Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/Shopify/semian

:monkey: Resiliency toolkit for Ruby for failing fast
https://github.com/Shopify/semian

bulkheads circuit-breaker resiliency ruby webscale

Last synced: about 1 month ago
JSON representation

:monkey: Resiliency toolkit for Ruby for failing fast

Awesome Lists containing this project

README 

        
## Semian ![Build Status](https://github.com/Shopify/semian/actions/workflows/test.yml/badge.svg)



![](http://i.imgur.com/7Vn2ibF.png)



Semian is a library for controlling access to slow or unresponsive external

services to avoid cascading failures.



When services are down they typically fail fast with errors like `ECONNREFUSED`

and `ECONNRESET` which can be rescued in code. However, slow resources fail

slowly. The thread serving the request blocks until it hits the timeout for the

slow resource. During that time, the thread is doing nothing useful and thus the

slow resource has caused a cascading failure by occupying workers and therefore

losing capacity. **Semian is a library for failing fast in these situations,

allowing you to handle errors gracefully.** Semian does this by intercepting

resource access through heuristic patterns inspired by [Hystrix][hystrix] and

[Release It][release-it]:



* [**Circuit breaker**](#circuit-breaker). A pattern for limiting the

  amount of requests to a dependency that is having issues.

* [**Bulkheading**](#bulkheading). Controlling the concurrent access to

  a single resource, access is coordinated server-wide with [SysV

  semaphores][sysv].



Resource drivers are monkey-patched to be aware of Semian, these are called

[Semian Adapters](#adapters). Thus, every time resource access is requested

Semian is queried for status on the resource first.  If Semian, through the

patterns above, deems the resource to be unavailable it will raise an exception.

**The ultimate outcome of Semian is always an exception that can then be rescued

for a graceful fallback**. Instead of waiting for the timeout, Semian raises

straight away.



If you are already rescuing exceptions for failing resources and timeouts,

Semian is mostly a drop-in library with a little configuration that will make

your code more resilient to slow resource access. But, [do you even need

Semian?](#do-i-need-semian)



For an overview of building resilient Ruby applications, start by reading [the

Shopify blog post on Toxiproxy and Semian][resiliency-blog-post]. For more in

depth information on Semian, see [Understanding Semian](#understanding-semian).

Semian is an extraction from [Shopify][shopify] where it's been running

successfully in production since October, 2014.



The other component to your Ruby resiliency kit is [Toxiproxy][toxiproxy] to

write automated resiliency tests.



# Usage



Install by adding the gem to your `Gemfile` and require the [adapters](#adapters) you need:



```ruby

gem 'semian', require: %w(semian semian/mysql2 semian/redis)

```



We recommend this pattern of requiring adapters directly from the `Gemfile`.

This ensures Semian adapters are loaded as early as possible and also

protects your application during boot. Please see the [adapter configuration

section](#configuration) on how to configure adapters.



## Adapters



Semian works by intercepting resource access. Every time access is requested,

Semian is queried, and it will raise an exception if the resource is unavailable

according to the circuit breaker or bulkheads.  This is done by monkey-patching

the resource driver. **The exception raised by the driver always inherits from

the Base exception class of the driver**, meaning you can always simply rescue

the base class and catch both Semian and driver errors in the same rescue for

fallbacks.



The following adapters are in Semian and tested heavily in production, the

version is the version of the public gem with the same name:



* [`semian/mysql2`][mysql-semian-adapter] (~> 0.3.16)

* [`semian/redis`][redis-semian-adapter] (~> 3.2.1)

* [`semian/net_http`][nethttp-semian-adapter]

* [`semian/activerecord_trilogy_adapter`][activerecord-trilogy-semian-adapter]

* [`semian-postgres`][postgres-semian-adapter]



### Creating Adapters



To create a Semian adapter you must implement the following methods:



1. [`include Semian::Adapter`][semian-adapter]. Use the helpers to wrap the

   resource. This takes care of situations such as monitoring, nested resources,

   unsupported platforms, creating the Semian resource if it doesn't already

   exist and so on.

2. `#semian_identifier`. This is responsible for returning a symbol that

   represents every unique resource, for example `redis_master` or

   `mysql_shard_1`. This is usually assembled from a `name` attribute on the

   Semian configuration hash, but could also be `:`.

3. `connect`. The name of this method varies. You must override the driver's

   connect method with one that wraps the connect call with

   `Semian::Resource#acquire`. You should do this at the lowest possible level.

4. `query`. Same as `connect` but for queries on the resource.

5. Define exceptions `ResourceBusyError` and `CircuitOpenError`. These are

   raised when the request was rejected early because the resource is out of

   tickets or because the circuit breaker is open (see [Understanding

   Semian](#understanding-semian). They should inherit from the base exception

   class from the raw driver. For example `Mysql2::Error` or

   `Redis::BaseConnectionError` for the MySQL and Redis drivers. This makes it

   easy to `rescue` and handle them gracefully in application code, by

   `rescue`ing the base class.



The best resource is looking at the [already implemented adapters](#adapters).



### Configuration



There are some global configuration options that can be set for Semian:



```ruby

# Maximum size of the LRU cache (default: 500)

# Note: Setting this to 0 enables aggressive garbage collection.

Semian.maximum_lru_size = 0



# Minimum time in seconds a resource should be resident in the LRU cache (default: 300s)

Semian.minimum_lru_time = 60

```



Note: `minimum_lru_time` is a stronger guarantee than `maximum_lru_size`. That

is, if a resource has been updated more recently than `minimum_lru_time` it

will not be garbage collected, even if it would cause the LRU cache to grow

larger than `maximum_lru_size`.



When instantiating a resource it now needs to be configured for Semian. This is

done by passing `semian` as an argument when initializing the client. Examples

built in adapters:



```ruby

# MySQL2 client

# In Rails this means having a Semian key in database.yml for each db.

client = Mysql2::Client.new(host: "localhost", username: "root", semian: {

  name: "master",

  tickets: 8, # See the Understanding Semian section on picking these values

  success_threshold: 2,

  error_threshold: 3,

  error_timeout: 10

})



# Redis client

client = Redis.new(semian: {

  name: "inventory",

  tickets: 4,

  success_threshold: 2,

  error_threshold: 4,

  error_timeout: 20

})

```



#### Thread Safety



Semian's circuit breaker implementation is thread-safe by default as of

`v0.7.0`. If you'd like to disable it for performance reasons, pass

`thread_safety_disabled: true` to the resource options.



Bulkheads should be disabled (pass `bulkhead: false`) in a threaded environment

(e.g. Puma or Sidekiq), but can safely be enabled in non-threaded environments

(e.g. Resque and Unicorn). As described in this document, circuit breakers alone

should be adequate in most environments with reasonably low timeouts.



Internally, semian uses `SEM_UNDO` for several sysv semaphore operations:



* Acquire

* Worker registration

* Semaphore metadata state lock



The intention behind `SEM_UNDO` is that a semaphore operation is automatically undone when the process exits. This

is true even if the process exits abnormally - crashes, receives a `SIG_KILL`, etc, because it is handled by

the operating system and not the process itself.



If, however, a thread performs a semop, the `SEM_UNDO` is on its parent process. This means that the operation

*will not* be undone when the thread exits. This can result in the following unfavorable behavior when using

threads:



* Threads acquire a resource, but are killed and the resource ticket is never released. For a process, the

ticket would be released by `SEM_UNDO`, but since it's a thread there is the potential for ticket starvation.

This can result in deadlock on the resource.

* Threads that register workers on a resource but are killed and never unregistered. For a process, the worker

count would be automatically decremented by `SEM_UNDO`, but for threads the worker count will continue to increment,

only being undone when the parent process dies. This can cause the number of tickets to dramatically exceed the quota.

* If a thread acquires the semaphore metadata lock and dies before releasing it, semian will deadlock on anything

attempting to acquire the metadata lock until the thread's parent process exits. This can prevent the ticket count

from being updated.



Moreover, a strategy that utilizes `SEM_UNDO` is not compatible with a strategy that attempts to the semaphores tickets manually.

In order to support threads, operations that currently use `SEM_UNDO` would need to use no semaphore flag, and the calling process

will be responsible for ensuring that threads are appropriately cleaned up. It is still possible to implement this, but

it would likely require an in-memory semaphore managed by the parent process of the threads. PRs welcome for this functionality.



#### Quotas



You may now set quotas per worker:



```ruby

client = Redis.new(semian: {

  name: "inventory",

  quota: 0.51,

  success_threshold: 2,

  error_threshold: 4,

  error_timeout: 20

})



```



Per the above example, you no longer need to care about the number of tickets.

Rather, the tickets shall be computed as a proportion of the number of active workers.



In this case, we'd allow 50% of the workers on a particular host to connect to this redis resource.

So long as the workers are in their own process, they will automatically be registered. The quota will

set the bulkhead threshold based on the number of registered workers, whenever a new worker registers.



This is ideal for environments with non-uniform worker distribution, and to eliminate the need to manually

calculate and adjust ticket counts.



**Note**:



- You must pass **exactly** one of options: `tickets` or `quota`.

- Tickets available will be the ceiling of the quota ratio to the number of workers

 - So, with one worker, there will always be a minimum of 1 ticket

- Workers in different processes will automatically unregister when the process exits.

- If you have a small number of workers (exactly 2) it's possible that the bulkhead will be too sensitive using quotas.

- If you use a forking web server (like unicorn) you should call `Semian.unregister_all_resources` before/after forking.



#### Net::HTTP

For the `Net::HTTP` specific Semian adapter, since many external libraries may create

HTTP connections on the user's behalf, the parameters are instead provided

by associating callback functions with `Semian::NetHTTP`, perhaps in an initialization file.



##### Naming and Options

To give Semian parameters, assign a `proc` to `Semian::NetHTTP.semian_configuration`

that takes a two parameters, `host` and `port` like `127.0.0.1`,`443` or `github_com`,`80`,

and returns a `Hash` with configuration parameters as follows. The `proc` is used as a

callback to initialize the configuration options, similar to other adapters.



```ruby

SEMIAN_PARAMETERS = { tickets: 1,

                      success_threshold: 1,

                      error_threshold: 3,

                      error_timeout: 10 }

Semian::NetHTTP.semian_configuration = proc do |host, port|

  # Let's make it only active for github.com

  if host == "github.com" && port.to_i == 80

    SEMIAN_PARAMETERS.merge(name: "github.com_80")

  else

    nil

  end

end



# Called from within API:

# semian_options = Semian::NetHTTP.semian_configuration("github.com", 80)

# semian_identifier = "nethttp_#{semian_options[:name]}"

```



The `name` should be carefully chosen since it identifies the resource being protected.

The `semian_options` passed apply to that resource. Semian creates the `semian_identifier`

from the `name` to look up and store changes in the circuit breaker and bulkhead states

and associate successes, failures, errors with the protected resource.



We only require that the `semian_configuration` be **set only once** over the lifetime of

the library.



If you need to return different values for the same pair of `host`/`port` value, you **must**

include the `dynamic: true` option. Returning different values for the same `host`/`port` values

without setting the `dynamic` option can lead to undesirable behavior.



A common example for dynamic options is the use of a thread local variable, such as

`ActiveSupport::CurrentAttributes`, for requests to a service acting as a proxy.



```ruby

SEMIAN_PARAMETERS = {

  # ...

  dynamic: true,

}



class CurrentSemianSubResource < ActiveSupport::CurrentAttributes

 attribute :sub_name

end



Semian::NetHTTP.semian_configuration = proc do |host, port|

  name = "#{host}_#{port}"

  if (sub_resource_name = CurrentSemianSubResource.sub_name)

    name << "_#{sub_resource_name}"

  end

  SEMIAN_PARAMETERS.merge(name: name)

end



# Two requests to example.com can use two different semian resources,

# as long as `CurrentSemianSubResource.sub_name` is set accordingly:

# CurrentSemianSubResource.set(sub_name: "sub_resource_1") { Net::HTTP.get_response(URI("http://example.com")) }

# and:

# CurrentSemianSubResource.set(sub_name: "sub_resource_2") { Net::HTTP.get_response(URI("http://example.com")) }

```



For most purposes, `"#{host}_#{port}"` is a good default `name`. Custom `name` formats

can be useful to grouping related subdomains as one resource, so that they all

contribute to the same circuit breaker and bulkhead state and fail together.



A return value of `nil` for `semian_configuration` means Semian is disabled for that

HTTP endpoint. This works well since the result of a failed Hash lookup is `nil` also.

This behavior lets the adapter default to whitelisting, although the

behavior can be changed to blacklisting or even be completely disabled by varying

the use of returning `nil` in the assigned closure.



##### Additional Exceptions

Since we envision this particular adapter can be used in combination with many

external libraries, that can raise additional exceptions, we added functionality to

expand the Exceptions that can be tracked as part of Semian's circuit breaker.

This may be necessary for libraries that introduce new exceptions or re-raise them.

Add exceptions and reset to the [`default`][nethttp-default-errors] list using the following:



```ruby

# assert_equal(Semian::NetHTTP.exceptions, Semian::NetHTTP::DEFAULT_ERRORS)

Semian::NetHTTP.exceptions += [::OpenSSL::SSL::SSLError]



Semian::NetHTTP.reset_exceptions

# assert_equal(Semian::NetHTTP.exceptions, Semian::NetHTTP::DEFAULT_ERRORS)

```



##### Mark Unsuccessful Responses as Failures



Unsuccessful responses (e.g. 5xx responses) do not raise exceptions,

and as such are not marked as failures by default.

The `open_circuit_server_errors` Semian configuration parameter may be set to enable this behaviour,

to mark unsuccessful responses as failures as seen below:



```ruby

SEMIAN_PARAMETERS = { tickets: 1,

                      success_threshold: 1,

                      error_threshold: 3,

                      error_timeout: 10,

                      open_circuit_server_errors: true }

```



#### Active Record



Semian supports Active Record adapter `trilogy`.

It can be configured in the `database.yml`:



```yml

semian: &semian

  success_threshold: 2

  error_threshold: 3

  error_timeout: 4

  half_open_resource_timeout: 1

  bulkhead: false # Disable bulkhead for Puma: https://github.com/shopify/semian#thread-safety

  name: semian_identifier_name



default: &default

  adapter: trilogy

  username: root

  password:

  host: localhost

  read_timeout: 2

  write_timeout: 1

  connect_timeout: 1

  semian:

    <<: *semian

```



Example cases for `activerecord-trilogy-adapter` can be run using

`BUNDLE_GEMFILE=gemfiles/activerecord_trilogy_adapter.gemfile bundle exec rake examples:activerecord_trilogy_adapter`



# Understanding Semian



Semian is a library with heuristics for failing fast. This section will explain

in depth how Semian works and which situations it's applicable for. First we

explain the category of problems Semian is meant to solve. Then we dive into how

Semian works to solve these problems.



## Do I need Semian?



Semian is not a trivial library to understand, introduces complexity and thus

should be introduced with care. Remember, all Semian does is raise exceptions

based on heuristics. It is paramount that you understand Semian before

including it in production as you may otherwise be surprised by its behaviour.



Applications that benefit from Semian are those working on eliminating SPOFs

(Single Points of Failure), and specifically are running into a wall regarding

slow resources. But it is by no means a magic wand that solves all your latency

problems by being added to your `Gemfile`. This section describes the types of

problems Semian solves.



If your application is multithreaded or evented (e.g. not Resque and Unicorn)

these problems are not as pressing. You can still get use out of Semian however.



### Real World Example



This is better illustrated with a real world example from Shopify. When you are

browsing a store while signed in, Shopify stores your session in Redis.

If Redis becomes unavailable, the driver will start throwing exceptions.

We rescue these exceptions and simply disable all customer sign in functionality

on the store until Redis is back online.



This is great if querying the resource fails instantly, because it means we fail

in just a single roundtrip of ~1ms. But if the resource is unresponsive or slow,

this can take as long as our timeout which is easily 200ms. This means every

request, even if it does rescue the exception, now takes an extra 200ms.

Because every resource takes that long, our capacity is also significantly

degraded. These problems are explained in depth in the next two sections.



With Semian, the slow resource would fail instantly (after a small amount of

convergence time) preventing your response time from spiking and not decreasing

capacity of the cluster.



If this sounds familiar to you, Semian is what you need to be resilient to

latency. You may not need the graceful fallback depending on your application,

in which case it will just result in an error (e.g. a `HTTP 500`) faster.



We will now examine the two problems in detail.



#### In-depth analysis of real world example



If a single resource is slow, every single request is going to suffer. We saw

this in the example before. Let's illustrate this more clearly in the following

Rails example where the user session is stored in Redis:



```ruby

def index

  @user = fetch_user

  @posts = Post.all

end



private

def fetch_user

  user = User.find(session[:user_id])

rescue Redis::CannotConnectError

  nil

end

```



Our code is resilient to a failure of the session layer, it doesn't `HTTP 500`

if the session store is unavailable (this can be tested with

[Toxiproxy][toxiproxy]). If the `User` and `Post` data store is unavailable, the

server will send back `HTTP 500`. We accept that, because it's our primary data

store. This could be prevented with a caching tier or something else out of

scope.



This code has two flaws however:



1. **What happens if the session storage is consistently slow?** I.e. the majority

   of requests take, say, more than half the timeout time (but it should only

   take ~1ms)?

2. **What happens if the session storage is unavailable and is not responding at

   all?** I.e. we hit timeouts on every request.



These two problems in turn have two related problems associated with them:

response time and capacity.



#### Response time



Requests that attempt to access a down session storage are all gracefully handled, the

`@user` will simply be `nil`, which the code handles. There is still a

major impact on users however, as every request to the storage has to time

out. This causes the average response time to all pages that access it to go up by

however long your timeout is. Your timeout is proportional to your worst case timeout,

as well as the number of attempts to hit it on each page. This is the problem Semian

solves by using heuristics to fail these requests early which causes a much better

user experience during downtime.



#### Capacity loss



When your single-threaded worker is waiting for a resource to return, it's

effectively doing nothing when it could be serving fast requests. To use the

example from before, perhaps some actions do not access the session storage at

all. These requests will pile up behind the now slow requests that are trying to

access that layer, because they're failing slowly. Essentially, your capacity

degrades significantly because your average response time goes up (as explained

in the previous section). Capacity loss simply follows from an increase in

response time. The higher your timeout and the slower your resource, the more

capacity you lose.



#### Timeouts aren't enough



It should be clear by now that timeouts aren't enough. Consistent timeouts will

increase the average response time, which causes a bad user experience, and

ultimately compromise the performance of the entire system. Even if the timeout

is as low as ~250ms (just enough to allow a single TCP retransmit) there's a

large loss of capacity and for many applications a 100-300% increase in average

response time. This is the problem Semian solves by failing fast.



## How does Semian work?



Semian consists of two parts: **Circuit Breaker** and **Bulkheading**.

To understand Semian, and especially how to configure it,

we must understand these patterns and their implementation.



Disable Semian via environment variable `SEMIAN_DISABLED=1`.



### Circuit Breaker



The circuit breaker pattern is based on a simple observation - if we hit a

timeout or any other error for a given service one or more times, we’re likely

to hit it again for some amount of time. Instead of hitting the timeout

repeatedly, we can mark the resource as dead for some amount of time during

which we raise an exception instantly on any call to it. This is called the

[circuit breaker pattern][cbp].



![](http://cdn.shopify.com/s/files/1/0070/7032/files/image01_grande.png)



When we perform a Remote Procedure Call (RPC), it will first check the circuit.

If the circuit is rejecting requests because of too many failures reported by

the driver, it will throw an exception immediately. Otherwise the circuit will

call the driver. If the driver fails to get data back from the data store, it

will notify the circuit. The circuit will count the error so that if too many

errors have happened recently, it will start rejecting requests immediately

instead of waiting for the driver to time out. The exception will then be raised

back to the original caller. If the driver’s request was successful, it will

return the data back to the calling method and notify the circuit that it made a

successful call.



The state of the circuit breaker is local to the worker and is not shared across

all workers on a server.



#### Circuit Breaker Configuration



There are four configuration parameters for circuit breakers in Semian:



* **circuit_breaker**. Enable or Disable Circuit Breaker. Defaults to `true` if not set.

* **error_threshold**. The amount of errors a worker encounters within `error_threshold_timeout`

  amount of time before opening the circuit,

  that is to start rejecting requests instantly.

* **error_threshold_timeout**. The amount of time in seconds that `error_threshold`

  errors must occur to open the circuit.

  Defaults to `error_timeout` seconds if not set.

* **error_timeout**. The amount of time in seconds until trying to query the resource

  again.

* **error_threshold_timeout_enabled**. If set to false it will disable

  the time window for evicting old exceptions. `error_timeout` is still used and

  will reset the circuit. Defaults to `true` if not set.

* **success_threshold**. The amount of successes on the circuit until closing it

  again, that is to start accepting all requests to the circuit.

* **half_open_resource_timeout**. Timeout for the resource in seconds when

  the circuit is half-open (supported for MySQL, Net::HTTP and Redis).



It is possible to disable Circuit Breaker with environment variable

`SEMIAN_CIRCUIT_BREAKER_DISABLED=1`.



For more information about configuring these parameters, please read

[this post](https://engineering.shopify.com/blogs/engineering/circuit-breaker-misconfigured).



### Bulkheading



For some applications, circuit breakers are not enough. This is best illustrated

with an example. Imagine if the timeout for our data store isn't as low as

200ms, but actually 10 seconds. For example, you might have a relational data

store where for some customers, 10s queries are (unfortunately) legitimate.

Reducing the time of worst case queries requires a lot of effort. Dropping the

query immediately could potentially leave some customers unable to access

certain functionality. High timeouts are especially critical in a non-threaded

environment where blocking IO means a worker is effectively doing nothing.



In this case, circuit breakers aren't sufficient. Assuming the circuit is shared

across all processes on a server, it will still take at least 10s before the

circuit is open. In that time every worker is blocked (see also "Defense Line"

section for an in-depth explanation of the co-operation between circuit breakers

and bulkheads) this means we're at reduced capacity for at least 20s, with the

last 10s timeouts occurring just before the circuit opens at the 10s mark when a

couple of workers have hit a timeout and the circuit opens. We thought of a

number of potential solutions to this problem - stricter timeouts, grouping

timeouts by section of our application, timeouts per statement—but they all

still revolved around timeouts, and those are extremely hard to get right.



Instead of thinking about timeouts, we took inspiration from Hystrix by Netflix

and the book Release It (the resiliency bible), and look at our services as

connection pools. On a server with `W` workers, only a certain number of them

are expected to be talking to a single data store at once. Let's say we've

determined from our monitoring that there’s a 10% chance they’re talking to

`mysql_shard_0` at any given point in time under normal traffic. The probability

that five workers are talking to it at the same time is 0.001%. If we only allow

five workers to talk to a resource at any given point in time, and accept the

0.001% false positive rate—we can fail the sixth worker attempting to check out

a connection instantly. This means that while the five workers are waiting for a

timeout, all the other `W-5` workers on the node will instantly be failing on

checking out the connection and opening their circuits. Our capacity is only

degraded by a relatively small amount.



We call this limitation primitive "tickets". In this case, the resource access

is limited to 5 tickets (see Configuration). The timeout value specifies the

maximum amount of time to block if no ticket is available.



How do we limit the access to a resource for all workers on a server when the

workers do not directly share memory? This is implemented with [SysV

semaphores][sysv] to provide server-wide access control.



#### Bulkhead Configuration



There are two configuration values. It's not easy to choose good values and we're

still experimenting with ways to figure out optimal ticket numbers. Generally

something below half the number of workers on the server for endpoints that are

queried frequently has worked well for us.



* **bulkhead**. Enable or Disable Bulkhead. Defaults to `true` if not set.

* **tickets**. Number of workers that can concurrently access a resource.

* **timeout**. Time to wait in seconds to acquire a ticket if there are no tickets left.

  We recommend this to be `0` unless you have very few workers running (i.e.

  less than ~5).



It is possible to disable Bulkhead with environment variable

`SEMIAN_BULKHEAD_DISABLED=1`.



Note that there are system-wide limitations on how many tickets can be allocated

on a system. `cat /proc/sys/kernel/sem` will tell you.



> System-wide limit on the number of semaphore sets.  On Linux

  systems before version 3.19, the default value for this limit

  was 128.  Since Linux 3.19, the default value is 32,000.  On

  Linux, this limit can be read and modified via the fourth

  field of `/proc/sys/kernel/sem`.



#### Bulkhead debugging on linux



Note: It is often helpful to examine the actual IPC resources on the system. Semian

provides an easy way to get the semaphore key:



```

irb> require 'semian'

irb> puts Semian::Resource.new(:your_resource_name, tickets: 42).key # do this from a dev machine

"0x48af51ea"

```



This key can then be used to easily inspect the semaphore on any host machine:



```

ipcs -si $(ipcs -s | grep 0x48af51ea | awk '{print $2}')

```



Which should output something like:



```

Semaphore Array semid=5570729

uid=8192         gid=8192        cuid=8192       cgid=8192

mode=0660, access_perms=0660

nsems = 4

otime = Thu Mar 30 15:06:16 2017

ctime = Mon Mar 13 20:25:36 2017

semnum     value      ncount     zcount     pid

0          1          0          0          48

1          42         0          0          48

2          42         0          0          27

3          31         0          0          48

```



In the above example, we can see each of the semaphores. Looking at the enum code

in `ext/semian/sysv_semaphores.h` we can see that:



* 0: is the semian meta lock (mutex) protecting updates to the other resources. It's currently free

* 1: is the number of available tickets - currently no tickets are in use because it's the same as 2

* 2: is the configured (maximum) number of tickets

* 3: is the number of registered workers (processes) that would be considered if using the quota strategy.



## Defense line



The finished defense line for resource access with circuit breakers and

bulkheads then looks like this:



![](http://cdn.shopify.com/s/files/1/0070/7032/files/image02_grande.png)



The RPC first checks the circuit; if the circuit is open it will raise the

exception straight away which will trigger the fallback (the default fallback is

a 500 response). Otherwise, it will try Semian which fails instantly if too many

workers are already querying the resource. Finally the driver will query the

data store. If the data store succeeds, the driver will return the data back to

the RPC. If the data store is slow or fails, this is our last line of defense

against a misbehaving resource. The driver will raise an exception after trying

to connect with a timeout or after an immediate failure. These driver actions

will affect the circuit and Semian, which can make future calls fail faster.



A useful way to think about the co-operation between bulkheads and circuit

breakers is through visualizing a failure scenario graphing capacity as a

function of time. If an incident strikes that makes the server unresponsive

with a `20s` timeout on the client and you only have circuit breakers

enabled--you will lose capacity until all workers have tripped their circuit

breakers. The slope of this line will depend on the amount of traffic to the now

unavailable service. If the slope is steep (i.e. high traffic), you'll lose

capacity quicker. The higher the client driver timeout, the longer you'll lose

capacity for. In the example below we have the circuit breakers configured to

open after 3 failures:



![resiliency- circuit breakers](https://cloud.githubusercontent.com/assets/97400/22405538/53229758-e612-11e6-81b2-824f873c3fb7.png)



If we imagine the same scenario but with _only_ bulkheads, configured to have

tickets for 50% of workers at any given time, we'll see the following

flat-lining scenario:



![resiliency- bulkheads](https://cloud.githubusercontent.com/assets/97400/22405542/6832a372-e612-11e6-88c4-2452b64b3121.png)



Circuit breakers have the nice property of re-gaining 100% capacity. Bulkheads

have the desirable property of guaranteeing a minimum capacity. If we do

addition of the two graphs, marrying bulkheads and circuit breakers, we have a

plummy outcome:



![resiliency- circuit breakers bulkheads](https://cloud.githubusercontent.com/assets/97400/22405550/a25749c2-e612-11e6-8bc8-5fe29e212b3b.png)



This means that if the slope or client timeout is sufficiently low, bulkheads

will provide little value and are likely not necessary.



## Failing gracefully



Ok, great, we've got a way to fail fast with slow resources, how does that make

my application more resilient?



Failing fast is only half the battle. It's up to you what you do with these

errors, in the [session example](#real-world-example) we handle it gracefully by

signing people out and disabling all session related functionality till the data

store is back online. However, not rescuing the exception and simply sending

`HTTP 500` back to the client faster will help with [capacity

loss](#capacity-loss).



### Exceptions inherit from base class



It's important to understand that the exceptions raised by [Semian

Adapters](#adapters) inherit from the base class of the driver itself, meaning

that if you do something like:



```ruby

def posts

  Post.all

rescue Mysql2::Error

  []

end

```



Exceptions raised by Semian's `MySQL2` adapter will also get caught.



### Patterns



We do not recommend mindlessly sprinkling `rescue`s all over the place. What you

should do instead is writing decorators around secondary data stores (e.g. sessions)

that provide resiliency for free. For example, if we stored the tags associated

with products in a secondary data store it could look something like this:



```ruby

# Resilient decorator for storing a Set in Redis.

class RedisSet

  def initialize(key)

    @key = key

  end



  def get

    redis.smembers(@key)

  rescue Redis::BaseConnectionError

    []

  end



  private



  def redis

    @redis ||= Redis.new

  end

end



class Product

  # This will simply return an empty array in the case of a Redis outage.

  def tags

    tags_set.get

  end



  private



  def tags_set

    @tags_set ||= RedisSet.new("product:tags:#{self.id}")

  end

end

```



These decorators can be resiliency tested with [Toxiproxy][toxiproxy]. You can

provide fallbacks around your primary data store as well. In our case, we simply

`HTTP 500` in those cases unless it's cached because these pages aren't worth

much without data from their primary data store.



## Monitoring



With [`Semian::Instrumentable`][semian-instrumentable] clients can monitor

Semian internals. For example to instrument just events with

[`statsd-instrument`][statsd-instrument]:



```ruby

# `event` is `success`, `busy`, `circuit_open`, `state_change`, or `lru_hash_gc`.

# `resource` is the `Semian::Resource` object (or a `LRUHash` object for `lru_hash_gc`).

# `scope` is `connection` or `query` (others can be instrumented too from the adapter) (is nil for `lru_hash_gc`).

# `adapter` is the name of the adapter (mysql2, redis, ..) (is a payload hash for `lru_hash_gc`)

Semian.subscribe do |event, resource, scope, adapter|

  case event

  when :success, :busy, :circuit_open, :state_change

    StatsD.increment("semian.#{event}", tags: {

      resource: resource.name,

      adapter: adapter,

      type: scope,

    })

  else

    StatsD.increment("semian.#{event}")

  end

end

```



# FAQ



**How does Semian work with containers?** Semian uses [SysV semaphores][sysv] to

coordinate access to a resource. The semaphore is only shared within the

[IPC][namespaces]. Unless you are running many workers inside every container,

this leaves the bulkheading pattern effectively useless. We recommend sharing

the IPC namespace between all containers on your host for the best ticket

economy. If you are using Docker, this can be done with the [--ipc

flag](https://docs.docker.com/engine/reference/run/#ipc-settings---ipc).



**Why isn't resource access shared across the entire cluster?** This implies a

coordination data store. Semian would have to be resilient to failures of this

data store as well, and fall back to other primitives. While it's nice to have

all workers have the same view of the world, this greatly increases the

complexity of the implementation which is not favourable for resiliency code.



**Why isn't the circuit breaker implemented as a host-wide mechanism?** No good

reason. Patches welcome!



**Why is there no fallback mechanism in Semian?** Read the [Failing

Gracefully](#failing-gracefully) section. In short, exceptions is exactly this.

We did not want to put an extra level on abstraction on top of this. In the

first internal implementation this was the case, but we later moved away from

it.



**Why does it not use normal Ruby semaphores?** To work properly the access

control needs to be performed across many workers. With MRI that means having

multiple processes, not threads. Thus we need a primitive outside of the

interpreter. For other Ruby implementations a driver that uses Ruby semaphores

could be used (and would be accepted as a PR).



**Why are there three semaphores in the semaphore sets for each resource?** This

has to do with being able to resize the number of tickets for a resource online.



**Can I change the number of tickets freely?** Yes, the logic for this isn't

trivial but it works well.



**What is the performance overhead of Semian?** Extremely minimal in comparison

to going to the network. Don't worry about it unless you're instrumenting

non-IO.



# Developing Semian



Semian requires a Linux environment for **Bulkheading**.

We provide a [docker-compose](https://docs.docker.com/compose/) file

that runs MySQL, Redis, Toxiproxy and Ruby in containers.

Use the steps below to work on Semian from a Mac OS environment.



## Prerequisites :



```bash

# install docker-for-desktop

$ brew cask install docker



# install latest docker-compose

$ brew install docker-compose



# install visual-studio-code (optional)

$ brew cask install visual-studio-code



# clone Semian

$ git clone https://github.com/Shopify/semian.git

$ cd semian

```



## Visual Studio Code

  - Open semian in vscode

  - Install recommended extensions (one off requirement)

  - Click `reopen in container` (first boot might take about a minute)



  See https://code.visualstudio.com/docs/remote/containers for more details



  If you make any changes to `.devcontainer/` you'd need to recreate the containers:



  - Select `Rebuild Container` from the command palette



  Running Tests:

  - `$ bundle exec rake` Run with `SKIP_FLAKY_TESTS=true` to skip flaky tests (CI runs all tests)



## Everything else



  Test semian in containers:

  - `$ docker-compose -f .devcontainer/docker-compose.yml up -d`

  - `$ docker exec -it semian bash`



  If you make any changes to `.devcontainer/` you'd need to recreate the containers:



  - `$ docker-compose -f .devcontainer/docker-compose.yml up -d --force-recreate`



  Run tests in containers:



  ```shell

  $ docker-compose -f ./.devcontainer/docker-compose.yml run --rm test

  ```



  Running Tests:

  - `$ bundle exec rake` Run with `SKIP_FLAKY_TESTS=true` to skip flaky tests (CI runs all tests)



### Running tests in batches



* *TEST_WORKERS* - Total number of workers or batches.

  It uses to identify a total number of batches, that would be run in parallel. *Default: 1*

* *TEST_WORKER_NUM* - Specify which batch to run. The value is between 1 and *TEST_WORKERS*. *Default: 1*



```shell

$ bundle exec rake test:parallel TEST_WORKERS=5 TEST_WORKER_NUM=1

```



### Debug



Build a semian native extension with debug information.



```shell

$ bundle exec rake clean --trace

$ export DEBUG=1

$ bundle exec rake build

$ bundle install

```



[hystrix]: https://github.com/Netflix/Hystrix

[release-it]: https://pragprog.com/titles/mnee2/release-it-second-edition/

[shopify]: http://www.shopify.com/

[mysql-semian-adapter]: lib/semian/mysql2.rb

[postgres-semian-adapter]: https://github.com/mschoenlaub/semian-postgres

[redis-semian-adapter]: lib/semian/redis.rb

[activerecord-trilogy-semian-adapter]: lib/semian/activerecord_trilogy_adapter.rb

[semian-adapter]: lib/semian/adapter.rb

[nethttp-semian-adapter]: lib/semian/net_http.rb

[nethttp-default-errors]: lib/semian/net_http.rb#L35-L45

[semian-instrumentable]: lib/semian/instrumentable.rb

[statsd-instrument]: http://github.com/shopify/statsd-instrument

[resiliency-blog-post]: https://engineering.shopify.com/blogs/engineering/building-and-testing-resilient-ruby-on-rails-applications

[toxiproxy]: https://github.com/Shopify/toxiproxy

[sysv]: http://man7.org/linux/man-pages/man7/svipc.7.html

[cbp]: https://en.wikipedia.org/wiki/Circuit_breaker_design_pattern

[namespaces]: http://man7.org/linux/man-pages/man7/namespaces.7.html