We can’t wait until this year’s MongoDB World, and are working hard behind the scenes. We want to make sure our biggest event is a fun-filled learning experience, and that attendees reflect our diverse community. As part of our commitment to changing the gender ratio in technology, we're excited to launch the Female Innovators at MongoDB World initiative.
Nominees will be notified of their nomination by April 15, 2016. The first 50 nominees to register will receive complimentary admission to MongoDB World, June 28-29 in NYC.
At the event they’ll be able to:
- Network with other female innovators through sessions and activities at the Women Who Code Lounge
- Meet the engineers behind the technology
- Learn best practices to amp up their skills, and the inside scoop on who’s doing what with MongoDB
- Explore community activities, including the Leaf Lounge, poster sessions, and our famous after party
Fill out the short nomination form to invite a woman who works or aspires to work in tech to attend our global conference. You can also nominate yourself! Make sure to act fast, a limited amount of tickets are available.
The deadline to submit a nomination is Friday, April 8. Eligible nominees will be notified of their acceptance status by April 15.
- Nominees must be 18 years old or older, and must identify as a female.
- Open to new participants of MongoDB World only.
- Can you nominate yourself? Absolutely!
Nominees will be notified of their nomination by April 15, 2016. The first 50 nominees to register will receive complimentary admission to MongoDB World, June 28-29 in NYC. View terms and conditions.
At-Rest Encryption in MongoDB 3.2: Features and Performance
Introduction MongoDB 3.2 introduces a new option for at-rest data encryption. In this post we take a closer look at the forces driving the need for increased encryption, MongoDB features for encrypting your data, as well as the performance characteristics of the new Encrypted Storage Engine. Data security is top of mind for many executives due to increased attacks as well as a series of data breaches in recent years that have negatively impacted several high profile brands. For example, in 2015, a major health insurer was a victim of a massive data breach in which criminals gained access to the Social Security numbers of more than 80 million people — resulting in an estimated cost of $100M. In the end, one of the critical vulnerabilities was the health insurer did not encrypt sensitive patient data stored at-rest. Data encryption is a key part of a comprehensive strategy to protect sensitive data. However, encrypting and decrypting data is potentially very resource intensive. It is important to understand the performance characteristics of your encryption technology to accurately conduct capacity planning. MongoDB 3.2: Delivering Native Encryption At-Rest MongoDB 3.2 provides a comprehensive encryption solution that protects your data, both in-flight and at-rest. For encryption-in-flight, MongoDB uses SSL/TLS, which ensures secure communication between your database and client, as well as inter-cluster traffic between nodes. Learn more about MongoDB and SSL/TLS . With the latest version 3.2 , MongoDB also includes a fully integrated encryption-at-rest solution that reduces cost and performance overhead. Encryption-at-rest is part of MongoDB Enterprise Advanced only, but is freely available for development and evaluation. We will take a closer look at this new option later in the post. Before 3.2, the primary methods to provide encryption-at-rest were to use 3rd party applications that encrypt files at the application, file system, or disk level. These methods work well with MongoDB but can add extra cost, complexity, and overhead. Additionally, disk and file system encryption might not protect against all situations. While disk level encryption protects from someone taking the physical drive from the machine, it does not protect from someone that has physical access to the machine and can override the file system. Similarly, file system encryption will prevent someone from overriding the file system, but does not preclude someone from gaining unauthorized access through the application or database layer. Database encryption mitigates these problems by adding an extra layer of security. Even if an administrator has access to the file system, he/she will first need to be authenticated to the database before decrypting the data files. MongoDB’s Encrypted Storage Engine supports a variety of encryption algorithms from the OpenSSL library. AES-256 in CBC mode is the default, while other options include GCM mode, as well as FIPS mode for FIPS-140-2 compliance. Encryption is performed at the page level to provide optimal performance. Instead of having to encrypt/decrypt the entire file or database for each change, only the modified pages need to be encrypted or decrypted. Additionally, the Encrypted Storage Engine provides safe and secure management of the encryption keys. Each encrypted node contains an internal database key that is used to encrypt/decrypt the data files. The database key is wrapped with an external master key, which must be given to the node for it to initialize. MongoDB uses operating system protection mechanisms, such as VirtualLock and mlock , that lock the process’ virtual memory space into memory, ensuring that keys are never written or paged to disk in unencrypted form. Evaluating Performance Encrypting and decrypting data requires the use of additional resources, and administrators will want to understand the performance impact to adjust capacity planning accordingly. In our Encrypted Storage Engine benchmarking tests, we saw an average throughput overhead between 10% and 20%. Let’s take a closer look at some benchmark data to show the results for Insert Only, Read Only, and 50%-Read/50%-Insert workloads. For our benchmark, we used Intel Xeon X5675 CPUs, which support the AES-NI instruction set, and ran the CPUs at high load(100%). There were four different configurations that we evaluated; “ Working Set Fits In Memory ”, “ Working Set Exceeds Memory ”, “ Encrypted ”, and “ Unencrypted ”. The ‘ Working Set ’ refers to the amount of data and indexes that is actively used by your system. Let’s first look at an Insert-Only workload. With a high CPU load, we see an encryption overhead of around ~16%. Now, let’s take a look at the results of our Read-Only Workload. We ran the benchmark between two scenarios; “ Working Set Fits In Memory ” and “ Working Set Exceeds Memory ”. From the benchmark results, the decryption overhead for a Read-Only workload ranges between 5–20%. Lastly, here are the benchmark results for a 50%-Read, 50%-Insert workload. For the 50%-Read/50%-Insert workloads, the encryption overhead ranges between 12%–20%. In addition to throughput, latency is also a critical component of encryption overhead. From our benchmark, average latency overheads ranged between 6% to 30%. Though average latency overhead was slightly higher than throughput overhead, latencies were still very low—all under 1ms. Average Latency(us) Unencrypted Encrypted % Overhead Insert Only Average Latency(us) 32.4 40.9 -26.5% Read Only Working Set Fits In Memory Avg Latency(us) 230.5 245.0 -6.3% Read Only Working Set Exceeds Memory Avg Latency(us) 447.0 565.8 -26.6% 50% Insert/50% Read Working Set Fits In Memory Avg Latency(us) 276.1 317.4 -15.0% 50% Insert/50% Read Working Set Exceeds Memory Avg Latency(us) 722.3 936.5 -29.7% MongoDB Atlas Encryption At Rest MongoDB Atlas is a database as a service and provides all the features of the database without the heavy lifting of setting up operational tasks. Developers no longer need to worry about provisioning, configuration, patching, upgrades, backups, and failure recovery. Atlas offers elastic scalability, either by scaling up on a range of instance sizes or scaling out with automatic sharding, all with no application downtime. MongoDB Atlas provides encryption of data-in-flight over the network and at rest on disk. Data-at-rest can be optionally protected using encrypted data volumes. Encrypted data volumes secure your data without the need for you to build, maintain, and secure your own key management infrastructure. Summary In this post, we looked at a few workloads to determine the impact of encryption with MongoDB's new Encrypted Storage Engine. The results demonstrate that the Encrypted Storage Engine provides a secure way to encrypt your data-at-rest, while maintaining exceptional performance. With the Encrypted Storage Engine and diligent capacity planning, you shouldn't have to make a tradeoff between high performance and strong security when encrypting data-at-rest. For users interested in a database as a service, MongoDB Atlas provides encrypted data volumes to ensure your data at rest is secure. Environment These tests were conducted on bare metal servers. Each server had the following specification: CPU : 3.06GHz Intel Xeon Westmere(X5675-Hexcore) RAM : 6x16GB Kingston 16GB DDR3 2Rx4 OS : Ubuntu 14.04-64 Network Card : SuperMicro AOC-STGN-i2S Motherboard : SuperMicro X8DTN+_R2 Document Size : 1KB Workload : YCSB Version : MongoDB 3.2 Learn More About Encryption and all of the security features available for MongoDB by reading our guide. MongoDB Security Architecture Guide Additional Resources Try MongoDB’s New Encrypted Storage Engine. Users can try the Encrypted Storage Engine free for unlimited development and evaluation. Read our installing MongoDB Enterprise 3.2 documentation . About the Author - Jason Ma Jason is a Principal Product Marketing Manager based in Palo Alto, and has extensive experience in technology hardware and software. He previously worked for SanDisk in Corporate Strategy doing M&A and investments, and as a Product Manager on the Infiniflash All-Flash JBOF. Before SanDisk, he worked as a HW engineer at Intel and Boeing. Jason has a BSEE from UC San Diego, MSEE from the University of Southern California, and an MBA from UC Berkeley.
MongoDB at AWS re:Invent 2020
While 2020 has been a challenging year, it has also given rise to new levels of innovative collaboration and agile thinking. Where better to experience both than at AWS re:Invent 2020? At MongoDB, we’re excited to partner with AWS on this free, 3-week virtual event, providing unlimited access to hundreds of sessions led by Cloud experts. Although we’ll miss the grand, buzzing halls of the Venetian Hotel and the celebratory sounds of slot machines this year, it’s still important to approach AWS re:Invent with a focused plan. Think of this year’s event as an opportunity to curate your own perfectly tailored experience. Check out this page for details of our fresh new lineup of deep-dives, targeted jam sessions and — of course — the annual MongoDB late-night party. Here are some of the highlights. AWS Jam — "Excel isn't a database!" Imagine this: It's your first week in a new job, and the VP of sales has already given you an important data task. The good news? From the start of the year, all your current sales data has been stored in MongoDB Atlas — allowing operational and analytical workloads to run on the live data set. The not-so-good news? That wasn't always the case. For years before they switched, their database (well, ”database”) of choice was… Excel. Fortunately someone took the initiative to export that data in CSV format and store it in S3, but now the sales team needs your help to analyze that data — and they need it fast. In our “Excel isn’t a database!” Jam Session, you’ll test and upgrade your skills by connecting MongoDB Atlas Data Lake to CSV data that’s been languishing in an S3 bucket. Then you’ll run an aggregation to complete the challenge and claim points. Game on! This jam session will be available on-demand for the duration of AWS re:Invent Databases & S3: Auto-archiving Breakout Session Databases are built for fast access, but this can also make them resource-intensive. As data grows, you may want to optimize performance (or cost) by migrating old or infrequently used data into cheap object storage. But this presents its own problems: automating the archival process, ensuring data consistency during failures, and either querying two data stores separately or building a query federation system. In this talk, you’ll learn about how we approached these problems while building Online Archive and Federated Query features into MongoDB Atlas, lessons learned from the experience, and how you can do the same. MongoDB Late Nite That’s right: it’s a party! In the spirit of Vegas, MongoDB will be hosting an interactive late-night bash complete with throw-back entertainment at our virtual after-hours event. Like Vegas, there’s something for everyone. Unlike Vegas, the odds are actually on your side. Get your adrenaline going and dial in for exclusive swag at our Home Shopping Network. Just sign on and dial into our custom QVC-reboot every hour for a chance to snag some really cool limited-release items. Stay tuned to the event website to find out what you can win, and when! Are you a Jeopardy lover? MongoDB Late Nite is your time to shine. Exercise your mental reflexes and get those synapses firing with hundreds of other party people inside episodes of dev-focused live trivia. And what kind of revelry is complete without a resident psychic on board? Join us at the Future of Coding for an interactive reading by a VERY accurate psychic. So kick back, grab a beverage and join us at the party from home. Let’s get in the spirit together! Sponsor Page/Online Booth Pop into our virtual sponsor booth at your convenience. Our product experts will be there to answer your questions one-on-one. Alternatively, if casually exploring resources is more your style, check out our self-serve content playlists. View these to dig deeper into MongoDB education, glean customer success stories and get up to speed on the latest product features.