Faas-flow - Function Composition for OpenFaaS
- Pure FaaS with OpenFaaS
- Fast Built with
Go
- Secured With
HMAC
- Stateless By design
- Tracing With
open-tracing
- Available As
faas-flow
template
Faas-flow tower visualizes and monitors flow functions
Overview
Faas-flow allows you to realize OpenFaaS function composition with ease. By defining a simple pipeline, you can orchestrate multiple functions without having to worry about the internals
func Define(flow *faasflow.Workflow, context *faasflow.Context) (err error) {
flow.SyncNode().Apply("Func1").Apply("Func2")
return
}
After building and deploying, it will give you an OpenFaaS function that orchestrates calling Func2
with the output of Func1
Use Cases
Faas-flow as a function composure provides the back-bone for building complex solutions and promote automation
Data Processing Pipeline
Faas-flow can orchestrate a pipeline with long and short running function performing ETL jobs without having to orchestrate them manually or maintaining a separate application. Faas-flow ensures the execution order of several functions running in parallel or dynamically and provides rich construct to aggregate results while maintaining the intermediate data
Application Orchestration Workflow
Functions are great for isolating certain functionalities of an application. Although one still need to call the functions, write workflow logic, handle parallel processing and retries on failures. Using Faas-flow you can combine multiple OpenFaaS functions with little codes while your workflow will scale up/down automatically to handle the load
Function Reusability
Fass-flow allows you to write function only focused on solving one problem without having to worry about the next. It makes function loosely coupled from the business logic promoting reusability. You can write the stateless function and use it across multiple applications, where Faas-flow maintains the execution state for individual workflow per requests
Pipeline Definition
By supplying a number of pipeline operators, the complex composition can be achieved with little work:
The above pipelines can be achieved with little, but powerfull code:
SYNC Chain
func Define(flow *faasflow.Workflow, context *faasflow.Context) (err error) {
flow.SyncNode().Apply("func1").Apply("func2").
Modify(func(data []byte) ([]byte, error) {
// do something
return data, nil
})
return
}
ASYNC Chain
func Define(flow *faasflow.Workflow, context *faasflow.Context) (err error) {
dag := flow.Dag()
dag.Node("n1").Apply("func1")
dag.Node("n2").Apply("func2").
Modify(func(data []byte) ([]byte, error) {
// do something
return data, nil
})
dag.Node("n3").Apply("func4")
dag.Edge("n1", "n2")
dag.Edge("n2", "n3")
return
}
PARALLEL Branching
func Define(flow *faasflow.Workflow, context *faasflow.Context) (err error) {
dag := flow.Dag()
dag.Node("n1").Modify(func(data []byte) ([]byte, error) {
// do something
return data, nil
})
dag.Node("n2").Apply("func1")
dag.Node("n3").Apply("func2").Modify(func(data []byte) ([]byte, error) {
// do something
return data, nil
})
dag.Node("n4", faasflow.Aggregator(func(data map[string][]byte) ([]byte, error) {
// aggregate branch result data["n2"] and data["n3"]
return []byte(""), nil
}))
dag.Edge("n1", "n2")
dag.Edge("n1", "n3")
dag.Edge("n2", "n4")
dag.Edge("n3", "n4")
return
}
DYNAMIC Branching
func Define(flow *faasflow.Workflow, context *faasflow.Context) (err error) {
dag := flow.Dag()
dag.Node("n1").Modify(func(data []byte) ([]byte, error) {
// do something
return data, nil
})
conditionalDags := dag.ConditionalBranch("C",
[]string{"c1", "c2"}, // possible conditions
func(response []byte) []string {
// for each returned condition the corresponding branch will execute
// this function executes in the runtime of condition C
return []string{"c1", "c2"}
},
faasflow.Aggregator(func(data map[string][]byte) ([]byte, error) {
// aggregate all dynamic branches results
return []byte(""), nil
}),
)
conditionalDags["c2"].Node("n1").Apply("func1").Modify(func(data []byte) ([]byte, error) {
// do something
return data, nil
})
foreachDag := conditionalDags["c1"].ForEachBranch("F",
func(data []byte) map[string][]byte {
// for each returned key in the hashmap a new branch will be executed
// this function executes in the runtime of foreach F
return map[string][]byte{"f1": data, "f2": data}
},
faasflow.Aggregator(func(data map[string][]byte) ([]byte, error) {
// aggregate all dynamic branches results
return []byte(""), nil
}),
)
foreachDag.Node("n1").Modify(func(data []byte) ([]byte, error) {
// do something
return data, nil
})
dag.Node("n2")
dag.Edge("n1", "C")
dag.Edge("C", "n2")
}
Full implementation of the above examples are available here
Faas-flow Design
The current design consideration is made based on the below goals
- Leverage the OpenFaaS platform
- Not to violate the notions of function
- Provide flexibility, scalability, and adaptability
Just as function as any other
Faas-flow is deployed and provisioned just like any other OpenFaaS function. It allows Faas-flow to take advantage of rich functionalities available on OpenFaaS. Faas-flow provide an OpenFaaS template (faas-flow
) and just like any other OpenFaaS function it can be deployed with faas-cli
Adapter pattern for zero intrumenttaion in code
Faas-flow function follows the adapter pattern. Here the adaptee is the functions and the adapter is the flow. For each node execution, Faas-flow handle the calls to the functions. Once the execution is over, it forwards an event to itself. This way the arrangement logic is separated from the functions and is implemented in the adapter. Compositions need no code instrumentations, making functions completely independent of the details of the compositions
Aggregate pattern as chaining
Aggregation of separate function calls is done as chaining. Multiple functions can be called from a single node with order maintained as per the chain. This way one execution node can be implemented as an aggregator function that invokes multiple functions collects the results, optionally applies business logic, and returns a consolidated response to the client or forward to next nodes. Faas-flow fuses the adapter pattern and aggregate pattern to support more complex use cases
Event driven iteration
OpenFaaS uses Nats for event delivery and Faas-flow leverages OpenFaaS platform. Node execution in Faas-flow starts by a completion event of one or more previous nodes. A completion event denotes that all the previous dependent nodes have completed. The event carries the execution state and identifies the next node to execute. With events Faas-flow asynchronously carry-on execution of nodes by iterating itself over and over till all nodes are executed
3rd party KV store for coordination
When executing branches, one node is dependent on more than one predecessor nodes. In that scenario, the event for completion is generated by coordination of earlier nodes. Like any distributed system the coordination is achieved via a centralized service. Faas-flow keeps the logic of the coordination controller inside of Faas-flow implementation and lets the user use any external synchronous KV store by implementing StateStore
Results from function execution and intermediate data can be handled by the user manually. Faas-flow provides data-store for intermediate result storage. It automatically initializes, store, retrieve and remove data between nodes. This fits great for data processing applications. Faas-flow keeps the logic of storage controller inside of Faas-flow implementation and lets the user use any external object storage by implementing DataStore
Faas-flow design is not fixed and like any good design, it is evolving. Please contribute to make it better.
Getting Started
This example implements a very simple flow to Greet
Get template
Pull faas-flow
template with the faas-cli
faas template pull https://github.com/s8sg/faas-flow
Create new flow function
Create a new function using faas-flow
template
faas new greet --lang faas-flow
Edit stack
Edit function stack file greet.yml
greet:
lang: faas-flow
handler: ./greet
image: greet:latest
environment:
read_timeout: 120 # A value larger than `max` of all execution times of Nodes
write_timeout: 120 # A value larger than `max` of all execution times of Nodes
exec_timeout: 0 # disable exec timeout
write_debug: true
combine_output: false
environment_file:
- flow.yml
Add configuration
Add a separate file flow.yml
with faas-flow related configuration.
environment:
gateway: "gateway:8080" # The address of OpenFaaS gateway, Faas-flow use this to forward completion event
# gateway: "gateway.openfaas:8080" # For K8s
enable_tracing: false # tracing allow to trace internal node execution with opentracing
enable_hmac: true # hmac adds an extra layer of security by validating the event source
Edit function defnition
Edit greet/handler.go
and Update Define()
func Define(flow *faasflow.Workflow, context *faasflow.Context) (err error) {
flow.SyncNode().
Modify(func(data []byte) ([]byte, error) {
result := "Hello " + string(data)
return []byte(result), nil
})
return nil
}
Build and Deploy
Build and deploy
faas build -f greet.yml
faas deploy -f greet.yml
This function will generate one Synchronous node
Modify("name") -> Hello name
All calls will be performed in one single execution of the flow function and result will be returned to the callee
Note: For flow that has more than one nodes, Faas-flow doesn't return any response. External storage or callback can be used to retrieve an async result
Invoke
echo "Adam" | faas invoke greet
Deploy FaaS-Flow Infra
FaaS-Flow infra allows to set up the components needed to run more advance workflows
Deploy in Kubernets
Deploy in Swarm
Request Tracking by ID
For each new request, faas-flow generates a unique Request Id
for the flow. The same Id is used when logging
2018/08/13 07:51:59 [Request `bdojh7oi7u6bl8te4r0g`] Created
2018/08/13 07:52:03 [Request `bdojh7oi7u6bl8te4r0g`] Received
The assigned request Id is set on the response header X-Faas-Flow-Reqid
One may provide custom request Id by setting X-Faas-Flow-Reqid
in the request header
Request Tracing by Open-Tracing
Request tracing can be retrieved from trace_server
once enabled. Tracing is the best way to monitor flows and execution status of each node for each request
Edit flow.yml
Enable tracing and add trace server as:
enable_tracing: true
trace_server: "jaegertracing:5775"
# trace_server: "jaegertracing.faas-flow-infra:5775" # use this for kubernets
Start The Trace Server
jaeger
(opentracing-1.x) is the tracing backend
Quick start with jaegertracing: https://www.jaegertracing.io/docs/1.8/getting-started/
Retrive the requestID from X-Faas-Flow-Reqid
header of response
Below is an example of tracing information for example-branching-in-Faas-flow in Faas-flow-tower
Use of Callback
To receive a result of long running FaaSFlow request, you can specify the X-Faas-Flow-Callback-Url
. FaaSFlow will invoked the callback URL with the final result and with the request ID set as X-Faas-Flow-Reqid
in request Header. X-Callback-Url
from OpenFaaS is not supported in FaaSFlow.
Pause, Resume or Stop Request
A request in faas-flow has three states :
- Running
- Paused
- Stopped
Faas-flow doesn't keep the state of a finished request
To pause a running request:
faas invoke <workflow_name> --query pause-flow=<request_id>
To resume a paused request
faas invoke <workflow_name> --query resume-flow=<request_id>
To stop an active (pasued/running) request
faas invoke <workflow_name> --query stop-flow=<request_id>
Use of context
Context can be used inside definition for differet usecases. Context provide verious information such as:
HttpQuery to retrivbe original request queries
State to get flow state
Node to get current node
along with that it wraps the DataStore to store data
Store data in context with DataStore
Context uses DataStore
to store/retrive data. User can do the same by
calling Get()
, Set()
, and Del()
from context
:
flow.SyncNode().
Modify(func(data []byte) {
// parse data and set to be used later
// json.Unmarshal(&req, data)
context.Set("commitsha", req.Sha)
}).
Apply("myfunc").
Modify(func(data []byte) {
// retrieve the data that was set in the context
commitsha, _ = context.GetString("commitsha")
// use the query
})
Geting Http Query to Workflow:
Http Query to flow can be used retrieved from context using context.Query
flow.SyncNode().Apply("myfunc", Query("auth-token", context.Query.Get("token"))). // pass as a function query
Modify(func(data []byte) {
token = context.Query.Get("token") // get query inside modifier
})
Use of request context:
Node, requestId, State is provided by the context
currentNode := context.GetNode()
requestId := context.GetRequestId()
state := context.State
for more details check Faas-flow GoDoc
External StateStore
for coordination controller
Any DAG which has a branch needs coordination for nodes completion events, also request execution state needs to me maintained. Faas-flow implements coordination controller and request state store which allows the user to use any external Synchronous KV store. User can define custom state-store with StateStore
interface
type StateStore interface {
// Configure the StateStore with flow name and request ID
Configure(flowName string, requestId string)
// Initialize the StateStore (called only once in a request span)
Init() error
// Set a value (override existing, or create one)
Set(key string, value string) error
// Get a value
Get(key string) (string, error)
// Compare and Update a value
Update(key string, oldValue string, newValue string) error
// Cleanup all the resorces in StateStore (called only once in a request span)
Cleanup() error
}
A StateStore
can be implemented with any KV Store that provides Synchronization
. The implemented StateStore
can be set with DefineStateStore()
at function/handler.go
:
// DefineStateStore provides the override of the default StateStore
func DefineStateStore() (faasflow.StateStore, error) {
consulss, err := consulStateStore.GetConsulStateStore(os.Getenv("consul_url"), os.Getenv("consul_dc"))
return consulss, err
}
StateStore
is mandetory for a FaaSFlow to operate.
Available state-stores:
External DataStore
for storage controller
Faas-flow uses the DataStore
to store partially completed data between nodes and request context data. Faas-flow implements a storage controller to handle storage that allows the user to use any external object-store. User can define custom data-store with DataStore
interface.
type DataStore interface {
// Configure the DaraStore with flow name and request ID
Configure(flowName string, requestId string)
// Initialize the DataStore (called only once in a request span)
Init() error
// Set store a value for key, in failure returns error
Set(key string, value string) error
// Get retrives a value by key, if failure returns error
Get(key string) (string, error)
// Del delets a value by a key
Del(key string) error
// Cleanup all the resorces in DataStore
Cleanup() error
}
Data Store can be implemented and set by user at the DefineDataStore()
at function/handler.go
:
// ProvideDataStore provides the override of the default DataStore
func DefineDataStore() (faasflow.DataStore, error) {
// initialize minio DataStore
miniods, err := minioDataStore.InitFromEnv()
return miniods, err
}
DataStore
is only needed for dags that stores intermediate data
Available data-stores:
Cleanup with Finally()
Finally provides an efficient way to perform post-execution steps of the flow. If specified Finally()
invokes in case of both failure and success of the flow. A Finally method can be set as:
func Define(flow *faasflow.Workflow, context *faasflow.Context) (err error) {
// Define flow
flow.SyncNode().Modify(func(data []byte) {
// parse data and set to be used later
// json.Unmarshal(&req, data)
context.Set("commitsha", req.Sha)
}).
Apply("myfunc").Modify(func(data []byte) {
// retrieve the data in different node from context
commitsha, _ = context.GetString("commitsha")
})
flow.OnFailure(func(err error) {
// failure handler
})
flow.Finally(func() {
// delete the state resource
context.Del("commitsha")
})
}
Contribute:
Issue/Suggestion Create an issue at Faas-flow-issue.
ReviewPR/Implement Create Pull Request at Faas-flow-pr.
Join Faasflow Slack for more