Servers are the central point of Zato. This is where services are running, where request issued by external applications arrive and where requests from Zato to other systems originate from.

Each server is a part of exactly one cluster. There is no limit of how many servers a cluster may contain.

Servers are implemented using gunicorn - this allows Zato servers to be asynchronous, meaning they are very fast, light on resources and able to accept large numbers of incoming HTTP connections.

There is no upper limit to the number of servers running in a single operating system although how many servers there are will be typically limited by how many CPUs the are (CPU_COUNT) and how many gunicorn workers will be started. For instance, if a server has 4 CPUs and you want for each server to have 2 gunicorn workers, it will make most sense to have between 2-4 servers (2 workers each) so that the total number of workers doesn’t exceed 2 * CPU_COUNT. Each worker is a separate OS process so adding more servers or workers would make them compete for CPU too strenuously.


For each cluster, exactly one server will be designated to a role of the singleton server. This is be the sever that will be responsible for managing the tasks that must not be run in more than one instance - a cluster’s scheduler and connectors.

When the first server in a cluster starts up, it is assigned the role of the singleton server, and the server will periodically update its keep-alive flag in the ODB. Other servers joining the cluster will each check if the singleton server is still alive and if the keep-alive flag isn’t updated in the expected interval, one of the other servers will become the singleton. This is known as the process of migrating a singleton server.


In front of each cluster is a high-availability load-balancer, implemented using an HAProxy instance running in a subprocess. The load-balancer makes sure the incoming HTTP traffic is evenly distributed across all the servers in a cluster while allowing the servers to join or leave the cluster without interrupting the message flow.

Redis and SQL ODB

Servers use Redis and an SQL Operational Database (ODB) for storing their configuration and statistics.

Redis is used as a message broker for exchanging information between servers and between the scheduler and servers. Servers never communicate directly, if it’s needed for one server to send a message to one or more servers, the message is published in Redis and other servers receive it from Redis. This is an asynchronous processes.

When the scheduler needs to invoke a service, it publishes a message to Redis, the message is picked up by one of the cluster’s servers and again, there is no direct communication between the scheduler and servers.

Connectors use Redis too. If a service needs to send a message to AMQP, IBM MQ or ZeroMQ, or if external applications use this protocols to send messages to Zato, they all are routed through Redis in an asynchronous manner.


Each cluster has a scheduler which can be used to schedule services to be invoked periodically. This can be used, for instance, to check for new files to process on FTP each 15 minutes or in similar situations.

Scheduler jobs can be:

  • one-time - for quick one-off jobs
  • interval-based - for recurring tasks
  • cron-style - similar to interval-based yet using cron syntax, this is meant to aid in migrating already existing tasks from cron to Zato


HTTP, FTP and SQL are protocols through which Zato services can connect to other applications directly, in a synchronous fashion.

HTTP can be either plain HTTP or HTTPS and uses the requests library. Any messages can be exchanged, JSON, XML, CSV or any other format although Zato has special support for the first two if you decide to use Zato’s Simple IO mechanism.

FTP should be understood as both FTP and FTPS. Note that Zato opens a new FTP connection for each service invocation, for instance - you scheduled a job to be run twice a minute, the job is to invoke a service which will fetch a file from an FTP. In that scenario, the service will open and close a new FTP connection twice a minute.

Supported SQL databases are Oracle and PostgreSQL. Access to SQL resources is implemented using the SQLAlchemy library.


AMQP, IBM MQ and ZeroMQ are protocols that Zato uses asynchronously through cluster connectors. For that protocols, each channel and an outgoing connection will start a new connector, e.g. if there are 3 AMQP channels and 2 ZeroMQ outgoing connections defined, there will be 5 connectors started by the singleton server.

Services and connectors communicate indirectly through Redis.

If a channel receives a new message, the message is taken off a queue, published on Redis, one of the servers subscribed receives it and a service is invoked.

Conversely, if a service needs to put a message on a queue, the message is first published to Redis, a connector pick it up and the message is sent to its destination.

Note that connectors are never redundant and there are always at least 2 clusters running in parallel needed to secure high-availability (HA), as discussed in a separate chapter, if any connectors are used.


Zato administrators use web admin and the CLI to manage clusters.

Web admin is a graphical browser-based console used for configuring most aspects of a running cluster. A single web admin instance can be used for connecting to more than one cluster. Web admin uses Zato’s public API for the management, it never directly updates a cluster’s state in the ODB.

The command-line interface is used to create, start and stop servers running in a cluster - as a security measure, these commands cannot be issued remotely through the web admin. CLI is also used for updating cryptographical material of servers and returning information regarding servers that isn’t available otherwise.