Tame Cloud Complex with F# powered DSLs

Yan Cui
Yan CuiSpeaker at Self
••
@theburningmonk tame |> (cloud <| complexity) |> with |> (fsharp >> powered >> DSLs)
Tame Cloud Complex with F# powered DSLs
Tame Cloud Complex with F# powered DSLs
Tame Cloud Complex with F# powered DSLs
Tame Cloud Complex with F# powered DSLs
image by nerovivo license : https://creativecommons.org/licenses/by-sa/2.0/
@theburningmonk Under-Abstraction
@theburningmonk Oversimplification
@theburningmonk Impedance Mismatch
@theburningmonk Amazon DynamoDB Amazon SimpleWorkflow Amazon CloudWatch CASE STUDY
@theburningmonk F# DSLs. Awesome!
@theburningmonk Amazon DynamoDB Amazon SimpleWorkflow Amazon CloudWatch CASE STUDY
@theburningmonk
@theburningmonk managed key-value store
@theburningmonk redundancy 9-9s guarantee
@theburningmonk great performance
@theburningmonk name your throughput
@theburningmonk
@theburningmonk can be changed on-the-fly
@theburningmonk
@theburningmonk infinitely scalable (but you still have to pay for it)
@theburningmonk
Hash Key Range Key
@theburningmonk Query: given a hash key filter on range key, or local secondary index
@theburningmonk
Hash Key Range Key Local Secondary Index Global Secondary Index
@theburningmonk Scan: FULL TABLE search (performance + cost concern)
@theburningmonk
Hash Key Range Key Local Secondary Index Global Secondary Index
Hash Key Range Key Local Secondary Index Who are the TOP 3 players in “Starship X” with a score of at least 1000? Global Secondary Index
@theburningmonk
@theburningmonk select GameTitle, UserId, TopScore from GameScores where GameTitle = “Starship X” and TopScore >= 1000 order desc limit 3 with (NoConsistentRead, Index(GameTitleIndex, true))
DynamoDB.SQL github.com/fsprojects/DynamoDb.SQL
@theburningmonk GOAL Disguise complexity
@theburningmonk GOAL SELECT UserId, TopScore FROM GameScore WHERE GameTitle CONTAINS “Zelda” ORDER DESC LIMIT 3 WITH (NoConsistentRead)
@theburningmonk Query AST Execution
F# & FParsec* *www.quanttec.com/fparsec External DSL via
@theburningmonk
@theburningmonk SELECT * FROM GameScore Abstract Syntax Tree (AST) FParsec
@theburningmonk SELECT * FROM GameScore keyword keyword * | attribute, attribute, … table name
@theburningmonk SELECT * FROM GameScore type Attributes = | Asterisk | Attributes of string[]
@theburningmonk SELECT * FROM GameScore type Query = { Attributes : Attributes Table : string }
@theburningmonk SELECT * FROM GameScore Parser for “SELECT” keyword pSelect
@theburningmonk SELECT * FROM GameScore pSelect let pSelect = skipStringCI "select"
@theburningmonk SELECT * FROM GameScore pSelect let pSelect = skipStringCI "select" matches the string “select” (Case Insensitive) and ignores it
@theburningmonk SELECT * FROM GameScore pFrom let pFrom = skipStringCI "from"
@theburningmonk SELECT * FROM GameScore Parser for a string that represents the table name pTableName
@theburningmonk SELECT * FROM GameScore pTableName let isTableName = isLetter <||> isDigit let pTableName = many1Satisfy isTableName
@theburningmonk SELECT * FROM GameScore pTableName let isTableName = isLetter <||> isDigit let pTableName = many1Satisfy isTableName
@theburningmonk SELECT * FROM GameScore pTableName let isTableName = isLetter <||> isDigit let pTableName = many1Satisfy isTableName
@theburningmonk SELECT * FROM GameScore pTableName let isTableName = isLetter <||> isDigit let pTableName = many1Satisfy isTableName
@theburningmonk SELECT * FROM GameScore pTableName let isTableName = isLetter <||> isDigit let pTableName = many1Satisfy isTableName parses a sequence of one or more chars that satisfies the predicate function
@theburningmonk SELECT * FROM GameScore pAsterisk * pAttributeName UserId, GameTitle, TopScore, …
@theburningmonk SELECT * FROM GameScore pAsterisk * pAttributeName UserId, GameTitle, TopScore, … let pAsterisk = stringCIReturn "*" Asterisk
@theburningmonk SELECT * FROM GameScore pAsterisk * pAttributeName UserId, GameTitle, TopScore, … let pAsterisk = stringCIReturn "*" Asterisk matches the specified string and return the given value
@theburningmonk SELECT * FROM GameScore pAsterisk * pAttributeName UserId, GameTitle, TopScore, … let isAttributeName = isLetter <||> isDigit let pAttributeName = many1Satisfy isAttributeName
@theburningmonk SELECT * FROM GameScore UserId, GameTitle, TopScore, … pAttributeName pCommapAsterisk * let pComma = skipStringCI ","
@theburningmonk SELECT * FROM GameScore UserId, GameTitle, TopScore, … pAttributeName pCommapAsterisk * let pAttributeNames = sepBy1 pAttributeName pComma
@theburningmonk SELECT * FROM GameScore UserId, GameTitle, TopScore, … pAttributeName pCommapAsterisk * let pAttributeNames = sepBy1 pAttributeName pComma parses one or more occurrences of pAttributeName separated by pComma
@theburningmonk SELECT * FROM GameScore UserId, GameTitle, TopScore, … pAttributeName pComma sepBy1 pAttributeNames pAsterisk *
@theburningmonk SELECT * FROM GameScore pAsterisk * pAttributeNames UserId, GameTitle, TopScore, …
@theburningmonk SELECT * FROM GameScore pAsterisk * pAttributeNames UserId, GameTitle, TopScore, … let pAttribute = pAsterisk <|> pAttributeNames
@theburningmonk SELECT * FROM GameScore pAsterisk * pAttributeNames UserId, GameTitle, TopScore, … let pAttribute = pAsterisk <|> pAttributeNames
@theburningmonk SELECT * FROM GameScore pAsterisk * pAttributeNames UserId, GameTitle, TopScore, … choice pAttribute
@theburningmonk SELECT * FROM GameScore pAttribute
@theburningmonk SELECT * FROM GameScore pAttribute pTableNamepFrompSelect
@theburningmonk SELECT * FROM GameScore pAttribute pTableNamepFrompSelect let pQuery = tuple4 pSelect pAttribute pFrom pTableName |>> (fun (_, attributes, _, table) -> { Attributes = attributes Table = table })
@theburningmonk SELECT * FROM GameScore pAttribute pTableNamepFrompSelect let pQuery = tuple4 pSelect pAttribute pFrom pTableName |>> (fun (_, attributes, _, table) -> { Attributes = attributes Table = table })
@theburningmonk SELECT * FROM GameScore pAttribute pTableNamepFrompSelect let pQuery = tuple4 pSelect pAttribute pFrom pTableName |>> (fun (_, attributes, _, table) -> { Attributes = attributes Table = table })
@theburningmonk SELECT * FROM GameScore pAttribute pTableNamepFrompSelect let pQuery = tuple4 pSelect pAttribute pFrom pTableName |>> (fun (_, attributes, _, table) -> { Attributes = attributes Table = table }) Query
@theburningmonk SELECT * FROM GameScore pAttribute pTableNamepFrompSelect tuple4 pQuery
@theburningmonk
@theburningmonk < 50 lines of code
@theburningmonk Amazing F# + FParsec =
@theburningmonk Recap
@theburningmonk
@theburningmonk select GameTitle, UserId, TopScore from GameScores where GameTitle = “Starship X” and TopScore >= 1000 order desc limit 3 with (NoConsistentRead, Index(GameTitleIndex, true))
@theburningmonk Amazon DynamoDB Amazon SimpleWorkflow Amazon CloudWatch CASE STUDY
@theburningmonk
@theburningmonk Decision Worker
@theburningmonk Decision Worker Poll
@theburningmonk Decision Worker Decision Task
@theburningmonk Decision WorkerDecide
@theburningmonk Activity Worker Decision Worker
@theburningmonk Activity Worker Decision Worker Poll
@theburningmonk Activity Worker Decision Worker Activity Task
@theburningmonk Activity Worker Decision Worker Complete
@theburningmonk Workers can run from anywhere
@theburningmonk
@theburningmonk input = “Yan” result = “Hello Yan!” Start Finish Activity
@theburningmonk
image by Ryan Hageman license : https://creativecommons.org/licenses/by-sa/2.0/
SWF-based Application
API
Heartbeats Error Handling Polling API
Activity Worker Decision Worker Heartbeats Error Handling Polling API
Activity Worker Decision Worker Heartbeats Error Handling Polling API Boilerplate
– Kris Jordan “Good simplicity is less with leverage, not less with less. Good simplicity is complexity disguised, not complexity denied.”
http://bit.ly/1pOLeKl
Tame Cloud Complex with F# powered DSLs
Start Finish Activity ?
@theburningmonk the workflow is implied by decision worker logic…
@theburningmonk instead..
@theburningmonk the workflow should drive decision worker logic
@theburningmonk the workflow should driveautomate decision worker logic
Amazon .SimpleWorkflow .Extensions github.com/fsprojects/Amazon.SimpleWorkflow.Extensions
@theburningmonk GOAL Remove boilerplates
@theburningmonk GOAL Code that matches the way you think
@theburningmonk Start Finish Activity
Tame Cloud Complex with F# powered DSLs
Tame Cloud Complex with F# powered DSLs
Start Finish Activity
Tame Cloud Complex with F# powered DSLs
@theburningmonk Workflows can be nested
Tame Cloud Complex with F# powered DSLs
Tame Cloud Complex with F# powered DSLs
input result
Tame Cloud Complex with F# powered DSLs
@theburningmonk Recap
Activity Worker Decision Worker Heartbeats Error Handling Polling API
Tame Cloud Complex with F# powered DSLs
@theburningmonk Amazon DynamoDB Amazon SimpleWorkflow Amazon CloudWatch CASE STUDY
@theburningmonk
@theburningmonk
@theburningmonk
@theburningmonk wanna find correlations?
@theburningmonk wanna find correlations? you can DIY it! ;-)
@theburningmonk “what latencies spiked at the same time as payment service?”
Amazon .CloudWatch .Selector github.com/fsprojects/Amazon.CloudWatch.Selector
@theburningmonk Find metrics whose 5 min average exceeded 1 second during last 12 hours
@theburningmonk cloudWatch.Select( unitIs “milliseconds” + average (>) 1000.0 @ last 12 hours |> intervalOf 5 minutes)
@theburningmonk cloudWatch.Select(“ unitIs ‘milliseconds’ and average > 1000.0 duringLast 12 hours at intervalOf 5 minutes”)
@theburningmonk “did any cache nodes’ CPU spike yesterday?”
@theburningmonk cloudWatch.Select( namespaceLike “elasticache” + nameLike “cpu” + max (>) 80.0 @ last 24 hours |> intervalOf 15 minutes)
@theburningmonk cloudWatch.Select( namespaceLike “elasticache” + nameLike “cpu” + max (>) 80.0 @ last 24 hours |> intervalOf 15 minutes) Regex
@theburningmonk
@theburningmonk
@theburningmonk
@theburningmonk namespaceIs ‘JustEat’ and nameLike ‘cpu’ and unitIs ‘milliseconds’ and average > 1000.0 duringLast 12 hours at intervalOf 5 minutes
@theburningmonk namespaceIs ‘JustEat’ and nameLike ‘cpu’ and unitIs ‘milliseconds’ and average > 1000.0 duringLast 12 hours at intervalOf 5 minutes Filters
@theburningmonk namespaceIs ‘JustEat’ and nameLike ‘cpu’ and unitIs ‘milliseconds’ and average > 1000.0 duringLast 12 hours at intervalOf 5 minutes TimeFrame
@theburningmonk namespaceIs ‘JustEat’ and nameLike ‘cpu’ and unitIs ‘milliseconds’ and average > 1000.0 duringLast 12 hours at intervalOf 5 minutes Period
@theburningmonk type Query = { Filter : Filter TimeFrame : TimeFrame Period : Period option }
@theburningmonk Query Internal DSL External DSL
@theburningmonk namespaceIs ‘JustEat’ and nameLike ‘cpu’ and unitIs ‘milliseconds’ and average > 1000.0 duringLast 12 hours at intervalOf 5 minutes
@theburningmonk type MetricTerm = Namespace | Name type Filter = | MetricFilter of MetricTerm * (string -> bool)
@theburningmonk namespaceIs ‘JustEat’ and nameLike ‘cpu’ and unitIs ‘milliseconds’ and average > 1000.0 duringLast 12 hours at intervalOf 5 minutes
@theburningmonk type MetricTerm = Namespace | Name type Unit = | Unit type Filter = | MetricFilter of MetricTerm * (string -> bool) | UnitFilter of Unit * (string -> bool)
@theburningmonk namespaceIs ‘JustEat’ and nameLike ‘cpu’ and unitIs ‘milliseconds’ and average > 1000.0 duringLast 12 hours at intervalOf 5 minutes
@theburningmonk type MetricTerm = Namespace | Name type Unit = | Unit type StatsTerm = | Average | Min | Max | Sum | SampleCount type Filter = | MetricFilter of MetricTerm * (string -> bool) | UnitFilter of Unit * (string -> bool) | StatsFilter of StatsTerm * (float -> bool)
@theburningmonk namespaceIs ‘JustEat’ and nameLike ‘cpu’ and unitIs ‘milliseconds’ and average > 1000.0 duringLast 12 hours at intervalOf 5 minutes
@theburningmonk type MetricTerm = Namespace | Name type Unit = | Unit type StatsTerm = | Average | Min | Max | Sum | SampleCount type Filter = | MetricFilter of MetricTerm * (string -> bool) | UnitFilter of Unit * (string -> bool) | StatsFilter of StatsTerm * (float -> bool) | CompositeFilter of Filter * Filter
@theburningmonk namespaceIs ‘JustEat’ and nameLike ‘cpu’ and unitIs ‘milliseconds’ and average > 1000.0 duringLast 12 hours at intervalOf 5 minutes
@theburningmonk type TimeFrame = | Last of TimeSpan | Since of DateTime | Between of DateTime * DateTime
@theburningmonk namespaceIs ‘JustEat’ and nameLike ‘cpu’ and unitIs ‘milliseconds’ and average > 1000.0 duringLast 12 hours at intervalOf 5 minutes
@theburningmonk type Period = | Period of TimeSpan
@theburningmonk type Query = { Filter : Filter TimeFrame : TimeFrame Period : Period option }
@theburningmonk Active Patterns a primer on
@theburningmonk allow patterns to be abstracted away into named functions
@theburningmonk Single-Case Patterns
@theburningmonk let (|Float|) input = match Double.TryParse input with | true, n -> n | _ -> failwithf “not a float [%s]” input
@theburningmonk let (|Float|) input = match Double.TryParse input with | true, n -> n | _ -> failwithf “not a float [%s]” input
@theburningmonk let (|Float|) input = match Double.TryParse input with | true, n -> n | _ -> failwithf “not a float [%s]” input Float : string -> float
@theburningmonk match someString with | Float 42.0 -> “ftw” | Float 11.0 -> “palprime” | Float x -> sprintf “just %f” x
@theburningmonk let (|Float|) input = match Double.TryParse input with | true, n -> n match someString with | Float 42.0 -> “ftw” | Float 11.0 -> “palprime” | Float x -> sprintf “just %f” x
@theburningmonk let (|Float|) input = match Double.TryParse input with | true, n -> n match someString with | Float 42.0 -> “ftw” | Float 11.0 -> “palprime” | Float x -> sprintf “just %f” x
@theburningmonk match someString with | Float 42.0 -> “ftw” | Float 11.0 -> “palprime” | Float x -> sprintf “just %f” x let (|Float|) input = match Double.TryParse input with | true, n -> n
@theburningmonk match someString with | Float 42.0 -> “ftw” | Float 11.0 -> “palprime” | Float x -> sprintf “just %f” x let (|Float|) input = match Double.TryParse input with | true, n -> n
@theburningmonk match “42” with | Float 42.0 -> “ftw” | Float 11.0 -> “palprime” | Float x -> sprintf “just %f” x
@theburningmonk match “boo” with | Float 42.0 -> “ftw” | Float 11.0 -> “palprime” | Float x -> sprintf “just %f” x Error!!!
@theburningmonk Partial Patterns
@theburningmonk let (|Float|_|) input = match Double.TryParse input with | true, n -> Some n | _ -> None
@theburningmonk let (|Float|_|) input = match Double.TryParse input with | true, n -> Some n | _ -> None Float : string -> float option
@theburningmonk match “boo” with | Float 42.0 -> “ftw” | Float 11.0 -> “palprime” | Float x -> sprintf “just %f” x | _ -> “not a float”
@theburningmonk match “boo” with | Float 42.0 -> “ftw” | Float 11.0 -> “palprime” | Float x -> sprintf “just %f” x | _ -> “not a float”
@theburningmonk Multi-Case Patterns
@theburningmonk let (|Prime|NotPrime|NaN|) input = match Double.TryParse input with | true, n when isPrime n -> Prime n | true, n -> NotPrime n | _ -> NaN
@theburningmonk let (|Prime|NotPrime|NaN|) input = match Double.TryParse input with | true, n when isPrime n -> Prime n | true, n -> NotPrime n | _ -> NaN
@theburningmonk let (|Prime|NotPrime|NaN|) input = match Double.TryParse input with | true, n when isPrime n -> Prime n | true, n -> NotPrime n | _ -> NaN
@theburningmonk let (|Prime|NotPrime|NaN|) input = match Double.TryParse input with | true, n when isPrime n -> Prime n | true, n -> NotPrime n | _ -> NaN
@theburningmonk let (|Prime|NotPrime|NaN|) input = match Double.TryParse input with | true, n when isPrime n -> Prime n | true, n -> NotPrime n | _ -> NaN
@theburningmonk match someString with | Prime n -> … | NotPrime n -> … | NaN -> …
@theburningmonk match someString with | Prime n & Float 11.0 -> … | Prime n -> … | Float 42.0 | Float 8.0 -> … | NotPrime n -> … | NaN -> …
@theburningmonk match someString with | Prime n & Float 11.0 -> … | Prime n -> … | Float 42.0 | Float 8.0 -> … | NotPrime n -> … | NaN -> …
@theburningmonk match someString with | Prime (IsPalindrome) -> … | Prime _ -> … | _ -> …
@theburningmonk Tokenise (string -> string list)
@theburningmonk [ “namespaceIs”; “‘JustEat’”; “and”; “nameLike”; “‘cpu’”; “and”; … ]
@theburningmonk “namespaceIs” “and” … F# List = LinkedList “‘JustEat’”
@theburningmonk “namespaceIs” “and” … F# List = LinkedList “namespaceIs” “‘JustEat’” “and”:::: :: tail cons (::) operator to prepend “‘JustEat’”
@theburningmonk “namespaceIs” “and” … F# List = LinkedList “namespaceIs” “‘JustEat’” “and”:::: :: tail match aList with | “‘JustEat’” works as a pattern too!
@theburningmonk let (|StringCI|_|) (str : string) (input : string) = if str.ToLower() = input.ToLower() then Some () else None let (|Float|_|) input = match System.Double.TryParse input with | true, n -> Some n | _ -> None
@theburningmonk let (|EmptyString|_|) input = if String.IsNullOrWhiteSpace input then Some () else None let (|StartsWith|_|) char (input : string) = if input.[0] = char then Some () else None let (|EndsWith|_|) char (input : string) = if input.[input.Length-1] = char then Some () else None
@theburningmonk let (|QuotedString|_|) (input : string) = match input with | EmptyString -> None | str when str.Length < 2 -> None | StartsWith ''' & EndsWith ''' -> Some <| input.Substring(1, input.Length - 2) | _ -> None
@theburningmonk let (|NamespaceIs|_|) = function | StringCI “NamespaceIs" :: QuotedString ns :: tl -> Some (eqFilter MetricFilter Namespace ns, tl) | _ -> None
@theburningmonk let (|NamespaceIs|_|) = function | StringCI “NamespaceIs" :: QuotedString ns :: tl -> Some (eqFilter MetricFilter Namespace ns, tl) | _ -> None namespaceIs ‘JustEat’ and nameLike ‘cpu’ and …
@theburningmonk let (|NamespaceIs|_|) = function | StringCI “NamespaceIs" :: QuotedString ns :: tl -> Some (eqFilter MetricFilter Namespace ns, tl) | _ -> None “namespaceIs” “‘JustEat’” :::: …
@theburningmonk let (|NamespaceIs|_|) = function | StringCI “NamespaceIs" :: QuotedString ns :: tl -> Some (eqFilter MetricFilter Namespace ns, tl) | _ -> None type MetricTerm = Namespace | Name type Filter = | MetricFilter of MetricTerm * (string -> bool)
@theburningmonk let (|NamespaceIs|_|) = function | StringCI “NamespaceIs" :: QuotedString ns :: tl -> Some (eqFilter MetricFilter Namespace ns, tl) | _ -> None “and” :: “nameLike” :: “‘cpu’” :: “and” :: …
@theburningmonk let rec loop acc = function | NamespaceIs (filter, tl) | NamespaceLike (filter, tl) | NameIs (filter, tl) | NameLike (filter, tl) | UnitIs (filter, tl) | Average (filter, tl) | Sum (filter, tl) | Min (filter, tl) | Max (filter, tl) | SampleCount (filter, tl) -> match tl with | And tl -> loop (filter::acc) tl | _ -> flatten (filter::acc), tl | _ -> failwith “No filters?!?!?”
@theburningmonk let rec loop acc = function | NamespaceIs (filter, tl) | NamespaceLike (filter, tl) | NameIs (filter, tl) | NameLike (filter, tl) | UnitIs (filter, tl) | Average (filter, tl) | Sum (filter, tl) | Min (filter, tl) | Max (filter, tl) | SampleCount (filter, tl) -> match tl with | And tl -> loop (filter::acc) tl | _ -> flatten (filter::acc), tl | _ -> failwith “No filters?!?!?”
@theburningmonk let rec loop acc = function | NamespaceIs (filter, tl) | NamespaceLike (filter, tl) | NameIs (filter, tl) | NameLike (filter, tl) | UnitIs (filter, tl) | Average (filter, tl) | Sum (filter, tl) | Min (filter, tl) | Max (filter, tl) | SampleCount (filter, tl) -> match tl with | And tl -> loop (filter::acc) tl | _ -> flatten (filter::acc), tl | _ -> failwith “No filters?!?!?”
@theburningmonk let rec loop acc = function | NamespaceIs (filter, tl) | NamespaceLike (filter, tl) | NameIs (filter, tl) | NameLike (filter, tl) | UnitIs (filter, tl) | Average (filter, tl) | Sum (filter, tl) | Min (filter, tl) | Max (filter, tl) | SampleCount (filter, tl) -> match tl with | And tl -> loop (filter::acc) tl | _ -> flatten (filter::acc), tl | _ -> failwith “No filters?!?!?”
@theburningmonk let rec loop acc = function | NamespaceIs (filter, tl) | NamespaceLike (filter, tl) | NameIs (filter, tl) | NameLike (filter, tl) | UnitIs (filter, tl) | Average (filter, tl) | Sum (filter, tl) | Min (filter, tl) | Max (filter, tl) | SampleCount (filter, tl) -> match tl with | And tl -> loop (filter::acc) tl | _ -> flatten (filter::acc), tl | _ -> failwith “No filters?!?!?”
@theburningmonk let parse (input : string) = input |> tokenize |> parseFilter |> parseTimeFrame |> parsePeriod
@theburningmonk Amazing F# =
@theburningmonk usable from anywhere you can run F# code e.g. F# REPL, executable, .. Internal DSL
@theburningmonk useful for building tools e.g. CLI, … External DSL
@theburningmonk
@theburningmonk
@theburningmonk
@theburningmonk Recap
@theburningmonk
@theburningmonk
@theburningmonk Amazon DynamoDB Amazon SimpleWorkflow Amazon CloudWatch CASE STUDY
@theburningmonk theburningmonk.com github.com/theburningmonk
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Tame Cloud Complex with F# powered DSLs

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Technology

The emergence of Cloud platforms has fundamentally changed the IT landscape. However, attempting to ride on this ever-expanding platform ecosystem wave has created a new set of challenges. Join Yan Cui in this talk as he draws on his extensive experience with AWS over the last 7 years to illustrate, with real-world use examples, how you can use F# to build internal and external DSLs to tame the complexity from these cloud services.

Yan Cui
Yan CuiSpeaker at Self

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