Click here to close now.


Linux Containers Authors: Carmen Gonzalez, Liz McMillan, Elizabeth White, AppDynamics Blog, Pat Romanski

Related Topics: @CloudExpo, Java IoT, Microservices Expo, Linux Containers, Open Source Cloud, Ruby-On-Rails

@CloudExpo: Article

Top Six Ruby on Rails Deployment Methods in AWS: Pros & Cons

I’ll examine various deployment choices in detail, walk through a thorough analysis and then provide recommendations

Setting up a deployment process on the cloud means a variety of choices. Most likely you're prepared to make some tradeoffs. But getting a view across these potential tradeoffs can be difficult. Here are six popular deployments and advice for making the best choice for your organization's needs.

Let's assume you want a deployment for a small startup with fewer than 20 developers, each needing to host a web app that's gaining traction and for which rapid growth is expected. Its requirements are as follows:

  • Autoscaling support to handle expected surges in demand
  • Maximizing developer efficiency by automating tedious tasks and improving dev flow
  • Encouraging mature processes for building a stable foundation as the codebase grows
  • Maintaining flexibility and agility to handle hotfixes of a relatively immature codebase
  • Counting on a few sources to fail, because any of them can cause deployment failure - imagine GitHub failing or a required plugin becoming unavailable

Narrowing the focus a bit more, let's assume the codebase is using Ruby on Rails, as is often the case. We'll examine various deployment choices in detail, walk through a thorough analysis and then provide recommendations for anyone that fits our sample client profile.

1. The Plain Vanilla AMI Method
Amazon OpsWorks: This proven deployment is a well-tested Amazon OpsWorks Standard recommendation. Each time a new node comes up fresh, it requires running all Chef recipes. To automate this process, Cloud-init is used to run scripts for handling code and environment updates that occur when running nodes.

Pros: This approach requires no AMI management. The process is straightforward, self-documenting and brings up a clean environment every time. Updates and patches are applied very quickly.

Cons: Bringing up new instances is extremely slow, there are many moving parts, and there's a high risk of failure.

Bottom Line: While this is a clean solution, the frequent-failure rate and amount of time needed for bringup makes the Plain Vanilla AMI impractical for a use case with autoscaling.

2. The Bake-Everything AMI Method
This deployment option is proven to work at Amazon Video and Netflix. It runs all Chef recipes once, fetches the codebase and then bakes and uses the AMI. Each change requires a new AMI and an ASG replacement within the ELB, including code and environment changes.

Keep in mind that the environment and configuration management parts of the deployment still need automation using tools like Chef and Puppet. Lack of automation can otherwise make AMI management a nightmare, as one tends to lose track of how the environment actually looks within the AMI.

Pros: Provides the fastest bringup, requires no installation, and includes the fewest moving parts, so error rates are very low.

Cons: Each code deployment requires baking a new AMI. This requires a lot of effort to ensure that the process is as fast as possible in order to avoid developer bottlenecks. This setup also makes it harder to deploy hotfixes.

Bottom Line: This is generally a best practice, but requires a certain level of codebase maturity and a high level of infrastructure sophistication. For example, Netflix has spent a lot of time speeding up the process of baking AMIs by using their Aminator project.

3. A Hybrid Method Using Chef to Handle Complete Deployment
This method strikes a balance between the Plain Vanilla AMI and the Bake-Everything AMI. An AMI is baked using Chef for configuration and environment, but one can't check the codebase or deploy the app. Chef does those once the node is brought up.

Pros: Since all packages are pre-installed, this method is significantly faster than using a Plain Vanilla AMI. Also, since the code is pulled once a node is commissioned, the ability to provide hotfixes is improved.

Cons: Because we're relying on Chef in production, there's a dependency on the repository, and pulling from the repository may fail.

Bottom Line: We consider this to be a medium-risk implementation due to its reliance on Chef.

4. A Hybrid Method Using Capistrano to Handle Code Deployment
This is similar to the hybrid Chef deployment approach, but with code deployed through Capistrano. Capistrano is a mature platform for deploying Rails code that includes several features and fail-safe mechanisms that make it better than Chef. In particular, if pull from the repository fails, Capistrano deploys an older revision from its backups.

Pros: The same as for the Chef hybrid, except that Capistrano is more mature than Chef, especially in handling repository failures.

Cons: It requires two tools instead of one, which increases management overhead even though they're tied together. In addition, the gap between environment and code is wider, and managing the tools separately is difficult.

Bottom Line: Capistrano is a better Rails solution for code deployment than Chef, and the ability to apply fixes quickly may make it the best solution.

5. The AMI-Bake and CRON-Based Chef-Client Method
This deployment method resembles that of the hybrids. However, it provisions features allow auto-propagation of changes because each AMI runs chef-client every N minutes. New AMIs are baked only for major changes. It can provide continuous deployment, but continuous deployment is an aggressive tactic that requires excellent continuous integration on the back end.

Pros: Allows continuous code deployment.

Cons: It's prone to errors if Continuous Integration is not stable. In addition, Chef re-bootstraps aren't reliable and may fail.

Bottom Line: Not recommended unless CI is solid.

6. The Cloud-Init and Docker Method
All indications are that Docker is the best choice for this use case. It comes closer to a bake-everything solution while getting around bake-everything's biggest drawbacks. It allows AMIs to be baked once and rarely changes after that. Both the environment and the app code are contained inside an LXC container, with each AMI consisting of one container. Upon code deployment, a new container is simply pushed, which provides deployment-process flexibility.

Pros: Docker containers provide a history with which one can compare containers, helps with issues of undocumented steps in image creation. Code and environment are tied together. The repository structure of containers leads to faster deployment than does which baking a new AMI. Docker also helps to create a local environment similar to the production environment.

Cons: Docker is still in early phases of development and suffers from some growing pains, including a few bugs, a limited tools ecosystem, some app compatibility issues and a limited feature set.

Bottom Line: If you adopt this approach, you'll be doing considerable trailblazing. There's little information available, so comparing notes with other pioneers will be helpful.

While there are many options for deploying Ruby on Rails in AWS environments, there isn't a single best solution. Taking the time to review the options and tradeoffs can save headaches along the way. Talk to peers and experienced consultants about their experiences before making the final decisions.

What are your comments in regard to using these deployments?

More Stories By Ali Hussain

Ali Hussain is CTO & Co-Founder of Flux7 Labs. He has been designing scalable and distributed systems for the last decade and is an AWS Certified Solutions Architect, Associate Level, earning this recognition with a score of 95%.

He began his career at Intel as part of the performance modeling team for Intel’s Atom microprocessor where he focused on benchmarking, power usage and workload optimization. Ali spent four years focused on performance modeling at ARM, Inc. At ARM he optimized the latency and throughput characteristics of systems, modeled performance, and brought a data-driven methodology to performance analyses. Ali acquired his passion for distributed systems while earning his MS at the University of Illinois at Urbana-Champaign. His Bachelor of Science (High Honors) in Computer Engineering was obtained from the University of Texas at Austin.

His current interests in Flux7 are in Enterprise Migration and configuration management

Comments (0)

Share your thoughts on this story.

Add your comment
You must be signed in to add a comment. Sign-in | Register

In accordance with our Comment Policy, we encourage comments that are on topic, relevant and to-the-point. We will remove comments that include profanity, personal attacks, racial slurs, threats of violence, or other inappropriate material that violates our Terms and Conditions, and will block users who make repeated violations. We ask all readers to expect diversity of opinion and to treat one another with dignity and respect.

@ThingsExpo Stories
SYS-CON Events announced today that Dyn, the worldwide leader in Internet Performance, will exhibit at SYS-CON's 17th International Cloud Expo®, which will take place on November 3-5, 2015, at the Santa Clara Convention Center in Santa Clara, CA. Dyn is a cloud-based Internet Performance company. Dyn helps companies monitor, control, and optimize online infrastructure for an exceptional end-user experience. Through a world-class network and unrivaled, objective intelligence into Internet conditions, Dyn ensures traffic gets delivered faster, safer, and more reliably than ever.
Today air travel is a minefield of delays, hassles and customer disappointment. Airlines struggle to revitalize the experience. GE and M2Mi will demonstrate practical examples of how IoT solutions are helping airlines bring back personalization, reduce trip time and improve reliability. In their session at @ThingsExpo, Shyam Varan Nath, Principal Architect with GE, and Dr. Sarah Cooper, M2Mi's VP Business Development and Engineering, will explore the IoT cloud-based platform technologies driving this change including privacy controls, data transparency and integration of real time context w...
Who are you? How do you introduce yourself? Do you use a name, or do you greet a friend by the last four digits of his social security number? Assuming you don’t, why are we content to associate our identity with 10 random digits assigned by our phone company? Identity is an issue that affects everyone, but as individuals we don’t spend a lot of time thinking about it. In his session at @ThingsExpo, Ben Klang, Founder & President of Mojo Lingo, will discuss the impact of technology on identity. Should we federate, or not? How should identity be secured? Who owns the identity? How is identity ...
The IoT market is on track to hit $7.1 trillion in 2020. The reality is that only a handful of companies are ready for this massive demand. There are a lot of barriers, paint points, traps, and hidden roadblocks. How can we deal with these issues and challenges? The paradigm has changed. Old-style ad-hoc trial-and-error ways will certainly lead you to the dead end. What is mandatory is an overarching and adaptive approach to effectively handle the rapid changes and exponential growth.
The buzz continues for cloud, data analytics and the Internet of Things (IoT) and their collective impact across all industries. But a new conversation is emerging - how do companies use industry disruption and technology enablers to lead in markets undergoing change, uncertainty and ambiguity? Organizations of all sizes need to evolve and transform, often under massive pressure, as industry lines blur and merge and traditional business models are assaulted and turned upside down. In this new data-driven world, marketplaces reign supreme while interoperability, APIs and applications deliver un...
Too often with compelling new technologies market participants become overly enamored with that attractiveness of the technology and neglect underlying business drivers. This tendency, what some call the “newest shiny object syndrome,” is understandable given that virtually all of us are heavily engaged in technology. But it is also mistaken. Without concrete business cases driving its deployment, IoT, like many other technologies before it, will fade into obscurity.
Electric power utilities face relentless pressure on their financial performance, and reducing distribution grid losses is one of the last untapped opportunities to meet their business goals. Combining IoT-enabled sensors and cloud-based data analytics, utilities now are able to find, quantify and reduce losses faster – and with a smaller IT footprint. Solutions exist using Internet-enabled sensors deployed temporarily at strategic locations within the distribution grid to measure actual line loads.
The Internet of Everything is re-shaping technology trends–moving away from “request/response” architecture to an “always-on” Streaming Web where data is in constant motion and secure, reliable communication is an absolute necessity. As more and more THINGS go online, the challenges that developers will need to address will only increase exponentially. In his session at @ThingsExpo, Todd Greene, Founder & CEO of PubNub, will explore the current state of IoT connectivity and review key trends and technology requirements that will drive the Internet of Things from hype to reality.
The Internet of Things (IoT) is growing rapidly by extending current technologies, products and networks. By 2020, Cisco estimates there will be 50 billion connected devices. Gartner has forecast revenues of over $300 billion, just to IoT suppliers. Now is the time to figure out how you’ll make money – not just create innovative products. With hundreds of new products and companies jumping into the IoT fray every month, there’s no shortage of innovation. Despite this, McKinsey/VisionMobile data shows "less than 10 percent of IoT developers are making enough to support a reasonably sized team....
You have your devices and your data, but what about the rest of your Internet of Things story? Two popular classes of technologies that nicely handle the Big Data analytics for Internet of Things are Apache Hadoop and NoSQL. Hadoop is designed for parallelizing analytical work across many servers and is ideal for the massive data volumes you create with IoT devices. NoSQL databases such as Apache HBase are ideal for storing and retrieving IoT data as “time series data.”
Today’s connected world is moving from devices towards things, what this means is that by using increasingly low cost sensors embedded in devices we can create many new use cases. These span across use cases in cities, vehicles, home, offices, factories, retail environments, worksites, health, logistics, and health. These use cases rely on ubiquitous connectivity and generate massive amounts of data at scale. These technologies enable new business opportunities, ways to optimize and automate, along with new ways to engage with users.
The IoT is upon us, but today’s databases, built on 30-year-old math, require multiple platforms to create a single solution. Data demands of the IoT require Big Data systems that can handle ingest, transactions and analytics concurrently adapting to varied situations as they occur, with speed at scale. In his session at @ThingsExpo, Chad Jones, chief strategy officer at Deep Information Sciences, will look differently at IoT data so enterprises can fully leverage their IoT potential. He’ll share tips on how to speed up business initiatives, harness Big Data and remain one step ahead by apply...
There will be 20 billion IoT devices connected to the Internet soon. What if we could control these devices with our voice, mind, or gestures? What if we could teach these devices how to talk to each other? What if these devices could learn how to interact with us (and each other) to make our lives better? What if Jarvis was real? How can I gain these super powers? In his session at 17th Cloud Expo, Chris Matthieu, co-founder and CTO of Octoblu, will show you!
As a company adopts a DevOps approach to software development, what are key things that both the Dev and Ops side of the business must keep in mind to ensure effective continuous delivery? In his session at DevOps Summit, Mark Hydar, Head of DevOps, Ericsson TV Platforms, will share best practices and provide helpful tips for Ops teams to adopt an open line of communication with the development side of the house to ensure success between the two sides.
SYS-CON Events announced today that ProfitBricks, the provider of painless cloud infrastructure, will exhibit at SYS-CON's 17th International Cloud Expo®, which will take place on November 3–5, 2015, at the Santa Clara Convention Center in Santa Clara, CA. ProfitBricks is the IaaS provider that offers a painless cloud experience for all IT users, with no learning curve. ProfitBricks boasts flexible cloud servers and networking, an integrated Data Center Designer tool for visual control over the cloud and the best price/performance value available. ProfitBricks was named one of the coolest Clo...
SYS-CON Events announced today that IBM Cloud Data Services has been named “Bronze Sponsor” of SYS-CON's 17th Cloud Expo, which will take place on November 3–5, 2015, at the Santa Clara Convention Center in Santa Clara, CA. IBM Cloud Data Services offers a portfolio of integrated, best-of-breed cloud data services for developers focused on mobile computing and analytics use cases.
SYS-CON Events announced today that Sandy Carter, IBM General Manager Cloud Ecosystem and Developers, and a Social Business Evangelist, will keynote at the 17th International Cloud Expo®, which will take place on November 3–5, 2015, at the Santa Clara Convention Center in Santa Clara, CA.
Developing software for the Internet of Things (IoT) comes with its own set of challenges. Security, privacy, and unified standards are a few key issues. In addition, each IoT product is comprised of at least three separate application components: the software embedded in the device, the backend big-data service, and the mobile application for the end user's controls. Each component is developed by a different team, using different technologies and practices, and deployed to a different stack/target - this makes the integration of these separate pipelines and the coordination of software upd...
Mobile messaging has been a popular communication channel for more than 20 years. Finnish engineer Matti Makkonen invented the idea for SMS (Short Message Service) in 1984, making his vision a reality on December 3, 1992 by sending the first message ("Happy Christmas") from a PC to a cell phone. Since then, the technology has evolved immensely, from both a technology standpoint, and in our everyday uses for it. Originally used for person-to-person (P2P) communication, i.e., Sally sends a text message to Betty – mobile messaging now offers tremendous value to businesses for customer and empl...
"Matrix is an ambitious open standard and implementation that's set up to break down the fragmentation problems that exist in IP messaging and VoIP communication," explained John Woolf, Technical Evangelist at Matrix, in this interview at @ThingsExpo, held Nov 4–6, 2014, at the Santa Clara Convention Center in Santa Clara, CA.