Tag Archives: Riak

The Future of Open Source Fiesta

April 28, 2014

On Monday, May 5th, Basho is co-hosting an open source happy hour and networking meetup. Partnering with GoGrid, we will bring together some of the greatest minds in open source to discuss current trends and where open source will be in the future. Drinks and appetizers will be provided. This meetup will take place from 6pm-8pm on May 5th at the 111 Minna Gallery in San Francisco. Space is limited, so be sure and RSVP quickly.

This meetup is also in conjunction with the Open Business Conference. Open Source has become ubiquitous in the enterprise and in the business layer, as more and more organizations are reaping its considerable benefits, including speed, efficiency and cost savings. Open Business Conference 2014 brings together the people who are building and deploying the latest in enabling technologies and solutions and teaches businesses how to put their data to use. Basho will be available to answer any questions about Riak and open source at the GoGrid booth. Open Business Conference takes place May 5-6 at the Palace Hotel in San Francisco.

To learn more about Basho’s partnership with GoGrid (and other partnerships), visit our Partners Page.

Basho

Riak for Gaming

April 16, 2014

The world of gaming can be unpredictable. It can be hard to judge if a game is going to be the next Angry Birds and experience exponential, global growth. Riak is designed to help gaming platforms handle this uncertainty with ease. Its focus on high availability means that all data remains accessibility, even during node failure. Its flexible data model and redundant, fault-tolerant design easily allows gaming platforms to store any type of data needed. Riak is also built for operational simplicity at scale, so Riak will seamlessly grow with data and popularity. Finally, the option for multi-datacenter replication means that gamers all over the world will get the same low-latency experience across multiple devices.

Top Use Cases for Riak in Gaming

  • Player Data: Riak provides low-latency, highly available data storage for key player data, including user and profile information, game performance, statistics and rankings, and more. Riak also provides many different tools for querying and indexing this data, such as Riak Search, Secondary Indexing, and MapReduce.
  • Session Storage: Riak is frequently used to store and serve session data with predictable low-latency – necessary for game play. Riak imposes no restrictions on the type of content stored (since all objects are stored on disk as binaries), so session data can be encoded in many ways and can evolve without administrative changes to schemas.
  • Social Information: Riak provides flexible, robust storage for social data such as social graph information, player profiles and relationships, and social authentication tokens.
  • Global Data Locality: When gaming, players require a low-latency experience, regardless of where they’re physically located. Otherwise, interrupted or slow game play can lead to poor user experience and possible user abandonment. Riak Enterprise’s multi-datacenter capabilities allow game data to be physically close to players and serve them data no matter where they happen to be.

Riak in Production

Riak is already in production by many top gaming platforms. Here’s a look at a few that have switched to Riak.

Rovio
Rovio is the creator of the popular mobile game, Angry Birds. Since user growth can be hard to predict, they needed an infrastructure that could support unexpected viral growth without failing or causing downtime. They selected Riak due to its ease-of-scale and fault tolerance. Riak now powers their new cartoon series, Angry Birds Toons, and new mobile games. Learn more about why they moved to Riak in this case study and video from GDC.

Hibernum
Hibernum is a creator and developer of unique gaming experiences that combine the latest in social gaming, top quality visuals and animations, and cutting edge design. They switched from a relational database to Riak due to the high availability, ability to scale to peak loads, and predictable operational cost. Riak is used to store user game information for one of their most popular social games. Check out the complete case study, Hibernum Selects Riak for User Data Storage.

Kiip
Kiip is a platform for building rewards and achievements into your games. Kiip replaced MongoDB with Riak in order to achieve low read/write latencies and horizontal scalability. Kiip uses Riak for storing and serving session and device data. Learn more from the video on scaling Riak to 25MM Ops/Day.

Riot Games
Riot Games is the creator of League of Legends and faced some challenges with supporting millions of concurrent players at any given moment. They switched to Riak from MySQL for their next generation stats system, which tracks gameplay statistics and stores terabytes of data that gets aggregated and presented to players in near real-time. More information on how they use Riak and why they selected it can be found here.

Data Modeling in Riak

Riak has a “schemaless” design. Objects are comprised of key/value pairs, which are stored in flat namespaces called buckets. Here are some common approaches to structuring gaming data with Riak’s key/value design:

Data Type Key Value
Player Data Login, Email, UUID Player Attributes (often stored as a JSON document); Player Rewards and Stats
Social Data Login, Email, UUID Player Profiles, Social Graph Information, Facebook/Twitter Tokens
Session Information User/Session ID Session Data
Image or Video Content Content Name, ID or Integer .JPG .PNG, .GIF or other image format; .MOV, .MPG, .MP4 or other video file format

To learn more about how gaming platforms can use Riak for their data needs, check out the complete overview, “Gaming on Riak: A Technical Introduction.” To get started with Riak, Contact Us or download it now.

Basho

Riak vs. Cassandra – A Brief Comparison

January 27, 2014

On the official Basho docs, we compare Riak to multiple other databases. We are currently working on updating these comparisons, but, in the meantime, we wanted to provide a more up-to-date comparison for one of the more common questions we’re asked: How does Riak compare to Cassandra?

Cassandra looks the most like Riak out of any other widely-deployed data storage technology in existence. Cassandra and Riak have architectural roots in Amazon’s Dynamo, the system Amazon engineered to handle their highly available shopping cart service. Both Riak and Cassandra are masterless, highly available stores that persist replicas and handle failure scenarios through concepts such as hinted handoff and read-repair. However, there are certain key differences between the two that should be considered when evaluating them.

Data Model

Amazon’s Dynamo utilized a Key/Value data model. Early in Cassandra’s development, a decision was made to diverge from keys and values toward a wide-row data model (similar to Google’s BigTable). This means Cassandra is a Key/Key/Value store, which includes the concept of Column Families that contain columns. With this model, Cassandra is able to handle high write volumes, typically by appending new data to a row. This also allows Cassandra to perform very efficient range queries, with the tradeoff being a more rigid data model since rows are “fixed” and non-sequential read operations often require several disk seeks.

On the other hand, Riak is a straight Key/Value store. We believe this offers the most flexibility for data storage. Riak’s schemaless design has zero restrictions on data type, so an object can be a JSON document at one moment and a JPEG at the next.

Like Cassandra, Riak also excels at high write volumes. Range queries can be a little more costly, though still achievable through Secondary Indexes. In addition, there are a number of data modeling tips and tricks for Riak that make it easy to expose access to data in ways that sometimes aren’t as obvious at first glance. Below are a few examples:

Multi-Datacenter Replication

In Riak, multi-datacenter replication is achieved by connecting independent clusters, each of which own their own hash ring. Operators have the ability to manage each cluster and select all or part of the data to replicate across a WAN. Multi-datacenter replication in Riak features two primary modes of operation: full sync and real-time. Data transmitted between clusters can be encrypted via OpenSSL out-of-the-box. Riak also allows for per-bucket replication for more granular control.

Cassandra achieves replication across WANs by splitting the hash ring across two or more clusters, which requires operators to manually define a NetworkTopologyStrategy, Replication Factor, a Replication Placement Strategy, and a Consistency Level for both local and cross data center requests.

Conflict Resolution and Object Versioning

Cassandra uses wall clock timestamps to establish ordering. The resolution strategy in this case is Last Write Wins (LWW), which means that data may be overwritten when there is write contention. The odds of data loss are magnified by (inevitable) server clock drift. More details on this can be found in the blog, “Clocks are Hard, or, Welcome to the Wonderful World of Distributed Systems.”

Riak uses a data structure called vector clocks to track the causal ordering of updates. This per-object ancestry allows Riak to identify and isolate conflicts without using system clocks.

In the event of a concurrent update to a single key, or a network partition that leaves application servers writing to Riak on both sides of the split, Riak can be configured to keep all writes and expose them to the next reader of that key. In this case, choosing the right value happens at the application level, allowing developers to either apply business logic or some common function (e.g. merge union of values) to resolve the conflict. From there, that value can be written back to Riak for its key. This ensures that Riak never loses writes.

For more information, visit Basho blog posts on Why Vector Clocks are Easy and Why Vector Clocks are Hard.

Riak Data Types, first introduced in Riak 1.4 and expanded in the upcoming Riak 2.0, are designed to converge automatically. This means Riak will transparently manage the conflict resolution logic for concurrent writes to objects.

Availability

In the event of server failures and network problems, Riak is designed to always accept read and write requests, even if the servers that are ordinarily responsible for that data are unavailable.

Cassandra will allow writes to (optionally) be stored on alternative servers, but will not allow that data to be retrieved. Only after the cluster is repaired and those writes are handed off to an appropriate replica server (with the potential data loss that timestamp-based conflict resolution implies, as discussed earlier) will the data that was written be available to readers.

Imagine a user working with a shopping cart when the application is unable to connect to the primary replicas. The user can re-add missing items to the cart but will never actually see the items show up in the cart (unless the application performs its own caching, which introduces more layers of complexity and points of failure).

Data Integrity

When handling missing or divergent/stale data, Riak and Cassandra have many similarities. Both employ a passive mechanism where read operations trigger the repair of inconsistent replicas (known as read-repair). Both also use Active Anti-Entropy, which builds a modified Merkle tree to track changes or new inserts on a per hash-ring-partition basis. Since the hash rings contain overlapping keys, the trees are compared and any divergent or missing data is automatically repaired in the background. This can be incredibly effective at combating problems such as bitrot, since Active Anti-Entropy does not need to wait for a read operation.

The key difference in implementation is that Cassandra uses short-lived, in-memory hash trees that are built per Column Family and generated as snapshots during major data compactions. Riak’s trees are on-disk and persistent. Persistent trees are safer and more conducive to ensuring data integrity across much larger datasets (e.g. 1 billion keys could easily cost 8-16GB of RAM in Cassandra versus 8-16GB of disk in Riak).

Summary

Both Cassandra and Riak are eventually consistent, scalable databases that have strengths for specific use cases. Each has hundreds of thousands of hours of engineering invested and the commercial backing and support offered by their respective companies, Datastax and Basho. At Basho, we have labored to make Riak very robust and easy to operate at both large and small scale. For more information on how Riak is being used, visit our Riak Users page. For a look at what’s to come, download the Technical Preview of Riak 2.0.

Tom Santero

Basho in 2013

December 30, 2013

2013 was a huge year for Basho Technologies and before we dive into 2014, we thought we’d take a moment to reflect on how far we’ve come.

Case Studies

2013 was the year of the Riak User. We love hearing about all the amazing ways companies across various industries are using Riak. This year, we were able to share dozens of exciting case studies. These include:

For even more Riak Users, check out the Users Page.

Releases

We released Riak 1.3, Riak 1.4, and the Technical Preview of Riak 2.0 this year. These releases added such features as Active Anti-Entropy, revamped Riak Control, queryability improvements, Riak Data Types, and much more. Be on the lookout for the general release of Riak 2.0 early next year.

This year we also open sourced Riak CS with the 1.3 release and released Riak CS 1.4. These releases added multi-part upload, Riak CS Control, and integration with OpenStack.

RICON

This year, we expanded RICON, Basho’s distributed systems conference, to both RICON East and RICON West. These were both sold out conferences that featured speakers from bitly, Comcast, Google, Netflix, Salesforce, The Weather Company, Turner Broadcasting, Twitter, and many more.

Partners

We drastically increased the number of Basho partners in 2013. For a full list of partners, check out the Partnerships Page. Some key ones to note include Tokyo Electron Device, SoftLayer, and Seagate.

Community

Our amazing community team hosted over 200 meetups around the world this year. On top of that, they also attended dozens of industry events to spread the word about Basho. Keep an eye on the Events Page to see where we’ll be in 2014.

2013 was a busy year but, with some exciting announcements coming, we look forward to an even busier 2014. Happy New Year!

Basho

Infographic: Down With Downtime

December 18, 2013

Downtime, planned or unplanned, is no longer an option. It can have a dramatic impact on revenue and lead to negative customer experiences and attrition. Luckily, distributed NoSQL databases (such as Basho Riak) are designed to provide high availability, even during network partition or server failure. This means there will never be an excuse for downtime again.

To help demonstrate the cost of downtime and how Riak can help, we have put together an infographic, “Down With Downtime.” Zoom in by clicking the image below.

If you are interested in getting started with Riak, you can download the latest version here. We also offer Tech Talks to help you and your team evaluate Riak.

Basho

"How is Riak different from Hadoop?"

October 28, 2013

The technology community is extremely agile and fast-paced. It can turn on a dime to solve business problems as they arise. However, with this agility comes budding terminology that can often provide false categorizations. This can lead to confusion, especially when companies evaluate new technologies based on a surface understanding of these terms. The world of data is full of these terms, including the notorious “NoSQL” and “big data.”

As described in a previous post, NoSQL is a misleading term. This term represents a response to changing business priorities that require more flexible, resilient architectures (as opposed to the traditional, rigid systems that often happen to use SQL). However, within the NoSQL space, there are dozens of players that can be as different from one another as they are from any of the various SQL-speaking systems.

Big data is another term that, while fairly self-explanatory, has been overused to the point of dilution. One reason why NoSQL databases have become necessary is because of their ability to easily scale to keep up with data growth. Simply storing a lot of data isn’t the solution though. Some data is more critical than others (and should be accessible no matter what) and some data needs to be analyzed to provide business insights. When digging into a business, big data is too vague a term to describe both of these use cases.

As these terms (to highlight a few) are used, it can lead to industry confusion. One area of confusion that we have experienced relates to Basho’s own distributed database, Riak, and the distributed processing system, Hadoop.

While these two systems are actually complementary, we are often asked “How is Riak different from Hadoop?”

To help explain this, it’s important to start with a basic understanding of both systems. Riak is a distributed database that is built for high availability, fault tolerance, and scalability. It is best used to store large amounts of critical data that applications and users need to constantly be able to access. Riak is built by Basho Technologies and can be used as an alternative to or in conjunction with relational databases (such as MySQL) or to other “NoSQL” databases (such as MongoDB or Cassandra).

Hadoop is a framework that allows for the distributed parallel processing of large data sets across clusters of computers. It was originally based on the “MapReduce” system, which was invented by Google. Hadoop consists of two core parts: the underlying Hadoop Distributed File System (HDFS), which ensures stored data is always available to be analyzed, and MapReduce, which allows for scalable computation by dividing and running queries over multiple machines. Hadoop provides an inexpensive, scalable solution for bulk data processing and is mostly used as part of an overarching analytics strategy, not for primary “hot” data storage.

One easy way to distinguish between the two is to look at some of the common use cases.

Riak Use Cases

Riak can be used by any application that needs to always have access to large amounts of critical data. Riak uses a key/value data model and is data-type agnostic, so operators can store any type of content in Riak. Due to the key/value model, certain industry use cases fit easily into Riak. These include:

  • Gaming – storing player data, session data, etc
  • Retail – underpinning shopping carts, product inventories, etc
  • Mobile – social authentication, text and multimedia storage, global data locality, etc
  • Advertising – serving ad content, session storage, mobile experiences, etc
  • Healthcare – prescription or patient records, patient IDs, health data that must always be available across a network of providers, etc

For a full list of use cases, check out our Users Page.

Hadoop Use Cases

Hadoop is designed for situations where you need to store unmodeled data and run computationally intensive analytics over that data. The original use cases of both MapReduce and Hadoop were to produce indexes for distributed search engines at Google and Yahoo respectively. Any industry that needs to do large scale analytics to better improve their business can use Hadoop. Some common examples include finance (build models to do accurate portfolio evaluations and risk analysis) and eCommerce (analyze shopping behavior to deliver product recommendations or better search results).

Riak and Hadoop are based on many of the same tenets, making their usage complementary for some companies. Many companies that utilize Riak today have created scripts, or processes, to pull data from Riak and push into other solutions (like Hadoop) for the purpose of historical archiving or future analysis. Recognizing this trend, Basho is exploring the creation of additional tools to simplify this process.

If you are interested in our thinking on these data export capabilities, please contact us.

In Summary

Every tool has its value. Hadoop excels at being used by a relatively small subset of the business to answer big questions. Riak excels at being used by a very large number of users and powering critical data for businesses.

Basho

Basho Releases eKinetic Driver and Integrated Riak Backend With Seagate Partnership

October 22, 2013

Today, Seagate has announced the availability of their Kinetic Open Storage platform, which simplifies data management, improves performance and scalability, all while lowering expenses. This fundamentally new architecture reduces costs by allowing applications to communicate directly with the storage system, eliminating the acquisition, deployment, and support costs of hyperscale storage infrastructures.

Basho has partnered with Seagate to help them develop this platform to provide interoperability and testing with Riak. Now, with the release of this platform, we want to make it easier for developers to test the Kinetic Open Storage platform with Riak. We have just released an alpha version of our eKinetic driver, which enables an Erlang-based high-performance socket connection to the drive. We have also released software to improve Riak backend compatibility by mapping a Riak backend to the drive library. Both are available for download https://github.com/basho-labs/riak_kinetic.

Not only does deploying Riak on this platform drastically simplify the management of data through a straightforward socket-based network interface, this simplification also increases I/O efficiency by removing bottlenecks and optimizing cluster management, data replication, migration, and active multi-datacenter performance. Additionally, it is expected that users will realize up to a 50% decrease in the Total Cost of Operations through simplified operations alone. Users can also maximize storage density through reduced power and cooling costs and build out cloud datacenters for even more savings.

Seagate Principal Technologist, James Hughes, will be speaking about the Kinetic Open Storage platform and Riak at RICON, Basho’s distributed systems conference. His talk, “Device Based Innovation to Enable Scale-Out Storage” will take place on October 29th at 12pm in Track Two. Seagate is also a sponsor of RICON.

For more information on Seagate’s Kinetic Open Storage platform, check out their full release. Additional information on the Basho/Seagate partnership can also be found here.

Basho

Scaling with Riak at ooVoo

October 2, 2013

Basho partner, Erlang Solutions, recently hosted a webinar that featured Riak powering the largest independent video communication service provider, ooVoo.

ooVoo has over 85 million users worldwide, with nearly 2.5 million users generating an average of 300 million minutes of video every day. These users also generate about 1,000 chat messages per second. With all of this activity, ooVoo adds nearly 40GB of data per day and now maintains tens of terabytes of data.

In 2012, ooVoo selected Riak to deploy new communication features and ensure no-single point of failure in their always-available architecture. Today, Riak is used to support cloud based chat history, rich interactive chat, group communication features, and an infinite retention policy.

In the webinar, ooVoo Senior Director and System Architect, Alex Fok, discusses their business requirements, architecture decisions, and business results from their deployment of Riak. The webinar is available here and can also be viewed below.

Basho

Riak CS vs. Riak

October 2, 2013

What Is Riak CS?

Riak CS is Basho’s open source large object (aka cloud storage) software, built on the rock-solid Riak database. It is API-compatible with Amazon’s S3 and OpenStack’s Swift object storage solutions.

In May of this year, we posted the top 5 questions we heard from customers and our community about Riak CS; today we’ll take a deeper dive into the technical details, specifically the differences between Riak CS and Riak itself.

Riak CS as Compared to Riak

Both Riak CS and Riak are, at their core, places to store objects. Both are open source and both are designed to be used in a cluster of servers for availability and scalability.

The fundamental distinction between the two is simple: Riak CS can be used for storing very large objects, into the terabyte size range, while Riak is optimized for fast storage and retrieval of small objects (typically no more than a few megabytes).

There are subtle differences; however, that can be obscured by the similarities between the two.

Why Would I Use Riak CS?

Riak CS is used for a variety of reasons. Some examples:

  • Private object storage services, for example for companies that want to store sensitive data behind their own firewalls.
  • Large binary object storage as part of a voice or video service.
  • An integrated component in an OpenStack cloud solution, storing and serving VM images on demand.

Tier 3, Yahoo! Japan, Datapipe, and Turner Broadcasting are just a few of the big names using Riak CS today.

What Does Riak CS Do That Riak Doesn’t?

Chunking

Riak CS carves large objects into small chunks of data to be distributed throughout a Riak cluster and, when used with Riak CS Enterprise, synchronized with remote data centers.

S3/OpenStack APIs

Without Riak CS, developers have the choice of using Riak’s native HTTP or Protocol Buffers APIs when developing solutions.

Riak CS adds compatibility with Amazon’s S3 and OpenStack’s Swift APIs. These offer very different semantics than Riak, and the advanced search capabilities in Riak such as Secondary Indexes and full text search are not available using S3 or Swift clients.

We strongly advise against it, but it is possible to work with Riak’s standard APIs “under the hood” when deploying a Riak CS solution.

Multi-Tenancy

The latest release of Riak offers no way to differentiate between clients. Riak CS, on the other hand, supports both authentication and authorization.

Work is actively underway to add a security model to Riak in the upcoming 2.0 release.

Buckets or Buckets?

Users of Riak CS store their objects in virtual containers (called buckets in Amazon S3 parlance, containers in OpenStack).

Riak also relies heavily on buckets for data storage and configuration but, despite the names, these buckets are not the same.

As an example of how this can cause confusion: the replication factor in Riak (the number of times a piece of data is stored in a cluster) is configurable per-bucket. Because Riak’s buckets do not underly the user buckets in Riak CS, this feature cannot be used to create tiered services.

Strong Consistency

Riak is designed to maximize availability; the price paid for that is delayed consistency when the network is split and clients are writing to both sides of the cluster.

Creating user accounts in Riak CS; however, led to the need for a mechanism to maintain strong consistency. If two people attempt to create user accounts with the same username on either side of a network partition, both cannot be allowed to succeed, or else a conflict will occur that is very difficult to automatically recover from.

Furthermore, user buckets in S3 (and OpenStack APIs as implemented in Riak CS) reside in a global rather than a user-specific namespace, so bucket creation must also be handled carefully.

Riak CS introduced a service named Stanchion that is designed to handle these specific requests to avoid conflicts. Stanchion is a single process running on a single Riak server (thus introducing a single point of failure for user account and bucket creation requests).

While it is possible to deploy Stanchion using common system tools to make a daemon process run in a highly available manner, Basho recommends doing so carefully and testing it thoroughly. Since the only impact of failure is to prevent user and bucket creation, it may be preferable to monitor and alert on failure. If two copies of Stanchion are running due to a network partition, its strong consistency guarantees will be lost.

With strong consistency options targeted for Riak 2.0, expect to see some changes.

Other Differences

Replication

Basho offers multi-datacenter replication with its Enterprise software licenses, and Riak CS Enterprise takes full advantage of that feature. Data can be written to one or more clusters in multiple data centers and be synchronized automatically between them.

There are two types of synchronization: real-time, which occurs as objects are written, and full sync, which happens on a periodic basis to compare the full contents of each cluster for any changes to be merged.

One key difference is that Riak CS maintains manifest files to track the chunks it creates, and it is these manifests that are distributed between clusters during real-time sync. The individual chunks are not synchronized until a full sync replication occurs, or until someone requests the file from a remote cluster. The manifest is made active for someone to retrieve the chunks after the original upload to the source cluster is complete.

Backends

A common mistake while installing Riak CS is to configure it using information specific to Riak rather than Riak CS. As an example, per the Riak CS installation instructions the relevant backend data store must be configured to riak_cs_kv_multi_backend, which is forked from Riak’s riak_kv_multi_backend. Using the latter will cause problems.

Riak (CS) Control

Riak Control is a web management console for Riak clusters; Riak CS Control is a web management console for Riak CS user accounts. Both are optional and both are useful in a Riak CS cluster.

Exposure to Internet

Exposing any database directly to the Internet is risky. Riak, currently lacking any concept of authentication, absolutely must not be accessible to untrusted networks.

Riak CS; however, is designed with Internet access in mind. It is still advisable to place a load balancer or proxy in front of a Riak CS cluster, for example to ease cluster maintenance/upgrades and to provide a central location to log and block potentially hostile access.

Riak CS servers will still have open Riak ports that must be protected from the Internet as you would any Riak servers.

Where to Next for Riak CS?

2013 has been a big year for Riak CS: it was released as open source in the spring, with OpenStack support added this summer. Still, there is much to do.

As mentioned above, improving or replacing Stanchion is a high priority.

We will continue to expand the API coverage for Riak CS. The next major targets are the copy object operations that Amazon S3 and OpenStack Swift offer.

Compression and more granular replication controls are also under consideration for future releases.

By building Riak CS atop the most robust open source distributed database in the world, we’ve created a very operationally friendly, powerful storage solution that can evolve to meet present and future needs. Feel free to give it a try if you aren’t already using it.

If you’re interested in hearing from the engineers who’ve made this software possible (and seeing just how far a highly available data storage solution can take you), join us October 29-30th for RICON West. RICON West is where Basho brings together industry and academia to discuss the rapidly expanding world of distributed systems, including Riak and Riak CS.

John Daily

Basho Events in October

September 30, 2013

While the biggest event of October is Basho’s distributed systems conference, RICON West, we will still be traveling the world to attend many other events this month. Here’s a look at where you can find us during the weeks leading up to RICON.

Monktoberfest: Basho’s Director of Marketing, Tyler Hannan, will be speaking at Monktoberfest on “Medieval Art, Collective Intelligence, and Language Abuse – The Ethos of Distributed Systems.” Monktoberfest will take place in Portland, ME from Oct. 3-4.

Erlang Factory Lite: Basho will have speakers at both the Chicago event (Oct. 4th) and the Berlin event (Oct. 16th). Check out talks from Chris Meiklejohn and Steve Vinoski to learn more about Riak, Erlang, and distributed systems.

CloudConnect Chicago: Basho is a sponsor and exhibitor of CloudConnect Chicago, taking place Oct. 21-23. Basho engineer, John Burwell, will also be speaking about building private clouds with Apache CloudStack and Riak CS.

O’Reilly Strata: Basho will be exhibiting and speaking at the upcoming O’Reilly Strata conference in New York from Oct. 28-30. Stop by our booth and find out why we will all be using distributed systems in the future.

For a full list of where we’ll be for the rest of the year, check out the Events Page. And don’t forget to get tickets to our nearly sold-out developers conference, RICON West.

Basho