Best Binary Trading Platform - 2020's Top Options Brokers

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platform binary options - 5 list!!! the best binary options brokers - you must now submitted by TopVideosCasino to u/TopVideosCasino [link] [comments]

Binary Options Trading Platform – Selecting The Best top binary options brokers

submitted by eventby90 to binaryoption [link] [comments]

MAME 0.222

MAME 0.222

MAME 0.222, the product of our May/June development cycle, is ready today, and it’s a very exciting release. There are lots of bug fixes, including some long-standing issues with classics like Bosconian and Gaplus, and missing pan/zoom effects in games on Seta hardware. Two more Nintendo LCD games are supported: the Panorama Screen version of Popeye, and the two-player Donkey Kong 3 Micro Vs. System. New versions of supported games include a review copy of DonPachi that allows the game to be paused for photography, and a version of the adult Qix game Gals Panic for the Taiwanese market.
Other advancements on the arcade side include audio circuitry emulation for 280-ZZZAP, and protection microcontroller emulation for Kick and Run and Captain Silver.
The GRiD Compass series were possibly the first rugged computers in the clamshell form factor, possibly best known for their use on NASA space shuttle missions in the 1980s. The initial model, the Compass 1101, is now usable in MAME. There are lots of improvements to the Tandy Color Computer drivers in this release, with better cartridge support being a theme. Acorn BBC series drivers now support Solidisk file system ROMs. Writing to IMD floppy images (popular for CP/M computers) is now supported, and a critical bug affecting writes to HFE disk images has been fixed. Software list additions include a collection of CDs for the SGI MIPS workstations.
There are several updates to Apple II emulation this month, including support for several accelerators, a new IWM floppy controller core, and support for using two memory cards simultaneously on the CFFA2. As usual, we’ve added the latest original software dumps and clean cracks to the software lists, including lots of educational titles.
Finally, the memory system has been optimised, yielding performance improvements in all emulated systems, you no longer need to avoid non-ASCII characters in paths when using the chdman tool, and jedutil supports more devices.
There were too many HyperScan RFID cards added to the software list to itemise them all here. You can read about all the updates in the whatsnew.txt file, or get the source and 64-bit Windows binary packages from the download page.

MAME Testers Bugs Fixed

New working machines

New working clones

Machines promoted to working

Clones promoted to working

New machines marked as NOT_WORKING

New clones marked as NOT_WORKING

New working software list additions

Software list items promoted to working

New NOT_WORKING software list additions

submitted by cuavas to emulation [link] [comments]

NanoFusion - Project Update and Next Steps

Build-Off Result

I'm sure some people will be wondering about the status of the NanoFusion project going forward. Naturally, the outcome of the Nano Build-Off was pretty disappointing for me personally. After initially receiving such a wave of positive feedback here on reddit, it was unfortunate to not even crack the top 20 projects.
In spite of that result, I think the community's desire to see a trustless privacy protocol in the Nano ecosystem is actually quite strong. I believe this Build-Off result is primarily a reflection of the judging criteria, which skewed strongly towards apps that were already somewhat polished, and able to be tested by one person within the space of 10 minutes. This naturally disfavours a project like NanoFusion which is still a proof-of-concept, and requires multiple participants in order to properly use it. All that to say, while I applaud the winning projects for their efforts, and extend my gratitude to Nanillionaire for sponsoring the event, I don't believe that the Build-Off result gives a full picture of the community's true priorities for future development of the Nano ecosystem.
Nevertheless this result points to a stark reality: NanoFusion is not yet ready for consumer use, not by a long shot.

What will it take for NanoFusion to be consumer-ready?

Protocol and Reference Implementation Status
There is a small amount of work to be done to finish the reference implementation of the protocol. The binary tree of input mix accounts has been constructed, but the code is not yet written to actually execute the mix, nor to trigger and execute refunds where necessary. That is really the last step that needs to be completed for the reference implementation, and it's not especially complicated. The tricky bit is that there are still a few bugs around communication between the clients that need ironing out. But those are relatively minor bugs, I'm confident they won't require fundamental changes to the protocol or the implementation architecture.
However, once the reference implementation is complete, that is where a whole new set of challenges begins.
Wallet Integration
The primary challenge will be to integrate NanoFusion into one or more popular wallets. For a privacy protocol to be most effective, we need as many people as possible using it. In a cryptocurrency like Nano, where transactions and addresses are all publicly visible on a block explorer, privacy is achieved by making it difficult to determine which transactions belong to you. Making it difficult is a matter of having your transactions get "lost in the crowd". The crowd of transactions that might potentially be yours is called the "anonymity set". We need that anonymity set to be as large as possible, which means we need as many people participating in Fusion events as possible.
The best way to achieve this is to get NanoFusion adopted by popular wallets, and ideally to have it enabled by default. The less decisions that a user needs to make in order to start participating, the better.
This raises one very important question. How do we make it as easy and appealing as possible for the developers of popular wallets to integrate this technology?
Workflow Design
In order to make NanoFusion integration appealing to wallet developers, I believe we need to gear NanoFusion integration around workflows that actually work for end-users of the wallet. This is not as simple as it appears.
The Nano ecosystem is currently geared around the assumption that addresses will tend to be re-used for many sends and receives. This is almost intrinsic to the ORV consensus mechanism. You keep your funds in one account, and the voting weight for that account is assigned to your representative.
In a UTXO-based cryptocurrency, BCH in particular, it is much more normal to use a separate subaddress for every incoming transaction. CashFusion on BCH works by taking all your different receive addresses and mixing the funds from those addresses together (along with the funds of many other people's subaddress sets). But on Nano it's different. Imagine you have an online store accepting Nano funds via BrainBlocks integration. If you receive 100 payments, you might have BrainBlocks forward them all to just one account that you own. But this makes it trivial for a customer to look at the block explorer and see all of your sales volume, which completely undermines your privacy.
In the context of something like BrainBlocks, it's easy to see how our e-commerce store could generate a new address for each transaction, and have BrainBlocks forward funds to that new address. Then we could run NanoFusion later to obscure the linkages between our individual sales. But what about addresses that are shared in public? Lots of people put up single Nano addresses to receive donations, etc. What does NanoFusion do with those? For NanoFusion to be most effective, a given user should NOT have just one input and one output account in the mix. It makes it too easy for their input and output accounts to be linked (at least to a moderate-to-high degree of probability) by the publicly visible amounts in the accounts.
For NanoFusion to be most effective, we need to develop a culture where it is normal for people to use a new address each time they receive some nano. How do we make it appealing for wallet developers to build their wallets this way? I don't really know. The only example of this pattern that I know is Nanonymous (https://github.com/LilleJohs/Nanonymous). We could potentially implement something like stealth addresses, so that the user really gives out one canonical public address, but a different receive address is actually used for each transaction "under the hood". However, that adds a whole new layer of complexity. It means wallets have to be upgraded to know how to interact with a stealth address.
API Design
Even if we could arrange things so that it was more common for individuals to have multiple input accounts to mix, we would still be left with another question. What would wallet developers want the API for NanoFusion to look like? By nature, NanoFusion requires a large number of messages to be sent back and forth between all of the mix participants. For security reasons, those messages cannot be sent all at once. Player A has to wait for Player B to send message 1 before it is safe (cryptographically) for Player A to reveal the content of message 2.
What should a library look like that manages that complexity on behalf of the wallet developer? What language should it be written in? I have begun this project under the assumption that the most common wallet-dev language would be javascript, but there may be cases where other platforms are needed.

Where To From Here?

Technical Reflections
Thinking through all of these practical challenges has given me a new perspective on the whole issue of cryptocurrency privacy protocols. I have a much greater respect for what has been achieved by the Monero project. In Monero, everyone actually uses the privacy protocol. As described above, that is no small accomplishment. Even though the privacy protocols for Dash, ZCash, BTC and BCH do basically work, their use is not widespread. Even leaving aside the issue of the extra transaction fees incurred (which is not such a problem for Nano), these optional privacy protocols are just not that convenient to use. Because not everyone uses them, the anonymity set is not nearly as large as it could be. And because not everyone uses them, transactions you do before and after a mix/fusion event leak metadata which can be used to undermine the privacy that you gained by using the privacy protocol in the first place.
Inevitably, NanoFusion will also suffer from this problem. Suppose that 20% of the Nano community starts regularly participating in fusions (a very generous estimate, given the low adoption rate of optional privacy features in the other cryptocurrencies mentioned). That still leaves the large majority of transactions probably re-using addresses most of the time. This means that the non-private majority will leak fresh metadata whenever they interact with accounts that were previously obscured through NanoFusion. This is not an easy problem to overcome. It can only be done with a culture shift towards ubiquitous privacy, and that can probably only be achieved by all major wallets agreeing to enable privacy features by default. Not an easy hill to climb.
Personal Circumstances
For the sake of transparency, I also want to mention that I will be stepping back from NanoFusion for a while. This is simply a necessity of life. Our first child will be born in a few months. Once that happens, I will obviously have a lot going on and much less time available to work on these kinds of side projects. Between now and then, I need to focus on other projects which have more potential to generate some income for my little family. I'm a dad now(!), and my family comes first.
I'm very glad to have (hopefully) contributed some useful groundwork for the process of bringing privacy to Nano. This project also gave me the chance to learn some new technologies at a much deeper level, I'm grateful that too. Neverthless, for the foreseeable future, I'll be stepping back. I don't make that decision lightly. I put a lot of blood, sweat and tears into bringing NanoFusion this far, so I definitely hope it doesn't just fall by the wayside. I hope others will pick it up and run with it in my absence.
Call to Action
Want to make NanoFusion happen? Here's what we really need next:
  1. Wallet Developers - we need you to speak up. Tell us, what would an ideal NanoFusion API look like? How can we make it as easy as possible for you to integrate NanoFusion into your wallet app? What programming language do you want to use to consume that API? What I would love to see is several wallet developers collaborating together to create a document describing their ideal API. That will make it much easier for potential developers to pick it up and start implementing it.
  2. Javascript developers - are any of you interested in stepping up and finishing off the last bits of the reference implementation for NanoFusion?
As always, details of the project are available at http://nanofusion.casa (including demo videos, technical whitepaper and the link to the GitHub repo).
God bless everyone, thank you to all those who have followed along and offered so much encouragement for this project.
submitted by fatalglory to nanocurrency [link] [comments]

switch: all save data erased?

Has anyone else had the game (whether on Switch or a different platform) just up and delete all of their save data? I was trying to do a sidequest perfectly (the hostages one in basin keep) and using 'return to title' to reload from a save, but after one of the returns to the title screen, the 'continue' option was gone, and there were no saves (neither manual nor auto) in the 'load game' menu.
I had been making manual saves fairly regularly, and for each one I made a new save file, so I had somewhere around 35 manual saves that all vanished along with the autosave. I already looked at Nintendo's auto save backup thing, but it seems to have already overwritten the cloud save with the new lack of any save data, and as far as I can tell it only holds the most recent version of the save data uploaded to it (y'know, just like a backup should work >_>). And yes, I did try turning off auto-backups, getting a new version on my local save, then restoring to the cloud backup, which is how I verified (to the best of my ability, at least) that the cloud version wasn't any good.
My questions:
submitted by sea-sparks to CrossCode [link] [comments]

MAME 0.222

MAME 0.222

MAME 0.222, the product of our May/June development cycle, is ready today, and it’s a very exciting release. There are lots of bug fixes, including some long-standing issues with classics like Bosconian and Gaplus, and missing pan/zoom effects in games on Seta hardware. Two more Nintendo LCD games are supported: the Panorama Screen version of Popeye, and the two-player Donkey Kong 3 Micro Vs. System. New versions of supported games include a review copy of DonPachi that allows the game to be paused for photography, and a version of the adult Qix game Gals Panic for the Taiwanese market.
Other advancements on the arcade side include audio circuitry emulation for 280-ZZZAP, and protection microcontroller emulation for Kick and Run and Captain Silver.
The GRiD Compass series were possibly the first rugged computers in the clamshell form factor, possibly best known for their use on NASA space shuttle missions in the 1980s. The initial model, the Compass 1101, is now usable in MAME. There are lots of improvements to the Tandy Color Computer drivers in this release, with better cartridge support being a theme. Acorn BBC series drivers now support Solidisk file system ROMs. Writing to IMD floppy images (popular for CP/M computers) is now supported, and a critical bug affecting writes to HFE disk images has been fixed. Software list additions include a collection of CDs for the SGI MIPS workstations.
There are several updates to Apple II emulation this month, including support for several accelerators, a new IWM floppy controller core, and support for using two memory cards simultaneously on the CFFA2. As usual, we’ve added the latest original software dumps and clean cracks to the software lists, including lots of educational titles.
Finally, the memory system has been optimised, yielding performance improvements in all emulated systems, you no longer need to avoid non-ASCII characters in paths when using the chdman tool, and jedutil supports more devices.
There were too many HyperScan RFID cards added to the software list to itemise them all here. You can read about all the updates in the whatsnew.txt file, or get the source and 64-bit Windows binary packages from the download page.

MAME Testers Bugs Fixed

New working machines

New working clones

Machines promoted to working

Clones promoted to working

New machines marked as NOT_WORKING

New clones marked as NOT_WORKING

New working software list additions

Software list items promoted to working

New NOT_WORKING software list additions

submitted by cuavas to MAME [link] [comments]

[x86] Sharing very early build of new 80186 PC emulator, looking for input

EDIT 2020-07-12: Updated link with latest version with many improvements, and updated GitHub link. I renamed the program.
This is an almost total rewrite of an old emulator of mine. It's in a usable state, but it's still got some bugs and is missing a lot of features that I plan to add. For example, most BIOSes break on my 8259 PIC emulation. A lot of work left to do.
I wanted to share it here as is because I'm looking for input on usability as well as opinions on the source code in general, if anybody is interested in giving it a shot. Either if you like it so far, and/or have some constructive criticism.
Here is the GitHub: https://github.com/mikechambers84/XTulator
And here is a pre-built 32-bit Windows binary, along with the ROM set and a small hard disk image that includes some ancient abandonware for testing purposes.
https://gofile.io/d/8wrNHA
You can boot the included disk image with the command XTulator -hd0 hd0.img
Use XTulator -h to see all of the available options. One cool feature that I have fun with is the TCP modem emulator. You can use it to connect to telnet BBSes using old school DOS terminal software, which sees it as if it were connected to a serial modem. The code for that module is a disaster that needs to be cleaned up, though...
EDIT 2020-07-12: There's working NE2000 ethernet emulation now. I adapted the module from Bochs. You'll need Npcap installed to use it. Use XTulator -h to see command line options for using the network.
The highest priority bugfix is the 8259 PIC code, because I want to see it booting other BIOSes. Next up is getting the OPL2 code to sound reasonable. I am now using Nuked OPL, though there is a volume issue with some channels in some games. Not sure why yet.
My Sound Blaster code is working pretty well, but a few games glitch out. I'll be working on that. I'm also going to be fixing a few small remaining issues with EGA/VGA soon, including some video timing inaccuracies. (Hblank, vsync etc)
I also still need to find the best cross-platform method of providing a file open dialog for changing floppy images on the fly.
Very long term goals are 286, then 386+ support including protected mode. I'd love to see it booting Linux or more modern versions of Windows than 3.0 one day. I suppose I'll have to rename it then. :)
submitted by UselessSoftware to EmuDev [link] [comments]

Imagining a Cities:Skylines 2

So how’s your quarantine going? I’ve been playing a fair amount of C:S lately and thought I might speculate on what could be improved in Cities: Skylines 2. Besides, it’s not like I have anything better to do.
What C:S gets right and wrong
Besides great modability and post-release support, C:S combines an agent based economy with a sense of scale. It also has the kind of road design tools that SC4 veterans would have killed for. District based city planning for things like universities was one of the best innovations in the genre in years, and the introduction of industry supply chains, while clunky and tacked on, brought much needed depth to the game.
C:S suffers most notably from a lack of revisit rate to previously constructed things. Build a power plant: forget about it. Build a port: forget about it. Build a downtown: forget about it. The player isn’t incentivized to revisit old parts of the city to upgrade and improve them. The district system for universities and industry was a fantastic innovation that demonstrated how to do this concept well, and consequently they are some of the most fun and engaging parts of the game.
The biggest criticism of C:S, despite its powerful design tools, is that it feels like a city painter. The systems feel rich at first, but become very formulaic after a few hours. There are no hard trade-offs. Providing every inch of your city with maximum services will not bankrupt you, nor will an economy of nothing but the rich and well-educated collapse from a lack of unskilled labor. In the end, every city dies of boredom once the player exhausts the game’s relatively shallow well of novelty.
The biggest areas for Improvement
submitted by naive_grandeur to CitiesSkylines [link] [comments]

Microservices: Service-to-service communication

The following excerpt about microservice communication is from the new Microsoft eBook, Architecting Cloud-Native .NET Apps for Azure. The book is freely available for online reading and in a downloadable .PDF format at https://docs.microsoft.com/en-us/dotnet/architecture/cloud-native/

Microservice Guidance
When constructing a cloud-native application, you'll want to be sensitive to how back-end services communicate with each other. Ideally, the less inter-service communication, the better. However, avoidance isn't always possible as back-end services often rely on one another to complete an operation.
There are several widely accepted approaches to implementing cross-service communication. The type of communication interaction will often determine the best approach.
Consider the following interaction types:
Microservice systems typically use a combination of these interaction types when executing operations that require cross-service interaction. Let's take a close look at each and how you might implement them.

Queries

Many times, one microservice might need to query another, requiring an immediate response to complete an operation. A shopping basket microservice may need product information and a price to add an item to its basket. There are a number of approaches for implementing query operations.

Request/Response Messaging

One option for implementing this scenario is for the calling back-end microservice to make direct HTTP requests to the microservices it needs to query, shown in Figure 4-8.

Figure 4-8. Direct HTTP communication
While direct HTTP calls between microservices are relatively simple to implement, care should be taken to minimize this practice. To start, these calls are always synchronous and will block the operation until a result is returned or the request times outs. What were once self-contained, independent services, able to evolve independently and deploy frequently, now become coupled to each other. As coupling among microservices increase, their architectural benefits diminish.
Executing an infrequent request that makes a single direct HTTP call to another microservice might be acceptable for some systems. However, high-volume calls that invoke direct HTTP calls to multiple microservices aren't advisable. They can increase latency and negatively impact the performance, scalability, and availability of your system. Even worse, a long series of direct HTTP communication can lead to deep and complex chains of synchronous microservices calls, shown in Figure 4-9:

Figure 4-9. Chaining HTTP queries
You can certainly imagine the risk in the design shown in the previous image. What happens if Step #3 fails? Or Step #8 fails? How do you recover? What if Step #6 is slow because the underlying service is busy? How do you continue? Even if all works correctly, think of the latency this call would incur, which is the sum of the latency of each step.
The large degree of coupling in the previous image suggests the services weren't optimally modeled. It would behoove the team to revisit their design.

Materialized View pattern

A popular option for removing microservice coupling is the Materialized View pattern. With this pattern, a microservice stores its own local, denormalized copy of data that's owned by other services. Instead of the Shopping Basket microservice querying the Product Catalog and Pricing microservices, it maintains its own local copy of that data. This pattern eliminates unnecessary coupling and improves reliability and response time. The entire operation executes inside a single process. We explore this pattern and other data concerns in Chapter 5.

Service Aggregator Pattern

Another option for eliminating microservice-to-microservice coupling is an Aggregator microservice, shown in purple in Figure 4-10.

Figure 4-10. Aggregator microservice
The pattern isolates an operation that makes calls to multiple back-end microservices, centralizing its logic into a specialized microservice. The purple checkout aggregator microservice in the previous figure orchestrates the workflow for the Checkout operation. It includes calls to several back-end microservices in a sequenced order. Data from the workflow is aggregated and returned to the caller. While it still implements direct HTTP calls, the aggregator microservice reduces direct dependencies among back-end microservices.

Request/Reply Pattern

Another approach for decoupling synchronous HTTP messages is a Request-Reply Pattern, which uses queuing communication. Communication using a queue is always a one-way channel, with a producer sending the message and consumer receiving it. With this pattern, both a request queue and response queue are implemented, shown in Figure 4-11.

Figure 4-11. Request-reply pattern
Here, the message producer creates a query-based message that contains a unique correlation ID and places it into a request queue. The consuming service dequeues the messages, processes it and places the response into the response queue with the same correlation ID. The producer service dequeues the message, matches it with the correlation ID and continues processing. We cover queues in detail in the next section.

Commands

Another type of communication interaction is a command. A microservice may need another microservice to perform an action. The Ordering microservice may need the Shipping microservice to create a shipment for an approved order. In Figure 4-12, one microservice, called a Producer, sends a message to another microservice, the Consumer, commanding it to do something.

Figure 4-12. Command interaction with a queue
Most often, the Producer doesn't require a response and can fire-and-forget the message. If a reply is needed, the Consumer sends a separate message back to Producer on another channel. A command message is best sent asynchronously with a message queue. supported by a lightweight message broker. In the previous diagram, note how a queue separates and decouples both services.
A message queue is an intermediary construct through which a producer and consumer pass a message. Queues implement an asynchronous, point-to-point messaging pattern. The Producer knows where a command needs to be sent and routes appropriately. The queue guarantees that a message is processed by exactly one of the consumer instances that are reading from the channel. In this scenario, either the producer or consumer service can scale out without affecting the other. As well, technologies can be disparate on each side, meaning that we might have a Java microservice calling a Golang microservice.
In chapter 1, we talked about backing services. Backing services are ancillary resources upon which cloud-native systems depend. Message queues are backing services. The Azure cloud supports two types of message queues that your cloud-native systems can consume to implement command messaging: Azure Storage Queues and Azure Service Bus Queues.

Azure Storage Queues

Azure storage queues offer a simple queueing infrastructure that is fast, affordable, and backed by Azure storage accounts.
Azure Storage Queues feature a REST-based queuing mechanism with reliable and persistent messaging. They provide a minimal feature set, but are inexpensive and store millions of messages. Their capacity ranges up to 500 TB. A single message can be up to 64 KB in size.
You can access messages from anywhere in the world via authenticated calls using HTTP or HTTPS. Storage queues can scale out to large numbers of concurrent clients to handle traffic spikes.
That said, there are limitations with the service:
Figure 4-13 shows the hierarchy of an Azure Storage Queue.

Figure 4-13. Storage queue hierarchy
In the previous figure, note how storage queues store their messages in the underlying Azure Storage account.
For developers, Microsoft provides several client and server-side libraries for Storage queue processing. Most major platforms are supported including .NET, Java, JavaScript, Ruby, Python, and Go. Developers should never communicate directly with these libraries. Doing so will tightly couple your microservice code to the Azure Storage Queue service. It's a better practice to insulate the implementation details of the API. Introduce an intermediation layer, or intermediate API, that exposes generic operations and encapsulates the concrete library. This loose coupling enables you to swap out one queuing service for another without having to make changes to the mainline service code.
Azure Storage queues are an economical option to implement command messaging in your cloud-native applications. Especially when a queue size will exceed 80 GB, or a simple feature set is acceptable. You only pay for the storage of the messages; there are no fixed hourly charges.

Azure Service Bus Queues

For more complex messaging requirements, consider Azure Service Bus queues.
Sitting atop a robust message infrastructure, Azure Service Bus supports a brokered messaging model. Messages are reliably stored in a broker (the queue) until received by the consumer. The queue guarantees First-In/First-Out (FIFO) message delivery, respecting the order in which messages were added to the queue.
The size of a message can be much larger, up to 256 KB. Messages are persisted in the queue for an unlimited period of time. Service Bus supports not only HTTP-based calls, but also provides full support for the AMQP protocol. AMQP is an open-standard across vendors that supports a binary protocol and higher degrees of reliability.
Service Bus provides a rich set of features, including transaction support and a duplicate detection feature. The queue guarantees "at most once delivery" per message. It automatically discards a message that has already been sent. If a producer is in doubt, it can resend the same message, and Service Bus guarantees that only one copy will be processed. Duplicate detection frees you from having to build additional infrastructure plumbing.
Two more enterprise features are partitioning and sessions. A conventional Service Bus queue is handled by a single message broker and stored in a single message store. But, Service Bus Partitioning spreads the queue across multiple message brokers and message stores. The overall throughput is no longer limited by the performance of a single message broker or messaging store. A temporary outage of a messaging store doesn't render a partitioned queue unavailable.
Service Bus Sessions provide a way to group-related messages. Imagine a workflow scenario where messages must be processed together and the operation completed at the end. To take advantage, sessions must be explicitly enabled for the queue and each related messaged must contain the same session ID.
However, there are some important caveats: Service Bus queues size is limited to 80 GB, which is much smaller than what's available from store queues. Additionally, Service Bus queues incur a base cost and charge per operation.
Figure 4-14 outlines the high-level architecture of a Service Bus queue.

Figure 4-14. Service Bus queue
In the previous figure, note the point-to-point relationship. Two instances of the same provider are enqueuing messages into a single Service Bus queue. Each message is consumed by only one of three consumer instances on the right. Next, we discuss how to implement messaging where different consumers may all be interested the same message.

Events

Message queuing is an effective way to implement communication where a producer can asynchronously send a consumer a message. However, what happens when many different consumers are interested in the same message? A dedicated message queue for each consumer wouldn't scale well and would become difficult to manage.
To address this scenario, we move to the third type of message interaction, the event. One microservice announces that an action had occurred. Other microservices, if interested, react to the action, or event.
Eventing is a two-step process. For a given state change, a microservice publishes an event to a message broker, making it available to any other interested microservice. The interested microservice is notified by subscribing to the event in the message broker. You use the Publish/Subscribe pattern to implement event-based communication.
Figure 4-15 shows a shopping basket microservice publishing an event with two other microservices subscribing to it.

Figure 4-15. Event-Driven messaging
Note the event bus component that sits in the middle of the communication channel. It's a custom class that encapsulates the message broker and decouples it from the underlying application. The ordering and inventory microservices independently operate the event with no knowledge of each other, nor the shopping basket microservice. When the registered event is published to the event bus, they act upon it.
With eventing, we move from queuing technology to topics. A topic is similar to a queue, but supports a one-to-many messaging pattern. One microservice publishes a message. Multiple subscribing microservices can choose to receive and act upon that message. Figure 4-16 shows a topic architecture.

Figure 4-16. Topic architecture
In the previous figure, publishers send messages to the topic. At the end, subscribers receive messages from subscriptions. In the middle, the topic forwards messages to subscriptions based on a set of rules, shown in dark blue boxes. Rules act as a filter that forward specific messages to a subscription. Here, a "GetPrice" event would be sent to the price and logging Subscriptions as the logging subscription has chosen to receive all messages. A "GetInformation" event would be sent to the information and logging subscriptions.
The Azure cloud supports two different topic services: Azure Service Bus Topics and Azure EventGrid.

Azure Service Bus Topics

Sitting on top of the same robust brokered message model of Azure Service Bus queues are Azure Service Bus Topics. A topic can receive messages from multiple independent publishers and send messages to up to 2,000 subscribers. Subscriptions can be dynamically added or removed at runtime without stopping the system or recreating the topic.
Many advanced features from Azure Service Bus queues are also available for topics, including Duplicate Detection and Transaction support. By default, Service Bus topics are handled by a single message broker and stored in a single message store. But, Service Bus Partitioning scales a topic by spreading it across many message brokers and message stores.
Scheduled Message Delivery tags a message with a specific time for processing. The message won't appear in the topic before that time. Message Deferral enables you to defer a retrieval of a message to a later time. Both are commonly used in workflow processing scenarios where operations are processed in a particular order. You can postpone processing of received messages until prior work has been completed.
Service Bus topics are a robust and proven technology for enabling publish/subscribe communication in your cloud-native systems.

Azure Event Grid

While Azure Service Bus is a battle-tested messaging broker with a full set of enterprise features, Azure Event Grid is the new kid on the block.
At first glance, Event Grid may look like just another topic-based messaging system. However, it's different in many ways. Focused on event-driven workloads, it enables real-time event processing, deep Azure integration, and an open-platform - all on serverless infrastructure. It's designed for contemporary cloud-native and serverless applications
As a centralized eventing backplane, or pipe, Event Grid reacts to events inside Azure resources and from your own services.
Event notifications are published to an Event Grid Topic, which, in turn, routes each event to a subscription. Subscribers map to subscriptions and consume the events. Like Service Bus, Event Grid supports a filtered subscriber model where a subscription sets rule for the events it wishes to receive. Event Grid provides fast throughput with a guarantee of 10 million events per second enabling near real-time delivery - far more than what Azure Service Bus can generate.
A sweet spot for Event Grid is its deep integration into the fabric of Azure infrastructure. An Azure resource, such as Cosmos DB, can publish built-in events directly to other interested Azure resources - without the need for custom code. Event Grid can publish events from an Azure Subscription, Resource Group, or Service, giving developers fine-grained control over the lifecycle of cloud resources. However, Event Grid isn't limited to Azure. It's an open platform that can consume custom HTTP events published from applications or third-party services and route events to external subscribers.
When publishing and subscribing to native events from Azure resources, no coding is required. With simple configuration, you can integrate events from one Azure resource to another leveraging built-in plumbing for Topics and Subscriptions. Figure 4-17 shows the anatomy of Event Grid.

Figure 4-17. Event Grid anatomy
A major difference between EventGrid and Service Bus is the underlying message exchange pattern.
Service Bus implements an older style pull model in which the downstream subscriber actively polls the topic subscription for new messages. On the upside, this approach gives the subscriber full control of the pace at which it processes messages. It controls when and how many messages to process at any given time. Unread messages remain in the subscription until processed. A significant shortcoming is the latency between the time the event is generated and the polling operation that pulls that message to the subscriber for processing. Also, the overhead of constant polling for the next event consumes resources and money.
EventGrid, however, is different. It implements a push model in which events are sent to the EventHandlers as received, giving near real-time event delivery. It also reduces cost as the service is triggered only when it's needed to consume an event – not continually as with polling. That said, an event handler must handle the incoming load and provide throttling mechanisms to protect itself from becoming overwhelmed. Many Azure services that consume these events, such as Azure Functions and Logic Apps provide automatic autoscaling capabilities to handle increased loads.
Event Grid is a fully managed serverless cloud service. It dynamically scales based on your traffic and charges you only for your actual usage, not pre-purchased capacity. The first 100,000 operations per month are free – operations being defined as event ingress (incoming event notifications), subscription delivery attempts, management calls, and filtering by subject. With 99.99% availability, EventGrid guarantees the delivery of an event within a 24-hour period, with built-in retry functionality for unsuccessful delivery. Undelivered messages can be moved to a "dead-letter" queue for resolution. Unlike Azure Service Bus, Event Grid is tuned for fast performance and doesn't support features like ordered messaging, transactions, and sessions.

Streaming messages in the Azure cloud

Azure Service Bus and Event Grid provide great support for applications that expose single, discrete events like a new document has been inserted into a Cosmos DB. But, what if your cloud-native system needs to process a stream of related events? Event streams are more complex. They're typically time-ordered, interrelated, and must be processed as a group.
Azure Event Hub is a data streaming platform and event ingestion service that collects, transforms, and stores events. It's fine-tuned to capture streaming data, such as continuous event notifications emitted from a telemetry context. The service is highly scalable and can store and process millions of events per second. Shown in Figure 4-18, it's often a front door for an event pipeline, decoupling ingest stream from event consumption.

Figure 4-18. Azure Event Hub
Event Hub supports low latency and configurable time retention. Unlike queues and topics, Event Hubs keep event data after it's been read by a consumer. This feature enables other data analytic services, both internal and external, to replay the data for further analysis. Events stored in event hub are only deleted upon expiration of the retention period, which is one day by default, but configurable.
Event Hub supports common event publishing protocols including HTTPS and AMQP. It also supports Kafka 1.0. Existing Kafka applications can communicate with Event Hub using the Kafka protocol providing an alternative to managing large Kafka clusters. Many open-source cloud-native systems embrace Kafka.
Event Hubs implements message streaming through a partitioned consumer model in which each consumer only reads a specific subset, or partition, of the message stream. This pattern enables tremendous horizontal scale for event processing and provides other stream-focused features that are unavailable in queues and topics. A partition is an ordered sequence of events that is held in an event hub. As newer events arrive, they're added to the end of this sequence. Figure 4-19 shows partitioning in an Event Hub.

Figure 4-19. Event Hub partitioning
Instead of reading from the same resource, each consumer group reads across a subset, or partition, of the message stream.
For cloud-native applications that must stream large numbers of events, Azure Event Hub can be a robust and affordable solution.

About the Author:
Rob Vettor is a Principal Cloud-Native Architect for the Microservice Enterprise Service Group. Reach out to Rob at [[email protected]](mailto:[email protected]) or https://thinkingincloudnative.com/weclome-to-cloud-native/
submitted by robvettor to microservices [link] [comments]

Kaput v1.0.0 - Now with more chill!

Kaput v1.0.0 - Now with more chill!

https://preview.redd.it/n4ad3y6kzva51.png?width=1280&format=png&auto=webp&s=3b73f824f8c467013a11e0e4adba0e8f251f1a88

Version 1.0.0 of Kaput-CLI has just been released to NPM.

Here are some of the things I've added in this version:
  • Torrent indexer searching kindly provided by chill.institute. You can now search all major indexers and add torrents to your Put account directly from the terminal!
  • Support for using multiple accounts.
  • Pure JSON output for some commands.
  • Option to list all files using the --all flag.
  • Added filters from the Put API. For example, you can choose to list only audio files.
  • Added debug which outputs the current state of the config file and where it is located on the disk.
  • You can now use environment variables to authenticate.
  • Other bug fixes and improvements.

Installation
  • NPM: npm install -g kaput-cli
  • As before, binaries for most platforms (Linux, Windows, MacOS) are also available on GitHub These do not require Node to be installed.

A lot of these changes were added because of people who reached out about them. If you'd like to see something else added, let me know! GitHub is the best place to make a request.
Thanks for the support, let me know if I've broken anything :)
submitted by dccfoux to putdotio [link] [comments]

Using LLVM with VSCode on Windows

Greetings!
I decided to set up VSCode to be able to code in C++ and build my programs using LLVM. So I downloaded official binaries of LLVM 10.0 and installed it on my Windows system, but unfortunately there is no guide on how to make VSCode use LLVM to build projects. Official tutorials suggest using VS C++ compiler or GCC with MinGWx64 and no one seems to be using LLVM on windows for some reason.
I don't want using VS C++ compiler because it will consume too much of my disk space which I don't want to trade and I don't want GCC on MinGW, well, because of MinGW and all the workaround to install it and setup. LLVM seemed to be the easiest option since it has official installer and platform support.
What is the easiest way to setup VSCode for building projects with LLVM on Windows? Or is there a reason to not even try doing so - that'd explain why no one writes guides about that! If it's not recommended to try LLVM for Windows, then what's going to be the best option otherwise? I just want to compile my projects with all the default configurations, I don't care about optimizations and etc. since the projects are just me studying algorithms with C++.
submitted by emissaryo to vscode [link] [comments]

List of New Supported Games and FAQ.

Hey guys! Here is a list of all the new supported games, you can download the Nucleus Co-Op scripts from the app now, the games listed here that are clickable link you to a guide but all are supported. You can also see all available scripts from the app now by pressing the view all option.
10 Miles to Safety
20XX
100% Orange Juice
200% Mixed Juice!
Abyssal Zone
Acceleration of SUGURI 2
A Hat in Time
Air Missions: HIND
Alien Breed Impact
Alien Breed 2: Assault
Alien Breed 3: Descent
Aliens Colonial Marines
Aliens vs Predator
Alien Swarm: Reactive Drop
Aragami: Shadow Edition
ARK: Survival Evolved
Ashen (steam version only)
Astroneer
Attack on Titan 2
ATV Drift & Tricks
Barony
Binary Domain
BioShock 2
Bit Dungeon III
Blades of Time
Bladestorm: Nightmare
Blood and Bacon
Bob Was Hungry
Borderlands
Borderlands 2
Borderlands: The Pre-Sequel
Borderlands GOTY Enhanced
Borderlands 3
Broomstick League
Bulletstorm: Full Clip Edition
Bunch of Heroes
CastleMiner Z
Clandestine
Cladun Returns: This is Segoku
Chivalry: Medieval Warfare
Citadel: Forged With Fire
Code of Princess
Conan Exiles (16 june 2020 update added Funcom Live Services and now the game is online only effectively breaking the splitscreen script. You need to downgrade to the previous version.)
Contagion
Contra: Rogue Corps
Counter-Strike: Source
Cube World
Cyberdimension Neptunia: 4 Goddesses Online
Daemon X Machina
Damnation
Dark Souls: Prepare to Die Edition
Day of Defeat: Source
Day of Infamy
Deadfall Adventures
Dead Island
Dead Island: DE
Dead Island Riptide: DE
Dead Rising 2
Dead Rising 2: Off the Record
Dead Rising 3
Dead Rising 4
Deathtrap
Debris
Deep Rock Galactic
Desolate
Dinosaur Hunt
Divinity: Dragon Commander
Divinity: Original Sin Enhanced Edition
Divinity: Original Sin 2
Don't Starve Together
Door Kickers
Dragon Ball Xenoverse
Dragon Ball: Xenoverse 2
Dragon Marked for Death
Dragon Quest Builders 2
Dungeon of the Endless
Dungeons 3
Dungeon Siege III
Dying Light
Dystopia
Earth Defense Force 4.1
Earth Defense Force 5
Earth Defense Force: Insect Armageddon
Earth Defense Force: Iron Rain
Earthfall
Enemy Front
F1 2012
Fade to Silence
Factorio
Fallout 76
F.E.A.R. 3
Final Exam
Feel The Snow
Fight The Dragon
Fistful of Frags
Forge Quest
Fortified
Front Mission Evolved
Full Mojo Rampage
Garry's Mod
Gas Guzzlers Extreme
Generation Zero
GOCCO OF WAR
God Eater Resurrection
God Eater 2 - Rage Burst
God Eater 3
God Mode
Grim Dawn
Ground Branch
GTFO
Guns n Zombies
Half-Life Deathmatch: Source
Half-Life 2: Deathmatch
Half-Minute Hero: The Second
Halo Custom Edition
Halo 2 LAN
Halo 2: Project Cartographer
Halo Online ElDewrito
Halo: The Master Chief Collection
Halo Wars: Definitive Edition
Hammerwatch
Hero Siege
Hunted: The Demon’s Forge
Human: Fall Flat
I am Weapon: Revival
Insurgency
Iron Brigade
It came from space, and ate our brains
KATANA KAMI: A Way of the Samurai Story
Killing Floor
Killing Floor 2
Killsquad
Kill to Collect
Lead and Gold: Gangs of the Wild West
Left 4 Dead 2
LEGO Worlds
Livelock
Lord of the Rings War in the North
Magicite
Mean Greens - Plastic Warfare
Mighty No. 9
Minecraft Java Edition
Monday Night Combat
Morphies Law
Mothergunship
NanoWars
Necropolis
Need For Speed Most Wanted 2005
Nioh: Complete Edition
Niffelheim
No Man's Sky
No More Room in Hell
Outbreak
Outbreak: TNN
Outland
Outward
Orcs Must Die! 2
ORION: Prelude
OVERKILL's The Walking Dead
Pacify
PAYDAY: The Heist
PAYDAY 2
Pirates, Vikings, and Knights II
PixARK
Portal Knights
Prevent The Fall
Primal Carnage: Extinction
Pure
Raft
Rage
Remnant: From the Ashes
Resident Evil 5
Resident Evil 6
Resident Evil Revelations
Re-Volt (RVGL)
RimWorld
Risk of Rain 2
Roguelands
Ryse: Son of Rome
Sacred 3
Saints Row The Third
Saints Row IV
Saints Row: Gat out of Hell
Sanctum
Sanctum 2
Scourge Outbreak
Secrets of Grindea
Senran Kagura: Shinovi Versus
Senran Kagura: Estival Versus
Senran Kagura: Peach Beach Splash
Serious Sam 2
Seven Days to Die
Sir, You Are Being Hunted
SkyDrift
Sniper Elite 3
Space Engineers
Space Hulk: Deathwing - Enhanced Edition
Spec Ops: The Line
Spintires
Starbound
Stardew Valley
Star Wars: Battlefront 2 (Classic, 2005)
Strange Brigade
Strength of the Sword: ULTIMATE
Styx: Shards of Darkness
Super Mario 64
Survivalist
Sven Coop
Sword Art Online Re: Hollow Fragment
Sword Art Online: Lost Song
Sword Art Online: Hollow Realization Deluxe Edition
Synergy
SYNTHETIK: Arena
SYNTHETIK: Legion Rising
Takedown: Red Sabre
Team Fortress 2
Teenage Mutant Ninja Turtles: Mutants in Manhattan
Teenage Mutant Ninja Turtles: Out of the Shadows
Terraria
TerraTech
The Blackout Club
The Darkness 2
The Forest
The Haunted: Hells Reach
theHunter: Call of the Wild
The Incredible Adventures of Van Helsing
The Incredible Adventures of Van Helsing II
The Incredible Adventures of Van Helsing III
The Incredible Adventures of Van Helsing Final Cut
The Mean Greens - Plastic Warfare
The Simple Apocalypse
The Watchers
Tokyo Ghoul:re Call to Exist
Tom Clancy's Rainbow Six: Vegas 2
Tomb Raider
Torchlight II
Toukiden: Kiwami
Toukiden 2
Unending Dusk
Unepic
Unloved
Unreal Tournament III
Umbrella Corps
Vagante
Warcraft III: The Frozen Throne
Warcraft III: Reign of Chaos
Warhammer 40,000: Space Marine
We Were Here Together
White Noise 2
World in Conflict: Complete Edition
Wreckfest
XCOM: Enemy Within
Zeno Clash II
Zombie Army Trilogy
Zombie Panic! Source

Frequently Asked Questions & Troubleshooting

(Under Construction, last updated: 06/06/20)
Q: What is Nucleus Co-Op?
A: https://www.youtube.com/watch?v=jbituCgu3Bc
Nucleus Co-Op is a free and open source tool for Windows that allows split-screen play on many games that do not initially support it. The app was originally created by Lucas Assis, Zerofox later took over and added a ton of new features and improvements to support a lot more games. Ilyaki later joined in and brought multiple keyboards/mice support and more great features to the table. The app is currently being developed and updated by these devs: Lucas Assis, Zerofox and Ilyaki.
R-mach too for making and supporting the website that hosts the Nucleus Co-Op scripts.
Also the further development of the app wouldn't have been possible without all the amazing contributions and hard work from the SplitScreen Dreams Discord members (which include the devs mentioned above) that made all the new Nucleus Co-Op scripts and continue to make new discoveries and scripts to support even more games, amon