Newsletter – Trends
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It has been several months since our last newsletter and we’ve been very busy working with a lot of new clients as well as getting the opportunity to continue working with some of our existing friends. We’ve also been busy working on our upcoming book, The Art of Scalability. The book will be released January 8th and is available now for preorder at Amazon, Barnes and Noble, Borders, and InformIT.
In our profession, we have a unique opportunity to study a lot of new technology as well as visit with hundreds of technology teams each year. This perspective allows us a vantage point to spot trends that are occurring across the technology spectrum. In this newsletter we are going to cover three of these technology trends that we think you should at least be aware of. Each organization and product offering is different so the applicability of these is going to need to be determined on an individual basis.
The concept of continuous deployment is the natural extension to continuous integration that is the practice of checking code into the source code repository early and often, compiling the code, and performing the integration tests on the new code. The goal of which is to ease the often very painful process of integrating multiple developer’s code after weeks of independent work. In order to make this process the most effective the automation of builds and smoke tests are highly recommended. For more information on continuous integration there are a lot of resources such as these books and articles.
Continuous deployment is when all code that is written for an application is immediately deployed into production. While still a very new concept, there are a growing number of companies that are beginning to adopt this process. Flicker and IMVU are two of the earliest. Eric Ries, CTO of IMVU, believes that this approach can improve software quality due to the discipline, automation, and rigorous standards that are required. In order to be successful Eric suggest a 5 step approach that includes continuous integration, source code commit checks, deployment scripts, alerting, and root cause analysis. You can read more about this process in a recent post.
Before dismissing this idea as not right for your organization consider what one of our clients does that achieves some of the benefits of the approach without so much of the risk. This particular company uses its own software, which many SaaS companies do at least from an administrative perspective, and they deploy each night’s build onto their internal system. They do not deploy each build onto their customer’s production environments but instead wait until the iteration is complete. The concern over disrupting the company’s internal operations are enough to enforce the rigor and achieve higher quality without taking on the risk of disrupting their customers.
Key-Value Stores and Task Specific Databases
In most Software as a Service or eCommerce applications the database is the central part of the entire system. While relational database management systems (RDBMS) are scalable as we have described in many of our posts, we also know that it can be intimidating for some technology orgs.
What we have seen and expect to see more of is the use of in memory key-value stores such as memcached and redis as a shared memory object cache that is the primary data source for the service or application. Writes work their way back to the relational database asynchronously and reads into the object cache work their way forward either scheduled or on demand. An even more cutting edge trend, although the term has been around since at least 1998, is memory-based architectures where the memory storage is the system of record and there is no relational database or persistent storage device.
A similar trend is the utilization of task specific databases such as Apache CouchDB that is a document-oriented database. CouchDB allows objects, that consist of named fields, to be queried and indexed in a MapReduce fashion and also offers incremental replication with bi-directional conflict resolution. This is obviously not a relational database nor is it an object oriented database but rather it is a query-able and index-able, table oriented reporting engine. The advantages are simpler implementation and administration as well as improved performance for a very specific task.
As services become more specialized and service level agreements demand faster response times, in memory data stores and task specific databases are very likely to be involved in more architectures as a layer between the application servers and the persistent storage or in place of them.
While not really a hot new trend this cloud computing is still at such a fledgling stage and evolving so rapidly that it will pay to keep a close eye on it. Some of the more recent introductions by Amazon in their cloud portfolio include auto scaling, load balancing, monitoring, and VPN. Auto Scaling allows you to automatically scale Amazon EC2 instances up or down according to predefined conditions. Instead of running your own software load balancer such as HAProxy, Elastic Load Balancing can perform the distribution of incoming traffic across multiple instances. Monitoring is now available through CloudWatch for EC2 instances but it is still pretty featureless other than load and traffic. For companies interested in extending their existing management capabilities such as security services, firewalls, and intrusion detection systems to include their AWS resources, Amazon now offers virtual private cloud. This enables companies to connect their existing infrastructure to a set of isolated AWS compute resources via a Virtual Private Network (VPN).
These are all Amazon specific functionality but the addition of these features are either already offered by other cloud providers or can be expected shortly. We still are weary to recommend a full production deployment in a single provider’s cloud but often see this as a viable solution for many customers for non-production environments, disaster recovery, and surge or flex capacity.