Middleware (or how do our processes speak to one-another)

About multi-process programming

In modern software engineering, you quickly reach the point where one process cannot handle all the tasks by itself. For performance, maintainability or reliability reasons you do have to write multi-process programs. One can also reach the point where he wants its softwares to speak to each-other. This situation raises the question: how will my processes “talk” to each other?

If you already have written such programs in C, you are probably familiar with the network sockets concept. Those are handy (at least compared to dealing with the TCP/IP layer yourself): it offers an abstraction layer and lets you have endpoints for sending and receiving data from a process to another. But quickly some issues arise:

  • How to handle many-to-many communications?
  • How to scale the solution?
  • How to have a clean code that doesn’t have to handle many direct connections and painful scenarios like disconnection/re-connection?
  • How can I handle safely all the corner cases with blocking/non-blocking reads/writes?

Almost every developer or every company has its own way to answer those questions, with the development of libraries responsible of communications between processes.

Of course, we do have our own solution too :)

So let’s take a look on what we call MiddleWare, our abstraction layer to handle communication between our processes and software instances.

What is MiddleWare ?

At Intersec, the sockets were quickly replaced by a first abstraction layer called ichannels. These channels basically simplify the creation of sockets, but we still deal with a point-to-point communication. So we started the development of MiddleWare, inspired by the works of iMatix on ØMQ.

First, let see how things were done before Middleware:

Middleware-img1

 

As you can see, every daemon or process had to open a direct connection to the other daemon he wanted to talk to, which leads to the issues described above.

Now, after the introduction of our MiddleWare layer:

Middleware-img2

So what MiddleWare is about? MiddleWare offers an abstraction layer for developers. With it, no need to manage connections and handle scenarios such as disconnection/re-connection anymore. We now communicate to services or roles, not to processes nor daemons.

MiddleWare is in charge of finding where the receiver is located and routing the message accordingly.

This solves many of the problems we were talking about earlier: the code of a daemon focuses on the applicative part, not on the infrastructure / network management part. It is now possible to have many-to-many communications (sending a message to N daemons implementing the same role) and the solution is scalable (no need to create multiple direct connections when adding a new service).

Services vs roles

MiddleWare is able to do service routing and/or role routing. A service is basically a process, the user can specify a host identifier and an instance identifier to get a channel to a specific instance of a service.

Processes can also expose roles: a role is a contract that associates a name with a duty and an interface. Example: "DB:master" can be a role of the master of the database, the one which can write in it, whereas "DB:slave" can be a role for a slave of the database, which has read-only replicate of it. One can also imagine a "User-list:listener" for example, which allows to register a callback for any user-list update.

Roles dissociate the processes from the purpose and allow extensibility of the software by allowing run-time additions of new roles in existing processes. Roles can be associated to a constraint (for example “unique” in cluster/site).

Those roles can also be attached to a module, as described in one of our previous post. As module can be easily rearranged, this adds another layer of abstraction between the code and the actual topology of the software.

Some examples from the API

How does an API for such a feature look like?

As described above, one of the main ideas of MiddleWare is to ease inter-processes communication handling, and let the developer focus on the applicative part of what he is doing. So it’s important to have very few steps to use the “basic” features: create a role if needed, create a channel and use it and handle replies.

So first of all, let’s take a look at the creation of a channel:

And here you are, no need to do more: no connection management, no need to look for the location of the service and the right network address in the product configuration. A simple function call give you a mw_channel_t pointer you can use to send messages. The first argument is what we call a service at intersec (as said above, it is basically a process). Here we just want to have a channel to our DB service. The second and third arguments indicate an host identifier and an instance identifier, if we want to target a specific instance of this service. Here, we just want a channel that targets all the available instances of the DB service by specifying -1 as both host and instance ids. Finally, the last argument indicates whether a direct connection is needed or not, but we will come back to this later.

Now let see some roles. Processes can register/unregister a role with that kind of API:

Pretty simple, isn’t it? All you need to do is give a name to your role. If we want to use a more complex role, with a unique in cluster constraint, we do have another function to do so:

The only difference is the need of a callback, which takes as arguments the name of the role and an enum value. This enum represents the status of the role. The callback will be called when the role is granted to a process by MiddleWare: the new owner get a MW_ROLE_OWNER status in its callback, the others get the MW_ROLE_TAKEN value.

On the client side, if you want to declare your role, all you have to do is:

And chan can now be used to send messages to our process which registered the "db:master" role.

How does this (wonderful) functionality work?

The key of MiddleWare is its routing tables. But to understand how it works, I need to introduce to you another concept of our product at Intersec: the master-process. No doubt it will ring a bell, as it is a common design pattern.

In our product, a single process is responsible for launching every sub-process and for monitoring them. This process is called the master process. It does not do much, but our products could not work without it. It detects when one of its child goes down and relaunch it if needed. It also handles communications to other software instances.

Now that you know what a master is in our Intersec environment, let’s go back to MiddleWare and its routing tables.

By default, the routing is done by our master process: every message is transmitted to the master which forwards it to the right host and then the right process.

The master maintains routing tables in order to be resilient to network connectivity issues. Those routing tables are built using a path-vector-like algorithm.

So let’s take a look to another picture which show the communication with more details:

Middleware-img3

As we can see, MiddleWare opens connections between every master processes and their childs. There are also connections between each master. From the developer’s standpoint, this is completely transparent. One can ask for a channel from the Core daemon to the Connector one, or a channel between the two Computation daemons for example, and then start to send/receive messages on these channels. MiddleWare will route these messages from the child lib to the master on the same host, then to the master on the receiving host, to finally transfer it to the destination process.

In case you expect a large amount of data to go through a channel, it is still possible to ask for a direct connection to a process during the creation of that channel. MiddleWare will still handle all the connection management complexity and from that point, everything will work exactly the same. Note that in our implementation we never have the guarantee that a message will go through a direct link, as MiddleWare will still route the queries throught the master if the direct link is not ready yet. Moreover, every communication from a service to another will use the direct link as soon as it exists.

Tradeoffs

Having such a layer in a software does not come without some drawbacks. The use of MiddleWare creates an overhead introduced by the abstraction cost: the routing table creation adds a bit of traffic each time a process starts or stop, or when roles are registered or unregistered.

As start-up and shutdown are not critical parts of the execution for us, it is fine to have a small overhead here. In the same way, roles registrations are not frequent, it is not an issue to add some operations during this step.

Finally, high traffic may put some load on our master process that must route the messages. Not a big issue on that one too, as our master does not do much beside message routing. The main responsibility of this process is to monitor its children, no complex calculation or time-consuming operations here. Moreover, if an heavy traffic is expected between two daemons, it is a good practice to ask for a direct link. This decreases the load on the master and therefore the risk of impacting MiddleWare.

C Modules

We do write complex software, and like everyone doing so, we need a way to structure our source code. Our choice was to go modular. A module is a singleton that defines a feature or a set of related feature and exposes some APIs in order for other modules to access these features. Everything else, including the details of the implementation, is private. Examples of modules are the RPC layer, the threading library, the query engine of a database, the authentication engine, … Then, we can compose the various daemons of our application by including the corresponding modules and their dependencies.

Most modules maintain an internal state and as a consequence they have to be initialized and deinitialized at some point in the lifetime of the program. An internal rule at Intersec is to name the constructor {module}_initialize() and the destructor {module}_shutdown(). Once defined, these functions have to be called and this is where everything become complicated when your program has tens of modules with complex dependencies between them.

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Blocks rewriting with clang

Introduction

Back in 2009, Snow Leopard was quite an exciting OS X release. It didn’t focus on new user-visible features but instead introduced a handful of low level technologies. Two of those technologies Grand Central Dispatch (a.k.a. GCD) and OpenCL were designed to help developers benefit from the new computing power of modern computer architectures: multicore processors for the former and GPUs for the latter.

Alongside the GCD engine came a C language extension called blocks. Blocks are the C-based flavor of what is commonly called a closure: a callable object that captures the context in which it was created. The syntax for blocks is very similar to the one used for functions, with the exception that the pointer star is * replaced by a caret ^. This allows inline definition of callbacks which often can help improving the readability of the code.

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Hackathon 0x1 – Pimp my Review or the Epic Birth of a Gerrit Plugin

The goal had been set a day or two prior to the beginning of the hackathon: we were hoping to make Gerrit better at recommending relevant reviewers for a given commit. To those who haven’t heard of it, Gerrit is a web-based code review system. It is a nifty Google-backed open-source project evolving amid an active community of users. We have been using this product here at Intersec since 2011 and some famous software projects also rely heavily on it for their development process.

Da Review Pimpers

This would be a good metaphor to illustrate our mindset at the beginning of the hackathon! (credits: Team Fortress 2)

Our team consisted of five people: Kamal, Romain, Thomas, Louis and Romain (myself).

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Memory – Part 6: Optimizing the FIFO and Stack allocators

Introduction

The most used custom allocators at Intersec are the FIFO and the Stack allocators, detailed in a previous article. The stack allocator is extremely convenient, thanks to the t_scope macro, and the FIFO is well fitted to some of our use cases, such as inter-process communication. It is thus important for these allocators to be optimized extensively.

We are two interns at Intersec, and our objective for this 6 week internship was to optimize these allocators as far as possible. Optimizing an allocator can have several meanings: it can be in terms of memory overhead, resistance to contention, performance… As the FIFO allocator is designed to work in single threaded environments, and the t_stack is thread local, we will only cover performance and memory overhead.

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Hackathon 0x1 – Interactive mode in Behave

Presentation of the Project

As testers, we spend a lot of time working on behave, our test automation framework1. Our test framework is a great tool, but it takes a lot of time starting and initializing the product, running tests one by one.

We are not only test automation developers. We also need to explore the product under test by experimenting again and again based on the information we gather along the way. Manual testing is the basic approach to perform non-trivial experiments, but it can benefit from automated testing as it offers a quick and reliable way to set up a product in any given state.

The hackathon2 was the perfect opportunity to buy ourselves a new exploratory tool to perform interactive automated testing. To do that, we needed to be able to:

  • Gain more control over the set up steps
  • Pause the product in order to manually test the state of the product
  • Select some more steps to run, check again, and so on
  • Explore with some automatic help

We elaborated an interactive mode to manage the run of a scenario. The goal was to be able to play each sentence on demand. This mode would help us in the future to reproduce issues and to set up the environment faster for testing purpose or even for customer demonstration.

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  1. behave is a clone of cucumber written in Python. It is based on the BDD (Behavior Driven Development) principles. Tests are described as a succession of english-sentences (assumptions, then actions, then results) which are themselves mapped to the corresponding Python code. 

  2. a hackathon is an event in which computer programmers and others involved in software development, including graphic designers, interface designers and project managers, collaborate intensively on software projects. Intersec promotes this event to focus and enhance project innovation 

DAZIO: Detecting Activity Zones based on Input/Output sms and calls activity for geomarketing and trade area analysis

Introduction

Telecom data is a rich source of information for many purposes, ranging from urban planning (Toole et al., 2012), human mobility patterns (Ficek and Kencl, 2012; Gambs et al., 2011), points of interest detection (Vieira et al., 2010), epidemic spread modeling (Lima et al., 2013), community detection (Morales et al., 2013) disaster planning (Pulse, 2013) and social interactions (Eagle et al., 2013).

One common task for these applications is to identify dense areas where many users stay for a significant time (activity zones), the regions relaying theses activity zones (transit zones) as well as the interaction between identified activity zones. Thus, in the present  article we will identify activity and transit zones to monitor and predict the activity levels in the telecom operators network based on the SMS and calls input/output activity levels issued from the Telecom Italia Big Data Challenge. The results of the present study could be directly applied to:

  • Location-Based Advertising
  • defining a suitable place to open a new store in a city
  • planning where to add cell towers to improve QoS

The contribution of this work is twofold: to present a model accounting for changes of activity levels (over time) and to predict those changes using Markov chains. We also propose a methodology to detect activity and transit zones.

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More about locality

In the third post of the memory series we briefly explained locality and why it is an important principle to keep in mind while developing a memory-intensive program. This new post is going to be more concrete and explains what actually happens behind the scene in a very simple example.

This post is a follow-up to a recent interview with a (brilliant) candidate1. As a subsidiary question, we presented him with the following two structure definitions:

The question was: what is the difference between these two structures, what are the pros and the cons of both of them? For the remaining of the article we will suppose we are working on an x86_64 architecture.

By coincidence, an intern asked more or less at the same time why we were using bar_t-like structures in our custom database engine.

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  1. we’re still hiring 

Memory – Part 5: Debugging Tools

Introduction

Here we are! We spent 4 articles explaining what memory is, how to deal with it and what are the kind of problems you can expect from it. Even the best developers write bugs. A commonly accepted estimation seems to be around of few tens of bugs per thousand of lines of code, which is definitely quite huge. As a consequence, even if you proficiently mastered all the concepts covered by our articles, you’ll still probably have a few memory-related bugs.

Memory-related bugs may be particularly hard to spot and fix. Let’s take the following program as an example:

This program is supposed to take a message as argument and print “hello <message>!” (the default message being “world”).

The behavior of this program is completely undefined, it is buggy, however it will probably not crash. The function build_message returns a pointer to some memory allocated in its stack-frame. Because of how the stack works, that memory is very susceptible to be overwritten by another function call later, possibly by fputs. As a consequence, if fputs internally uses sufficient stack-memory to overwrite the message, then the output will be corrupted (and the program may even crash), in the other case the program will print the expected message. Moreover, the program may overflow its buffer because of the use of the unsafe sprintf function that has no limit in the number of bytes written.

So, the behavior of the program varies depending on the size of the message given in the command line, the value of MAX_LINE_SIZE and the implementation of fputs. What’s annoying with this kind of bug is that the result may not be obvious: the program “works” well enough with simple use cases and will only fail the day it will receive a parameter with the right properties to exhibit the issue. That’s why it’s important that developers are at ease with some tools that will help them to validate (or to debug) memory management.

In this last article, we will cover some free tools that we consider should be part of the minimal toolkit of a C (and C++) developer.

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