them answers to your password recovery questions. Not all hackers will impact you directly. Reading your public information can help them impersonate you or for money. Other risks include providing answers to the password security questions publicly. You can go into the security settings for all of these accounts and limit who can see your information. The safer option is always to delete the information. ask your relatives 4. Use a More Private Search Engine As amazing as Google's search engine is, there is one HUGE drawback of using it. It knows everything about you. Google knows the products you buy, your income, medical history, relationship problems, and what websites you may go on . afterhours Turning your browser to incognito mode erases your local browser history, but it does not erase Google's records of your web activity. The best way to prevent them from tracking your web activity is to use a different search engine. DuckDuckGo, a privacy-focused alternative, is not as good as Google for search results, but they are good enough the majority of the time. The best part is that their "privacy policy is simple: we don’t collect or share any of your personal information". This mission statement is on their if you scroll down. homepage 5. Enable 2-Factor Authentication 2-Factor authentication (2FA) means that any user who signs into your account must enter a password and confirm their identity via email, phone call, text message, or a random code-generator app. Because of , 2FA by text message is not as secure as it used to be. I would highly recommend using a random code-generator app whenever that is an option. I know that many financial institutions, like Fidelity and Wealthfront, offer users the option to authenticate via a random code-generator app. SIM swaps 6. Move Crypto Assets to a Secure Location Some crypto platforms, such as , allow you to move your crypto holdings into a more secure location. At Coinbase, these are called vaults. With crypto stored in a , as opposed to a digital wallet, it makes it harder for hackers to quickly withdraw any of your funds. Coinbase vault 7. Block Quick Money Transfers Financial institutions often allow you to lockdown certain accounts. This prevents a potential unauthorized user from electronically transferring money, shares, and assets to their own account. However, it could make it more inconvenient for you as well. I would at least take a look at the security settings options for your bank accounts. 8. Use a VPN VPN means virtual private network. They provide privacy and anonymity when you are online by masking your internet protocol (IP) address so your actions online actions are virtually untraceable. VPNs hide your browsing history, IP address, location, and the presence of your devices. Hiding this information helps protect data you send and receive from your devices and protects your privacy when it comes to web activity like googling advice on a medical condition ( ). When I say devices, this includes anything that can connect online, including your phone, tablet, or any "smart" object. Source Personally, I use which allows you to stream 5 devices simultaneously for $8.32/month. It allows your network to be hosted in dozens of cities and countries, such as Netherlands, Germany, and Hong Kong. I have also heard good things about . The entire setup only takes about five minutes. All you need to do is download the VPN software from the provider, open it up, and select which city you want to be rerouted from. If you want more options on providers, this provides a good starting point. Express VPN Proton VPN page 9. Use a Password Manager Password managers are software that allows you to organize, encrypt, store, and retrieve your passwords for all of your accounts. You only need to remember the one master password. With a password manager, it makes it easier to use more complex passwords and change them on a consistent basis. Many of them can even generate random passwords for you. You can find a good overview of their benefits . I started using one about a year ago and find it a reasonable value. A familiar option is who recently launched their own password manager service. here Dropbox 10. Enable Firewall Protection at Home Firewalls are software programs or hardware devices that filter and examine the information coming through your internet connection per . If installed in your home, they can help prevent unauthorized users from accessing your WIFI network. While a basic wireless router provides a firewall, it only provides protection against rudimentary cyber attacks. If you want stronger protection and additional security features, then I would recommend purchasing a better firewall. Over the past few months, I have been looking into a that was recommended by one of my colleagues in IT. McAfee provider Parting Thoughts I would be a hypocrite if I didn't admit that I do not follow ALL of these safeguards. However, I have adopted an increasing number of them over the past few years. Most of these items are extremely affordable or provide very little disruption to your day-to-day life. If there is anything we learned this year, it's that some of the most dangerous risks are not visible to the naked eye. ~ The Data Generalist Image source: Unsplash

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Team building is not popular. One survey found of workers dislike team-building activities. Perhaps many have been scarred by the forced fun of clumsy corporate team building events. But there’s real value there to be unlocked. How well a team communicates can be more important than how skilled its members are. 31% We’ll look at studies on the importance of good communication. We’ll see that the key aspect is psychological safety - people have to feel comfortable voicing ideas and disagreeing. Building a safe environment should be key to nurturing a team. Teams vs Collections of Individuals A common claim against team building is that it is pointless. This, I think, comes from a problematic assumption that work is mostly about individuals performing tasks. Many people think of work primarily in terms of their personal workload and getting through their queue of tasks. Of course . It’s relevant to communication and negotiation. It’s also important to how invested people feel in the team’s work. team building isn’t very relevant to individual task performance but it’s very important to collective decision-making There’s a notion in the social sciences called ‘ ’ and it represents the intelligence of a group, analogous to IQ for individuals. You might naturally think that teams with high IQ members will have the highest collective intelligence. But that’s not what happens. collective intelligence than the IQ of its members. Team members understanding one another and being receptive to one another’s states of mind was more important than their individual intelligence. This may seem counterintuitive but can make sense for highly collaborative work. An author of the study explains: An MIT study found better correlation between the team’s social perceptiveness and its collective intelligence That doesn’t mean that individual ability doesn't matter. What we’re saying is that what matters is both that individual ability and co-ordinating it effectively. - Anita Woolley Not all challenges require coordination in the same way. Some things really are purely individual tasks. But making software requires a lot of communication. Consider the communication involved in these facets of making software: The purpose of making software is to fulfil business objectives. That means understanding the users and how they fit into the objectives. A design has to be worked out to fulfil the intended objectives. The design has to be broken into smaller parts. Different parts of software delivery are handled by specialists dedicated to that area. UX, UI, product management, backend development, testing, support etc. And these parts interact. Code gets reviewed and signed off. Conflicting aims have to be prioritised. Tasks and subtasks have to be scheduled and co-ordinated. Software is a world of specialists. And specialisation is important for mastering specific skills and efficiently dividing labour. But specialisation can also lead us to forget how interconnected the work of making software really is. Why Team Building Matters Teams only perform well when members can communicate well with each other. This finding from the is pretty intuitive. What’s less intuitive is that . MIT study the most effective communication requires an environment of psychological safety Google 180+ teams from 2013 - 2015. The surveys found that the team’s dynamics mattered more to the team’s performance than the skills of its individuals. The best teams answered yes to the question “Can we take risks on this team without feeling insecure or embarrassed?”. Google called this the question. studied psychological safety Google also found that good teams answered yes to these questions: “Can we count on each other to do high-quality work on time?” “Are goals, roles, and execution plans on our team clear?” “Are we working on something that is personally important for each of us?” But the big question that really made the difference was “Can we take risks on this team without feeling insecure or embarrassed?” This psychological safety question mattered more than the other questions and more than the abilities of the team members. Why is psychological safety important? Teams have to be able to voice ideas that might sound silly. Ideas that seem silly at first can be developed into something successful. Teams can’t be creative if they can’t explore a wide range of possibilities. People have to feel comfortable voicing concerns and working through problems. Otherwise you get elephants in the room and avoidance of conflict. Not all possibilities can be explored at once and teams have to prioritise. That means disagreements. Healthy and necessary disagreements. Individuals will avoid this kind of conflict unless they feel comfortable and they trust that others won’t get personal. The point is not just that ideas should always be judged fairly and given a good hearing. People need to feel confident that ideas will be judged fairly. And confident that they can voice fair criticism without prompting a personal reaction. When team members are sensitive to one another as individuals then they’re better placed to see that criticism of an idea is not criticism of the person that voiced it. That gets easier if you relate to one another. It helps to understand one another’s perspectives and communication styles. If team building can help produce more trusting environments, it can help deliver on the psychological safety. And the google study found psychological safety to be the main determinant of team performance. How to Approach Team Building Effectively It would be a missed opportunity to think that you’re only building a team if you’ve paid a company to run a team building event. Some of the best team building can happen spontaneously. It might be at lunch or part of the team’s normal work. The Tuckman model of group development suggests that team building will often happen naturally: (Image from .) Sean Connor on medium Under the model teams evolve through phases: First teams are forming. They’ll initially be averse to conflict and getting to know both each other and their objectives. As the team enters the storming phase, it will start to test boundaries and work out what it wants to do. This phase can involve some negative forms of conflict as people are uncertain of how to interact with one another and how to best fulfil their roles. In the norming phase the team approaches conflict with more understanding and maturity. Here we see healthy conflict as objectives become clarified and approaches agreed. Then roles become better defined and output goes up in the norming phase. Output continues to go up into the performing phase, as the team gets even better at tackling the problems it’s tasked with. It’s not that a team just goes through these phases once and then it’s set. It might be that teams go through these phases repeatedly as their objectives shift. The key point is that . There can be lots of ways to nurture teamwork. It doesn’t have to be called team building. The main thing is to create opportunities for people to interact freely and in a relaxed way. So consider letting teams choose their own activities. team development is something to be encouraged and nurtured and not forced There are for team building and many designed to help people open up and share more of their personalities. But jumping straight to games that ask people to reveal their personalities might not help win round any sceptics. lots of games Team building doesn’t have to be removed from the work itself so long as the environment is relaxed and collaborative. When Google released their study showing the importance of psychological safety, they also released a guide for day-to-day . It's also worth considering . fostering of psychological safety games to help better practice of Agile It’s ok to do a dedicated off-site team building session but it’s a bigger thing so needs care about buy-in. If you don’t genuinely answer objections about the purpose then people may just go through the motions. So expect to need to . explain why you’re doing it Be careful about the motivations for team building. It’s easy to see a team with problems and think they need team building. But it might be that the team’s objectives aren’t clear or aren’t realistic. Sometimes issues in team interactions are just a symptom of problems coming from outside the team. If there are issues about direction and leadership, then team building alone won’t fix them. Clumsy imposition of team building sessions can naturally lead to frustration. But team building need not all be tarred with this brush. There are lots of good ways to nurture team cultures. Teamwork can be improved and building teams is an important aim to have. (Title Image by from .) GraphicMama-team Pixabay

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Why Team Building Matters - Winning Over Sceptics

It's quite ironic how my reasons for signing up to write an article at Hacker Noon was to purge the frustrations caused by social networks of the day. What happens to be the first thing asked of me as a new member?  It is to edit my profile, and add my social media links: Linkedin, Twitter, Facebook etc. The Problems with Social Media It's perfectly reasonable to expect a rising network to leverage from other people's networks, politicians do it, businesses do it, we all do it. But what happens to those individuals who due to the randomness of the world we live in happen to be outside those networks. Are the networks omnipresent to the point that the real isn't as important as the perceived? Say for a multitude of reasons, someone decides to be a contrarian to a rising trend, let's suppose it's a new tech platform he or she happens to hear about called Linkedin.  Can the social & professional implications that result from such contrarian behavior just be written off as collateral damage for an otherwise well oiled social network that helps b2b advertising? The more daunting question is what happens in the future? Who can imagine a world where a child grows up and refuses to sign up for Facebook, Youtube or Linkedin? Will he or she be ostracised into conformity or is their an end in sight to this technological follower fetishism?

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This is a hands-on course on how to deploy a fully Serverless web app using the . You will learn how to: AWS CDK Structure **CDK Stacks **to deploy an application from end-to-end Deploy a integrated with for dynamic requests processing Store data in a fast and cost-effective way with REST API AWS Lambda DynamoDB Use as a source for in an event-driven architecture DynamoDB streams Lambda Ingest and manipulate loads of data streams with Kinesis Firehose Deploy and query a with , and your entire application health in a single place using Data Lake Athena S3 GlueMonitor Dashbird You can use the resources declared in this demo application as a starting point to mix and adapt to your own architectures later, which should save you quite some time. The App and Architecture The demo app is a public blog where anyone can read, publish and like posts. It’s available . Go ahead and publish something in the top-left corner (yellow button) and also “like” articles already published. Check out the codebase on . on this link this repo Frontend Backend Data Lake and Analytical Querying What is the AWS CDK? CDK stands for Cloud Development Kit. Think of it as CloudFormation (CF) in your preferred language (Python, Typescript, C#, etc). Roughly speaking, it works like this: 1. You declare cloud resources using classes provided by the CDK libraries. Example: aws_cdk aws_s3
my_bucket = aws_s3.Bucket(self, ) from import 'MyBucket' 2. Run CDK deploy 3. CDK translates this to a CloudFormation template and deploy it on AWS for you. In case you would like to dig deeper, that will get your basics started. I also strongly recommend reading the . AWS also has a workshop official CDK documentation Advantages using the AWS CDK Use languages that are more expressive than YAML or JSON, for instance. Less - much less! - verbose than CloudFormation templates. Easier to apply reusability and inheritance principles to infrastructure code. Better integration with IDEs for code completion, IntelliSense, etc. Possible to test your infra code, just as any other software Portable: since it’s just a wrapper around CF, we can easily port it to JSON or YAML Disadvantages of using the AWS CDK Although released as a stable project by the AWS team, many parts (a lot of the good ones) are still experimental and APIs may change in backwards incompatible ways. It’s under constant development. During the preparation of this course, I had to upgrade my libraries three times. Documentation is still lacking at some parts and you will need to look at the CDK code, occasionally, to understand how to declare certain things. Deploy it yourself Although we have provided an online demo, you can also deploy this app in your own AWS account: Clone the repo: git clone git@github.com:byrro/serverless-website-demo.git sls-demo; cd sls-demo Setup your virtual environment: virtualenv -p /urs/bin/python3.8 .env; source .env/bin/activate; pip install -r requirements Specify an AWS account ID: ** export AWS_ACCOUNT_ID=1234567890 Deploy all three stacks: cdk deploy sls-blog; cdk deploy sls-blog-api; cdk deploy sls-blog-analytical ** You can also hard code your Account ID in the CDK project, as I’ll show in a minute; When starting a new project from scratch, you would run . This is not necessary for this demo, since the project is already created. cdk init --language [python|typescript|...] Monitoring Deploying this architecture in the cloud and blindly believing it will work flawlessly is not reasonable. We want to be the first one to know when something is not right to act upon it as quickly as possible. In this project, I used for its ease of use and seamless integration. Instead of having to deploy an agent inside my code, Dashbird plugs into my Stacks that I can deploy with the effort of one click. It not only monitors Lambda function errors, but also other resources that we’re using, such as DynamoDB tables. They even suggest cross-referenced against industry best practices. Dashbird through a CloudFormation template insights for architectural improvements Finally, Dashbird offers a free-forever plan. It’s a no-brainer to try it out by . registering for free How a CDK project is structured A CDK project creates an “Application”. This app may have one or more “Stacks”. A Stack is a group of cloud resources (Lambda functions, S3 buckets, etc) that are instantiated using CDK classes. It’s also possible to have multiple applications in a single CDK project. App Object Creating a CDK app is as simple as: app = core.App() When you run , an initial application with basic boilerplate code is created for you in the project root, under . cdk init --language [language] app.py The next thing we need is an environment, which is composed of an AWS Account ID and Region: env = env = core.Environment(
    account= ,
    region= ,
) 1234567890 'us-east-1' Declaring an environment is not required (CDK can infer from your AWS credentials), but is a good practice. Most of us work with multiple AWS accounts. It’s easy to mess around with several projects, accounts, credentials. When we explicitly set the environment in the CDK app, it’s locked and prevents mistaken deployments. Now we declare our stacks: my_project.my_project_stack MyStack

my_stack = MyStack(
    app, ,
    env=env,
) from import 'my-stack' This is how we our stacks for deployment. In the next section we’ll see how to those stacks. instantiate declare Stack Object The Stack object is where we our AWS resources. It inherits from the core.Stack CDK class and accepts a scope - which is our app object - a string identifier and an environment. declare ( . ): ( , : . , : , : . ,
            ** ,
            ) -> : (). ( , , ** )

        # class MyStack core Stack def __init__ self scope core Construct id str env core Environment kwargs None super __init__ scope id kwargs Declare AWS resources here Declaring AWS resources To declare AWS resources, we need a specific library for each service. Here’s a list of all and their counterparts. Other flavors are and . Python libraries Typescript Java .NET Let’s see how a basic REST API would be declared (typing expressions were removed for readability purposes): aws_cdk aws_apigateway, aws_lambda = aws_lambda.Function(
            self, ,
            runtime=aws_lambda.Runtime.PYTHON_3_8,
            code=aws_lambda.Code.asset( my_lambda.handler sls-blog-rest-api-gateway from import ( . ): ( , , , ): (). ( , , ** ) class MyStack core Stack def __init__ self scope id env super __init__ scope id kwargs my_lambda 'MyLambda' 'my_lambda_folder),
            handler=' ',
        )

        aws_apigateway.LambdaRestApi(
            self,
            ' ',
            handler=my_lambda,
        ) We first declare a Lambda function . We point its code to the . Inside this folder, there should be a file, containing a function called . This handler function should accept Lambda invocations normally (an and objects). my_lambda my_lambda_folder my_lambda.py handler event context Next, a is declared, using as the handler (not to confuse with the Lambda’s handler function). This will create a new API Gateway REST API integrated with using an . All HTTP requests will be routed to the Lambda function. LambdaRestApi my_lambda my_lambda AWS_PROXY integration type Our Project App & Stacks comprises one application with three Stacks. They’re all declared in the and files. This project app.py sls_website_stack.py Below we’ll walk through all Stacks in a high level. I encourage you to inspect the to learn how these resources are declared and also integrated. For example: a Kinesis Firehose is created in one Stack and referenced in another to include its name as an environment variable for the Lambda function that will interact with it. stacks file Except for the frontend static Stack - which is small - you will notice that resources are initialized with a (null) value in the beginning. The reason is that, even though the CDK is generally more succinct than CloudFormation, it can still be lengthy enough to clutter the view of the entire Stack. Having each resource declared first in one line, I can provide a short summary of everything that’s in the Stack and then instantiate the CDK classes in other methods. None = static_stack

        # SQS Queues
        self.queue_ddb_streams_dlq = None  # Dead-letter-queue DDB streams

        # DynamoDB Tables
        self.ddb_table_blog = None  # Single-table all blog content

        # DynamoDB Event Sources
        self.ddb_source_blog = None  # Blog table streams source

        # DynamoDB Indexes
        self.ddb_gsi_latest = None  # GSI ordering articles by timestamp

        # Lambda Functions
        self.lambda_blog = None  # Serves requests to the blog public API
        self.lambda_stream_reader = None  # Processes DynamoDB streams

        # Continues other resources... ( . ): ( , , , , ): (). ( , , ** ) . class SlsBlogApiStack core Stack def __init__ self scope id env static_stack super __init__ scope id kwargs self static_stack for for with Notice it takes another Stack object ( ) as an argument to its initialization. In the file, you can see that the is initialized passing the as an argument. static_stack app.py SlsBlogApiStack SlsBlogStack We use it to reference the CloudFront distribution domain ( ) in the Lambda environment variables. This variable can be used to customize the HTTP response header to comply with . This illustrates one way to easily integrate and reference information from one Stack into another within a CDK project. d1qmte5oc6ndq5.cloudfront.net Access-Control-Allow-Origin CORS standards At the end of the initialization, another method is called to instantiate the CDK classes for each resource and configure their parameters. self.create_cdk_resources() Next we’ll walk through each of our project’s Stacks. Stack 1: static website Our focus is on the Serverless backend, so the frontend here is terribly rough and simple. It’s stored in an S3 Bucket and distributed through a CloudFront CDN. CDK has a helpful class called BucketDeployment. It takes the contents of a directory and sync to an S3 bucket. In this case, we stored the frontend code in the folder. website_static aws_s3_deployment.BucketDeployment(
    self, ,
    sources=[aws_s3_deployment.Source.asset( )],
    destination_bucket=static_bucket,
    distribution=cdn,
) 'SlsBlogStaticS3Deployment' 'website_static' Stack 2: API/backend Our backend consists of an API Gateway (REST) connected to a . Microservices receives a lot of press, but you probably shouldn’t always break your applications in several functions. A Monolith is just fine - -, really. monolithic Lambda function and sometimes recommended This API & Lambda support a single endpoint (with GET and POST methods) with a queryString “action”, which takes three parameters: : populates the latest blog posts get-latest-articles : triggered when someone likes an article like-article : post a new blog article publish-article Here’s the power of the CDK model. We can create a REST API with 10 lines of code: rest_api_blog = aws_apigateway.LambdaRestApi(
    self, ,
    handler=lambda_blog,  # Previously declared Lambda 'sls-blog-rest-api-gateway' = . ( ),
    ),
) function deploy_options aws_apigateway StageOptions stage_name= ,
        throttling_rate_limit=lambda_param_max_concurrency,
        logging_level=aws_apigateway.MethodLoggingLevel( 'api' 'INFO' One nice little thing is that Lambda memory is used as a cache for the latest articles. We load the cache container outside the Lambda handler function. It remains in memory even after an invocation ends and is available for subsequent requests. Learn more here about . how to use Lambda as a cache mechanism MAX_CACHE_AGE: int = # In seconds
CACHE_LATEST_ARTICLES: Dict[str, Union[int, list]] = { : time.time(), : [],
} 120 'last_update' 'articles' All the data is stored in DynamoDB (DDB) using a , in . The site only shows the latest blog articles and items get after a few days by setting a attribute. single-table design on-demand mode auto-deleted by DDB time-to-live ddb_attr_time_to_live = ddb_param_max_parallel_streams = ddb_table_blog = aws_dynamodb.Table(
    self, ,
    partition_key=aws_dynamodb.Attribute(
        name= ,
        type=aws_dynamodb.AttributeType.STRING,
    ),
    billing_mode=aws_dynamodb.BillingMode.PAY_PER_REQUEST,
    point_in_time_recovery=True,
    removal_policy=core.RemovalPolicy.DESTROY,
    time_to_live_attribute=self.ddb_attr_time_to_live,
    stream=aws_dynamodb.StreamViewType.NEW_AND_OLD_IMAGES,
) 'time-to-live' 5 'sls-blog-dynamo-table' 'id' The DDB table also has a that makes it easier to retrieve articles ordered by date for the site: GSI (Global Secondary Index) self.ddb_table_blog.add_global_secondary_index(
    index_name= ,
    partition_key=aws_dynamodb.Attribute(
        name= ,
        type=aws_dynamodb.AttributeType.STRING,
    ),
    sort_key=aws_dynamodb.Attribute(
        name= ,
        type=aws_dynamodb.AttributeType.NUMBER,
    ),
    projection_type=aws_dynamodb.ProjectionType.ALL,
) 'latest-blogs' 'item-type' 'publish-timestamp' Modifications to DDB items generate streams that are processed by a . These streams are then repackaged and sent to a Kinesis Firehose stream processor. second Lambda function DDB doesn’t provide the flexibility that SQL databases offer and many choose , for example. Although Aurora is a great service, personally I prefer DDB for its simplicity and reliable, consistent performance. But sometimes we do need to run analytical queries, those with aggregations and on-the-fly filters. For that, we’ll be using Athena (more in the next Stack). Aurora Serverless Stack 3: analytical querying A Kinesis Firehose Stream is responsible for batching data inserted/modified in DDB, converting them to Apache Parquet format and storing in dedicated S3 buckets. From S3, we create a Data Lake with AWS Glue (used to declare our data schemas) and Athena (used to query the data). Athena is extremely powerful. We can statements ( ) to query terabytes of data and pay on-demand ($0.005 per GB of data scanned). Using Parquet not only improves query speed, but also reduces cost by minimizing the amount of data Athena needs to scan for each query. use SQL SELECT with some limitations Queries that are impossible or expensive/slow in DynamoDB, such as aggregations and JOINs, are fast and cheap in Athena. The two services combine each other in a perfect way, so that your application has optimized transactional storage and flexible analytical querying capabilities. We can use Athena to query all articles ever published and cross-reference with likes and HTTP metadata (source IP address, country, device type, etc). Even articles that were already expired by DynamoDB TTL (time-to-live) would continue to be available in the Data Lake. For example, which countries are liking the most articles? In the AWS Console, we get something like this: Queries can also be executed programmatically with or (e.g. ) to integrate anywhere we need this data. Athena API AWS SDKs Python’s boto3 Athena also supports JOINs. Here’s an example joining articles and HTTP metadata to analyze the most popular authors among readers of a particular country: Deployment CDK can deploy one Stack at a time. Since we have three, it’s necessary to specify which one when running the command. We do that by passing in the Stack ID as a CLI argument. For example, the following command will deploy the SlsBlogApiStack (id: ): CDK deploy sls-blog-api cdk deploy sls-blog-api Since all Stacks involve some type of permission granting, CDK asks for confirmation before deploying those resources. You can review the permissions requested and hit y when it’s good to go. Wrapping up We’ve covered how to structure CDK apps and add a bunch of AWS Resources to deploy with a simple command. CDK deploy If you’re new to the CDK - and as suggested early in the article -, it’s strongly recommended to follow AWS and . CDK workshop documentation Keep an eye on future publications as well, as is releasing other examples and tutorials to reap the most out of AWS serverless services with the power of infra automation with CDK or else. Dashbird Previously published at https://dashbird.io/blog/crash-course-aws-cdk-serverless-rest-api-data-lake-analytical-querying/

Apache

Glue

Initialized

Yellow

2022 - HackerNoon Contributor of the Year - Aws

2022 - HackerNoon Contributor of the Year - Cloud Computing

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Nominated for 2022 - HackerNoon Contributor of the Year - Cloud Computing

Nominated for 2022 - HackerNoon Contributor of the Year - Devops

Nominated for 2022 - HackerNoon Contributor of the Year - Serverless

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Quick Guide to AWS CDK and Serverless with REST API and Data Lake Analytical Querying

When working with embedded systems that depend on speed or have a minimal amount of memory, C is a perfect language of choice. This is a short paper about why you should learn C and the benefits of doing so. To add some credibility to this story, let me introduce myself. My name is Eric and I am a computer science student in Sweden. I have been programming for quite some time now and I feel like it is time to share some of my opinions about C, one of the best programming languages to learn. Background story C is an old language, to be formal, it appeared the first time in 1972. The language was developed to combines the capabilities of an assembly language with the feature of high-level language. Despite its age, the language is still widely used today because of its power and ease of use. When working with embedded systems that depend on speed or have a minimal amount of memory, C is a perfect language of choice. Because of its age, many individuals claim that C is not necessary, that newer languages could replace it. However, every language has its purpose and that is what I would like to explain to you. Why should you learn C? So the question still remains... Why should you learn a programming language that was created nearly 50 years ago? Let me list some of the reasons below. It's Fast Combination of low-level and high-level programming Memory management Challenging Good support C is fast When talking about C, I often hear that " ". However, C is not fast, it's just not slow as all the other more complicated programming languages like Java & C# that has support for garbage collection and so on. C is such a fast language So the reason for C being fast is that it's lightweight and does not handle stuff for you. You as a programmer have the power to control what features you would like to implement. C is a combination of high & low-level programming In C you can create drivers for specific hardware, but at the same time, you can develop a nice desktop application. This is a combination of low-level and high-level programming. I think that this is one of the most important aspects to remember, that C is capable of creating nearly anything you can imagine. Some might say that C is not necessary to learn since you will not use it that much. I do not agree with that since, in the beginning, it is all about learning the principals of programming, not the language itself . When you know the fundamentals, you can learn any language you want in a shorter time since you only need to learn the syntax and minor differences. (even though you will learn the language as well) The C Programming Language Will be Relevant in Years to Come C has been around since the early '70s and is here to stay for a long time. The reason is that C is the foundation for a lot of big software out there. This means that there will be plenty of job opportunities for you, especially if you would like to work with embedded systems. . Embedded systems are another major subject, but if you feel like you want to learn more about it, I would like to recommend watching Jacob Sorber on YouTube His channel is also good when learning C. When comparing C to other languages there are a lot of similarities. Maybe is this because the newer languages have inherited syntax from C? This means that even if you do not want to work with C, it is still not a waste of time since you will have an easier time learning other languages. How do you learn C? Back when I learned C, I used to watch a lot of youtube videos, read guides online, and most importantly, practice! Learning C is not complicated if you got the motivation for it, simply do as I did. There are websites that could help you with the practice part. is one example. The website will ask you to solve a problem and then check whether or not you did it right. Hackerrank Final Words Yes, you should learn C no matter the year since the language is a good foundation to stand on and will make you a good programmer. That's the quick version of why you should learn C and why it's a good language. Happy learning!

Assembly

Should you learn C in 2020/2021?

An Auction Runs by A Clock An auction system either live or timed runs by the clock. In a live auction, one often runs calls on a bid according to a clock. In a timed auction, you start and end an auction by the clock, and you show the users a countdown timer. Browser Times Cannot Be Trusted In a browser, gives you the user local time, according to the user's computer local time. As users reside in different time zones, and moreover may have inaccurate computer clock, or they may just intentionally modify that clock, the local time will be different. new Date() Obviously, one cannot let the user observe any time-dependent functionality, and make any time-dependent action, based on a clock which is the same for all users of the auction system. A Central Clock is Needed Hence, an auction system logically needs a central clock, and that clock has to be projected to all users in all case where relative times, such as a countdown timer, or absolute times, such as auction start and end times, are observed by the user on a web page. The web page might show absolute times in the user time zone, but the local time has to be derived from the central clock. Such a central clock has to be implemented at the server, as this is the only place where we can rely on. And needs to be transmitted to the user web page. Such a transmission can be either upon a time-based event, such as auction start or end or periodically, with the web page adjusting the content dynamically, such as advancing a countdown timer. The presence of a central clock implies the need for a real-time web application to which the server sends updates. Implementing a Central Clock Node.js Server-Side Integrate the web page and the server with . Socket.IO At the server run or , for an event-based action or periodic update, respectively. setTimeout setInterval Front-End Event-Based: At the front-end listen to a socket event for an event-based auction, e.g. socket.on( , (data) => {}); 'advanceCall' Or socket.on( , (data) => {}); 'startAuction' Front-End Periodic: socket.on( , (data) => {}); 'time' Laravel Server-Side Use to implement a timer, either periodic, ReactPHP $timer = $loop->addPeriodicTimer($time, {
     broadcast( TimeSignal(json_encode(...)));
}); ( ) ( ) function use &$task new where is a . TimeSignal Laravel event Or one time, $timer = $loop->addTimer($time, {
	   broadcast( AuctionCall(json_encode(...))); 
}); ( ) ( ) function use &$task new where is a Laravel event. AuctionCall For more details, see my article . Timer Server in ReactPHP Events are broadcast using or . Laravel Echo Server Laravel Websockts Front-End Listen for events with Socket.io, .Echo.channel( )
    .listen( , (e) => {
            
    }); window 'auction-events' 'startAuction' Or .Echo.channel( )
    .listen( , (e) => {
            
        
    }); window 'time-signal' 'time' Previously published at https://yoramkornatzky.com/post/an-auction-system-needs-a-central-clock

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An Auction System Needs a Central Clock

The artificial intelligence applied research startup Abzu identifies false news with its proprietary QLattice. In the latest , (that’s 38% surveyed in January 2020, a fall of four percentage points from 2019)¹. Imagine the numbers today. Reuters Institute Digital News Report less than four in ten people said that they trust most news most of the time Today’s global crises make it all too obvious the necessity for dependable and factual journalism, yet we are exposed to a continuum of information authored by innumerable sources with debatable credentials. Slaves to our most basic emotions — fear, disgust, and surprise² — we are inflamed by an addictive negative feedback loop of our own creation. We crave the truth, but data shows we force-feed ourselves lies. That’s why it’s . so exciting that artificial intelligence paired with a media marketplace could save us from our own humanity By any definition, it’s dishonesty of describes seven types of fake news³, ranging from accidental to insidious. The defines it as three “notions”: dis-information, mis-information, and mal-information⁴. Claire Wardle First Draft Council of Europe By any definition, no matter how nuanced the spectrum of intent, . And although the behind the creation is integral to understanding the misinformation ecosystem, the — simply the ability to identify content as true or false — is highly difficult for humans. false news is dishonesty why what And what is most worrisome is the increasing global effect of false news over our political, economic, and social well-being. ² “Fake news is not a problem of potential swing voters being misled. It reflects the potential for people on the extremes to be trapped in echo chambers that aren’t just reinforcing their opinions, but providing them with false and misleading factual claims that seem to reinforce those opinions .” Make a list of possible rabble-rousers and their intentions — rogue nationalities, organized activists, propagandists, trolls, or excitable grandparents — . the devil is in the dissemination, not the details Don’t blame the bot A study done by Soroush Vosoughi, Deb Roy, and Sinan Aral in 2018 found that “robots accelerated the spread of true and false news at the same rate, implying that false news spreads more than the truth because humans, not robots, are more likely to spread it.” Their research found that falsehoods travel six times faster, on average, than truth. And although falsehoods outpaced the truth on every subject, the pace for politics was unparalleled². When campaigns use incorrect imagery with the intent to sway and shock, as a , they prey on our natural tendency towards sensationalism. new ad for President Trump’s reelection campaign did to reinforce the presence of “chaos & violence” in the US Exactly the intensity of emotional reactions induced by a story influences human behavior requires more study, but we do know that content which arouses greater fear, disgust, and surprise compels individuals to share farther, faster, and deeper². how If a human brain can’t evaluate a story’s veracity, especially under emotional duress, two Danish growth startups, and , wondered if a robot brain could. Abzu Byrd Turns out, Abzu’s proprietary QLattice — a — through Byrd’s platform — a media marketplace for news outlets — . new artificial intelligence technology can rate the truthiness of content very, very well Abzu’s proprietary AI identifies false news is a leading breaking news and content platform that connects news outlets with photographers and videographers in real time through their marketplace. is an artificial intelligence applied research startup with a pioneering, and neural networks. Byrd Byrd Breaking Abzu explainable and transparent machine learning technology inspired by quantum mechanics Together, these Danish startups have built a solution that , rating media with a probability score of trustworthiness. automatically detects, and flags, falsified content in breaking news Each story and corresponding media undergo a machine learning verification process that captures the majority of false content, even as news breaks. If the artificial intelligence is uncertain, Byrd manually verifies content. The transparent and explainable graph-based models from Abzu allow Byrd to precisely understand what inputs have been used to determine if content has been falsified. This means that Abzu’s transparent and explainable AI models allow Byrd to understand specifically why content was flagged as false, no matter the intent behind the falsification. Once the — the ability to identify content as true or false — has been taken out of our sweaty and clumsy human hands and put into a robot’s capable and steady algorithms, then the behind false news creation can be explored. what why This will empower journalists and the news media to explore and tell stories more thoroughly, accurately, and confidently. In a world of increasing instability, . that is the kind of data-driven decision making that creates transformational industry leaders What a time to be a̵l̵i̵v̵e̵ dead inside It’s vital for media networks to ensure stories are true and trustworthy. Mortal extremes exacerbate our consumption of and attitude towards news media, and we don’t need another crisis or election to remind us how susceptible we are to conspiracies and misinformation. False news is an increasing global “infodemic” precisely because journalists — professional rationalists in emotional storms — no longer govern journalism. Greater access to social media and other platforms used to circulate news provides greater access to a wider range of sources and “alternative facts”. But Abzu and Byrd see a different future: one where journalists and the news media can identify the trustworthiness of content with conviction, and can navigate the news ecosystem to a more transparent and trustworthy place. “Our photographers are a crucial source of information, and we need to identify anyone trying to bring distrust into the media flow. With Abzu, we have been able to identify the majority of falsified news and also understand the reasons why stories are being falsified. It has given us another tool to fight fake news — and this tool applies itself.” Mikkel Reymann Stephensen, co-founder of Byrd When falsehoods are 70% more likely to be retweeted than the truth², how can humans preserve a news ecosystem that values and promotes accuracy? By introducing a little cold rationality to the environs; an artificially intelligent ally to save us from our own humanity. About Abzu was born from a desire to challenge the fundamental assumptions of contemporary AI, believing that the future of AI lies in the more lifelike simulation of self-organizing systems. Abzu’s pioneering machine learning technology is inspired by quantum mechanics and neural networks, resulting in a transparent and trustworthy AI. Founded in January 2018, Abzu is an applied research startup with offices in Copenhagen, Denmark and Barcelona, Spain. Abzu About Byrd is a leading content platform that connects media outlets with photographers and videographers in real time. Byrd’s platform makes it easy, enticing, and worthwhile for anyone to help media cover the news. The subscription-based marketplace is designed for journalists and news outlets to access high-quality media anytime and anywhere. Byrd [1] . Reuters Institute for the Study of Journalism, 2020, . Digital News Report 2020 https://reutersinstitute.politics.ox.ac.uk/sites/default/files/2020-06/DNR_2020_FINAL.pdf [2] . Science, 2018, . The Spread of True and False News Online https://science.sciencemag.org/content/359/6380/1146 [3] First Draft, 2017. . Fake News. It’s Complicated. https://firstdraftnews.org/latest/fake-news-complicated/ [4] Council of Europe report, 2017. . Information Disorder: Toward an Interdisciplinary Framework for Search and Policymaking. https://rm.coe.int/information-disorder-report-november-2017/1680764666

Flow

How We're Fighting False News with Artificial Intelligence

Shaun an 18-year adult who just got Internet-connected at his home. Having enthusiasm about the engineering of electronic devices and how the technology works. Exploring the vast Internet universe he quickly discovered the person who develops a program for a computer and machines is a software engineer. Perhaps, the boy didn’t have an idea, software engineering was just a leaf in a tree of technology. Having too few options to study technology he start studying Computer Engineering in his nearby college denying the fact that the field contains a majority of Mathematics, Physics, and Chemistry where Shaun was always lacking behind at his school days. As in every college story, there was also a trend of my friend earned $$ this week online or my friend has a website that is giving him $$ monthly, or my friend has a Youtube channel with 1k Subscribers. But the trend was not that impressive that could satisfy his inner cravings. Instead of catching tiny Anchovy every day, Shaun had a plan to grab a giant Fish. That doesn’t mean he never tried catching Anchovy. Fishing requires a large amount of fishing net, and other essential tools and the main thing is patience which he lacked. In a pond where there are already a lot of fishers involved, he would rarely get an Anchovy fish or even a fish. The idea of thinking big is always good, but it always take years of practice and continuous work to achieve mastery on something. Shaun off course was not from a family, who could afford him the essentials to catch a fish. Even his daily driver fishing rod was outdated and fishing for him was not smooth. Every student thoughts to be capable enough to afford the essentials for themselves, he was set to start a side hustle which is of course Youtube for any teenager geek person. Starting out was smooth, as he had heard enough success stories of those YouTubers. He was setting out to be the one among them. Perhaps, Youtube requires consistency and patience. He failed to manage his college studies and Youtube both at the same time. “Everybody is a genius. But if you judge a by its ability to climb a tree, it will live its whole life believing that it is stupid.” Albert Einstein wrote, fish Finally finishing his college after 3 years, perhaps without certification and with a lot of backs. He set himself to be a programmer that would pay him enough to buy him a good desk setup. The trend was of course a Web Developer around his area, where he was never fond of. But he always thought a million-dollar idea will pop in his head, he had already learned to program in his college days. Seeking a million-dollar idea, he was gathering all the problems that exist in his society or even the whole country. However, the problems were too complex to solve that it would require a Quantum computing or the Master algorithm. The essence of the million-dollar idea was slowly fading with the ideas having too complex to develop. But deep down there he was was interested in developing cool and intelligent software. After doing Java vs Python for almost 2 weeks he finally decided to learn both of them, Java in the morning and Python in the evening. Trying to hold a sweet in both hands he was confused about which to eat first. He began his learning journey however his old pal (machine) was getting older, and the pal was struggling to handle the process of Android Studio, the burden of Android Studio has turned the machine into less the computer but more the heater. - Albert Einstein “Only one who devotes himself to a cause with his whole strength and soul can be a true master. For this reason mastery demands all of a person.” After months of learning and practicing Android Development, he was finally able to add (Calculator) to his portfolio. A pretty great achievement. He didn’t stop there, Clock, Timer app, Pomodoro app, and To-Do app, he kept adding for the next more months. Now the game was stepped up, the boy wanted to compete with Facebook, Instagram, or Snapchat. Remembered? The million-dollar idea app was still there. Pretty quickly he started creating a social media app. 2 weeks later, he was still figuring out how to create a UI. Trying to bring down a mountain with a hammer, how long could you do it? After hitting the mountain 20–30 times he was already frustrated. Now he desired to get a job so he could survive, more than the survival he was into satisfying his inner cravings to have a good desk setup. Besides studying and pondering on multiple projects, he is always busy watching the MKBHD desk setup or the fancy new gadgets on Youtube. With frequent engagement with the video, the expectation level would reach above 100% however on clicking the link of Amazon the expectation would suddenly decrease below 10% seeing the price. (The price of a single gadget is the monthly income of an average individual in his country). Creating an unrealistic expectation always leads to disappointment and unpleasure which is directly proportional to burnout. Stop looking at things you cannot afford. Lessons to be learned from a young programmer Shaun: Microsoft, Google, Apple, or even Pyramid wasn’t built in a day. Perhaps to master swimming you have to start with a small pond or pool, with built-up confidence over the practice you will feel confident to dive into any river or sea. Understand we cannot learn everything or build anything in a single day, it requires time and patience. It’s is necessary to take breaks. Start with small, whatever you can afford. You don’t require a high-end workstation or even a MacBook to build greater things. A perfect desk setup is a myth. Engineer your set up whatever you have and make it comfortable to boost your productivity. You don’t require that Herman Miller Chair that you saw unboxing from one of your Youtuber. We aren’t computers. We can’t go at full speed 24/7. We’re humans and we need breaks. Perfection is the enemy of progress Never learn a skill just because it has the highest salary or higher demands. If you are a beginner, you should always focus only on limited things. Build up your base first, if you are jumping from one skill to another it will take a longer time to achieve mastery on it. Being not able to earn anything from your skill, your brain will stop releasing dopamine. Example: If you are learning Front-end development. Master it first, you don’t need to jump to learn the highest demanded skills like Data Science and Machine Learning. Whatever you’ve learned, try to land a job with that skill you can catch up with another skill anytime sooner after surviving. Mastery requires time and patience, don’t try to learn everything at once. (Bruce Lee: I fear not the man who has practiced 10,000 kicks once, but I fear the man who has practiced one kick 10,000 times.) No one gets paid higher from Hottest Jobs, we get paid for our skills. We cannot eat everything at once. If you cannot afford a perfect desk setup or fancy gadgets, watching it on Youtube is totally a waste of time, it increases your inner cravings with which you will not be able to focus on your current work. It forces your brain to earn those needs where soon you will begin to crave for money. Hence you lose your focus. An atomic habits, that needs to be done every day: Know your time and limit, and usually take breaks. Perhaps, the best thing to offer your busiest brain a glimpse of nature by visiting nearby parks or natural areas. Previously published behind a paywall at https://medium.com/@devson/the-flop-story-of-a-young-developer-febe0c9bd3a2

What You Can Learn From a Young Developer's Missteps 

Target

From the Brink of Suicide to Bliss: How Hormones Destroyed and Saved My Life

Ask traders how they find the next breakout move, the next runner that’s going to skyrocket to +2000% profit. They’ll likely spout a bunch of technical indicators, screeners, Bollinger Bands, RSI, Stochastic Indicators… the list could go on. Before we even get to these tools, we first need to understand what the stock is from. So without further ado, here is your lesson on Trading Range. breaking out What is a Trading Range? When you start to look at charts, one thing you’ll likely notice is the predictable stair-step pattern. This tells you if a stock is moving in an upward or downward trend. But trends are only one part of the trading equation. For the majority of the time, securities move within a price range. This is characterised by a stock bouncing back and forth between two prices. We refer to this as the ‘Trading Range.’ The trading range has two defined price levels. The top or ceiling of the trading range provides price ‘resistance’. The bottom or floor offers price ‘support’. If a stock is moving within a trading range, there is relative market consensus about the stock’s value. When the stock breaks from one of these levels, this indicates momentum and a possible new trend forming. Or it could just be a fake-out — more on this later. Identifying and measuring the strength of support and resistance zones is essential to successful trading. The strength of the trading range is determined by the length, depth and trading volume. The greater the depth, the higher the trading volume, and the longer the trading range — the stronger the range is considered. For traders, these levels of support and resistance aren’t just lines in a chart. They are valuable markers, fundamental in identifying entry, exit, stop loss, profit taking levels, and risk to reward ratios. The basics of any successful trading plans. There are a number of range-bound trading strategies traders use to capitalize on stocks moving within a trade range. We take a look at some below. Support and Resistance A simple strategy to use in well established trading ranges, is to buy at support and sell at resistance. Buy low, sell high. Not exactly a thrilling trading setup. But it’s one that could pocket you consistent profits if used correctly. As with all trading strategies, risk management is essential. You can set a stop loss just outside the trading zone to minimise risk. However, you should beware of the fakeouts. Trading ranges have a tendency to attract lots of traders, which could increase volatility. Market makers are also known to purposely trigger lots of sell top orders by momentarily driving the price down. Only to then buy and drive the price back upward. To avoid being stopped out, you can use wider stop losses — but only if it meets your risk profile. Breakouts and Breakdowns Trading ranges don’t last forever. There will be a time when price breaks the levels of support and resistance and a new trend begins. A breakout is when the price breaks above resistance, while a breakdown is where the price falls below support. Where a breakout or breakdown is fueled by large volume, this tells us that there is widespread activity by other traders and reinforces the reliability of the break. To avoid ‘chasing’ the price, traders who didn’t open positions the breakout often wait for retracement before entering a trade. Retracement should be a higher low (vice versa if shorting) and not a return to the trading range. By waiting for the first retracement, traders are better able to trust the validity of the breakout as it shows a genuine shift in supply and demand. Short-term traders will have exited their positions and taken their profits, causing the retracement, and new traders step in to take advantage of the new trend. before Again risk management is crucial and stop losses should be utilised as part of your exit strategy to protect against failed breakouts. How to Find the Next Runner? Follow the Big Money As the market cycles between trend and trading range, it’s crucial to learn how to spot potential break, before it happens. The key is to look at volume. By tracking volume we get clues as to the future price direction. We can track volume by looking at option order flows and tape data. Unlike stocks where order flows are complicated by secrecy and time lag, with option order flows, all trades are printed shortly after execution. The order flow tells us where the trades are being made, the size, type and name. There are no secrets, it’s all on the tape. When you notice option contracts starting to trade in high amounts of volume compared to their previous average, you can deduce that something ‘unusual’ is going on. When we say ‘high amounts of volume’ we generally mean five times the average daily volume, but the higher the better. We take particular interest in unusual activity like this, as it can indicate that somebody out there, might know something not yet public and is betting there will be a big move in the underlying asset. As option contracts have expiration dates, high volumes in weekly options could mean that someone is expecting a big move or break to happen imminently. We pay even closer attention when there have been large individual orders (the size of the usual day average) or multiple smaller orders executed just milliseconds apart. This suggests that an institution or ‘big money’ is making the bet and something big might just be happening on the horizon. And in the case of smaller block orders, you can guess that the ‘big money’ is trying to stay under the radar. Be Wary of Hedges Option flows need to be interpreted carefully. Where a large increase in volume comes ahead of a catalyst like an earnings report or an announcement, it’s safe to assume that the unusual activity is likely just a large hedge taking place, rather than an impulsive directional move. Hedges are defensive plays. To protect their long term positions, big institutions will buy options to reduce short-term exposure to volatility from catalysts like a disappointing earnings report. But where there is no catalyst in sight, we may infer that someone is anticipating large moves in the underlying stock. By following the big money, we can get clues as to what the institutions are thinking and how they are positioning themselves. From this we can deduce when a break is near and decide whether or not to capitalise on it  —  that’s an edge. Technical analysis is not an exact science. But by pairing technical analysis with options flow data, traders are able to see the ‘bigger picture’ of what is actually happening in the background and plan their moves accordingly. The key to becoming a better trader is learning to identify and pre-empt the impulsive moves and recognising when they present real trading opportunities. Don’t rush headfirst into a trade. . Map out key areas of support and resistance, monitor how the stock behaves as the price moves, look at option flows for clues to future trends and then plan your trade from there. Have a plan

Trading Range: Finding Your Next Runners

As the COVID-19 pandemic continues in several countries, causing notable modifications to occur in workplaces; organizations are grabbing on to artificial intelligence, IoT services and as-a-service (aaS) models to conform to the fast-emerging realities. Therefore, only an alternative approach of collaboration can stimulate the clattered productivity and effectiveness of the global workforce in an enterprise, as these changes are sure to have a lasting influence on future workplace practices. Enterprises are looking for a method of transferring employee dependence on physical hardware and allocating increased investment into the software sphere, this is where UCaaS is implemented. What Is Unified Communications as a Service (UCaaS)? UCaaS is an enterprise-focussed service dedicated to streamlining the transmission of communication through cloud-based services. Unified Communications as a Service offer organizations innovative features, integration potentialities and functionality that would not have been feasible with conventional communication systems. While “UC” stands for Unified Communications, the 'as a service' features of the technology implies that it can administer unified communications anywhere, at any time, over the cloud. UCaaS eradicates the necessity for expensive IT infrastructure and the support of a full IT team by implementing UC on the back-end which can be done by Cloud service providers. Before the cloud-integrated technologies, telecom service providers offered IP Centrex and Hosted communications services. These were practically similar to the current UCaaS capability, except for the fact that “virtualization” has determined that the distribution of unified communication as a service is so much more compelling. A few examples of prominent UCaaS providers include Twilio, Voxbone, 8x8 and Zoom Video Communications. How The COVID-19 Pandemic Is Accelerating Cloud Adoption The coronavirus (COVID-19) outbreak is proffering a unique possibility where business administrators, globally, have to promptly enable their workforces to operate remotely for an extensive period. Consequently, enterprises are including remote work practices, where collaboration holds the solution to meet the expectations among the administration and employees. According to Future Market Insights, the Coronavirus pandemic is anticipated to expedite cloud adoption, not only as a technological adaptation but also as an operating model. Several large and medium enterprises all across the globe are acknowledging the boundaries of their current environments and struggling with the effect of the pandemic on their businesses. In response to the current scenario, UCaaS solution providers and companies are taking appropriate actions to satisfy consumer demand for cloud usage, due to the sudden shift to a remote-first workforce. Moreover, Unified communication as a service (UCaaS) market is expected to grow exponentially and witness an upsurge in demand citing the Coronavirus pandemic, as remote working has become the current norm. The Benefit Of UCaaS Under The Current Scenario By implementing unified communications through cloud-based services providers, an enterprise can minimize hardware expenses, improve work from home efficiencies, therefore enhancing employee productivity. As is oft-touted, UCaaS enables businesses the possibility to: Promptly achieve advanced features and functions with moderate CAPEX Integrated connection center and quicker customer management capabilities Diminish the hazard of technology obsolescence Gain access to proficient outsourcing organizations, bypassing ownership and operation Software development companies can enhance team collaboration and workstream collaboration specialities Change IT staff responsibilities to more substantial projects Increase resource collaboration when working away from the office and keep them updated with business developments AI and machine learning with advanced features such as intelligent call routing Enterprises can remotely manage and administer systems, users, and employee work collaboration Workplace management with IoT services, multimedia messages and online messaging How Different As-a-Service (aaS) Products Are Emerging Nowadays The COVID-19 has thrust the “future of work” to the forefront of revolution with shocking speed, from the rise of robots and the trends in IoT services to machine learning and Artificial Intelligence. All these inclinations point to an innovative world that’s shaping up quite distinctively from anything we’ve ever seen, or worked in, before. While Unified Communications evolves, its main objective currently is to integrate enterprise communication tools so that collaboration can be made simple. These tools combine real-time monitoring, video calling, instant messaging, desktop sharing, and web/mobile applications. With the use of UC, all these technologies can be combined into one neat little but major package. Here are the different As-a-Service (aaS) products that provide a consistent user experience. United Communications as a Service (UCaaS) Just like SaaS, UCaaS empowers enterprises to only spend on what they require and utilize. In essence, UCaaS presents both communication and collaboration by cloud integration, thereby experiencing instant connections across several devices. Communications Platform-as-a-Service (CPaaS) Along with UCaaS, enterprises are now considering CPaaS, the Communications Platform-as-a-Service technology. CPaaS provides several of the communicative tools as the UCaaS framework but grants them as objects that can be integrated via APIs into the core applications of an enterprise. Contact Center as-a-Service (CCaaS) CCaaS, as the name indicates can develop enhanced customer service experience. As a result, some collaboration technologies featured in UCaaS and CPaaS typically overlap with the features by CCaaS. By using all three 'as-a-Service' models, enterprises can overcome the impact COVID-19 has on the interaction and collaboration between employees or businesses. The Rise of Technology During Covid-19 Pandemic The intense competition and increasing consumer expectations are reconstructing the dynamics of Unified communication as a service (UCaaS) technology, encouraging solution providers to innovate and enhance their customer engagement. The prompt transition among consumers towards cloud communication is stressing for the necessity for improved customer productivity and network flexibility and is proposing possibilities for exceptional communication and collaboration tools. The COVID-19 pandemic has emerged as an unprecedented challenge for humankind as various sectors, industries, and individuals attempts to mitigate the uncertainties associated with it. From a business perspective, it bodes for enterprises to switch to remote working, , and implement the different models of Unified Communication as a Service (UCaaS). adopt the latest IoT services The impact is felt everywhere, right from human interactions, workplace practices, remote working, and has also affected our leisure time. The circumstance has driven various sectors into a novel era whether it’s how to manage collaboration while working remotely, how to minimize interaction with trending IoT services and also how to minimize the spread of COVID while keeping the workforce engaged and operational in general.

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Remote technologies and opportunities were already sweepingly popular before the nasty COVID-19 outbreak. 2020’s global pandemic and the resulting massive lockdown reinforced the industry-wide reach of online education and underlying technologies, boosting the growth of the EdTech industry by an annual 17-25%. The shift of both formal (school and university) and corporate education toward online is now stronger than ever, spawning new tech and business trends and dramatically popularizing the existing market tendencies. This extends the horizons of the E-Learning and EdTech market for all eager entrepreneurs and service providers to grab a piece of cake. Along with new wide opportunities, however, niche challenges come into play as well. We’ve surveyed a number of EdTech CEOs working in the industry to learn what relevant issues they face and how they overcome market challenges when it comes to software development and product distribution among the ever-growing audience of users. For this EdTech report, we’ve also analyzed the major market statistics to see the big picture of the industry conditions and software building tendencies that form the massive popularity of EdTech nowadays. Challenges EdTech Companies Must Overcome As rich and promising as the EdTech market is, it can’t but have a good share of competition. EdTech solution providers have to fight for their right to sell their creations to clients. The brightest examples include challenges of technology in education related to lack of funding. Many companies struggle and lose a lot of money in attempts to acquire customers. All because numerous ambitious startups lack sufficient funding. And that’s in the market where the potential demand greatly exceeds the offer, with millions of schools, thousands of colleges and universities waiting for their time to upgrade technologically. Then, there are also debatable EdTech business questions, like what should be the top priority for providers in the field - scaling or monetization. The thing is, investors are more focused on working with long-standing, established businesses able to bring regular profits stably. That’s why the scale-first-monetize-later business development strategy becomes increasingly preferred in the field. This model may even help change the situation with funding shortages if enough startups start adopting it timely. To dive into more detail, according to our own thorough EdTech industry analysis, here are the most relevant EdTech challenges businesses must face to break into the education sector: (32%). Long Sales Cycles When it comes to corporate politics and K-12 specifics, lots of bureaucracy is involved in the approval and adoption of new functional elements, which takes a lot of time to settle. The ultimate way to tackle this challenge is to focus on customers, their needs and rates of satisfaction to build transparent, smoothly-flowing business relationships. (26%). Limited Budgets Establishments may also lack the budget and wait until they get another round of funding from their sponsors to purchase a new EdTech solution. Other reasons for budget shortages may be numerous (lack of funding, poor economics, etc.). (16%). Oversaturated Market The competition is fierce. We’re talking about a growing and emerging field that still has lots of unexplored and unmonetized patches. (11%). Slow-moving in Accepting Innovation Companies, as well as people, are also afraid to integrate and invest in something not yet properly assimilated in their country. Even if they see great results in other countries, being a pioneer may be too much of a weight to carry. (5%). Non-sustainable Monetization Model Many companies still need to adopt efficient monetization models to be able to better introduce their solutions to the mass market. (5%). Achievability for Non-technical Users Many people need time to get a hang of certain technology, even if it’s very intuitive. There are people who don’t really use electronics that much in their daily lives. This spawns difficulties with integrating certain EdTech solutions among studying audiences. Read in full The Challenges of Building an EdTech Company Report .

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Introduction Armin Ronacher has become a prolific contributor to the Python software ecosystem, having created such widely used projects as Flask and Jinja2. Over the last 10 years, he had worked on various Open Source and commercial projects, and we were extremely excited to speak with him about his life and career. In this interview, Armin talks about his work at Sentry, shares his thoughts on handling errors in the backend, speaks about the differences between Rust and , the "gradual typing" approach, and, of course, the secrets of his work-life balance. Python The Interview - Your job title is Director of Engineering. What does your everyday work look like at Sentry? From a scheduling point of view my day is typically split into two parts. I work from 9 to around 3 pm/4 pm when I pick up the kids from daycare. Then I have a second slot late in the evening/night for meetings across timezones. That segmentation works well for me because that way I have time with the kids when it's light outside. In terms of what I do in many ways, my role is to make sure that all the people that work with me are aligned on the things that matter. This is particularly important because Sentry is a company with multiple locations across timezones. Really it's a mix of hiring, solving people problems, assisting in system architecture, shaping or communicating product vision to the actual projects and then a lot of assisting with odd engineering issues. Armin: - The popular "full-stack" approach promotes developers to write both frontend and backend code. As a developer who knows lots of programming languages and technology stacks, do you approve such a practice? It's a complex question because what's full stack on a complex project really? Sure for a trivial application it only really consists of a CRUD backend and some frontend, and you can comprehend the entire thing. But that process does not at all work for us, because Sentry is a much more complex endeavour. The simplified description of what Sentry is is a service to take crash and performance reports and show them to the user. However, from a technical perspective Sentry is a very complex processing pipeline with multiple databases, multiple services to process the reports before they are persisted. The idea that a single individual could be tasked with working on all these components to ship a feature is not just unrealistic, it's also very inefficient. So my answer to if I approve on this practice would very much depend on the type of project. Armin: React - Recent Mozilla restructuring hit lots of Rust language developers. How do you think that will affect language development? For me personally it hurts to see the developments at Mozilla. Like Mozilla, we're an Open Source project made into a commercial enterprise and our paths crossed a few times. We're sometimes leveraging Mozilla technologies in the same way Mozilla uses ours. I think for Rust as a whole the changes at Mozilla will surely affect the language, but I don't think Rust will take any damage from it. But no longer having the Servo project will definitely have an impact on how the language and community evolve. Armin: - What do you think is the main reason why Python packaging is still so complicated? It's a very complex story but I believe it comes down to technical challenges and lack of focus. For instance, to contrast this with the Rust community packaging was recognized as an important thing and a community project (cargo) for packaging was made part of the language development. In the Python world, these efforts are always separate. The packaging infrastructure (pip, setup tools, virtualenv) are largely developed independently from the language. From the technical side, there are many shortcomings in Python that stand in the way of a better user experience. For instance, you can only load a single version of a library at the same time, limiting how "wild" you can go with dependencies. Armin: - Comparing Python, Rust, TypeScript, and other languages you work with: what do you think is the best strategy for an average developer to handle errors in their backend code? Since I work for a company specialized in crash reporting I am exposed to a large number of backend errors :) My learning from that is that you should spend the same amount of time designing the error types as the return values. You cannot have enough contextual information on errors. There is a shocking amount of code that just writes error messages into an exception and calls it a day. Then eventually someone will want to respond to those errors and starts parsing the error messages. This type of "stringly typed error handling" is a source of a lot of frustration. I remember some database handling code that checked for a certain type of connection error by parsing the error message and handling multiple languages (German, French etc.) since the database on the other side would localize error messages. Armin: - Are there any Python language or ecosystem features that you really miss while working with Rust? For sure. Python is a very mature and grown-up language so whenever you switch somewhere else, there is a wealth of stuff that's just not there. It will take a lot of time for other ecosystems to become as wealthy as Python's. One of the first things I noticed when writing more Rust is that the ecosystem was quick to adapt to typical "2020" things but less so to older technologies. The first time I had to interface with XML instead of JSON I noticed how weak Rust's XML support is for instance. Another thing is just that Python as a rather "slow" language doesn't punish you much with adding more debugging features into a production build. In Rust. you can't really do that without throwing one of the best features (the performance) out of the window. That causes you to program very differently. Armin: - What do you think is the best way to evaluate software developer expertise? A hard question for me. I feel like the right way to hire or assess people does not exist, a lot comes down to how good you are at assessing people in general. There is a whole community of people that do nothing but grinding interview questions from FAANG companies and that has for sure changed things quite a bit. We're also in the situation that my teams are often working on issues which are pretty unique, so it's more important to find out if developers are interested in solving unique and sometimes frustrating problems and how they work in a team on tricky things. Armin: - Do you think Python is still the best general-purpose programming language we should teach first to new developers? Do we have any alternatives in 2020? I'm not sure if I thought Python was ever the best general-purpose programming language, but I always thought it strikes a pretty good balance. Despite all of its shortcomings and frustrations it causes, it's quite good for solving problems quickly and in that sense, it's as good in 2020 as it was 15 years ago. I thought for a while that JavaScript would replace it but somehow the community has embraced such a complexity that even the simplest things become complex. I'm still faster making a throw-away project in Python than JavaScript just by the fact that I only need a handful of libraries. If I were to teach someone programming in 2020 I would probably pick C, Rust and Python as languages and Python to a large degree because you can also show them the interpreter source code and they will be able to understand how it works behind the scenes. That's not true for many other popular languages. Armin: - With so many programming languages to work with, what operating system and IDE do you prefer? Computers are terrible. I have a love/hate relationship with macOS. Still using it and every time I try to use something else, I'm back in a few weeks. I deploy to Linux machines though and there is plenty of Windows around in my life. IDE wise I use Visual Studio Code with Vim bindings and I still use Vim independently a lot. Armin: - The new "async/await" syntax and concepts were recently introduced into Python, Rust, TypeScript: all the languages you work with. What is your opinion on this approach to handling concurrency in our code? I'm torn. I think it has a lot of benefits when used the right way but it hides the challenges of concurrency too much. It also makes lack of backpressure management more apparent and I would guess that most async/await code in existence would fall over if I try to bring it to the tipping point. This is something that traditional multi-threading code (which mostly uses a pool) does not suffer from out of the box. It's also important to understand that just because multiple languages have async/await how they actually approach it is very different. Rust's and JavaScript's async/await designs couldn't be more different. Armin: - Python seems to be eating the world. Can you name any real competitors to it as a general-purpose programming language? Python seems to be eating the world largely because of data science. I think while it loses popularity in the web world it's quickly making up these losses in the data world. Because JavaScript isn't good at numbers (to put it bluntly) it has less of a footing there. That said, I think JavaScript is just out of necessity becoming more and more popular. Armin: - With all your Flask and open-source background strengthened up with Sentry work you are an expert on programming languages. What do you think about the future of Python? I think it will become more and more specialized into some ecosystems and completely give up on others. This is somewhat consistent with how it has worked in the past too. For instance, Python gave up on becoming a language for embedding (Game or application scripting etc.) or mobile development. It's also not something you would use as the preferred language for Desktop apps, particularly if you want to get into app stores. It is however probably going to become more popular for serverless, data science and scripting infrastructure. I noticed a shift in the users of my template engine from classical web applications to more and more infrastructure scripting (Ansible, salt) for instance. Armin: - What do you think about the new "gradual typing" approach introduced into Python, JavaScript (via TypeScript), Ruby, PHP, and other dynamic languages? I think it's great. I absolutely love TypeScript and I think if more languages want to learn from somewhere, that project is what should be copied. Armin: - As both a father of three children and a software development lead, how do you organize your work-life balance and avoid burnouts? At the time of writing still two kids though days away (fingers crossed). The first and most important thing is that I'm not parenting alone. With my wife, I have a wonderful partner and we are taking care of our kids together. To help us with that, the next most important thing is to find good daycare. You can't be a good parent 24/7 but you can make sure that the time you spend with them you give them the right attention. Particularly during the early pandemic days, we had the kids at home all the time and I noticed how that was not good for us or them. They spent more time on TV and iPad as we had to juggle work meetings with taking care of them. Armin: For me personally, since we live in Vienna and the head office is in San Francisco I adopted a bicameral model of working twice with a break in between. For me this is ideal, but I don't think it would work for everybody. I started doing a list where I write down when and why something emotionally upset or stressed me in a week to try to optimize away from that. Eventually, you start understanding yourself a bit better. Out of that, some patterns emerge. Once I identify a situation that has the chance to upset me I now no longer try to prevent or avoid it. Instead, I try to recognize early that it's going to evoke some emotional response in me. Doesn't always work, but overall has helped me a lot. For instance, Slack notifications no longer disrupt me as much as they used to do even without turning on do not disturb. The Conclusion We had a great time speaking with Armin and learning more about his approach to life & writing code.

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Interview: Flask Creator Armin Ronacher

In this three-part podcast, I had the pleasure of speaking to Microsoft Engineer Nataraj Sindam. In Hacker Noon's 2020 Noonie Awards, Nataraj was the 2nd runner up in the category. Hacker Noon Contributor of the Year for Business Strategy In our podcast, we talked about the following topics: The push vs pull life The cons of recommendation systems Freemium models Business strategy Writing on Hacker Noon The Indian startup economy The United States working visa complications Watch the snippets and full podcast below! Part 1: The Reciprocation Effect: How Fornite and Spotify Make Millions In this podcast snippet, Nataraj and I talk about The Freemium Model and The Reciprocation Effect, a pricing strategy used by some of the world’s largest companies, including Fortnite and Spotify. Part 2: The Push vs Pull Life: Cons of Recommendation Systems In this second podcast snippet, Nataraj and I talk about the push vs pull life and the cons of recommendation systems used at Netflix, Youtube, Amazon, and more. Part 3 [Full Podcast]: Microsoft Engineer Talks about India’s Startup Economy, Business Strategy, and Writing This is the full 1-hour podcast where Nataraj and I talk about the following topics: The push vs pull life The cons of recommendation systems Freemium models Business strategy Writing on Hacker Noon The Indian Startup Economy United States working visa complications Nataraj has a lot of insights into the Indian startup economy and what it's like working as an engineer at Microsoft via a H1-B Visa. I highly recommend everyone check this podcast out. FOLLOW NATARAJ ON SOCIAL MEDIA: https://www.linkedin.com/in/natarajsindam/ https://twitter.com/natarajsindam CHECK OUT NATARAJ’S END2END PODCAST: https://open.spotify.com/show/39sihqVOYpq60z8UA6FYbw https://podcasts.apple.com/us/podcast/end-2-end/id1482225169 Finally, please be sure to take a look at for more great talks with the best and brightest minds in tech today. our podcasts page

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The Push vs. Pull Life, India's Startup Economy, and Business Strategy w/Nataraj Sindam 

HackerNoon Tech Stories Archive October 24th, 2020

How Gamers Decide Tomorrow’s Technology

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An Introductory Guide to Ethereum and Dai

@stenivan
Sten Ivan

10 Cybersecurity Tips Everyone Should Follow

@DataGeneralist
Steven Finkelstein

Why Team Building Matters - Winning Over Sceptics

@ryandawsonuk
Ryan Dawson

If a Tree Falls and it's not on Linkedin, Who Knows?

@lazarus
Yohan

Quick Guide to AWS CDK and Serverless with REST API and Data Lake Analytical Querying

@taavi-rehemagi
Taavi Rehemägi

Should you learn C in 2020/2021?

@zeppsan
Eric Qvarnström

An Auction System Needs a Central Clock

@kornatzky
Yoram Kornatzky

How We're Fighting False News with Artificial Intelligence

@Elyse
Elyse Sims

What You Can Learn From a Young Developer's Missteps

@devson
DevSon

From the Brink of Suicide to Bliss: How Hormones Destroyed and Saved My Life

@thingsvarious
Thingsvarious

Trading Range: Finding Your Next Runners

@leah-mathieson
Leah Mathieson

How the Pandemic Has Driven the Rise of Collaboration Through UCaas

@ricky-philip
Ricky Philip

The Challenges of Building an EdTech Company in the Post-COVID World

@globalluxsoft
Andrew Radomsky

Interview: Flask Creator Armin Ronacher

@elizabethlvova
Elizabeth Lvova

The Push vs. Pull Life, India's Startup Economy, and Business Strategy w/Nataraj Sindam

@Limarc
Limarc Ambalina

HackerNoon Tech Stories Archive October 24th, 2020

@jonathankingstonJonathan Kingston

@stenivanSten Ivan

@DataGeneralistSteven Finkelstein

@ryandawsonukRyan Dawson

@lazarusYohan

@taavi-rehemagiTaavi Rehemägi

@zeppsanEric Qvarnström

@kornatzkyYoram Kornatzky

@ElyseElyse Sims

@devsonDevSon

@thingsvariousThingsvarious

@leah-mathiesonLeah Mathieson

@ricky-philipRicky Philip

@globalluxsoftAndrew Radomsky

@elizabethlvovaElizabeth Lvova

@LimarcLimarc Ambalina