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Developing & Application Integration

Event-Based Cost Control In AWS Glue: Build

In this post, I build my event-based AWS Glue automated cost control process using serverless managed services.

Table of Contents

Introduction

Last time, I examined some unexpected AWS Glue costs and designed an event-based cost control process architecture. I also wrote this user story:

As an AWS account owner, I want Glue interactive sessions to stop automatically after a chosen duration so that I don’t accidentally generate unexpected and avoidable costs.

Here, I’m going to build my event-based Glue cost control process using these AWS services:

  • SNS
  • CloudTrail
  • Step Functions
  • EventBridge
  • CloudWatch

The order is based on dependencies, which I will explain shortly. Some of these resources already exist, so let’s start by reviewing those.

Existing Resources

I have two existing SNS topics that this process will use. These are general-purpose topics used for all my Step Functions notifications. They are:

  • failure-stepfunction
  • success-stepfunction

Both topics are largely alike, with the main difference being the distinct subaddressing in their respective email endpoints.

CloudTrail

Let’s start by examining an AWS Glue CreateSession CloudTrail event record. I haven’t included a full Glue CreateSession CloudTrail event record here because:

  • They’re around 90 lines long. Each.
  • They contain sensitive data.

The AWS documentation covers CloudTrail record contents in full for those curious.

Here’s part of a Glue CreateSession CloudTrail event record. This one shows session glue-studio-datapreview-e09f88a9-4d7f-4e64-95f2-e435fbd1963a:

JSON
{
    "eventSource": "glue.amazonaws.com",
    "eventName": "CreateSession",
    "requestParameters": {
        "id": "glue-studio-datapreview-e09f88a9-4d7f-4e64-95f2-e435fbd1963a",
        "command": {
            "name": "glueetl",
            "pythonVersion": "3"
        },
        "idleTimeout": 30,
        "maxCapacity": 2,
        "glueVersion": "4.0",
        "requestOrigin": "GlueStudioDataPreview"
    },
}

Here, requestParameters contains the new session’s details including its ID:

JSON
{
    "eventSource": "glue.amazonaws.com",
    "eventName": "CreateSession",
    "requestParameters": {
        "id": "glue-studio-datapreview-e09f88a9-4d7f-4e64-95f2-e435fbd1963a",
        "command": {
            "name": "glueetl",
            "pythonVersion": "3"
        },
        "idleTimeout": 30,
        "maxCapacity": 2,
        "glueVersion": "4.0",
        "requestOrigin": "GlueStudioDataPreview"
    },
}

This is the Glue Interactive Session’s unique identifier. I’ll be using this in my event-based Glue cost control build shortly. For now, understand that:

  • The Glue Interactive Session’s ID is found in the event record’s requestParameters object.
  • The requestParameters object is in turn found in the event record’s details object.

This is represented as:

JSON
detail.requestParameters.id

I’m going to pass this ID to a Step Functions state machine later. Speaking of which…

Step Functions

In this section, I start creating my event-based Glue cost control build automation. This consists of two components:

  • An event router – built with an EventBridge rule.
  • A service orchestrator – built with a Step Functions state machine.

Since the state machine will be the EventBridge rule’s target, I must create the state machine first.

State Machine Actions

The state machine’s architecture was covered in my previous post. As a reminder, when given a Glue SessionID the state machine must:

  • Wait for a set period.
  • Stop the Glue session.
  • Trigger a confirmation email.

So let’s run through each step, starting with how the Glue SessionID is acquired.

Getting Glue Session ID

When executing a Step Functions state machine, an optional JSON input can be specified. There are several ways to supply this input:

2024 12 14 StateMachineInputJSON

For my event-based Glue cost control build, a typical JSON input will be:

JSON
{
  "session_id": "glue-studio-datapreview-123-456-789"
}

This can then be used in the other states as "$.session_id"

The state machine must then enter a wait state.

Wait

Step Functions has a built-in Wait state for handling delays. I want a thirty-second delay. This is configurable both in Workflow Studio and Amazon States Language (ASL):

JSON
    "Wait": {
      "Type": "Wait",
      "Seconds": 30,
      "Next": "StopGlueSession"
    },

The state machine must then stop the Glue session.

Glue: Stop Session

To understand what’s needed here, let’s review the Glue StopSession API reference. ID is the only required parameter, which comes from the earlier JSON input.

This is represented in ASL as:

JSON
{
  "Id.$": "$.session_id"
}

Now, as discussed previously, this action can fail. In the example below, a Glue StopSession request fails because the session is still being provisioned. Since nothing has started, there is nothing to stop:

JSON
{
  "cause": "Session is in PROVISIONING status (Service: Glue, Status Code: 400, Request ID: null)",
  "error": "Glue.IllegalSessionStateException",
  "resource": "stopSession",
  "resourceType": "aws-sdk:glue"
}

To that end, I’ve added retry parameters. Upon error, StopGlueSession will retry three times, with a ten-second delay between attempts. If the third retry fails, then the state machine’s error handling will be invoked.

This is the state’s ASL:

JSON
    "StopGlueSession": {
      "Type": "Task",
      "Resource": "arn:aws:states:::aws-sdk:glue:stopSession",
      "Parameters": {
        "Id.$": "$.session_id"
      },
      "Next": "SNS Publish",
      "Retry": [
        {
          "ErrorEquals": [
            "States.ALL"
          ],
          "IntervalSeconds": 10,
          "MaxAttempts": 3
        }
      ]
    },

Where:

  • "Id.$": "$.session_id" is the Glue SessionID from the JSON input.
  • "ErrorEquals": ["States.ALL"] captures all errors.
  • "IntervalSeconds": 10, "MaxAttempts": 3 sets the retry parameters.

Finally, the state machine must trigger a confirmation email.

SNS: Publish

I usually avoid state machine success notifications to avoid alarm fatigue, but I decided to include them here for two reasons:

  • I can check the state machine is working without accessing AWS.
  • I can see excessive activity without viewing logs.

Here, I publish a message to my existing success-stepfunction SNS topic using SNS’s optimised integration:

JSON
"SNS Publish": {
      "Type": "Task",
      "Resource": "arn:aws:states:::sns:publish",
      "Parameters": {
        "TopicArn": "arn:aws:sns:eu-west-1:[REDACTED]:success-stepfunction",
        "Message.$": "States.Format('Hi! AWS Step Functions has stopped this Glue session for you: {}', $)"
      },
      "End": true
    }

I customised the Message.$ parameter using the States.Format intrinsic function:

  • The string starting with 'Hi!... is the message I want SNS to use.
  • {} is a placeholder for the value I want to insert.
  • $ is the state machine data to insert into {}

This produces a better email notification for the user:

Hi! AWS Step Functions has stopped this Glue session for you: {Id=glue-studio-datapreview-3f905608-50f1-4b9e-80e2-f4071feb2282}

Finally, "End": true stops the state machine.

Final Workflow

The state machine is now as follows:

stepfunctions graph

With this auto-generated ASL:

JSON
{
  "StartAt": "Wait",
  "States": {
    "Wait": {
      "Type": "Wait",
      "Seconds": 30,
      "Next": "StopGlueSession"
    },
    "StopGlueSession": {
      "Type": "Task",
      "Resource": "arn:aws:states:::aws-sdk:glue:stopSession",
      "Parameters": {
        "Id.$": "$.session_id"
      },
      "Next": "SNS Publish",
      "Retry": [
        {
          "ErrorEquals": [
            "States.ALL"
          ],
          "IntervalSeconds": 10,
          "MaxAttempts": 3
        }
      ]
    },
    "SNS Publish": {
      "Type": "Task",
      "Resource": "arn:aws:states:::sns:publish",
      "Parameters": {
        "TopicArn": "arn:aws:sns:eu-west-1:[REDACTED]:success-stepfunction",
        "Message.$": "States.Format('Hi! AWS Step Functions has stopped this Glue session for you: {}', $)"
      },
      "End": true
    }
  },
  "Comment": "When given a Glue SessionID start a wait, stop the session and send an SNS message."
}

There’s one more aspect to sort out. What happens if the state machine fails?

Error Logging

Firstly, let’s examine the state of events if the state machine fails:

  • A Glue session must have started.
  • An Eventbridge Rule must have sent the event to Step Functions.
  • One of the state machine states must have failed.

Unless the failing state is SNS:Publish, then there is an active Glue session still incurring costs. Therefore, triggering an alarm is much more appropriate than a notification. Alarm creation requires sending the state machine logs to CloudWatch.

By default, new state machines do not enable logging due to storage expenses. However, in this case, the log storage cost will be significantly lower than that of an unattended Glue Session. So I activate the logging for my state machine.

Step Functions log levels range from ALL to ERROR to FATAL to OFF, which are explained in the AWS documentation. As I’m only interested in failures, I select ERROR and include the execution data. This consists of execution input, data passed between states and execution output:

2024 12 14 StateMachineLogging

Next, I create a new CloudWatch log group called /aws/vendedlogs/states/GlueSession-WaitAndStop-Logs. This will form the basis of my failure alerting.

CloudWatch

Here, I configure the CloudWatch resources for my event-based Glue cost control build.

Log Groups & Metrics

The previously configured GlueSession-WaitAndStop-Logs group receives all the Step Functions state machine’s ERROR events. In most cases, these are Glue.IllegalSessionStateException events:

JSON
{
    "id": "7",
    "type": "TaskFailed",
    "details": {
        "cause": "Session is in PROVISIONING status (Service: Glue, Status Code: 400, Request ID: b1baaf14-ae89-4106-a286-87cf5445de6c)",
        "error": "Glue.IllegalSessionStateException",
        "resource": "stopSession",
        "resourceType": "aws-sdk:glue"
    },

Note the TaskFailed event type – it indicates the failure of a single state, not the entire state machine. Thus, I don’t need alerts for those events.

However, there are also ExecutionFailed events like these:

JSON
{
    "id": "5",
    "type": "ExecutionFailed",
    "details": {
        "cause": "An error occurred while executing the state 'StopGlueSession' (entered at the event id #4). The JSONPath '$.session_id' specified for the field 'Id.$' could not be found in the input '{\n  \"sessionId\": \"\"\n}'",
        "error": "States.Runtime"
    },

I definitely want to know about these! ExecutionFailed means the entire state machine failed, and there’s probably a Glue Session still running!

These events are captured as ExecutionsFailed CloudWatch metrics. Keep in mind that the AWS Step Functions console automatically publishes various metrics irrespective of logging configurations, including ExecutionFailed. However, in my experience, having both the metrics and failure logs centralised in CloudWatch simplifies troubleshooting.

Next, let’s use these metrics to create an alarm.

Alarm

Creating a CloudWatch alarm begins with selecting the ExecutionsFailed metric from States > Execution Metrics

2024 12 13 CWMetrics

This alarm will have a static value threshold with a value greater than zero, which is checked every minute. When the alarm’s state is In Alarm, an email notification will be sent to my failure-stepfunction SNS topic.

Finally, CloudWatch creates a new alarm graph:

2024 12 13 CWAlarm

So that’s everything state machine needs. Next, how do I pass the Glue SessionID to it?

EventBridge

In this section, I create the EventBridge Rule responsible for handling my event-based Glue cost control build’s events.

EventBridge Rule Anatomy

EventBridge Rules specify the criteria for routing events from an event bus to designated targets like Lambda functions, Step Functions and SQS queues. They use event patterns to filter incoming events and identify targets to route to, enabling event-driven and event-based workflows without custom processing logic.

Creating an EventBridge Rule involves three steps:

  • Define rule detail
  • Build event pattern
  • Select target

Define Rule Detail

Besides the name and description, this section is mainly concerned with:

  • Event Bus: The event bus to monitor for events. Default is fine.
  • Rule Type: EventBridge’s rule type. This can either match an event pattern or operate on a schedule (this is different from EventBridge Scheduler – Ed).

Next, let’s discuss event patterns!

Build Event Pattern

Firstly, event patterns are a very expansive topic, so please refer to the EventBridge user guide afterwards for definitions and examples.

Event patterns act as filters, defining how EventBridge identifies whether to send an event to a target. The EventBridge console provides options for sample events and testing patterns.

As a reminder, this is part of a typical CreateSession event record from which I want to capture ID:

JSON
"eventSource": "glue.amazonaws.com",
"eventName": "CreateSession",
"requestParameters": {
  "id": "glue-studio-datapreview-3f905608-50f1-4b9e-80e2-f4071feb2282",
  "role": "arn:aws:iam::[REDACTED]:role/service-role/AWSGlueServiceRole-wordpress_bronze",
        "command": {
            "name": "glueetl",
            "pythonVersion": "3"
        },
        "idleTimeout": 30
....

EventBridge currently has three pattern creation methods:

  • Schema: Using either manual entry or the schema registry.
  • Pattern Form: Using pre-defined EventBridge templates.
  • Custom Pattern: Using a manual JSON editor.

Pattern Form offers a series of dropdowns that quickly construct the desired pattern:

2024 12 28 EventBridgeEventPattern

Selecting AWS Services > Glue > AWS API Call via CloudTrail creates this event pattern:

JSON
{
  "source": ["aws.glue"],
  "detail-type": ["AWS API Call via CloudTrail"],
  "detail": {
    "eventSource": ["glue.amazonaws.com"]
  }
}

This will send all Glue events to the target, so it could use some refinement. An eventName can be added to the pattern either by manual editing or via the Specific Operation(s) setting.

The updated pattern will now only send Glue CreateSession events:

JSON
{
  "source": ["aws.glue"],
  "detail-type": ["AWS API Call via CloudTrail"],
  "detail": {
    "eventSource": ["glue.amazonaws.com"],
    "eventName": ["CreateSession"]
  }
}

Select Target

Finally, I must select the EventBridge Rule’s target – my state machine. This is why I created the state machine first; for it to be an EventBridge target it must first exist.

At this point, I could pass the whole event to the state machine. However, the state machine had no way to parse the SessionID from the event. While JSONata could now meet this requirement, it wasn’t a Step Functions feature back in June.

Luckily, EventBridge offers relevant settings here. One of these – an Input Transformer – can customise an event’s text before EventBridge sends it to the rule’s target. Input Transformers consist of an Input Path and Input Template.

An Input Path uses a JSON path and key-value pairs to reference items in events and store them as variables. For instance, capturing ID from this event:

JSON
"eventSource": "glue.amazonaws.com",
"eventName": "CreateSession",
"requestParameters": {
  "id": "glue-studio-datapreview-3f905608-50f1-4b9e-80e2-f4071feb2282",
  "role": "arn:aws:iam::[REDACTED]:role/service-role/AWSGlueServiceRole-wordpress_bronze",
        "command": {
            "name": "glueetl",
            "pythonVersion": "3"
        },
        "idleTimeout": 30
....

Requires this Input Path:

JSON
{
  "id": "$.detail.requestParameters.id"
}

In which:

  1. $.detail accesses the detail object of the CloudTrail event record.
  2. $.detail.requestParameters accesses the requestParameters object within detail.
  3. Finally, $.detail.requestParameters.id accesses the id value within requestParameters.

This is passed to an Input Template, mapping the path’s output to a templated key-value pair. This is then passed to the rule target verbatim, replacing placeholders with the Input Path values.

So this template:

JSON
{
  "session_id": "<id>"
}

Produces a JSON object comprising a "session_id": string and the Input Path’s Glue SessionID value:

JSON
{
  "session_id": "glue-studio-datapreview-3f905608-50f1-4b9e-80e2-f4071feb2282"
}

This will be passed as the JSON input when executing the state machine.

That’s everything done now. So let’s see if it works!

Testing

This section tests my event-based Glue cost control build.

In the following tests, a Glue Interactive Session was started with the build fully active and was observed in the AWS console. AWS assigned the SessionID glue-studio-datapreview-3f905608-50f1-4b9e-80e2-f4071feb2282.

EventBridge Rule

Expectation: When a Glue CreateSession CloudTrail event record is created:

  • EventBridge matches the CloudTrail event record to my EventBridge Rule.
  • The EventBridge Rule triggers and defines a session_id variable.
  • The EventBridge Rule executes my target state machine with session_id JSON input.

Result: CloudWatch indicates EventBridge matched the CloudTrail Event Record to my EventBridge Rule’s Event Pattern, executing the intended actions:

2024 06 11 EventBridgeCWGraph

The EventBridge Rule’s extracts the glue-studio-datapreview-3f905608-50f1-4b9e-80e2-f4071feb2282 SessionID from the CloudTrail Event Record and adds it as a JSON input when executing the targeted GlueSession-WaitAndStop state machine.

Step Functions State Machine

Expectation: When a Glue CreateSession CloudTrail event record is created:

  • State machine is executed with session_id JSON input.
  • Glue StopSession API is called after 30 seconds.
  • If the first StopSession API call fails, a retry occurs after ten seconds.
  • A confirmation email is sent to the user.

Result: State machine executes successfully:

2024 06 11 StepFGraph

The state machine logs also correctly show a thirty-second wait between rows 2 and 3 (the start and end of the Wait state):

2024 06 11 StepFExec

Additionally, if a Glue.IllegalSessionStateException error occurs, a retry occurs after ten seconds (see rows 7 and 8):

2024 12 13 SFRetry

Finally, SNS sends the correct email to the user:

2024 06 11 GmailNotif

The failure alarm is tested later.

Glue Session

Expectation: When an Interactive Session starts while the EventBridge Rule is enabled, it is automatically stopped thirty seconds after becoming active.

Result: This session runs for seventy seconds. Although this exceeds thirty seconds, keep in mind that the session needs to be provisioned before it can be stopped.

2024 06 11 GlueSessionConsole

These results can also be verified using the Glue Get-Session AWS CLI command:

Bash
[cloudshell-user@ip-[REDACTED] ~]$ aws glue get-session --id glue-studio-datapreview-3f905608-50f1-4b9e-80e2-f4071feb2282

{
    "Session": {
        "Id": "glue-studio-datapreview-3f905608-50f1-4b9e-80e2-f4071feb2282",
        "CreatedOn": "2024-06-11T12:23:04.586000+00:00",
        "Status": "STOPPED",
        
	[REDACTED]
	
        "WorkerType": "G.1X",
        "CompletedOn": "2024-06-11T12:24:30.210000+00:00",
        "ExecutionTime": 70.384,
        "DPUSeconds": 140.768,
        "IdleTimeout": 30
    }
}
(END)

CloudWatch Alarm

The CloudWatch Alarm was tested by briefly changing the Step Function state machine’s IAM policy to deny the StopSession action and then starting a new Interactive Session, forcing the desired failure without altering the cost control process itself.

Expectation: If the state machine fails, then a CloudWatch Alert is sent to the user.

Result: Upon the state machine’s failure, an ExecutionsFailed metric is emitted to CloudWatch, shown in this chart:

2024 06 11 CloudWatchMetric

This triggers the CloudWatch Alarm when its Sum > 0 threshold condition is met, changing the alarm’s state to In Alarm and sending an email notification using my failure-stepfunction SNS topic:

2024 06 11 CloudWatchAlerting

And with that, all tests are successful. Now let’s look at the costs.

Cost Analysis

This section analyses the costs of my event-based Glue cost control build. There are two aspects to this:

  • Cost Expenditure: How much is the cost control process costing me to run?
  • Cost Savings: How much money am I saving on the stopped Glue Sessions?

Because the biggest test of all is whether this build satisfies the user story. Does it prevent unexpected and avoidable costs?

Cost Expenditure

Firstly, let’s examine my event-based Glue cost control build costs between June 2024 and November 2024:

2024 12 13 CostsZero

So I guess this kinda makes my point. Zero cost doesn’t mean zero usage though, so let’s check the bills for that period.

Caveat: I didn’t tag any of my resources (yes ok I know), so this usage is for the entire account.

CloudTrail & CloudWatch Usage

CloudTrail FreeEventsRecorded:

Service Period Metric Quantity
CloudTrail 2024-06 FreeEventsRecorded 33,217
CloudTrail 2024-07 FreeEventsRecorded 28,993
CloudTrail 2024-08 FreeEventsRecorded 40,682
CloudTrail 2024-09 FreeEventsRecorded 29,891
CloudTrail 2024-10 FreeEventsRecorded 36,208
CloudTrail 2024-11 FreeEventsRecorded 28,630

CloudWatch Alarms:

Service Period Metric Quantity
CloudWatch 2024-06 Alarms 0.919
CloudWatch 2024-07 Alarms 2
CloudWatch 2024-08 Alarms 2.126
CloudWatch 2024-09 Alarms 2
CloudWatch 2024-10 Alarms 2
CloudWatch 2024-11 Alarms 2

CloudWatch Metrics:

Service Period Metric Quantity
CloudWatch 2024-06 Metrics 5.29
CloudWatch 2024-07 Metrics 0.372
CloudWatch 2024-08 Metrics 4.766
CloudWatch 2024-09 Metrics 0.003
CloudWatch 2024-10 Metrics 4.003
CloudWatch 2024-11 Metrics 4.626

CloudWatch Requests:

Service Period Metric Quantity
CloudWatch 2024-06 Requests 696
CloudWatch 2024-07 Requests 15
CloudWatch 2024-08 Requests 230
CloudWatch 2024-09 Requests 0
CloudWatch 2024-10 Requests 181
CloudWatch 2024-11 Requests 122

EventBridge, SNS & Step Functions Usage

EventBridge EventsInvocation:

Service Period Metric Quantity
EventBridge 2024-06 EventsInvocation 30
EventBridge 2024-07 EventsInvocation 31
EventBridge 2024-08 EventsInvocation 31
EventBridge 2024-09 EventsInvocation 30
EventBridge 2024-10 EventsInvocation 31
EventBridge 2024-11 EventsInvocation 30

SNS NotificationDeliveryAttempts-SMTP:

Service Period Metric Quantity
SNS 2024-06 NotificationDeliveryAttempts-SMTP 52
SNS 2024-07 NotificationDeliveryAttempts-SMTP 29
SNS 2024-08 NotificationDeliveryAttempts-SMTP 85
SNS 2024-09 NotificationDeliveryAttempts-SMTP 2
SNS 2024-10 NotificationDeliveryAttempts-SMTP 58
SNS 2024-11 NotificationDeliveryAttempts-SMTP 11

SNS Requests:

Service Period Metric Quantity
SNS 2024-06 Requests-Tier1 315
SNS 2024-07 Requests-Tier1 542
SNS 2024-08 Requests-Tier1 553
SNS 2024-09 Requests-Tier1 325
SNS 2024-10 Requests-Tier1 366
SNS 2024-11 Requests-Tier1 299

Step Functions StateTransition:

Service Period Metric Quantity
Step Functions 2024-06 StateTransition 388
Step Functions 2024-07 StateTransition 180
Step Functions 2024-08 StateTransition 566
Step Functions 2024-09 StateTransition 300
Step Functions 2024-10 StateTransition 616
Step Functions 2024-11 StateTransition 362

All within free tier. So how did Glue fare?

Cost Savings

Next, let’s pull my InteractiveSessions costs between June 2024 and November 2024:

2024 12 13 CostsGlue

The high June costs kickstarted this process, and there’s a massive difference between June and the others! September isn’t a mistake – I was kinda busy.

Glue Costs

Here are the actual costs:

Service Period Metric Quantity Cost $
Glue 2024-06 InteractiveSessions 5.731 DPU-Hour 2.52
Glue 2024-07 InteractiveSessions 0.197 DPU-Hour 0.09
Glue 2024-08 InteractiveSessions 2.615 DPU-Hour 1.15
Glue 2024-09 InteractiveSessions 0.000 DPU-Hour 0.00
Glue 2024-10 InteractiveSessions 2.567 DPU-Hour 1.13
Glue 2024-11 InteractiveSessions 0.079 DPU-Hour 0.03
TOTAL 4.92

While these aren’t exactly huge sums, there are two items to consider here:

Glue Estimated Savings

Finally, what saving does this represent? While I can’t get a value from AWS Billing, I can reasonably estimate one. Firstly, using the AWS Calculator for Glue I calculated the cost of an Interactive Session that times out:

2 DPUs x 0.50 hours x 0.44 USD per DPU-Hour = 0.44 USD

https://calculator.aws/#/createCalculator/Glue

Next, I went back through my records and found how many sessions had been stopped each month:

Period Stops
2024-06 11
2024-07 5
2024-08 61
2024-09 0
2024-10 53
2024-11 2

Caveat: To be fair to AWS, some sessions were created while I was working on a Glue ETL job with automation enabled. So, while the automation was continually stopping sessions, I was constantly starting new ones. Thus, Glue isn’t the money pit I perhaps make out, and I’m not that careless with leaving them on!

By multiplying the number of stopped sessions by 0.44, I can determine each month’s potential cost, then subtract the actual cost to find the estimated savings:

Period Stops Potential Cost $ Actual Cost $ Est. Saving $
2024-06 11 4.84 2.52 2.32
2024-07 5 2.20 0.09 2.11
2024-08 61 26.84 1.15 25.69
2024-09 0 0.00 0.00 0.00
2024-10 53 23.32 1.13 22.19
2024-11 2 0.88 0.03 0.85
TOTAL 132 58.08 4.92 53.16

Almost $55! Even if I reduce that by 50% based on the caveat, that’s still around a $25 saving. And with no setup costs!

Summary

In this post, I built my event-based AWS Glue automated cost control process using serverless managed services.

I’m pleased with the outcome! My generally busy Summer and Autumn inadvertently tested this process for six months, and it’s been fine throughout! I may soon extend the state machine’s waiting duration, which only needs a parameter change for one state.

The great thing about this process is that it isn’t limited to Glue; EventBridge can use nearly all AWS services as event sources. I’m seriously impressed with EventBridge. It’s poked me about Glacier restores, scheduled my ETLs and now is also saving me a few quid!

If this post has been useful then the button below has links for contact, socials, projects and sessions:

SharkLinkButton 1

Thanks for reading ~~^~~

Categories
Architecture & Resilience

Event-Based Cost Control In AWS Glue: Architecture

In this post, I examine some unexpected AWS Glue costs and design an event-based cost control process architecture.

Table of Contents

Introduction

Last month, I finished a series of data pipeline posts using, among other services, AWS Glue. During this series I made many discoveries – some more desirable than others. One such undesirable was a cost spike in early June! Not enough to trigger a budget alarm, but still higher than expected at that time.

To Cost Explorer! These were the results:

2024 06 24 AWSCostsStartJune

Those Glue costs were…unexpected. While this doesn’t look like much, in contrast my entire May 2024 bill was $1.08. So June saw an almost 150% cost increase over just three days!

This post has two sections. Firstly, the Discovery section examines the costs in closer detail and considers potential solutions. Secondly, the Architecture section examines the decisions made for and the technical implementation of the chosen solution.

Discovery

This section examines the costs in closer detail and considers potential solutions. I’ll structure the cost analysis using three questions:

  • How are the costs made up?
  • What specifically is generating the costs?
  • Why are the costs being generated?

The How

Question 1: How are the costs made up?

Firstly, let’s break down the costs. The earlier chart shows that Glue is the main cost driver – I now want to drill down into the API-level costs. I can do this by changing the chart’s dimension to API Operation.

This updates it to:

2024 06 24 AWSCostsStartJuneDimAPI

And the raw data to:

2024 06 24 AWSCostsStartJuneTable

The main costs here are all Glue APIs, with the top two being:

  • GlueInteractiveSession
  • Jobrun

No operation is tax – Ed

Jobrun was easy to account for, as I was testing some Glue ETL jobs at the time. But I was unfamiliar with GlueInteractiveSession, and as it was the biggest cost driver it became the focus of my ongoing investigation.

The What

Question 2: What specifically is generating the costs?

So what is the GlueInteractiveSession API? What does it do? And how does it accrue costs? Let’s begin with the AWS User Guide definition:

The interactive sessions API describes the AWS Glue API related to using AWS Glue interactive sessions to build and test extract, transform, and load (ETL) scripts for data integration.

https://docs.aws.amazon.com/glue/latest/dg/aws-glue-api-interactive-sessions.html

AWS Glue Interactive Sessions offer serverless, on-demand Apache Spark environments that work seamlessly with Glue ETL jobs. These sessions allow for the live development, testing, and enhancement of data processing steps and ETL tasks. They can easily connect to data from various AWS services such as S3, DynamoDB, and Redshift.

Interactive Sessions let users preview data without running full ETL jobs. This offers several benefits during development and testing:

  • Data modifications are only temporary during an Interactive Session, protecting the original data from undesired and unintended changes.
  • Jobs can be evaluated step by step rather than after each complete run, allowing for quicker development and testing compared to always executing the full job. And because of this…
  • When testing ETL steps, interactive sessions usually use fewer resources than a Glue job, thus reducing costs.

Speaking of costs, Glue Interactive Sessions billing is similar to Glue ETL Job billing and is based on the following factors:

  1. Duration: How long the session runs, measured in seconds.
  2. Resource Usage: The resources consumed during the session, such as CPU, memory, and storage.

This all sounds good. So why is my bill so high?

The Why

Question 3: Why are the costs being generated?

So I now know that:

  • The GlueInteractiveSession API is the main cost driver.
  • My Glue Interactive Sessions are linked to my AWS Glue ETL Jobs.

Let’s now examine why the GlueInteractiveSession API is suddenly generating higher costs.

The How chart shows that GlueInteractiveSession costs can happen irrespective of Jobrun costs. Indeed – on June 03 there were no Jobrun costs. So running Glue ETL jobs isn’t causing these charges.

Helpfully, the AWS Glue console has a dedicated Interactive Sessions section that shows session instance histories. Upon inspection, I found lots of this:

2024 12 08 GlueSessionTImeout

So, timeouts. Timeouts are good. They stop Interactive Sessions from running indefinitely, and sessions started from the Glue console automatically get a 30-minute timeout.

What was more concerning was the number of timeouts I found: three on June 02 and six on June 03. That’s nine sessions, each of which timing out after 30 minutes. That’s four and a half hours of unused compute I’m being billed for! How are these timeouts happening?

…About that. I often open multiple browser tabs to compare screens quickly when I’m trying things out. Here, each new Glue ETL Job browser tab starts a new interactive session based on my commands, and I forget to close these sessions afterwards. Oops!

Solutions

So now I know the cost’s root cause is my own ineptitude, how do I fix this? There are several options:

Permission Blocking: I could deny CreateSession requests using IAM and SCPs. This solution works for non-data-facing AWS accounts but creates unreasonable barriers for Glue-based console workstreams elsewhere.

Parameter Adjustment: The CreateSession API has an IdleTimeout parameter that controls the number of minutes when idle before the session times out. Although this can be easily configured through the CLI or SDK, I haven’t found a way to adjust it in the console yet.

Local Sessions: AWS maintains a Glue Labs Docker image intended for local AWS Glue job script development and testing. This would replace the cloud-based Interactive Sessions entirely and is arguably the best solution for data teams and at scale. The main reason I’m not using it here is that I’m the only user of this particular AWS account.

Event-Based Automation: All Interactive Sessions are stopped using the StopSession API regardless of reason. This includes the timeout process. An automated mechanism that invokes this API after a set period would effectively emulate a timeout. Additionally, since I oversee this process, I’m able to swiftly adjust the duration as needed.

And so I finally have a user story:

As an AWS account owner, I want Glue interactive sessions to stop automatically after a chosen duration so that I don’t accidentally generate unexpected and avoidable costs.

Finally, there is one further topic I want to address…

Event-Based Vs Event-Driven

Let’s examine the difference between event-based and event-driven. Mainly because I thought this was an event-driven process for months until I did some digging.

Now, I’m no expert on this. However, James Eastham is. Go watch this. It’s only six minutes – I’ll wait.

Ok good. For those who are time-strapped or want the highlights:

  • Event-based systems are technical events. Represented in a data context as API calls like ObjectCreated and CrawlerStarted.
  • Event-driven systems are business events. Represented in a data context as processes like Refresh Started and Sales Data Ingested.

My Glue Cost Control system is event-based because it is governed entirely by AWS events and API calls: StartSession will trigger some AWS automation that ultimately invokes StopSession.

So what does that automation look like? Well…

Architecture

This section examines the decision-making and technical implementation of my AWS Glue event-based cost control architecture. In my investigations, I discovered that AWS is way ahead of me!

Existing AWS Solution

The AWS Big Data blog has a 2023 post about enforcing boundaries on AWS Glue interactive sessions using this architecture:

The whole process is listed here, and the post’s code is in a GitHub repo. In summary:

  • The Glue Interactive Session creates a CloudTrail Event Record.
  • An EventBridge Rule captures the event and invokes a Lambda function.
  • The Lambda function inspects the event and acts depending on set boundaries.
  • SNS handles user notifications.
  • SQS and CloudWatch handle errors.

I’m using this architecture as a basis for my event-based Glue cost control process with some changes.

Architectural Decisions

This section outlines my adjustments to the AWS architecture to better align with my event-based Glue cost control process.

Replace Lambda With Step Functions

The AWS solution uses a Lambda function for event inspection and API interaction. This function has lots going on. But my needs are far simpler and fall well within the remit of a Step Functions workflow.

Many AWS heavyweights evangelize Step Functions over Lambda. Most recently, Eric Johnson dedicated a slide of his 2024 re:Invent session to this mantra:

“Step Functions first,
Step Functions always.”

For this use case, I’m inclined to agree. Step Functions offers several advantages over Lambda here:

Service Integration: Lambda’s interactivity with other AWS services requires manual code (e.g. a Python boto3 client). Step Functions offer no-code AWS service integrations that interact directly with AWS APIs. So my Step Function will be faster to develop.

Error Handling: Lambda relies on the function code for error handling and retries. In contrast, Step Functions offer configurable built-in no-code error handling and retry mechanisms, making my Step Function more resilient.

Ongoing Maintenance: While AWS manages the Lambda service, the function code still needs runtime maintenance, security patching and general refactoring as it ages. Conversely, Step Functions use static JSON and YAML-based ASL, so my Step Function will require less ongoing maintenance.

Step Function Model

There are two Step Function models: Standard Workflows and Express Workflows. I’ll be using a Standard workflow here. Two factors drive this decision:

API Behaviour: Changing a Glue Interactive Session is not an idempotent action. Requesting a change to a session in an invalid state produces an IllegalSessionState exception. For example, the below error is thrown when trying to stop a Glue job that hasn’t yet been fully provisioned:

JSON
{
  "cause": "Session is in PROVISIONING status (Service: Glue, Status Code: 400, Request ID: null)",
  "error": "Glue.IllegalSessionStateException",
  "resource": "stopSession",
  "resourceType": "aws-sdk:glue"
}

Express Workflows utilize an at-least-once model, meaning an execution might run multiple times. Sending several requests that are very likely to fail will create confusion and waste resources. In contrast, Standard Workflows adhere to an exactly-once model with optional retries, significantly reducing the likelihood of these problems.

And speaking of resource use…

Cost: Express Workflow executions are charged according to how often they run, the duration of each run and the memory consumed during the process. Standard Workflow executions are billed based on the number of state transitions and feature a generous and indefinite free tier.

Standard Workflows are a better option here because my workflow requires waiting. While Express Workflows may not be too costly, I’d still be paying for the wait. And remember – the whole point is to reduce avoidable costs! Conversely, Standard Workflows would stay entirely within the free tier at the expected volumes.

Remove The SQS Queue

I’ve removed the SQS queue simply because I don’t need it here. It was originally intended to record events that triggered a Lambda function failure. However, the Step Function workflow’s inbuilt auditing will now capture this.

Considering the Frugal Architect Mindset and AWS Well-Architected Framework‘s Cost Optimization Pillar, the SQS queue’s financial and development costs are no longer justified. This cements its removal.

Architecture Diagram

This is my event-based Glue Cost Control process architecture diagram:

In this solution:

  1. User interacts with a Glue ETL Job and creates an Interactive Session.
  2. Glue CreateSession event is created.
  3. Glue CreateSession event creates a CloudTrail event record.
  4. EventBridge matches the event record to an event rule.
  5. Eventbridge extracts the event’s SessionID and passes it to the Step Functions workflow, which waits for the set duration.
  6. Workflow passes SessionID to the Glue StopSession API. This action retries twice if it is unsuccessful.
  7. Finally, Workflow triggers an SNS email confirming the session’s stop.

Additionally, several services send logs to CloudWatch and gain permissions using IAM. If the Step Function fails, a CloudWatch alarm triggers a user email.

Summary

In this post, I examined some unexpected AWS Glue costs and designed an event-based cost control process architecture.

Once I understood the problem clearly, I iterated on an existing AWS architecture to build my bespoke event-based process. My architecture diagram shows how the key components work together and provides a clear implementation roadmap. In the next post I’ll start the build!

If you found this post helpful, the button below will take you to my contact details, socials, projects, and sessions.

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Thanks for reading ~~^~~