How MySQL is able to scale to 200 Million QPS - MySQL Cluster

This is a guest post by Andrew Morgan, MySQL Principal Product Manager at Oracle.

The purpose of this post is to introduce MySQL Cluster - which is the in-memory, real-time, scalable, highly available version of MySQL. Before addressing the incredible claim in the title of 200 Million Queries Per Second it makes sense to go through an introduction of MySQL Cluster and its architecture in order to understand how it can be achieved.

Introduction to MySQL Cluster

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Stuff The Internet Says On Scalability For May 15th, 2015

Hey, it's HighScalability time:

Stand a top a volcano and survey the universe.  (By Shane Black & Judy Schmidt)

• 1 million: Airbnb's room inventory; 2 billion: Telegram messages sent daily; Two billion: photos shared daily on Facebook; 10,000: sensors in every Airbus wing
• Quotable Quotes:
  • Silicon Valley: “We’re about shaving yoctoseconds off latency for every layer in the stack,” he said. “If we rent from a public cloud, we’re using servers that are, by definition, generic and unpredictable.”
  • @liviutudor: Netflix: approx 250 Cassandra clusters over 7,000+ server instances #cloud
  • @GreylockVC: "More billion-dollar marketplaces will be created in the next five years than in the previous 20." - @simonrothman 
  • CDIXON: Exponential growth curves in the “feels gradual” phase are deceptive. There are many things happening today in technology that feel gradual and disappointing but will soon feel sudden and amazing.
  • @badnima: OH: "The gossip protocol has reached its scaling limits"
  • marcosdumay: People get pretty excited every time physicists talk about information. The bottom line is that information manipulation is just Math, viewed by a different angle.
  • Bill Janeway: There's only one way to hedge against uncertainty in venture capital...cash and control. Enough cash that when something goes wrong you can buy time to figure out what is and assess what you can do about it. 
  • zylo4747's coworker: Where's the step about preparing to have all your plans crushed and rushing shit out the door as fast as possible?
  • Martin Fowler: don't even consider microservices unless you have a system that's too complex to manage as a monolith. 
  • @postwait: Ingesting, querying, & visualizing data isn't a monitoring system. It isn't even sufficient plumbing for such a system. #srecon15europe
  • @techsummitpr: "Up to date weather conditions? It's not a marvel from Google, it's a marvel from the National Weather Service." @timoreilly #techsummitpr
  • @sovereignfund: Verified as legit: The top 25 hedge fund managers earn more than all kindergarten teachers in U.S. combined. 
  • Adrian Colyer: In their evaluation, the authors found that mixing MapReduce and memcached traffic in the same network extended memcached latency in the tail by 85x compared to an interference free network. 
  • @BenedictEvans: US ecommerce revenues 1999: $12bn 2013: $219bn
  • Gregory Hickok: the brain samples the world in rhythmic pulses, perhaps even discrete time chunks, much like the individual frames of a movie. From the brain’s perspective, experience is not continuous but quantized.
  • David Bollier: There is no master inventory of commons. They can arise whenever a community decides it wishes to manage a resource in a collective manner, with a special regard for equitable access, use and sustainability.


• What’s Next for Moore’s Law?: I predict that Intel's 10nm process technology will use Quantum Well FETs (QWFETs) with a 3D fin geometry, InGaAs for the NFET channel, and strained Germanium for the PFET channel, enabling lower voltage and more energy efficient transistors in 2016, and the rest of the industry will follow suit at the 7nm node.


• Don't read How to Build a Unicorn From Scratch – and Walk Away with Nothing if you are easily frightened. Years of work down the drain. **chills** To walk safely through the Valley: Focus on terms, not just valuation; Build a waterfall; Don’t do bad business deals just to get investment capital; Understand the motivations of others; Understand your own motivation.


• How do you build a real-time chat system? Scaling Secret: Real-time Chat. Goal was to handle 50,000 simultaneous conversations. Pusher was used to deliver messages. For a database Secret used Google App Engine’s High-Replication Datastore. Some nice details on the schema and other issues. Good thread on HN where the main point of contention is should an expensive service like Pusher be used to do something so simple? Usual arguments about wasting money vs displaying your hacker plumage. 


• Under the hood: Facebook’s cold storage system. A top to bottom reengineering to save power for infrequently accessed photos. Yes, that's cool. Each cold storage datacenter uses 1/6th the energy as a normal datacenter while storing hundreds of petabytes of data. Erasure coding is used to store data. Data is scanned every 30 days to recreate any lost data.  As capacity is added data is rebalanced to the new racks. No file system is used at all. 

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To see the Future of the Apple Watch Just Go to Disneyland

by AreteStock

Removing friction. That’s what the Apple Watch is good at.

Many think watches are a category flop because they don’t have that obvious killer app. Like hot sauce, maybe a watch isn’t something you eat all by itself, but it gives whatever you sprinkle it on a little extra flavor?

Walk into your hotel, the system recognizes you, your room number pops up on your watch, you walk directly to your room and unlock it with your watch.

Walk into an airport, your flight displays on your watch along with directions to your terminal. To get on the plane you just flash your watch. On landing, walk to your rental car and unlock it with your watch.

A notification arrives that it’s time to leave for your meeting, traffic is bad, best get an early start.

While shopping you check with your partner if you need milk by talking directly through your watch. In the future you’ll just know if you need milk, but we’re not there yet.

You can do all these things with a phone. Google Now, for example. What the easy accessibility of the watch does in these scenarios is remove friction. It makes it natural for a complex backend system to talk to you about things it learns from you and your environment. Hiding in a pocket or a purse, a phone is too inconvenient and too general purpose. Your watch becomes a small custom viewport on to a much larger more connected world.

After developing my own watch extension, using other extensions, and listening to a lot of discussion on the subject, it’s clear the form factor of a watch is very limiting and will always be limiting. You’ll never be able to do much UI-wise on a watch. Even the cleverest programmers can only do so much with so little screen real estate and low resource usage requirements. Instagram and Evernote simply aren’t the same on a watch.

But that’s OK. Every device has what it does well. It takes time for users and developers to explore a new device space.

What a watch does well is not so much enable new types of apps, but plug people into much larger and smarter systems. This is where the friction is removed.

Re-enchanting the World Disneyland Style

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Sponsored Post: Learninghouse, OpenDNS, MongoDB, Internap, Aerospike, SignalFx, InMemory.Net, Couchbase, VividCortex, MemSQL, Scalyr, AiScaler, AppDynamics, ManageEngine, Site24x7

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• The Cloud Platform team at OpenDNS is building a PaaS for our engineering teams to build and deliver their applications. This is a well rounded team covering software, systems, and network engineering and expect your code to cut across all layers, from the network to the application. Learn More


• At Scalyr, we're analyzing multi-gigabyte server logs in a fraction of a second. That requires serious innovation in every part of the technology stack, from frontend to backend. Help us push the envelope on low-latency browser applications, high-speed data processing, and reliable distributed systems. Help extract meaningful data from live servers and present it to users in meaningful ways. At Scalyr, you’ll learn new things, and invent a few of your own. Learn more and apply.


• UI Engineer– AppDynamics, founded in 2008 and lead by proven innovators, is looking for a passionate UI Engineer to design, architect, and develop our their user interface using the latest web and mobile technologies. Make the impossible possible and the hard easy. Apply here.


• Software Engineer - Infrastructure & Big Data – AppDynamics, leader in next generation solutions for managing modern, distributed, and extremely complex applications residing in both the cloud and the data center, is looking for a Software Engineers (All-Levels) to design and develop scalable software written in Java and MySQL for backend component of software that manages application architectures. Apply here.

Fun and Informative Events

• 90 Days. 1 Bootcamp. A whole new life. Interested in learning how to code? Concordia St. Paul's Coding Bootcamp is an intensive, fast-paced program where you learn to be a software developer. In this full-time, 12-week on-campus course, you will learn either .NET or Java and acquire the skills needed for entry-level developer positions. For more information, read the Guide to Coding Bootcamp or visit bootcamp.csp.edu.


• June 2nd – 4th, Santa Clara: Register for the largest NoSQL event of the year, Couchbase Connect 2015, and hear how innovative companies like Cisco, TurboTax, Joyent, PayPal, Nielsen and Ryanair are using our NoSQL technology to solve today’s toughest big data challenges. Register Today.


• The Art of Cyberwar: Security in the Age of Information. Cybercrime is an increasingly serious issue both in the United States and around the world; the estimated annual cost of global cybercrime has reached $100 billion with over 1.5 million victims per day affected by data breaches, DDOS attacks, and more. Learn about the current state of cybercrime and the cybersecurity professionals in charge with combatting it in The Art of Cyberwar: Security in the Age of Information, provided by Russell Sage Online, a division of The Sage Colleges.


• MongoDB World brings together over 2,000 developers, sysadmins, and DBAs in New York City on June 1-2 to get inspired, share ideas and get the latest insights on using MongoDB. Organizations like Salesforce, Bosch, the Knot, Chico’s, and more are taking advantage of MongoDB for a variety of ground-breaking use cases. Find out more at http://mongodbworld.com/ but hurry! Super Early Bird pricing ends on April 3.

Cool Products and Services

• Turn chaotic logs and metrics into actionable data. Scalyr replaces all your tools for monitoring and analyzing logs and system metrics. Imagine being able to pinpoint and resolve operations issues without juggling multiple tools and tabs. Get visibility into your production systems: log aggregation, server metrics, monitoring, intelligent alerting, dashboards, and more. Trusted by companies like Codecademy and InsideSales. Learn more and get started with an easy 2-minute setup. Or see how Scalyr is different if you're looking for a Splunk alternative or Loggly alternative.


• Instructions for implementing Redis functionality in Aerospike. Aerospike Director of Applications Engineering, Peter Milne, discusses how to obtain the semantic equivalent of Redis operations, on simple types, using Aerospike to improve scalability, reliability, and ease of use. Read more.


• SQL for Big Data: Price-performance Advantages of Bare Metal. When building your big data infrastructure, price-performance is a critical factor to evaluate. Data-intensive workloads with the capacity to rapidly scale to hundreds of servers can escalate costs beyond your expectations. The inevitable growth of the Internet of Things (IoT) and fast big data will only lead to larger datasets, and a high-performance infrastructure and database platform will be essential to extracting business value while keeping costs under control. Read more.


• SignalFx: just launched an advanced monitoring platform for modern applications that's already processing 10s of billions of data points per day. SignalFx lets you create custom analytics pipelines on metrics data collected from thousands or more sources to create meaningful aggregations--such as percentiles, moving averages and growth rates--within seconds of receiving data. Start a free 30-day trial!


• InMemory.Net provides a Dot Net native in memory database for analysing large amounts of data. It runs natively on .Net, and provides a native .Net, COM & ODBC apis for integration. It also has an easy to use language for importing data, and supports standard SQL for querying data. http://InMemory.Net


• VividCortex goes beyond monitoring and measures the system's work on your MySQL and PostgreSQL servers, providing unparalleled insight and query-level analysis. This unique approach ultimately enables your team to work more effectively, ship more often, and delight more customers.


• MemSQL provides a distributed in-memory database for high value data. It's designed to handle extreme data ingest and store the data for real-time, streaming and historical analysis using SQL. MemSQL also cost effectively supports both application and ad-hoc queries concurrently across all data. Start a free 30 day trial here: http://www.memsql.com/


• aiScaler, aiProtect, aiMobile Application Delivery Controller with integrated Dynamic Site Acceleration, Denial of Service Protection and Mobile Content Management. Also available on Amazon Web Services. Free instant trial, 2 hours of FREE deployment support, no sign-up required. http://aiscaler.com


• ManageEngine Applications Manager : Monitor physical, virtual and Cloud Applications.


• www.site24x7.com : Monitor End User Experience from a global monitoring network.

If any of these items interest you there's a full description of each sponsor below. Please click to read more...

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Designing for Scale - Three Principles and Three Practices from Tapad Engineering

This is a guest post by Toby Matejovsky, Director of Engineering at Tapad (@TapadEng).

Here at Tapad, scaling our technology strategically has been crucial to our immense growth. Over the last four years we’ve scaled our real-time bidding system to handle hundreds of thousands of queries per second. We’ve learned a number of lessons about scalability along that journey.

Here are a few concrete principles and practices we’ve distilled from those experiences:

• Principle 1: Design for Many
• Principle 2: Service-Oriented Architecture Beats Monolithic Application
• Principle 3: Monitor Everything
• Practice 1: Canary Deployments
• Practice 2: Distributed Clock
• Practice 3: Automate To Assist, Not To Control

Principle 1: Design for Many

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Stuff The Internet Says On Scalability For May 8th, 2015

Hey, it's HighScalability time:

Not spooky at all. A 1,000 robot self-organizing flash mob.

• 400 ppm: global CO2 concentration; 13.1 billion: distance in light-years of farthest galaxy
• Quotable Quotes:
  • Pied Piper: It’s built on a universal compression engine that stacks on any file, data, video or image no matter what size.
  • Bokardo: 1 hour of research saves 10 hours of development time
  • @12Knocksinna: Microsoft uses Cassandra open source tech to help manage the 500+ million events generated by Office 365 hourly (along with SQL and Azure)
  • @antirez: Redis had a lot of client libs ASAP. By reusing the Redis protocol, Disque is getting clients even faster, and 2700 Github stars in 9 days!
  • @blueben: AWS Glacier seems like a great DR option until you realize it costs $180,000 to retrieve your 100TB archive in an emergency.
  • Peter Diamandis: The best way to become a billionaire is to solve a billion-person problem.
  • Cordkillers: YouTube visits up 40% from last year
  • @acroll: "It's about economics not innovation, otherwise we'd all be flying Concorde instead of Jumbo Jets." @JulieMarieMeyer #StrataHadoop
  • @DLoesch: Start time delayed because cable systems are overloaded due to PPV buys. Insane. Don't snooze, don't lose! #MayPac
  • grauenwolf: This is where unit test fanboys piss me off. They claim that they can't use integration tests because they are too slow. I claim that they need integration tests to find their slow queries.
  • nuclearqtip: The open source world needs a standardized trust model for binary artifacts. 
  • Greg Ferro: SDN and SNA are about as similar Model T Ford & any modern car. For the record, no drives a Model T Ford to work everyday. Stop comparing SDN to SNA. Its pointless.
  • Urs Hölzle: Now the decade of work we put into NoSQL is available to everyone using GCP.  One way it shows that we've been working on this longer than anyone else: 99% read latency is 6ms vs ~300ms for other systems.
  • Swardley: Cloud is not about saving money - never was. It's about doing more stuff with exactly the same amount of money. That can cause a real headache in competition. 
  • Johns Hopkins: scientists have discovered that neurons are risk takers: They use minor "DNA surgeries" to toggle their activity levels all day, every day. 


• Tesla's Powerwall has already sold out. So will Tesla's next gigafactory be a terafactory or a petafactory?


• Something to keep in mind when hiring: 21% of [NFL] Hall of Fame players were selected in the 4th round or later.


• Move along, nothing to see here. Brett Slatkin: I wonder how long it will be before people realize that all of this server orchestration business is a waste of time? Ultimately, what you really want is to never think about systems like Borg that schedule processes to run on machines. That's the wrong level of abstraction. You want something like App Engine, vintage 2008 platform as a service, where you run a single command to deploy your system to production with zero configuration.


• Can any product withstand Aphyr's Jepsen partition torture test? Aeropspike, Elasticsearch, MongoDB, RabbitMQ, Riak, Cassandra, Kafka, NuoDB, Postgres, Redis, all had problems when stress tested under network partitions. Not surprising really, as Aphyr says, "Distributed systems design is really hard." That we find problems in popular well regarded products indicates that "We need formal theory, written proofs, computer verification, and experimental demonstration that our systems make the tradeoffs we think they make. As systems engineers, we continually struggle to erase the assumption of safety before that assumption causes data loss or downtime. We need to clearly document system behaviors so that users can make the right choices. We must understand our systems in order to explain them–and distributed systems are hard to understand." gmagnusson has a good sense of things: "I admire the work that Aphyr does - though at the end of the day, I need to build systems that work for the problem I'm trying to solve (and I have to choose from real things that are available). These technologies in general are trying to address really hard problems and design and architecture is the art of balancing tradeoffs. Nothing is going to be perfect. Yet."  

Don't miss all that the Internet has to say on Scalability, click below and become eventually consistent with all scalability knowledge (which means this post has many more items to read so please keep on reading)...

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Varnish Goes Upstack with Varnish Modules and Varnish Configuration Language

This is a guest post by Denis Brækhus and Espen Braastad, developers on the Varnish API Engine from Varnish Software. Varnish has long been used in discriminating backends, so it's interesting to see what they are up to.

Varnish Software has just released Varnish API Engine, a high performance HTTP API Gateway which handles authentication, authorization and throttling all built on top of Varnish Cache. The Varnish API Engine can easily extend your current set of APIs with a uniform access control layer that has built in caching abilities for high volume read operations, and it provides real-time metrics.

Varnish API Engine is built using well known components like memcached, SQLite and most importantly Varnish Cache. The management API is written in Python. A core part of the product is written as an application on top of Varnish using VCL (Varnish Configuration Language) and VMODs (Varnish Modules) for extended functionality.

We would like to use this as an opportunity to show how you can create your own flexible yet still high performance applications in VCL with the help of VMODs.

VMODs (Varnish Modules)

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Elements of Scale: Composing and Scaling Data Platforms

This is a guest repost of Ben Stopford's epic post on Elements of Scale: Composing and Scaling Data Platforms. A masterful tour through the evolutionary forces that shape how systems adapt to key challenges.

As software engineers we are inevitably affected by the tools we surround ourselves with. Languages, frameworks, even processes all act to shape the software we build.

Likewise databases, which have trodden a very specific path, inevitably affect the way we treat mutability and share state in our applications.

Over the last decade we’ve explored what the world might look like had we taken a different path. Small open source projects try out different ideas. These grow. They are composed with others. The platforms that result utilise suites of tools, with each component often leveraging some fundamental hardware or systemic efficiency. The result, platforms that solve problems too unwieldy or too specific to work within any single tool.

So today’s data platforms range greatly in complexity. From simple caching layers or polyglotic persistence right through to wholly integrated data pipelines. There are many paths. They go to many different places. In some of these places at least, nice things are found.

So the aim for this talk is to explain how and why some of these popular approaches work. We’ll do this by first considering the building blocks from which they are composed. These are the intuitions we’ll need to pull together the bigger stuff later on.

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Stuff The Internet Says On Scalability For May 1st, 2015

Hey, it's HighScalability time:

Got containers? Gorgeous shot of the CSCL Globe (by Walter Scriptunas II), world's largest container ship: 1,313ft long; 19,000 standard containers.

• $3000: Tesla's new 7kWh daily cycle battery.
• Quotable Quotes:
  • @mamund: "Turns out there is nothing about HTTP that I like" --  Douglas Crockford 
  • @PeterChch: Your little unimportant site might be hacked not for your data but for your aws resources. E.g. bitcoin mining.
  • @Joseph_DeSimone: I find it stunning that Google's annual R&D budget totaled $9.8 billion and the Budget for the National Science Foundation was $7.3 billion
  • @jedberg: The new EC2 container service adds the missing granularity to #ec2
  • Randy Shoup: “Every service at Google is either deprecated or not ready yet.”  -- Google engineering proverb
  • @mtnygard: Today the ratio of admins to servers in a well-behaved scalable web companies is about 1 to 10,000. @botchagalupe #craftconf
  • @joshk: Data: There Are Over 9x More Private IPOs Than Actual Tech IPOs 
  • @nwjsmith: “Systems are not algorithms. Systems are much more complex.“ #CraftConf @skamille
  • kk: “Because the center of the universe is wherever there is the least resistance to new ideas.”
  • John Allspaw: Stop thinking that you’re trying to solve a troubleshooting problem; you’re not. Instead of telling me about how your software will solve problems, show me that you’re trying to build a product that is going to join my team as an awesome team member, because I’m going to think about using/buying your service in the same way that I think about hiring.
  • @mpaluchowski: "Netflix is a #logging system that happens to play movies." #CraftConf
  • John Wilke:  Resiliency is more important than performance.
  • @peakscale: The server/cattle metaphor rubs me the wrong way... all the farmers I knew and worked for named and cared about their herd.
  • @aphyr: "We've managed to run 40 services in prod for three years without needing to introduce a consensus system" @skamille, #CraftConf
  • @ryantomlinson: “Spotify have been using DNS for service discovery for a long time” #CraftConf
  • @csanchez: Google "we start over 2 billion containers per week" containers, containers, containers! #qconlondon 
  • @tyler_treat: If you're using RabbitMQ, consider replacing it with Kafka. Higher throughput, better replication, replayability. Same goes for other MQs.
  • @tastapod: @botchagalupe telling #CraftConf how it is! “Yelp is spinning up 8 containers a second. This is the real sh*t, man!”
  • @mpaluchowski: "A static #alert threshold won't be any good next week. It must be calculated." #CraftConf
  • @mtnygard: #craftconf @randyshoup “Microservices are an answer to a scaling problem, not a business problem.”  So right.
  • @adrianco: @mtnygard @randyshoup speed of development is the business problem that leads to Microservices.
  • @b6n: the aws financials should be a wake-up call to anyone still thinking cloud isn't a game of raw scale
  • @mtnygard: The “edge” used to be top-of-rack. Then the hypervisor. Now it’s the container. That’s 100x the number of IPs. — @botchagalupe #craftconf
  • @idajantis: 'An escalator can never break; it can only become stairs' - nice one by @viktorklang at #CraftConf on Distributed Systems failing gracefully
  • @jessitron: "You should store your data in a real database and replicate it to Elasticsearch." @aphyr #CraftConf


• A telling difference between Google and Apple: Google Now becomes a more robust platform with 70 new partner apps. Apple takes an app-centric view of the world and Google not surprisingly takes a data centric view. With Google developers feed Google data for Google to display. With Apple developers feed Apple apps for users to consume. On Apple developers push their own brand and control functionality through bundled extensions, but Google will have the perspective to really let their deep learning prowess sing. So there's a real choice.


• How appropriate that game theory is applied to cyberwarfare. Mutually Assured Destruction isn't just for nukes. Pentagon Announces New Strategy for Cyberwarfare: “Deterrence is partially a function of perception,” the new strategy says. “It works by convincing a potential adversary that it will suffer unacceptable costs if it conducts an attack on the United States, and by decreasing the likelihood that a potential adversary’s attack will succeed.


• Reducing big data using ideas from quantum theory makes it easier to interpret. So maybe QM is nature's way of making sense of the BigData that is the Universe?


• Synergy is not always BS. Cheaper bandwidth or bust: How Google saved YouTube: YouTube was burning through $2 million a month in bandwidth costs before the acquisition. What few knew at the time was that Google was a pioneer in data center technology, which allowed it to dramatically lower the costs of running YouTube.


• In a winner take all market is the cost of customer acquisition pyrrhic? Uber Burning $750 Million in a Year.


• The cloud behind the cloud. Apple details how it rebuilt Siri on Mesos: Apple’s custom Mesos scheduler is called J.A.R.V.I.S.; Apple uses J.A.R.V.I.S. as its internal platform-as-a-service; Apple’s Mesos cluster spans thousands of nodes and runs about a hundred services; Siri’s Mesos backend represents its third generation, and a move away from “traditional” infrastructure.

Don't miss all that the Internet has to say on Scalability, click below and become eventually consistent with all scalability knowledge (which means this post has many more items to read so please keep on reading)...

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Paper: DNACloud: A Tool for Storing Big Data on DNA

"From the dawn of civilization until 2003, humankind generated five exabytes (1 exabytes = 1 billion gigabytes) of data. Now we produce five exabytes every two days and the pace is accelerating."

-- Eric Schmidt, Executive Chairman, Google, August 4, 2010. 

Where are we going to store the deluge of data everyone is warning us about? How about in a DNACloud that can store store 1 petabyte of information per gram of DNA?

Writing is a little slow. You have to convert your data file to a DNA description that is sent to a biotech company that will send you back a vile of synthetic DNA. Where do you store it? Your refrigerator.

Reading is a little slow too. The data can apparently be read with great accuracy, but to read it you have to sequence the DNA first, and that might take awhile.

The how of it is explained in DNACloud: A Tool for Storing Big Data on DNA (poster). Abstract:

The term Big Data is usually used to describe huge amount of data that is generated by humans from digital media such as cameras, internet, phones, sensors etc. By building advanced analytics on the top of big data, one can predict many things about the user such as behavior, interest etc. However before one can use the data, one has to address many issues for big data storage. Two main issues are the need of large storage devices and the cost associated with it. Synthetic DNA storage seems to be an appropriate solution to address these issues of the big data. Recently in 2013, Goldman and his collegues from European Bioinformatics Institute demonstrated the use of the DNA as storage medium with capacity of storing 1 peta byte of information on one gram of DNA and retrived the data successfully with low error rate [1]. This significant step shows a promise for synthetic DNA storage as a useful technology for the future data storage. Motivated by this, we have developed a software called DNACloud which makes it easy to store the data on the DNA. In this work, we present detailed description of the software.

 Related Articles

• On Optimal Family of Codes for DNA Storage
• Towards practical, high-capacity, low-maintenance information storage in synthesized DNA
• Information Storage in DNA