Tackling a new world order

Sun-Rise-On-Earth-From-Space-Wallpaper-600x300So, my company recently (within the past couple years) made a major tactical shift from the world of Microsoft-centered development to a very strict adherence to open-source technologies. Driven primarily by our rapid growth and the inability/difficulty for much of our existing MS infrastructure to grow with us. It has served us well thus far but, we have grown beyond the point where it made sense to keep paying the massive licensing fees and developing creative workarounds for scalability. (I have no doubt many would disagree with this rationale. Just my opinion.) This has caused a lot of confusion and consternation throughout the organization.

For the most part, the development and architecture groups embraced this change. Like myself, we have a crew that is interested in the best solution for the job. Regardless of the fact we have been working, almost exclusively, in the MS .NET world for years and this change means a major commitment and investment by all parties. (Those not interested have moved-on without any hard feelings, hopefully, on either side.) However, this is still a fairly steep hill to climb. It’s not that we just need to switch languages from say, C# to java. That is the easy part. There is a whole new ecosystem to adjust (or re-adjust) to. In addition, we are changing our entire system architecture from traditional, datacenter-deployed, applications to cloud-based, globally-distributed applications. This involves all of us and takes significant learning and knowledge sharing across groups as well as new development practices, QA processes and deployment mechanisms and processes.

However, all of this is far beyond the scope of this blog post. Today I just want to begin by kicking off a series regarding one subject that has come-up a lot and is becoming a pain point for teams across the organization. That is that, now that we are cutting ties with our historical datastore (MS SQL Server), what open source database should I choose for my application?

Part of this decision has been helped by the fact that we have had various members of our development and architecture teams do formal reviews of various options. Currently, we have three solutions that are accepted as zero-barrier options. (By this, I just mean that the use of them has been approved and does not require additional justification. Not that there are not barriers such as a learning-curve.)

The current options are as follows:

  • Cassandra
  • MongoDb
  • MySQL

Great, polyglot persistence. No trouble there. Just use the right store for the job. Right? Well, remember, this is a whole new world for most of us here. (And, arguably, for everybody that might read this post.) We are used to one option, MS SQL Server. We would model our data using RDBMS standards. Normalizing data as best we could while balancing relative performance. Then model our application domain objects to stored procedures that did various joins, subqueries, etc. to get the data in the exact “shape” we needed to work with.

So, now the directive comes along to change your data store with a general preference being the use of the approved NoSQL options. So, the question, predictably, arises “Why do I need to change the way I have always worked?” Well, this is a complicated question to answer. And, really, the answer is you don’t. However, as with every decision you will ever make, you have to be willing to make trade-offs if you want to stay the course. The trade-offs in the new “cloudified” world of sticking with a traditional RDBMS like MySQL vs making the shift to something like Cassandra or MongoDb, are pretty steep. But there are still use cases where it would make sense.

So, in the next few posts I plan on tackling this question as well as some others to the best of my ability. In addition, I would like to lay-out what I feel are good guidelines for choosing among the various types of databases available given a knowledge of the following:

  • The type or shape of the data you plan to store or use.
  • The volume of the data. (How big is the data? Either individual items or number of items.)
  • How you plan to use the data.

Other ideas will likely creep-in as I tend to stray off-topic from time-to-time. But, I will attempt to stay focused and do my best to add value to this overall discussion both for my organization and to those out there that might be going through similar transitions at their work.

I hope this series is informative. Please add responses or ask questions as I go. I have a thick skin and can handle criticism. I tend to learn the most from those that don’t agree with me.

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Thoughts on Gluecon 2014

Just trying to digest all of the great conversation from this years Gluecon in Denver. Overall, I’d say it was a great success. Lots of interesting topics covered, not surprisingly, centered on the cloud, big data, DevOps and APIs. However discussions went well-beyond the standard discussions around high-level concepts, or “Use this cool new tool. It will make you the hit of the party!”

There were certainly a broad range of tools and products on display but, what I found (maybe naively?) was that, for the most part the talks were very well-vetted by the hosts to limit marketing spiel and offer really pertinent content to help us practitioners do our jobs in the best, most open, manner possible.

Some particularly strong takeaways for me were the following:

API design is not something you can fudge any longer. It takes serious thought. Real top-down thought. Ahead of time. You must think of how you want your API to be shaped. Meaning, start with your clients. Architects and developers have to start by thinking “If I were a client, with no knowledge of the implementation, how would I expect to interact with it?”

For example, let’s say we have a some content, say books, that we want to offer an API for. The first thing you should think is “Who are the clients of my API likely to be?” Depending on your product, your clients may be web and app developers in your company or some other company that wants to use our API to offer content to their customers or both. Either way, your client is likely to be a web or app developer. So, now that you know this, start designing your API to their needs. If you are lucky enough to know your potential clients, USE THAT ADVANTAGE!

More on this topic in future posts…

Building for scale has never been easier. Or more challenging. Sound like I’m confused? Well, maybe. But, what I mean is that the tools to build highly scalable systems have never been so available to us developers and architects. There was a time, not too long ago, that to build an application to handle the type of load that APIs like those from Twitter, Facebook, and many others are seeing  these days, you had to, typically, overbuild up-front. Over-provision hardware (even if just reserving rackspace and creating standard hardware specs to hasten hardware delivery time), shard your database of choice from the get-go (or at least think logically how you might), build complicated threading and synchronization logic into your code, etc. etc.

Now, while you still need to consider these things up-front, you have choices to ease the burden. Obviously, choosing a hosted cloud solution like aws, rackspace, azure, etc. is, at least in my humble opinion, a no-brainer. At least for most organizations that don’t have the resources of a google or Microsoft. With this decision made, you can start focusing on your app. And in that realm there are more choices than ever as well. From brilliant, auto-scaling, sharding, replicating databases like cassandra or riak (and others), right down to the languages you use. Java 8 comes with new, improved features like completable futures and the new, improved stream class. Then you have options like scala, node.js, etc. Take your pick.

But, this plethora of options also leads to the second part of my statement that this has also never been a more challenging time to build scalable apps. First, you have more to evaluate, and thus learn. Don’t get me wrong. The constant change of this field is the reason I got into it in the first place. I thrive on change. But not everybody does. Even on a given, hand-selected, team you are likely to have dissenters and individuals digging their heels in the dirt. Image how THIS concept scales to large teams and organizations.

That said, I see this as an exciting time of change and progress for our industry. And I/we can’t convince everybody of this. So, get on-board or get out of the way!

Deploying applications to the cloud must be quick, repeatable and predictable. Containers are the future. Learn the concepts. Pick a tool or tools and learn that/them. Then, when (not if) things change. You’ll be better prepared for it. That’s it. (Partially because this is an area I’m admittedly weak in myself.)

API SDKs suck! Ok, so I actually do not buy into this, but it was a very common theme (both sides well-represented) at this years Gluecon. Thanks mostly to an excellent day one keynote by John Sheehan at Runscope “API SDKs Will Ruin Your Life”.

Like I said, I don’t completely agree with this assertion. But, to be honest, I don’t think John does either. However, he and others made some good points. One that hit particularly close-to-home for me was the double-edged sword of how the SDK abstracts developer’s from the actual interface of an API. This abstraction eases adoption by you APIs clients. That is a VERY GOOD thing! However, as John stated, the vast majority of issues that occur with API integrations are “on the wire”. Meaning, more or less, something is wrong with the request or response. However, if you abstract this interaction from your clients, all they know is “my request did not succeed”. More API savvy developers may take the next step of inspecting the request/response before contacting you. But, if they do, barring an obvious issue like malformed requests or forgetting to pass auth, they will likely jus be faced with an unintelligible error message of some sort.

So, my counter to this argument is three-fold. Document you APIs well. Be it the old-fashioned way by manually producing help docs or with something, in my opinion, infinitely better like swagger. Just do it! It will save you many headaches in the future. Secondly, back to my first point, design your APIs intelligently with your clients in mind first. If your API is easy to navigate for an average person (test it out on somebody!), it will make the interaction less painful to begin with so your API may, potentially, need less abstraction by the SDK. Lastly I say you must strive to make the errors your API returns just as comprehensible as the non-errors. By this I mean things like returning proper error codes and human-readable descriptions. Not just a generic 400 with “Bad Request” or what have you. I know all-too-well this is hard to do up-front. You can’t predict all the ways requests may fail. But, if you try, you can think of the more common ones and handle them more elegantly. You are likely coding defensively against them to prevent failures on your end anyway. For those that arise after the fact, adapt. That is why you have that rapid, repeatable, deploy process mentioned above.

Summary

Ok, so I have rambled-on waaaayyyy too long and have not even come close to covering the above topics let alone concepts that piqued my interest but need more research on my part to speak to like cluster management with yarn or mesos. But suffice it to say, this is one of the most relevant, content-packed conferences going for the more technical audience. If you missed it this year, I highly recommend searching for the content and discussions sure to be posted in the coming days. And, see if you can make it next year. It will pay-off in spades.

Links

Excellent list of links to this years notes and presentations online provided by James Higginbotham.

http://launchany.com/gluecon-2014/