As a result of a network migration from AWS Classic networking to AWS VPC networking, the public-facing IP addresses of MongoDB’s services, including both JIRA (jira.mongodb.org) and MMS (mms.mongodb.com and api-backup.mongodb.com), will be changing on Thursday, January 29, 2015 (16:00 UTC / 11:00 EDT).
The current IP addresses and new IP addresses are documented (along with a procedure for making a seamless change, if you have them hard-coded anywhere) here.
This will only impact Customers that * are using DNS TTL overrides, * have our IP addresses hard-coded into one or more of their systems * or have firewalls controlling outbound access to those IP addresses.
Workarounds In the scenario where there is a hard-coded IP address, it will need to be changed on Thursday, January 29, 2015 (16:00 UTC / 11:00 EDT) or access to our systems will be degraded once the IP address change has been made. Please also note that the old IPs will be decommissioned shortly after and at that point access will be lost completely until your systems are updated.
Firewalls can add both sets of IP addresses in advance, and then remove the old IP addresses once the change has been made. DNS servers should be adjusted to honor the TTL returned during this process, or will need their caches manually cleared once the change has been made. Hard-coded IP addresses in applications should be switched to use DNS or will need to be manually adjusted post-change.
If you have any questions about this change or need help implementing any workarounds on your systems, feel free to file a ticket in JIRA prior to the change date and we will work with you to make sure that your team can make the appropriate updates on your side.
Leaf in the Wild: Qihoo Scales with MongoDB
Leaf in the Wild posts highlight real world MongoDB deployments. Read other stories about how companies are using MongoDB for their mission-critical projects. 100+ apps, 1,500+ Instances, 20B Queries per Day Qihoo is China’s number 1 Android mobile distribution platform. Qihoo is also China’s top malware protection company, providing products for both web and mobile platforms. A MongoDB user since 2011, Qihoo has built over 100 different applications on MongoDB – including new services and migrations from MySQL and Redis – running on 1,500+ instances and supporting 20 billion queries per day. I had the chance to sit down with Yang Yan Jie, the Senior DBA at Qihoo to learn more about how and why they use MongoDB, his scaling best practices, and recommendations for those getting started with the database. Can you start by telling us about Qihoo? Qihoo 360 Technology Co. Ltd. is a leading Chinese Internet company. At the end of June 2014, we had around 500 million monthly active PC Internet users and over 640 million mobile users. Recognizing malware protection as a fundamental need of all Internet and mobile users, we built our large user base by offering comprehensive, effective and user-friendly Internet and mobile security products and services to protect users' computers and mobile devices against malware and malicious websites. Our products and services are supported by our cloud-based security technology, which we believe is one of the most advanced and robust technologies in the malware protection industry. We monetize our user base primarily through online advertising and Internet value-added services. In terms of our market position, we are: A top three Internet Company as measured by user base in China No. 1 Android-based mobile distribution platform in China No. 1 provider of Internet and mobile malware protection products and services in China No. 2 PC search engine in China When did Qihoo start using MongoDB? We were a very early adopter of MongoDB, building our first applications on the database back in 2011. I think we were using version 1.8 then! How is Qihoo using MongoDB today? MongoDB has become our standard modern database platform. We now have over 100 applications powered by MongoDB – both external customer-facing services and internal business applications. In total we have more than 1,500 MongoDB instances running on our in-house built “HULK” cloud platform, collectively serving 20 billion queries per day. Three particularly critical applications for our business are: Location-based mobile search application. We use MongoDB with its geospatial indexes and queries to deliver geo-aware search results to mobile users. The user can be searching for anything, from a local restaurant, to a shop, to a car dealership. The app will detect their location and serve search results based on proximity. MongoDB handles 1.2 billion queries per day from this application. Caching layer for user authentication data. Qihoo is a central portal for many Chinese Internet users. We have many partners that our users can connect to directly after logging into our site. We provide Single Sign On (SSO) to multiple services so users don’t need to keep providing their security credentials as they navigate around the web. The user’s SSO session is cached in MongoDB for ultra-fast access. MongoDB supports millions of concurrent users, handling 30,000 operations per second and 1.8 billion queries daily. Log analytics platform. We need to know our infrastructure is running well. Our internal business users also want to measure user engagement with new promotions and campaigns. To accomplish this, we collect log data from all of our Linux, Apache web server and Tomcat servers, and stream it directly into MongoDB. From there, our internal business users can generate real time analytics and reports using our PHP-based Business Intelligence (BI) platform. MongoDB stores 2.5 billion documents at any one time across 18 shards configured with 3-node replica sets for always-on availability. MongoDB serves nearly 3 billion queries per day, including 1 billion writes. What other databases do you use? MongoDB is one of the three database technologies used in our company. It isn’t necessarily suitable for all applications, so we also use MySQL for relational data problems and Redis for certain caching use-cases. Over time, we have migrated more than a dozen projects from MySQL and Redis to MongoDB. What factors drove this migration? Our goal is to use the best technology where it best fits. In the case of MySQL, migration was driven by scalability and developer productivity. As a relational database, MySQL does not scale out, so as our user base grew above 100 million active users, we hit the limits of how far we could push MySQL. MongoDB auto-sharding allows us to scale on-demand using commodity hardware. The MongoDB data model is also far more flexible. Our developers can get more done and iterate faster with MongoDB than they can with the relational model. In the case of Redis, the migrations were driven by cost and flexibility. We found that MongoDB meets our low latency caching requirements for many applications, while it’s on-disk persistence reduces the need to provision costly systems configured with high-memory footprints. In addition, there is much more you can do with MongoDB’s document data model than you can with Redis’ Key-Value model. This translates directly to richer application functionality. For applications where data volumes are expected to grow rapidly, we choose MongoDB over Redis. Tell us about the platforms you are running MongoDB on. Most of our applications are PHP based. We run CentOS on x86 hardware. We have standardized on local SSD storage as this gives us the best performance. We are running MongoDB 2.4 and the latest 2.6 releases. We are also looking forward to MongoDB 3.0! How is MongoDB configured? We run both single replica sets and sharded clusters, depending on the application. We have data centres across the country, with the main ones located in Beijing. We deploy MongoDB on our private cloud across multiple data centers, both for disaster recovery and for low latency local reads and writes. We don’t control our own fiber, so network quality is out of our control. For the most critical apps, we spin up identical MongoDB clusters in multiple data centers and use our own message queue to replicate between them – this gives us assurance of maintaining availability in the face of network partitions. How do you manage your MongoDB deployment? We have developed a centralized orchestration web platform, which we call the HULK cloud platform. It is used by nearly all of our technical engineers to control our mission critical infrastructure and services. It is a complex piece of engineering which we are very proud of. When we originally started the cloud platform project, we hoped it would allow our engineers to stand on the shoulders of giants, relying on the platform to speed up the time to market for their applications. Hence we named it “HULK”. HULK currently provides elastic services such as Web, relational database, NoSQL and distributed storage, etc. At same time, the open platform concept attracted various internal teams to move their applications onto the platform. The re-platforming of these applications provided immediate access to other LoBs internally, and in the process of doing that we helped the business groups to attain higher efficiency and greater technology expertise. MongoDB is one of the most critical services on HULK and it is fully integrated into the platform with a high degree of automation, allowing us to operate more than 1,500 MongoDB instances with just one and a half DBAs. The DBAs can perform “one click deployment” and “one click upgrade” tasks via the HULK management interface. All backup and monitoring is fully automated. For instance, if you add a new MongoDB node or cluster, HULK automatically configures the monitoring and backup strategy, as well as deploy the necessary agents. For developers, they can monitor a multitude of MongoDB metrics and status. In addition, they can open a ticket right on the management portal itself, instead of using email or IM, all with a few mouse clicks. How do you backup MongoDB? We use a combination of approaches, governed by the application’s RPO and RTO objectives: Filesystem backups. This is the default approach. We shut down a secondary replica set member and snapshot the filesystem image Incremental replication. For continuous backup, we have built a tool that tails the MongoDB oplog. We use this approach for more critical apps where we need faster restoration of service Delayed replicas . We use this approach for additional assurances, again governed by how quickly we need to bring the data back Can you share any best practices on scaling your MongoDB infrastructure? There are three tips I would like to share: From a DBA perspective, invest time to understand application usage. The developers will give their guidance, but we generally take any number they give us and add 50%! If you encounter performance issues, start with your hardware. We found upgrading from hard disks to SSDs gave us an instant performance boost without any other optimizations. For highly dynamic, write-intensive workloads, make sure you monitor storage fragmentation and compact regularly if needed. Are you measuring the impact of MongoDB on your business? Yes – in terms of time to market. An example of the impact this makes is our reaction to the 2014 earthquake in Yunnan province. Everyone in China wanted to have access to the latest updates and to be able to check in on friends and family in the region. The business felt the best way to do this was to build an app that verified and then consolidated newsfeeds from multiple sources. We designed the app in the morning after the earthquake, coded it in the afternoon and launched it in the evening. One business day from concept to production. Only MongoDB could support that velocity of development. Are you looking forward to MongoDB 3.0? We started testing MongoDB 3.0 and filing bugs as soon as we could get our hands on the first Release Candidate. We are especially excited about document level concurrency control. This will further improve write scaling and fully saturate the latest generation of dense multi-core systems we are using now. Compression is also a huge benefit for us. We have standardized on SSDs, so compression means we can pack more onto each drive, which will bring costs down. It will also give us another performance boost as fewer bits are read from disk, making better use of disk I/O cycles. What advice would you give to those considering using MongoDB for their next project? MongoDB’s document data model and dynamic schema bring great flexibility and power. But they also bring great responsibility! I’d recommend not storing multitudes of different document types and formats within a single collection as it makes ongoing application maintenance complex. Split out documents of different types and structures into their own collections. We have implemented tools that scan and sample documents from each collection. If variances in structure exceed our best practices, we alert the devs so they can go and address the issue. So that is where I’d start. Mr. Yang – I’d like to thank you for taking the time to share your insights with the MongoDB community. Struggling to scale your relational database? Download our Migration White Paper: Migration White Paper About the Author - Mat Keep Mat is part of the MongoDB product marketing team, responsible for building the vision, positioning and content for MongoDB’s products and services, including the analysis of market trends and customer requirements. Prior to MongoDB, Mat was director of product management at Oracle Corp. with responsibility for the MySQL database in web, telecoms, cloud and big data workloads. This followed a series of sales, business development and analyst / programmer positions with both technology vendors and end-user companies.
Australian Start-Up Ynomia Is Building an IoT Platform to Transform the Construction Industry and its Hostile Environments
The trillion dollar construction industry has not yet experienced the same revolution in technology you might have expected. Low levels of R&D and difficult working environments have led to a lack of innovation and fundamental improvements have been slow. But one Australian start-up is changing that by building an Internet of Things (IoT) platform to harness construction and jobsite data in real time. “Productivity in construction is down there with hunting and fishing as one of the least productive industries per capita in the entire world. It's a space that's ripe for people to come in and really help,” explains Rob Postill , CTO at Ynomia. Ynomia has already been closely involved with many prestigious construction projects, including the residential N06 development in London’s famous 2012 Olympic Village. It was also integral to the construction of the Victoria University Tower in Australia. Link to Podcast Episode Here “These projects involve massive outflow of money: think about glass facades on modern buildings, which can represent 20-30 percent of the overall project cost. They are largely produced in China and can take 12 weeks to get here,” says Postill. “Meanwhile, the plasterer, the plumber, the electrician are all waiting for those glass facades to be put on so it is safe for them to work. If you get it wrong, you can go in the deep red very quickly.” To tackle these longstanding challenges, Ynomia aims to address the lack of connectivity, transparency and data management on construction sites, which has traditionally resulted in the inefficient use of critical personnel, equipment and materials; compressed timelines; and unpredictable cash flows. To optimize productivity, Ynomia offers a simple end-to-end technology solution that creates a Connected Jobsite. Helping teams manage materials, tools, and people across the worksite in real time. IOT in a Hostile Environment The deployment of technology in construction is often fraught with risk. As a result, construction sites are still largely run on paper, such as blueprints, diagrams and models as well as the more traditional invoices and filing. At the same time, there is a constant need to track progress and monitor massive volumes of information across the entire supply chain. Engineers, builders, electricians, plumbers, and all the other associated professionals need to know what they need to do, where they need to be, and when they need to start. “The environment is hostile to technology like GPS, computers, and mobile phone reception because you have a lot of Faraday cages and lots of water and dust,” explains Postill. “You can't have somebody wandering around a construction site with a laptop; it'll get trashed pretty quickly." Enter MongoDB Atlas “On a site, you might be talking about materials, then if you add to that plant & equipment, or bins, or tools etc, you're rapidly getting into thousands and thousands of tags, talking all the time, every day,” said Postill. That means thousands of tags now send millions of readings on Ynomia building sites around the world. All these IoT data packets must be stored efficiently and accurately so Ynomia can reassemble the history of what has happened and track tagged inventory, personnel, and vehicles around the site. Many of the tag events are also safety critical so accuracy is a vital component and packets can't be missed. To address these needs Ynomia was looking for a database that was scalable, flexible, resilient and could easily handle a wide variety of fast-changing sensor data captured from multiple devices. The final component Postill was looking for in a database layer was freedom: a database that didn't lock them into a single cloud platform as they were still in the early stages of assessing cloud partners. The Commonwealth Scientific and Industrial Research Organisation , which Postill had worked with in the past, suggested MongoDB , a general purpose, document-based database built for modern applications. “The most important factor was that the database is event-driven, which I knew would be difficult in the traditional relational model. We deal with millions of tag readings a day, which is a massive wall of data,” said Postill. A Cloud Database Ynomia is using MongoDB Atlas , the global cloud database service, now hosted on Microsoft Azure. Atlas offers best-in-class automation and proven practices that combine availability, scalability, and compliance with the most demanding data security and privacy standards. “When we started we didn't know enough about the problem and we didn't want to be constrained," explained Postill. "MongoDB Atlas gives us a cloud environment that moves with us. It allows us to understand what is happening and make changes to the architecture as we go." Postill says this combination of flexibility and management tooling also allows his developers to focus on business value not undifferentiated code. One example Postill gave was cluster administration: "Cluster administration for a start-up like us is wasted work," he said. "We’re not solving the customer's problem. We're not moving anything on. We’re focusing on the wrong thing. For us to be able to just make that problem go away is huge. Why wouldn’t you?" Atlas also gives Ynomia the option to spin out new clusters seamlessly anywhere in the world. This allows customers to keep data local to their construction site, improving latency and helping solve for regional data regulations. Real Time Analytics The company has also deployed MongoDB Charts, which takes this live data and automatically provides a real time view. Charts is the fastest and easiest way to visualize event data directly from MongoDB in order to act instantly and decisively based on the real-time insights generated by event-driven architecture. It allows Ynomia to share dashboards so all the right people can see what they need to and can collaborate accordingly. “Charts enables us to quickly visualize information without having to build more expensive tools, both internally and externally, to examine our data,” comments Postill. “As a startup, we go through this journey of: what are we doing and how are we doing it? There's a lot of stuff we are finding out along the way on how we slice and re-slice our data using Charts.” A Platform for Future Growth Ynomia is targeting a huge market and is set for ambitious growth in the coming years. How the platform, and its underlying architecture, can continue to scale and evolve will be crucial to enabling that business growth. “We do anything we can to keep things simple,” concluded Postill. “We pick technology partners that save us from spending time we shouldn't spend so we can solve real problems. We pick technologies that roll with the punches and that's MongoDB.” When we started we didn't know enough about the problem and we didn't want to be constrained," explained Postill. "MongoDB Atlas gives us a cloud environment that moves with us. It allows us to understand what is happening and make changes to the architecture as we go. Rob Postill, CTO, Ynomia