Zato—Agile ESB, SOA, REST and Cloud Integrations in Python
Zato is a Python-based platform for integrating applications and exposing back-end services to front-end clients. It's an ESB (Enterprise Service Bus) and an application server focused on data integrations. The platform doesn't enforce any limits on architectural style for designing systems and can be used for SOA (Service Oriented Architecture), REST (Representational State Transfer) and for building systems of systems running in-house or in the cloud.
At its current version of 1.1 (at the time of this writing), Zato supports HTTP, JSON, SOAP, SQL, AMQP, JMS WebSphere MQ, ZeroMQ, Redis NoSQL and FTP. It includes a browser-based GUI, CLI, API, security, statistics, job scheduler, HAProxy-based load balancer and hot-deployment. Each piece is extensively documented from the viewpoint of several audiences: architects, admins and programmers.
Zato servers are built on top of gevent and gunicorn frameworks that are responsible for handling incoming traffic using asynchronous notification libraries, such as libevent or libev, but all of that is hidden from programmers' views so they can focus on their job only.
Servers always are part of a cluster and run identical copies of services deployed. There is no limit on how many servers a single cluster can contain.
Each cluster keeps its configuration in Redis and an SQL database. The former is used for statistics or data that is frequently updated and mostly read-only. The latter is where the more static configuration shared between servers is kept.
Zato promotes loose coupling, reusability of components and hot-deployment. The high-level goal is to make it trivial to access or expose any sort of information. Common integration techniques and needs should be, at most, a couple clicks away, removing the need to reimplement the same steps constantly, slightly differently in each integration effort.
Everything in Zato is about minimizing the interference of components on each other, and server-side objects you create can be updated easily, reconfigured on fly or reused in other contexts without influencing any other.
This article guides you through the process of exposing complex XML data to three clients using JSON, a simpler form of XML and SOAP, all from a single code base in an elegant and Pythonic way that doesn't require you to think about the particularities of any format or transport.
To speed up the process of retrieving information by clients, back-end data will be cached in Redis and updated periodically by a job-scheduled service.
The data provider used will be US Department of the Treasury's real long-term interest rates. Clients will be generic HTTP-based ones invoked through curl, although in practice, any HTTP client would do.
The Process and IRA Services
The goal is to make it easy and efficient for external client applications to access long-term US rates information. To that end, you'll make use of several features of Zato:
Scheduler will be employed to invoke a service to download the XML offered by treasury.gov and parse interesting data out of it.
Redis will be used as a cache to store the results of parsing the XML.
Zato encourages the division of each business process into a set of IRA services—that is, each service exposed to users should be:
Interesting: services should provide a real value that makes potential users pause for a moment and, at least, contemplate using the service in their own applications for their own benefit.
Reusable: making services modular will allow you to make use of them in circumstances yet unforeseen—to build new, and possibly unexpected, solutions on top of lower-level ones.
Atomic: a service should have a well defined goal, indivisible from the viewpoint of a service's users, and preferably no functionality should overlap between services.
The IRA approach closely follows the UNIX philosophy of "do one thing and do it well" as well as the KISS principle that is well known and followed in many areas of engineering.
When you design an IRA service, it is almost exactly like defining APIs between the components of a standalone application. The difference is that services connect several applications running in a distributed environment. Once you take that into account, the mental process is identical.
Anyone who already has created an interesting interface of any sort in a single-noded application written in any programming language will feel right like home when dealing with IRA services.
From Zato's viewpoint, there is no difference in whether a service corresponds to an S in SOA or an R in REST; however, throughout this article, I'm using the the former approach.
Dariusz Suchojad is a systems architect specializing in SOA/ESB/EAI/BPM/SSO with 12 years of experience completing projects for enterprise customers in telecommunications and banking.
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