App Functions SDK - Pipeline Function APIs
All pipeline functions define a type and a factory function which is used to initialize an instance of the type with the required options. The instances returned by these factory functions give access to their appropriate pipeline function pointers when setting up the function pipeline.
Example
NewFilterFor([] {"Device1", "Device2"}).FilterByDeviceName
Batching
Included in the SDK is an in-memory batch function that will hold on to your data before continuing the pipeline. There are three functions provided for batching each with their own strategy.
Factory Method | Description |
---|---|
NewBatchByTime(timeInterval string) | This function returns a BatchConfig instance with time being the strategy that is used for determining when to release the batched data and continue the pipeline. timeInterval is the duration to wait (i.e. 10s ). The time begins after the first piece of data is received. If no data has been received no data will be sent forward. |
NewBatchByCount(batchThreshold int) | This function returns a BatchConfig instance with count being the strategy that is used for determining when to release the batched data and continue the pipeline. batchThreshold is how many events to hold on to (i.e. 25 ). The count begins after the first piece of data is received and once the threshold is met, the batched data will continue forward and the counter will be reset. |
NewBatchByTimeAndCount(timeInterval string, batchThreshold int) | This function returns a BatchConfig instance with a combination of both time and count being the strategy that is used for determining when to release the batched data and continue the pipeline. Whichever occurs first will trigger the data to continue and be reset. |
Examples
NewBatchByTime("10s").Batch
NewBatchByCount(10).Batch
NewBatchByTimeAndCount("30s", 10).Batch
Property | Description |
---|---|
IsEventData | The IsEventData flag, when true, lets this function know that the data being batched is Events and to un-marshal the data a []Event prior to returning the batched data. |
MergeOnSend | The MergeOnSend flag, when true, will merge the [][]byte data to a single[]byte prior to sending the data to the next function in the pipeline. |
Batch with IsEventData
flag set to true.
batch := NewBatchByTimeAndCount("30s", 10)
batch.IsEventData = true
...
batch.Batch
Batch with MergeOnSend
flag set to true.
batch := NewBatchByTimeAndCount("30s", 10)
batch.MergeOnSend = true
...
batch.Batch
Batch
Batch
- This pipeline function will apply the selected strategy in your pipeline. By default, the batched data returned by this function is [][]byte
. This is because this function doesn't need to know the type of the individual items batched. It simply marshals the items to JSON if the data isn't already a []byte
.
Warning
Keep memory usage in mind as you determine the thresholds for both time and count. The larger they are the more memory is required and could lead to performance issue.
Compression
There are two compression types included in the SDK that can be added to your pipeline. These transforms return a []byte
.
Factory Method | Description |
---|---|
NewCompression() | This factory function returns a Compression instance that is used to access the compression functions. |
GZIP
CompressWithGZIP
- This pipeline function receives either a string
,[]byte
, or json.Marshaler
type, GZIP compresses the data, converts result to base64 encoded string, which is returned as a []byte
to the pipeline.
Example
NewCompression().CompressWithGZIP
ZLIB
CompressWithZLIB
- This pipeline function receives either a string
,[]byte
, or json.Marshaler
type, ZLIB compresses the data, converts result to base64 encoded string, which is returned as a []byte
to the pipeline.
Example
NewCompression().CompressWithZLIB
Conversion
There are two conversions included in the SDK that can be added to your pipeline. These transforms return a string
.
Factory Method | Description |
---|---|
NewConversion() | This factory function returns a Conversion instance that is used to access the conversion functions. |
JSON
TransformToJSON
- This pipeline function receives an dtos.Event
type and converts it to JSON format and returns the JSON string to the pipeline.
Example
NewConversion().TransformToJSON
XML
TransformToXML
- This pipeline function receives an dtos.Event
type, converts it to XML format and returns the XML string to the pipeline.
Example
NewConversion().TransformToXML
Event
This enables the ability to wrap data into an Event/Reading
Factory Method | Description |
---|---|
NewEventWrapperSimpleReading(profileName string, deviceName string, resourceName string, valueType string) | This factory function returns an EventWrapper instance configured to push a Simple reading. TheEventWrapper instance returned is used to access core data functions. |
NewEventWrapperBinaryReading(profileName string, deviceName string, resourceName string, mediaType string) | This factory function returns an EventWrapper instance configured to push a Binary reading. The EventWrapper instance returned is used to access core data functions. |
NewEventWrapperObjectReading(profileName string, deviceName string, resourceName string) | This factory function returns an EventWrapper instance configured to push an Object reading. The EventWrapper instance returned is used to access core data functions. |
Wrap Into Event
WrapIntoEvent
- This pipeline function provides the ability to Wrap data in an Event/Reading. The data passed into this function from the pipeline is wrapped in an EdgeX Event with the Event and Reading metadata specified from the factory function options. The function returns the new EdgeX Event with ID populated.
Example
NewEventWrapperSimpleReading("my-profile", "my-device", "my-resource", "string").Wrap
Data Protection
There are two transforms included in the SDK that can be added to your pipeline for data protection.
AESProtection
Factory Method | Description |
---|---|
NewAESProtection(secretName string, secretValueKey string) | This function returns a Encryption instance initialized with the passed in secretName and secretValueKey |
It requires a 64-byte key from secrets which is split in half, the first half used for encryption, the second for generating the signature.
Encrypt
: This pipeline function receives either a string
, []byte
, or json.Marshaller
type and encrypts it using AES256 encryption, signs it with a SHA512 hash and returns a []byte
to the pipeline of the following form:
initialization vector | ciphertext | signing hash |
---|---|---|
16 bytes | variable bytes | 32 bytes |
Example
transforms.NewAESProtection(secretName, secretValueKey).Encrypt(ctx, data)
Note
The Algorithm
used with app-service-configurable configuration to access this transform is AES256
Reading data protected with this function is a multistep process:
- base64 decode (for languages other than go - example code assumes hex encoding)
- extract hash from payload (last 32 bytes)
- validate hash - if this step fails decryption should not be attempted
- decrypt ciphertext + remove padding
Signing Hash Validation
def hash(cipher_hex, key):
# Extract the 32 bytes of the Hash signature from the end of the cipher_hex
extract_hash = cipher_hex[-64:]
# last 32 bytes of the 64 byte key used by the encrypt function (2 hex digits per byte)
private_key = key[-64:]
# IV & ciphertext
content = cipher_hex[:-64]
hash_text = hmac.new(key=bytes.fromhex(private_key), msg=(bytes.fromhex(content) + bytearray(8)), digestmod='SHA512')
# Calculated tag is only the the first 32 bytes of the resulting SHA512
calculated_hash = hash_text.hexdigest()[:64]
if extract_hash == calculated_hash:
return "true"
else:
return "false", extract_hash, calculated_hash
If the signing hash can be validated, the message is OK to decrypt
Payload Decryption
def decrypt(cipher_hex, key):
# first 32 bytes of the 64 byte key used by the encrypt function (2 hex digits per byte)
private_key = bytes.fromhex(key[:64])
# Extract the cipher text (remaining bytes in the middle)
cipher_text = cipher_hex[32:]
cipher_text = bytes.fromhex(cipher_text[:-64])
# Extract the 16 bytes of initial vector from the beginning of the data
iv = bytes.fromhex(cipher_hex[:32])
# Decrypt
cipher = AES.new(private_key, AES.MODE_CBC, iv)
plain_pad = cipher.decrypt(cipher_text)
unpadded = Padding.unpad(plain_pad, AES.block_size)
return unpadded.decode('utf-8')
Export
There are two export functions included in the SDK that can be added to your pipeline.
HTTP Export
Factory Method | Description |
---|---|
NewHTTPSender(url string, mimeType string, persistOnError bool) | This factory function returns a HTTPSender instance initialized with the passed in url, mime type and persistOnError values. |
NewHTTPSenderWithSecretHeader(url string, mimeType string, persistOnError bool, headerName string, secretName string, secretValueKey string) | This factory function returns a HTTPSender instance similar to the above function however will set up the HTTPSender to add a header to the HTTP request using the headerName for the field name and the secretName and secretValueKey to pull the header field value from the Secret Store. |
NewHTTPSenderWithOptions(options HTTPSenderOptions) | This factory function returns a HTTPSender using the passed in options to configure it. |
// HTTPSenderOptions contains all options available to the sender
type HTTPSenderOptions struct {
// URL of destination
URL string
// MimeType to send to destination
MimeType string
// PersistOnError enables use of store & forward loop if true
PersistOnError bool
// HTTPHeaderName to use for passing configured secret
HTTPHeaderName string
// SecretName to search for configured secret
SecretName string
// SecretValueKey is the key for configured secret data
SecretValueKey string
// URLFormatter specifies custom formatting behavior to be applied to configured URL.
// If nothing specified, default behavior is to attempt to replace placeholders in the
// form '{some-context-key}' with the values found in the context storage.
URLFormatter StringValuesFormatter
// ContinueOnSendError allows execution of subsequent chained senders after errors if true
ContinueOnSendError bool
// ReturnInputData enables chaining multiple HTTP senders if true
ReturnInputData bool
}
HTTP POST
HTTPPost
- This pipeline function receives either a string
, []byte
, or json.Marshaler
type from the previous function in the pipeline and posts it to the configured endpoint and returns the HTTP response. If no previous function exists, then the event that triggered the pipeline, marshaled to json, will be used. If the post fails and persistOnError=true
and Store and Forward
is enabled, the data will be stored for later retry. See Store and Forward for more details. If ReturnInputData=true
the function will return the data that it received instead of the HTTP response. This allows the following function in the pipeline to be another HTTP Export which receives the same data but is configured to send to a different endpoint. When chaining for multiple HTTP Exports you need to decide how to handle errors. Do you want to stop execution of the pipeline or continue so that the next HTTP Export function can attempt to export to its endpoint? This is where ContinueOnSendError
comes in. If set to true
the error is logged and the function returns the received data for the next function to use. ContinueOnSendError=true
can only be used when ReturnInputData=true
and cannot be use when PersistOnError=true
.
Example
POST
NewHTTPSender("https://myendpoint.com","application/json",false).HTTPPost
PUT
NewHTTPSender("https://myendpoint.com","application/json",false).HTTPPut
POST with secure header NewHTTPSenderWithSecretHeader("https://myendpoint.com","application/json",false,"Authentication","/jwt","AuthToken").HTTPPost
PUT with secure header NewHTTPSenderWithSecretHeader("https://myendpoint.com","application/json",false,"Authentication","/jwt","AuthToken").HTTPPPut
HTTP PUT
HTTPPut
- This pipeline function operates the same as HTTPPost
but uses the PUT
method rather than POST
.
URL Formatting
The configured URL is dynamically formatted prior to the POST/PUT request. The default formatter (used if URLFormatter
is nil) simply replaces any placeholder text, {key-name}
, in the configured URL with matching values from the new Context Storage
. An error will occur if a specified placeholder does not exist in the Context Storage
. See the Context Storage documentation for more details on seeded values and storing your own values.
The URLFormatter
option allows you to override the default formatter with your own custom URL formatting scheme.
Example
Export the Events to different endpoints base on their device name
Url="http://myhost.com/edgex-events/{devicename}"
HTTP Request Header Parameters
Method | Description |
---|---|
SetHttpRequestHeaders(httpRequestHeaders map[string]string) | This function sets the request header parameters which will be passed in HTTP request |
Example
httpRequestHeaders = map[string]string{ "Connection": "keep-alive", "From": "user@example.com" }
SetHttpRequestHeaders(httpRequestHeaders)
MQTT Export
Factory Method | Description |
---|---|
NewMQTTSecretSender(mqttConfig MQTTSecretConfig, persistOnError bool) | This factory function returns a MQTTSecretSender instance initialized with the options specified in the MQTTSecretConfig and persistOnError . |
NewMQTTSecretSenderWithTopicFormatter(mqttConfig MQTTSecretConfig, persistOnError bool, topicFormatter StringValuesFormatter) | This factory function returns a MQTTSecretSender instance initialized with the options specified in the MQTTSecretConfig , persistOnError and topicFormatter . See Topic Formatting below for more details. |
type MQTTSecretConfig struct {
// BrokerAddress should be set to the complete broker address i.e. mqtts://mosquitto:8883/mybroker
BrokerAddress string
// ClientId to connect with the broker with.
ClientId string
// The name of the secret in secret provider to retrieve your secrets
SecretName string
// AutoReconnect indicated whether or not to retry connection if disconnected
AutoReconnect bool
// KeepAlive is the interval duration between client sending keepalive ping to broker
KeepAlive string
// ConnectTimeout is the duration for timing out on connecting to the broker
ConnectTimeout string
// Topic that you wish to publish to
Topic string
// QoS for MQTT Connection
QoS byte
// Retain setting for MQTT Connection
Retain bool
// SkipCertVerify
SkipCertVerify bool
// AuthMode indicates what to use when connecting to the broker.
// Options are "none", "cacert" , "usernamepassword", "clientcert".
// If a CA Cert exists in the SecretName data then it will be used for
// all modes except "none".
AuthMode string
// Will contains the Last Will configuration for the MQTT Client
Will WillConfig
}
type WillConfig struct {
// Enabled enables Last Will capability on the client connection
Enabled bool
// Payload is the Last Will Message sent to other clients that are subscribed to the Will Topic
Payload string
// Qos is the Quality of Service for the Will Topic
Qos byte
// Retained is the "retain" setting for the Will Topic
Retained bool
// Topic is the topic the Last Will message is published when service disconnects from MQTT Broker
Topic string
}
See MQTT Last Will for more details on MQTT Last Will capability.
EdgeX 3.1
Last Will capability is new in EdgeX 3.1
Secrets in the Secret Store may be located at any SecretName however they must have some or all the follow keys at the specified in the secret data:
username
- username to connect to the brokerpassword
- password used to connect to the brokerclientkey
- client private key in PEM formatclientcert
- client cert in PEM formatcacert
- ca cert in PEM format
The AuthMode
setting you choose depends on what secret values above are used. For example, if "none" is specified as auth mode all keys will be ignored. Similarly, if AuthMode
is set to "clientcert" username and password will be ignored.
Topic Formatting
The configured Topic is dynamically formatted prior to publishing . The default formatter (used if topicFormatter
is nil) simply replaces any placeholder text, {key-name}
, in the configured Topic
with matching values from the new Context Storage
. An error will occur if a specified placeholder does not exist in the Context Storage
. See the Context Storage documentation for more details on seeded values and storing your own values.
The topicFormatter
option allows you to override the default formatter with your own custom topic formatting scheme.
Filtering
There are four basic types of filtering included in the SDK to add to your pipeline. There is also an option to Filter Out
specific items. These provided filter functions return a type of dtos.Event
. If filtering results in no remaining data, the pipeline execution for that pass is terminated. If no values are provided for filtering, then data flows through unfiltered.
Factory Method | Description |
---|---|
NewFilterFor([]string filterValues) | This factory function returns a Filter instance initialized with the passed in filter values with FilterOut set to false . This Filter instance is used to access the following filter functions that will operate using the specified filter values. |
NewFilterOut([]string filterValues) | This factory function returns a Filter instance initialized with the passed in filter values with FilterOut set to true . This Filter instance is used to access the following filter functions that will operate using the specified filter values. |
type Filter struct {
// Holds the values to be filtered
FilterValues []string
// Determines if items in FilterValues should be filtered out. If set to true all items found in the filter will be removed. If set to false all items found in the filter will be returned. If FilterValues is empty then all items will be returned.
FilterOut bool
}
Note
Either strings or regular expressions are accepted as filter values.
By Profile Name
FilterByProfileName
- This pipeline function will filter the event data down to Events that either have (For) or don't have (Out) the specified profiles names.
Example
NewFilterFor([] {"Profile1", "Profile2"}).FilterByProfileName
NewFilterFor([] {"Profile[0-9]+"}).FilterByProfileName
By Device Name
FilterByDeviceName
- This pipeline function will filter the event data down to Events that either have (For) or don't have (Out) the specified device names.
Example
NewFilterFor([] {"(Device)1, Device2"}).FilterByDeviceName
NewFilterFor([] {"(Device)[0-9]+"}).FilterByDeviceName
By Source Name
FilterBySourceName
- This pipeline function will filter the event data down to Events that either have (For) or don't have (Out) the specified source names. Source name is either the resource name
or command name
responsible for the Event creation.
Example
NewFilterFor([] {"Source1", "Source2"}).FilterBySourceName
NewFilterFor([] {"Source[0-9]+"}).FilterBySourceName
By Resource Name
FilterByResourceName
- This pipeline function will filter the Event's reading data down to Readings that either have (For) or don't have (Out) the specified resource names. If the result of filtering is zero Readings remaining, the function terminates pipeline execution.
Example
NewFilterFor([] {"Resource1", "Resource2"}).FilterByResourceName
NewFilterFor([] {"Resource[0-9]+"}).FilterByResourceName
JSON Logic
Factory Method | Description |
---|---|
NewJSONLogic(rule string) | This factory function returns a JSONLogic instance initialized with the passed in JSON rule. The rule passed in should be a JSON string conforming to the specification here: http://jsonlogic.com/operations.html. |
Evaluate
Evaluate
- This is the pipeline function that will be used in the pipeline to apply the JSON rule to data coming in on the pipeline. If the condition of your rule is met, then the pipeline will continue and the data will continue to flow to the next function in the pipeline. If the condition of your rule is NOT met, then pipeline execution stops.
Example
NewJSONLogic("{ \"in\" : [{ \"var\" : \"device\" },
[\"Random-Integer-Device\",\"Random-Float-Device\"] ] }").Evaluate
Note
Only operations that return true or false are supported. See http://jsonlogic.com/operations.html# for the complete list of operations paying attention to return values. Any operator that returns manipulated data is currently not supported. For more advanced scenarios checkout LF Edge eKuiper.
Tip
Leverage http://jsonlogic.com/play.html to get your rule right before implementing in code. JSON can be a bit tricky to get right in code with all the escaped double quotes.
Response Data
There is one response data function included in the SDK that can be added to your pipeline.
Factory Method | Description |
---|---|
NewResponseData() | This factory function returns a ResponseData instance that is used to access the following pipeline function below. |
Content Type
ResponseContentType
- This property is used to set the content-type of the response.
Example
responseData := NewResponseData()
responseData.ResponseContentType = "application/json"
Set Response Data
SetResponseData
- This pipeline function receives either a string
,[]byte
, or json.Marshaler
type from the previous function in the pipeline and sets it as the response data that the pipeline returns to the configured trigger. If configured to use theEdgeXMessageBus
trigger, the data will be published back to the EdgeX MessageBus as determined by the configuration. Similar, if configured to use theExternalMQTT
trigger, the data will be published back to the external MQTT Broker as determined by the configuration. If configured to use HTTP
trigger the data is returned as the HTTP response.
Note
Calling SetResponseData()
and SetResponseContentType()
from the Context API in a custom function can be used in place of adding this function to your pipeline.
Tags
There is one Tags transform included in the SDK that can be added to your pipeline.
Factory Method | Description |
---|---|
NewTags(tags map[string]interface{} ) Tags |
This factory function returns a Tags instance initialized with the passed in collection of generic tag key/value pairs. This Tags instance is used to access the following Tags function that will use the specified collection of tag key/value pairs. This allows for generic complex types for the Tag values. |
Add Tags
AddTags
- This pipeline function receives an Edgex Event
type and adds the collection of specified tags to the Event's Tags
collection.
Example
var myTags = map[string]interface{}{
"MyValue" : 123,
"GatewayId": "HoustonStore000123",
"Coordinates": map[string]float32 {
"Latitude": 29.630771,
"Longitude": "-95.377603",
},
}
NewGenericTags(myTags).AddTags
MetricsProcessor
MetricsProcessor
contains configuration and functions for processing the new dtos.Metrics
type.
Factory Method | Description |
---|---|
NewMetricsProcessor(additionalTags map[string]interface{}) (*MetricsProcessor, error) | This factory function returns a `MetricsProcessor instance initialized with the passed in collection of additionalTags (name/value pairs). This MetricsProcessor instance is used to access the following functions that will process a dtos.Metric instance. The additionalTags are added as metric tags to the processed data. An error will be returned if any of the additionalTags have an invalid name. Currently must be non-blank. |
ToLineProtocol
ToLineProtocol
- This pipeline function will transform the received dtos.Metric
to a Line Protocol
formatted string. See https://docs.influxdata.com/influxdb/v2.0/reference/syntax/line-protocol/ for details on the Line Protocol
syntax.
Note
When ToLineProtocol
is the first function in the functions pipeline, the TargetType
for the service must be set to &dtos.Metric{}
. See Target Type section for details on setting the service's TargetType
. The Trigger configuration must also be set so SubscribeTopics="edgex/telemetry/#"
in order to receive the dtos.Metric
data from other services. See the new App Service Configurable metrics-influxdb
profile for an example.
Example
mp, err := NewMetricsProcessor(map[string]string{"MyTag":"MyTagValue"})
if err != nil {
... handle error
}
...
mp.ToLineProtocol
Warning
Any service using the MetricsProcessor
needs to disable its own Telemetry reporting to avoid circular data generation from processing. To do this set the servicesWriteable.Telemetry
configuration to:
[Writable.Telemetry]
Interval = "0s" # Don't report any metrics as that would be cyclic processing.