Jul
31
2018
--

The Istio service mesh hits version 1.0

Istio, the service mesh for microservices from Google, IBM, Lyft, Red Hat and many other players in the open-source community, launched version 1.0 of its tools today.

If you’re not into service meshes, that’s understandable. Few people are. But Istio is probably one of the most important new open-source projects out there right now. It sits at the intersection of a number of industry trends, like containers, microservices and serverless computing, and makes it easier for enterprises to embrace them. Istio now has more than 200 contributors and the code has seen more than 4,000 check-ins since the launch of  version 0.1.

Istio, at its core, handles the routing, load balancing, flow control and security needs of microservices. It sits on top of existing distributed applications and basically helps them talk to each other securely, while also providing logging, telemetry and the necessary policies that keep things under control (and secure). It also features support for canary releases, which allow developers to test updates with a few users before launching them to a wider audience, something that Google and other webscale companies have long done internally.

“In the area of microservices, things are moving so quickly,” Google product manager Jennifer Lin told me. “And with the success of Kubernetes and the abstraction around container orchestration, Istio was formed as an open-source project to really take the next step in terms of a substrate for microservice development as well as a path for VM-based workloads to move into more of a service management layer. So it’s really focused around the right level of abstractions for services and creating a consistent environment for managing that.”

Even before the 1.0 release, a number of companies already adopted Istio in production, including the likes of eBay and Auto Trader UK. Lin argues that this is a sign that Istio solves a problem that a lot of businesses are facing today as they adopt microservices. “A number of more sophisticated customers tried to build their own service management layer and while we hadn’t yet declared 1.0, we hard a number of customers — including a surprising number of large enterprise customer — say, ‘you know, even though you’re not 1.0, I’m very comfortable putting this in production because what I’m comparing it to is much more raw.’”

IBM Fellow and VP of Cloud Jason McGee agrees with this and notes that “our mission since Istio’s launch has been to enable everyone to succeed with microservices, especially in the enterprise. This is why we’ve focused the community around improving security and scale, and heavily leaned our contributions on what we’ve learned from building agile cloud architectures for companies of all sizes.”

A lot of the large cloud players now support Istio directly, too. IBM supports it on top of its Kubernetes Service, for example, and Google even announced a managed Istio service for its Google Cloud users, as well as some additional open-source tooling for serverless applications built on top of Kubernetes and Istio.

Two names missing from today’s party are Microsoft and Amazon. I think that’ll change over time, though, assuming the project keeps its momentum.

Istio also isn’t part of any major open-source foundation yet. The Cloud Native Computing Foundation (CNCF), the home of Kubernetes, is backing linkerd, a project that isn’t all that dissimilar from Istio. Once a 1.0 release of these kinds of projects rolls around, the maintainers often start looking for a foundation that can shepherd the development of the project over time. I’m guessing it’s only a matter of time before we hear more about where Istio will land.

Jul
31
2018
--

Webinar Wednesday, August 1, 2018: Migrating to AWS Aurora, Monitoring AWS Aurora with PMM

Migrating to AWS Aurora

Migrating to AWS AuroraPlease join Autodesk’s Senior DevOps Engineer, Sanjeet Deshpande, Autodesk’s Senior Database Engineer, Vineet Khanna, and Percona’s Sr. MySQL DBA, Tate McDaniel as they present Migrating to AWS Aurora, Monitoring AWS Aurora with PMM on Wednesday, August 1st, 2018, at 5:00 PM PDT (UTC-7) / 8:00 PM EDT (UTC-4).

Amazon Web Services (AWS) Aurora is one of the most popular cloud-based RDBMS solutions. The main reason for Aurora’s success is because it’s based on the InnoDB storage engine.

In this session, we will talk about how you can efficiently plan for migrating to AWS Aurora using Terraform and Percona products and solutions. We will share our Terraform code for launching AWS Aurora clusters, look at tricks for checking data consistency, verify migration paths and effectively monitor the environment using Percona Monitoring and Management (PMM).

The topics in this session include:

  • Why AWS Aurora? What is the future of AWS Aurora?
  • Build Aurora infrastructure
  • Using Terraform (without data)
  • Restore using Terraform and Percona XtraBackup (using AWS S3 bucket)
  • Verify data consistency
  • Aurora migration
  • 1:1 migration
  • Many:1 migration using Percona Server for MySQL multi-source replication
  • Show benchmarks and PMM dashboard
  • Demo

Register for the webinar.

Sanjeet DeshpandeSanjeet Deshpande, Senior DevOps Engineer

Sanjeet is a Senior DevOps having 10+ years of experience and currently working with Autodesk, Singapore. He is experienced in architecting, deploying and managing the cloud infrastructures/applications and automation experience. Sanjeet has worked extensively on AWS services like Lambda, SQS, RDS, SNS to name a few. He has also worked closely with the engineering team for different applications and suggested changes to improve their application uptime.

Tate McDanielTate Mcdaniel, Sr. MySQL DBA

Tate joined Percona in June 2017 as a Remote MySQL DBA. He holds a Bachelors degree in Information Systems and Decision Strategies from LSU. He has 10+ years of experience working with MySQL and operations management. His great love is application query tuning. In his off time, he races sailboats, travels the Caribbean by sailboat, and drives all over in an RV.

Vineet KhannaVineet Khanna, Senior Database Engineer

Vineet Khanna, Senior Database Engineer at Autodesk, has 10+ years of experience as a MySQL DBA. His main professional interests are managing complex database environments, improving database performance, and architecting high availability solutions for MySQL. He has handled database environments for organizations like Chegg, Zendesk, and Adobe.

The post Webinar Wednesday, August 1, 2018: Migrating to AWS Aurora, Monitoring AWS Aurora with PMM appeared first on Percona Database Performance Blog.

Jul
30
2018
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A pickaxe for the AI gold rush, Labelbox sells training data software

Every artificial intelligence startup or corporate R&D lab has to reinvent the wheel when it comes to how humans annotate training data to teach algorithms what to look for. Whether it’s doctors assessing the size of cancer from a scan or drivers circling street signs in self-driving car footage, all this labeling has to happen somewhere. Often that means wasting six months and as much as a million dollars just developing a training data system. With nearly every type of business racing to adopt AI, that spend in cash and time adds up.

Labelbox builds artificial intelligence training data labeling software so nobody else has to. What Salesforce is to a sales team, Labelbox is to an AI engineering team. The software-as-a-service acts as the interface for human experts or crowdsourced labor to instruct computers how to spot relevant signals in data by themselves and continuously improve their algorithms’ accuracy.

Today, Labelbox is emerging from six months in stealth with a $3.9 million seed round led by Kleiner Perkins and joined by First Round and Google’s Gradient Ventures.

“There haven’t been seamless tools to allow AI teams to transfer institutional knowledge from their brains to software,” says co-founder Manu Sharma. “Now we have over 5,000 customers, and many big companies have replaced their own internal tools with Labelbox.”

Kleiner’s Ilya Fushman explains that “If you have these tools, you can ramp up to the AI curve much faster, allowing companies to realize the dream of AI.”

Inventing the best wheel

Sharma knew how annoying it was to try to forge training data systems from scratch because he’d seen it done before at Planet Labs, a satellite imaging startup. “One of the things that I observed was that Planet Labs has a superb AI team, but that team had been for over six months building labeling and training tools. Is this really how teams around the world are approaching building AI?,” he wondered.

Before that, he’d worked at DroneDeploy alongside Labelbox co-founder and CTO Daniel Rasmuson, who was leading the aerial data startup’s developer platform. “Many drone analytics companies that were also building AI were going through the same pain point,” Sharma tells me. In September, the two began to explore the idea and found that 20 other companies big and small were also burning talent and capital on the problem. “We thought we could make that much smarter so AI teams can focus on algorithms,” Sharma decided.

Labelbox’s team, with co-founders Ysiad Ferreiras (third from left), Manu Sharma (fourth from left), Brian Rieger (sixth from left) Daniel Rasmuson (seventh from left)

Labelbox launched its early alpha in January and saw swift pickup from the AI community that immediately asked for additional features. With time, the tool expanded with more and more ways to manually annotate data, from gradation levels like how sick a cow is for judging its milk production to matching systems like whether a dress fits a fashion brand’s aesthetic. Rigorous data science is applied to weed out discrepancies between reviewers’ decisions and identify edge cases that don’t fit the models.

“There are all these research studies about how to make training data” that Labelbox analyzes and applies, says co-founder and COO Ysiad Ferreiras, who’d led all of sales and revenue at fast-rising grassroots campaign texting startup Hustle. “We can let people tweak different settings so they can run their own machine learning program the way they want to, instead of being limited by what they can build really quickly.” When Norway mandated all citizens get colon cancer screenings, it had to build AI for recognizing polyps. Instead of spending half a year creating the training tool, they just signed up all the doctors on Labelbox.

Any organization can try Labelbox for free, and Ferreiras claims hundreds have. Once they hit a usage threshold, the startup works with them on appropriate SaaS pricing related to the revenue the client’s AI will generate. One called Lytx makes DriveCam, a system installed on half a million trucks with cameras that use AI to detect unsafe driver behavior so they can be coached to improve. Conde Nast is using Labelbox to match runway fashion to related items in their archive of content.

Eliminating redundancy, and jobs?

The big challenge is convincing companies that they’re better off leaving the training software to the experts instead of building it in-house where they’re intimately, though perhaps inefficiently, involved in every step of development. Some turn to crowdsourcing agencies like CrowdFlower, which has their own training data interface, but they only work with generalist labor, not the experts required for many fields. Labelbox wants to cooperate rather than compete here, serving as the management software that treats outsourcers as just another data input.

Long-term, the risk for Labelbox is that it’s arrived too early for the AI revolution. Most potential corporate customers are still in the R&D phase around AI, not at scaled deployment into real-world products. The big business isn’t selling the labeling software. That’s just the start. Labelbox wants to continuously manage the fine-tuning data to help optimize an algorithm through its entire life cycle. That requires AI being part of the actual engineering process. Right now it’s often stuck as an experiment in the lab. “We’re not concerned about our ability to build the tool to do that. Our concern is ‘will the industry get there fast enough?’” Ferreiras declares.

Their investor agrees. Last year’s big joke in venture capital was that suddenly you couldn’t hear a startup pitch without “AI” being referenced. “There was a big wave where everything was AI. I think at this point it’s almost a bit implied,” says Fushman. But it’s corporations that already have plenty of data, and plenty of human jobs to obfuscate, that are Labelbox’s opportunity. “The bigger question is ‘when does that [AI] reality reach consumers, not just from the Googles and Amazons of the world, but the mainstream corporations?’”

Labelbox is willing to wait it out, or better yet, accelerate that arrival — even if it means eliminating jobs. That’s because the team believes the benefits to humanity will outweigh the transition troubles.

“For a colonoscopy or mammogram, you only have a certain number of people in the world who can do that. That limits how many of those can be performed. In the future, that could only be limited by the computational power provided so it could be exponentially cheaper” says co-founder Brian Rieger. With Labelbox, tens of thousands of radiology exams can be quickly ingested to produce cancer-spotting algorithms that he says studies show can become more accurate than humans. Employment might get tougher to find, but hopefully life will get easier and cheaper too. Meanwhile, improving underwater pipeline inspections could protect the environment from its biggest threat: us.

“AI can solve such important problems in our society,” Sharma concludes. “We want to accelerate that by helping companies tell AI what to learn.”

Jul
30
2018
--

Google Calendar makes rescheduling meetings easier

Nobody really likes meetings — and the few people who do like them are the ones with whom you probably don’t want to have meetings. So when you’ve reached your fill and decide to reschedule some of those obligations, the usual process of trying to find a new meeting time begins. Thankfully, the Google Calendar team has heard your sighs of frustration and built a new tool that makes rescheduling meetings much easier.

Starting in two weeks, on August 13th, every guest will be able to propose a new meeting time and attach to that update a message to the organizer to explain themselves. The organizer can then review and accept or deny that new time slot. If the other guests have made their calendars public, the organizer can also see the other attendees’ availability in a new side-by-side view to find a new time.

What’s a bit odd here is that this is still mostly a manual feature. To find meeting slots to begin with, Google already employs some of its machine learning smarts to find the best times. This new feature doesn’t seem to employ the same algorithms to proposed dates and times for rescheduled meetings.

This new feature will work across G Suite domains and also with Microsoft Exchange. It’s worth noting, though, that this new option won’t be available for meetings with more than 200 attendees and all-day events.

Jul
30
2018
--

Upcoming Webinar Tuesday, 7/31: Using MySQL for Distributed Database Architectures

Distributed Database Architectures

Distributed Database ArchitecturesPlease join Percona’s CEO, Peter Zaitsev as he presents Using MySQL for Distributed Database Architectures on Tuesday, July 31st, 2018 at 7:00 AM PDT (UTC-7) / 10:00 AM EDT (UTC-4).

 

In modern data architectures, we’re increasingly moving from single-node design systems to distributed architectures using multiple nodes – often spread across multiple databases and multiple continents. Such architectures bring many benefits (such as scalability and resiliency), but can also bring a lot of pain if incorrectly designed and executed.

In this presentation, we will look at how we can use MySQL to engineer distributed multi-node systems.

Register for the webinar.

Peter ZaitsevPeter Zaitsev, CEO and Co-Founder

Peter Zaitsev co-founded Percona and assumed the role of CEO in 2006. As one of the foremost experts on MySQL strategy and optimization, Peter leveraged both his technical vision and entrepreneurial skills to grow Percona from a two-person shop to one of the most respected open source companies in the business. With over 140 professionals in 30 plus countries, Peter’s venture now serves over 3000 customers – including the “who’s who” of internet giants, large enterprises and many exciting startups. Inc. 5000 named Percona to their list in 2013, 2014, 2015 and 2016. Peter was an early employee at MySQL AB, eventually leading the company’s High-Performance Group. A serial entrepreneur, Peter co-founded his first startup while attending Moscow State University where he majored in Computer Science. Peter is a co-author of High-Performance MySQL: Optimization, Backups, and Replication, one of the most popular books on MySQL performance. Peter frequently speaks as an expert lecturer at MySQL and related conferences, and regularly posts on the Percona Database Performance Blog. He has also been tapped as a contributor to Fortune and DZone, and his ebook Practical MySQL Performance Optimization is one of Percona’s most popular downloads.

 

The post Upcoming Webinar Tuesday, 7/31: Using MySQL for Distributed Database Architectures appeared first on Percona Database Performance Blog.

Jul
28
2018
--

Blogs ‘n’ YouTube

Hey folks, I thought I'd share some interesting travel-related blogs and YouTube channels that I follow:

Blogs

totesmboats.blogspot.com

Ester has decided to live on a houseboat on Lake Union, Seattle. Follow her journey.

rootlessroutes.com

Follow Eli, who in her 50's decided to take to the road on an endless road trip with her cat, and she hasn't looked back. Such a great adventure and awesome photography too.

toeuropeandbeyond.com

Another great travel blog, lots of Europe and elsewhere.

You Tube Channels

vagabrothers

Two brothers travelling the world. Great video quality as well as tons of advice about what to see and travel tips. They've even started making VR movies.

Wolters World

Quick travel advice for countries and cities all over the world. I watch every video but alas, they're nearly all just talking heads with a few travel scenes thrown in. But the advice is solid.

Sailing SV Delos

Absolutely hands down the best sailing video channel ever! A bunch of fun folks circumnavigating the world over the last 7-8 years on a 53' Amel Super Maramu 2000. Go back to Episode 1 (and we're up to like 188 now) and watch them in order to see the evolution of the adventure and the crew. The early videos were primitive but stick with it because now they are some of the best videographers in the business – totally pro-broadcast quality.

Sailing Yacht Ruby Rose

Nick and Terysa sail a 38' Southerner monohull, and have travelled from Europe, across the Atlantic to the Caribbean, and are now heading to Bermuda and back across the Atlantic to Europe. Lots of fun and travel videography, and as a Brit, I like Nick, since he's English and curses a lot. ?

Gone with the Wynns

Jason and Nikki are great adventurers. They started off touring the USA and Canada in an RV, and those videos are very informative if you're considering the RV nomadic lifestyle. A couple of years ago they bought a Leopard catamaran in Florida, learned to sail it (!) and meandered through the Bahamas, down to Panama and Equador, and now plan to cross the Pacific. Great, fun travel videos (it's not all sailing!) with their 2 cats.

Sailing La Vagabonde

Riley and Elayna are an Australian Couple who've been on a round the world sail for years. Currently they're sailing a Outremer catamaran, having gone around the Mediterranean and across the Atlantic to the Caribbean, but they started on a 45' Beneteau monohull. For the best experience, go back to Episode 1 and watch them all in order.

 

Jul
27
2018
--

Percona Server for MongoDB 3.4.16-2.14 Is Now Available

MongoRocks

Percona Server for MongoDB 3.4Percona announces the release of Percona Server for MongoDB 3.4.16-2.14 on July 27, 2018. Download the latest version from the Percona web site or the Percona Software Repositories.

Percona Server for MongoDB is an enhanced, open source, and highly-scalable database that is a fully-compatible, drop-in replacement for MongoDB 3.4 Community Edition. It supports MongoDB 3.4 protocols and drivers.

Percona Server for MongoDB extends MongoDB Community Edition functionality by including the Percona Memory Engine and MongoRocks storage engine, as well as several enterprise-grade features. It requires no changes to MongoDB applications or code.

This release is based on MongoDB 3.4.16 and does not include any additional changes.

The Percona Server for MongoDB 3.4.16-2.14 release notes are available in the official documentation.

The post Percona Server for MongoDB 3.4.16-2.14 Is Now Available appeared first on Percona Database Performance Blog.

Jul
27
2018
--

This Week in Data with Colin Charles 46: OSCON Recap, Google Site Reliability Workbook

Colin CharlesJoin Percona Chief Evangelist Colin Charles as he covers happenings, gives pointers and provides musings on the open source database community.

OSCON happened last week and was incredible. It is true there was less of a database focus, and a lot more topics covered. In fact, you’d have found it hard to find database content. There was plenty of interesting content around AI/ML, cloud, SRE, blockchain and more. As a speaker, the 40-minute sessions that included a Q and A session was quite compact (I felt it was a little too short, and many speakers sped up towards the end). I guess it will make for more blog content.

The conference’s open source ethos is still extremely strong, and the keynotes exemplified that. It was not just the 20th anniversary of OSCON, but also the 20th anniversary of the Open Source Initiative (OSI). Percona is a sponsor (and I am an individual member). From a sponsor standpoint, Home Depot had a huge booth, but so did the NSA – who, along with giving out stickers, were actively recruiting. Readers might recall mention of NSA’s involvement with LemonGraph and the other data open source data projects from column 43.

Google just released The Site Reliability Workbook, which looks like the full PDF (“launch day edition”) of their new book. It includes practical ways to implement SRE. You can pre-order the book, and the official release date is August 4, 2018. This should be the best companion to Site Reliability Engineering: How Google Runs Production Systems, which I highly recommend reading first before getting to the workbook. After a quick perusal of the new release, I can say I like it — the case studies from Evernote and Home Depot, are all very interesting from a database standpoint (MySQL, Cloud SQL). Plenty of information is relevant if you’re a Prometheus user as well. I say skim the PDF, and devour the book!

Releases

Link List

Industry Updates

  • Elastic is on a spree of grabbing folk – Massimo Brignoli (ex-MongoDB, SkySQL, Oracle, and MySQL) joins as a Principal Solutions Architect, and Gerardo Narvaja joins as Sr. Solutions Architect for Pacific Northwest. He departs MariaDB Corporation, and has previously been at Tokutek, Pythian and MySQL.
  • Morgan Tocker (LinkedIn) has joined PingCAP as Senior Product & Community Manager. Previously he was both product manager and community manager at Oracle for MySQL, had a stint at Percona and also was at the original MySQL AB.
  • Baron Schwartz is now Chief Technology Officer of VividCortex, and Amena Ali has become the new CEO.

Upcoming Appearances

Feedback

I look forward to feedback/tips via e-mail at colin.charles@percona.com or on Twitter @bytebot.

The post This Week in Data with Colin Charles 46: OSCON Recap, Google Site Reliability Workbook appeared first on Percona Database Performance Blog.

Jul
26
2018
--

Slack forms key alliance as Atlassian throws in the towel on enterprise chat

With today’s announcement from Atlassian that it was selling to Slack the IP assets of its two enterprise communications tools, HipChat and Stride, it closes the book on one of the earliest competitors in the modern enterprise chat space. It also was a clear signal that Slack is not afraid to take on its giant competitors by forming key alliances.

That the announcement came from Slack co-founder and CEO Stewart Butterfield on Twitter only exacerbated that fact. Atlassian has a set of popular developer tools like Jira, Confluence and Bitbucket. At this point, HipChat and Stride had really become superfluous to the company and they sold the IP to their competitor.

Not only is Slack buying the assets and Atlassian is effectively shutting down these products, Atlassian is also investing in Slack, a move that shows it’s throwing its financial weight behind the company, as well, and forming an alliance with them.

Slack has been burning it up since in launched in 2014 with just 16,000 daily active users. At last count, in May, the company was reporting 8 million active users, 3 million of which were paid. That’s up from 6 million DAUs and 2 million paid users in September 2017. At the time, the company was reporting $200 million in annual recurring revenue. It’s a fair bet with the number of paid users growing by one-third at last count, that revenue number has increased significantly, as well.

Slack and products of its ilk like Workplace by Facebook, Google Hangouts and Microsoft Teams are trying to revolutionize the way we communicate and collaborate inside organizations. Slack has managed to advance the idea of enterprise communications that began in the early 2000s with chat clients, advanced to Enterprise 2.0 tools like Yammer and Jive in the mid-2000s and finally evolved into modern tools like Slack we are using today in the mobile-cloud era.

Slack has been able to succeed so well in business because it does much more than provide a channel to communicate. It has built a platform on top of which companies can plug in an assortment of tools they are using every day to do their jobs, like ServiceNow for help desk tickets, Salesforce for CRM and marketing data and Zendesk for customer service information.

This ability to provide a simple way to do all of your business in one place without a lot of task switching has been a Holy Grail of sorts in the enterprise for years. The two previously mentioned iterations, chat clients and Enterprise 2.0 tools, tried and failed to achieve this, but Slack has managed to create this single platform and made it easy for companies to integrate services.

This has been automated even further by the use of bots, which can act as trusted assistants inside of Slack, providing additional information and performing tasks for you on your behalf when it makes sense.

Slack has an otherworldly valuation of more than $5 billion right now, and is on its way to an eventual IPO. Atlassian might have thrown in the towel on enterprise communications, but it has opened the door to getting a piece of that IPO action while giving its customers what they want and forming a strong bond with Slack.

Others like Facebook and Microsoft also have a strong presence in this space and continue to build out their products. It’s not as though anyone else is showing signs of throwing up their hands just yet. In fact, just today Facebook bought Redkix to enhance its offering by giving users the ability to collaborate via email or the Workplace by Facebook interface, but Atlassian’s acquiescence is a strong signal that if you had any doubt, Slack is a leader here — and they got a big boost with today’s announcement.

Jul
26
2018
--

Amazon’s AWS continues to lead its performance highlights

Amazon’s web services AWS continue to be the highlight of the company’s balance sheet, once again showing the kind of growth Amazon is looking for in a new business for the second quarter — especially one that has dramatically better margins than its core retail business.

Despite now running a grocery chain, the company’s AWS division — which has an operating margin over 25 percent compared to its tiny margins on retail — grew 49 percent year-over-year in the quarter compared to last year’s second quarter. It’s also up 49 percent year-over-year when comparing the most recent six months to the same period last year. AWS is now on a run rate well north of $10 billion annually, generating more than $6 billion in revenue in the second quarter this year. Meanwhile, Amazon’s retail operations generated nearly $47 billion with a net income of just over $1.3 billion (unaudited). Amazon’s AWS generated $1.6 billion in operating income on its $6.1 billion in revenue.

So, in short, Amazon’s dramatically more efficient AWS business is its biggest contributor to its actual net income. The company reported earnings of $5.07 per share, compared to analyst estimates of around $2.50 per share, on revenue of $52.9 billion. That revenue number fell under what investors were looking for, so the stock isn’t really doing anything in after-hours, and Amazon still remains in the race to become a company with a market cap of $1 trillion alongside Google, Apple and Microsoft.

This isn’t extremely surprising, as Amazon was one of the original harbingers of the move to a cloud computing-focused world, and, as a result, Microsoft and Google are now chasing it to capture up as much share as possible. While Microsoft doesn’t break out Azure, the company says it’s one of its fastest-growing businesses, and Google’s “other revenue” segment that includes Google Cloud Platform also continues to be one of its fastest-growing divisions. Running a bunch of servers with access to on-demand compute, it turns out, is a pretty efficient business that can account for the very slim margins that Amazon has on the rest of its core business.

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