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Serverless observability - a hero's perspective

Yan Cui
Yan Cui

Yan Cui, an AWS Serverless Hero, will talk about the learnings from using serverless at scale. He will cover the challenges for observability in serverless asynchronous workloads and the patterns to address those challenges, like using centralized logging, correlation IDs, tracing, lambda extensions.

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Serverless OBSERVABILITY A hero’s perspective
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@theburningmonk theburningmonk.com What do I mean by “observability”?
3
Monitoring watching out for known failure modes in the system, e.g. network I/O, CPU, memory usage, …
4
@theburningmonk theburningmonk.com Observability being able to debug the system, and gain insights into the system’s behaviour
5
@theburningmonk theburningmonk.com In control theory, observability is a measure of how well internal states of a system can be inferred from knowledge of its external outputs. https://en.wikipedia.org/wiki/Observability
6
@theburningmonk theburningmonk.com In control theory, observability is a measure of how well internal states of a system can be inferred from knowledge of its external outputs. https://en.wikipedia.org/wiki/Observability including non- functional outputs
7
@theburningmonk theburningmonk.com These are the four pillars of the Observability Engineering team’s charter: • Monitoring • Alerting/Visualization • Distributed systems tracing infrastructure • Log aggregation/analytics “ ” http://bit.ly/2DnjyuW - Observability Engineering at Twitter
8
@theburningmonk theburningmonk.com microservices death stars circa 2015
9
@theburningmonk theburningmonk.com microservices death stars circa 2015 mm… I wonder what’s going on here…
10
Serverless observability - a hero's perspective
11
Serverless observability - a hero's perspective
12
Serverless observability - a hero's perspective
13
@theburningmonk theburningmonk.com microservices death stars circa 2015 I got this!
14
Serverless observability - a hero's perspective
15
@theburningmonk theburningmonk.com
16
Yan Cui http://theburningmonk.com @theburningmonk AWS user for 10 years
17
http://bit.ly/yubl-serverless
18
Yan Cui http://theburningmonk.com @theburningmonk Developer Advocate @
19
Serverless observability - a hero's perspective
20
Yan Cui http://theburningmonk.com @theburningmonk Independent Consultant advise training delivery
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theburningmonk.com/courses
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Learn GraphQL and AppSync by building a Twitter clone with these technologies appsyncmasterclass.com
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realworldserverless.com
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@theburningmonk theburningmonk.com
25
@theburningmonk theburningmonk.com Concurrency is in your application
26
@theburningmonk theburningmonk.com Concurrency is in your application Agent
27
@theburningmonk theburningmonk.com Concurrency is in your application Agent
28
@theburningmonk theburningmonk.com Concurrency is in your application Agent Shares the same CPU, memory and bandwidth as application
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@theburningmonk theburningmonk.com API Gateway
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@theburningmonk theburningmonk.com API Gateway Lambda
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@theburningmonk theburningmonk.com API Gateway Lambda Worker Worker Worker Worker Worker Worker Worker Worker Worker
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@theburningmonk theburningmonk.com API Gateway Lambda Worker Worker Worker Worker Worker Worker Worker Worker Worker Busy Busy Busy Busy Busy Busy
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@theburningmonk theburningmonk.com API Gateway Lambda Worker Worker Worker Worker Worker Worker Worker Worker Worker Busy Busy Busy Busy Busy Busy
34
@theburningmonk theburningmonk.com API Gateway Lambda Worker Worker Worker Worker Worker Worker Worker Worker Worker Busy Busy Busy Busy Busy Busy Only processes one request at a time
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@theburningmonk theburningmonk.com API Gateway Lambda Worker Worker Worker Worker Worker Worker Worker Worker Worker Busy Busy Busy Busy Busy Busy Only processes one request at a time Runs in an AWS-managed baremetal EC2 instance
36
@theburningmonk theburningmonk.com Resource overhead is irrelevant. Think latency overhead instead.
37
@theburningmonk theburningmonk.com Resource overhead is irrelevant. Think latency overhead instead.
38
@theburningmonk theburningmonk.com https://www.youtube.com/watch?v=xmacMfbrG28
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@theburningmonk theburningmonk.com Built-in collection of: Metrics Logs Traces CloudWatch Metrics CloudWatch Logs X-Ray
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challenges
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Background Processing Time
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@theburningmonk theburningmonk.com user request user request user request user request user request user request user request critical paths: minimise user-facing latency handler handler handler handler handler handler handler
43
@theburningmonk theburningmonk.com user request user request user request user request user request user request user request critical paths: minimise user-facing latency StatsD handler handler handler handler handler handler handler rsyslog background processing: batched, asynchronous, low overhead
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@theburningmonk theburningmonk.com No background processing*.
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@theburningmonk theburningmonk.com No background processing*. * you can work around this with Lambda extensions
46
(potential) Data Loss When workers are garbage collected
47
@theburningmonk theburningmonk.com Lambda cold start
48
@theburningmonk theburningmonk.com Lambda data is batched between invocations
49
@theburningmonk theburningmonk.com Lambda idle data is batched between invocations
50
@theburningmonk theburningmonk.com Lambda idle garbage collection data is batched between invocations
51
@theburningmonk theburningmonk.com Lambda
52
@theburningmonk theburningmonk.com my code send metrics
53
@theburningmonk theburningmonk.com my code send metrics
54
@theburningmonk theburningmonk.com my code send metrics internet internet press button something happens
55
Serverless observability - a hero's perspective
56
Lambda Extension to the rescue!
57
Lambda Extension to the rescue! Think “sidecar” but for Lambda ;-)
58
@theburningmonk theburningmonk.com Your code Time Invoke Idle Shutdown Runtime shutdown
59
@theburningmonk theburningmonk.com Your code Time Extension Invoke Idle Runtime shutdown Shutdown
60
@theburningmonk theburningmonk.com Your code Time Extension Invoke Idle Runtime shutdown Shutdown
61
@theburningmonk theburningmonk.com Your code Time Extension Invoke Idle Shutdown 2s Extension shutdown Runtime shutdown
62
@theburningmonk theburningmonk.com Lambda idle garbage collection data is batched between invocations
63
@theburningmonk theburningmonk.com Your code Time Extension Invoke Idle Shutdown 2s Extension shutdown Runtime shutdown Flush buffered telemetry data
64
@theburningmonk theburningmonk.com Your code Time Extension Invoke Idle Shutdown 2s Extension shutdown Runtime shutdown 5-10 mins on average
65
@theburningmonk theburningmonk.com my code send metrics
66
@theburningmonk theburningmonk.com Your code Time Extension Invoke Idle Shutdown 2s Extension shutdown Runtime shutdown
67
@theburningmonk theburningmonk.com Your code Time Extension Invoke Idle Shutdown 2s Extension shutdown Runtime shutdown You pay for this time too
68
@theburningmonk theburningmonk.com Your code Time Extension Invoke Idle Shutdown 2s Extension shutdown Runtime shutdown Return function response
69
@theburningmonk theburningmonk.com Your code Time Extension Invoke Idle Shutdown 2s Extension shutdown Runtime shutdown Return function response Send telemetry data
70
Lots of async invocations
71
@theburningmonk theburningmonk.com http://bit.ly/2Dpidje
72
@theburningmonk theburningmonk.com ? functions are often chained together via asynchronous invocations
73
@theburningmonk theburningmonk.com ? SNS Kinesis EventBridge CloudWatch Logs IoT DynamoDB S3 SES
74
@theburningmonk theburningmonk.com S3 Lambda
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@theburningmonk theburningmonk.com S3 Lambda DynamoDB Lambda
76
@theburningmonk theburningmonk.com S3 Lambda DynamoDB Lambda API Gateway Lambda
77
@theburningmonk theburningmonk.com S3 Lambda DynamoDB Lambda API Gateway Lambda EventBridge Lambda
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@theburningmonk theburningmonk.com S3 Lambda DynamoDB Lambda API Gateway Lambda EventBridge Lambda Lambda
79
@theburningmonk theburningmonk.com Tracing through asynchronous invocations can be difficult
80
@theburningmonk theburningmonk.com Use correlation IDs to find related logs
81
@theburningmonk theburningmonk.com S3 Lambda DynamoDB Lambda API Gateway Lambda EventBridge Lambda Lambda How to inject correlation IDs?
82
@theburningmonk theburningmonk.com S3 Lambda DynamoDB Lambda API Gateway Lambda EventBridge Lambda Lambda How to inject correlation IDs? How to inject correlation IDs? How to inject correlation IDs?
83
@theburningmonk theburningmonk.com https://github.com/getndazn/dazn-lambda-powertools
84
@theburningmonk theburningmonk.com S3 Lambda DynamoDB Lambda API Gateway Lambda EventBridge Lambda Lambda
85
@theburningmonk theburningmonk.com S3 Lambda DynamoDB Lambda API Gateway Lambda EventBridge Lambda Lambda Microservice 1 Microservice 2 Microservice 3
86
@theburningmonk theburningmonk.com S3 Lambda DynamoDB Lambda API Gateway Lambda EventBridge Lambda Lambda Microservice 1 Microservice 2 Microservice 3 AWS account 1 AWS account 2 AWS account 3
87
Log Aggregation
88
@theburningmonk theburningmonk.com
89
@theburningmonk theburningmonk.com
90
@theburningmonk theburningmonk.com
91
@theburningmonk theburningmonk.com CloudWatch Logs is an async event source for Lambda
92
@theburningmonk theburningmonk.com Concurrent Executions Time regional max concurrency functions that are delivering business value
93
@theburningmonk theburningmonk.com Concurrent Executions Time regional max concurrency functions that are delivering business value ship logs
94
@theburningmonk theburningmonk.com either set concurrency limit on the log shipping function (and potentially lose logs due to throttling) or…
95
@theburningmonk theburningmonk.com
96
@theburningmonk theburningmonk.com 1 shard = 1 concurrent execution i.e. control the no. of concurrent executions with no. of shards
97
@theburningmonk theburningmonk.com or consider using Lambda Extensions
98
@theburningmonk theburningmonk.com or consider using Lambda Extensions Optionally disable CloudWatch Logs to save on cost
99
@theburningmonk theburningmonk.com Your code Time Extension Invoke Idle Shutdown 2s Extension shutdown Runtime shutdown Return function response Send logs
100
Distributed Tracing
101
@theburningmonk theburningmonk.com S3 Lambda DynamoDB Lambda API Gateway Lambda EventBridge Lambda Lambda
102
X-Ray
103
Serverless observability - a hero's perspective
104
Serverless observability - a hero's perspective
105
@theburningmonk theburningmonk.com Some services are not supported e.g. Kinesis, DynamoDB
106
@theburningmonk theburningmonk.com HTTP/HTTPs traffic only
107
@theburningmonk theburningmonk.com Requires manual instructation of AWS SDK and HTTP module
108
AWS offers a lot of built-in tools, but…
109
@theburningmonk theburningmonk.com assembly are required
110
@theburningmonk theburningmonk.com assembly are required lots of decisions for you to make
111
@theburningmonk theburningmonk.com assembly are required
112
@theburningmonk theburningmonk.com Have to use (and learn) multiple services
113
@theburningmonk theburningmonk.com Not one complete package
114
Many vendors cater for serverless workloads, but…
115
@theburningmonk theburningmonk.com Their focus is still on serverful applications, and has shallow support for serverless architectures (e.g. poor support for async workloads)
116
@theburningmonk theburningmonk.com
117
Serverless observability - a hero's perspective
118
@theburningmonk theburningmonk.com github.com/theburningmonk
Serverless OBSERVABILITY A hero’s perspective
@theburningmonk theburningmonk.com What do I mean by “observability”?
Monitoring watching out for known failure modes in the system, e.g. network I/O, CPU, memory usage, …
@theburningmonk theburningmonk.com Observability being able to debug the system, and gain insights into the system’s behaviour
@theburningmonk theburningmonk.com In control theory, observability is a measure of how well internal states of a system can be inferred from knowledge of its external outputs. https://en.wikipedia.org/wiki/Observability
@theburningmonk theburningmonk.com In control theory, observability is a measure of how well internal states of a system can be inferred from knowledge of its external outputs. https://en.wikipedia.org/wiki/Observability including non- functional outputs
@theburningmonk theburningmonk.com These are the four pillars of the Observability Engineering team’s charter: • Monitoring • Alerting/Visualization • Distributed systems tracing infrastructure • Log aggregation/analytics “ ” http://bit.ly/2DnjyuW - Observability Engineering at Twitter
@theburningmonk theburningmonk.com microservices death stars circa 2015
@theburningmonk theburningmonk.com microservices death stars circa 2015 mm… I wonder what’s going on here…
Serverless observability - a hero's perspective
Serverless observability - a hero's perspective
Serverless observability - a hero's perspective
@theburningmonk theburningmonk.com microservices death stars circa 2015 I got this!
Serverless observability - a hero's perspective
@theburningmonk theburningmonk.com
Yan Cui http://theburningmonk.com @theburningmonk AWS user for 10 years
http://bit.ly/yubl-serverless
Yan Cui http://theburningmonk.com @theburningmonk Developer Advocate @
Serverless observability - a hero's perspective
Yan Cui http://theburningmonk.com @theburningmonk Independent Consultant advise training delivery
theburningmonk.com/courses
Learn GraphQL and AppSync by building a Twitter clone with these technologies appsyncmasterclass.com
realworldserverless.com
@theburningmonk theburningmonk.com
@theburningmonk theburningmonk.com Concurrency is in your application
@theburningmonk theburningmonk.com Concurrency is in your application Agent
@theburningmonk theburningmonk.com Concurrency is in your application Agent
@theburningmonk theburningmonk.com Concurrency is in your application Agent Shares the same CPU, memory and bandwidth as application
@theburningmonk theburningmonk.com API Gateway
@theburningmonk theburningmonk.com API Gateway Lambda
@theburningmonk theburningmonk.com API Gateway Lambda Worker Worker Worker Worker Worker Worker Worker Worker Worker
@theburningmonk theburningmonk.com API Gateway Lambda Worker Worker Worker Worker Worker Worker Worker Worker Worker Busy Busy Busy Busy Busy Busy
@theburningmonk theburningmonk.com API Gateway Lambda Worker Worker Worker Worker Worker Worker Worker Worker Worker Busy Busy Busy Busy Busy Busy
@theburningmonk theburningmonk.com API Gateway Lambda Worker Worker Worker Worker Worker Worker Worker Worker Worker Busy Busy Busy Busy Busy Busy Only processes one request at a time
@theburningmonk theburningmonk.com API Gateway Lambda Worker Worker Worker Worker Worker Worker Worker Worker Worker Busy Busy Busy Busy Busy Busy Only processes one request at a time Runs in an AWS-managed baremetal EC2 instance
@theburningmonk theburningmonk.com Resource overhead is irrelevant. Think latency overhead instead.
@theburningmonk theburningmonk.com Resource overhead is irrelevant. Think latency overhead instead.
@theburningmonk theburningmonk.com https://www.youtube.com/watch?v=xmacMfbrG28
@theburningmonk theburningmonk.com Built-in collection of: Metrics Logs Traces CloudWatch Metrics CloudWatch Logs X-Ray
challenges
Background Processing Time
@theburningmonk theburningmonk.com user request user request user request user request user request user request user request critical paths: minimise user-facing latency handler handler handler handler handler handler handler
@theburningmonk theburningmonk.com user request user request user request user request user request user request user request critical paths: minimise user-facing latency StatsD handler handler handler handler handler handler handler rsyslog background processing: batched, asynchronous, low overhead
@theburningmonk theburningmonk.com No background processing*.
@theburningmonk theburningmonk.com No background processing*. * you can work around this with Lambda extensions
(potential) Data Loss When workers are garbage collected
@theburningmonk theburningmonk.com Lambda cold start
@theburningmonk theburningmonk.com Lambda data is batched between invocations
@theburningmonk theburningmonk.com Lambda idle data is batched between invocations
@theburningmonk theburningmonk.com Lambda idle garbage collection data is batched between invocations
@theburningmonk theburningmonk.com Lambda
@theburningmonk theburningmonk.com my code send metrics
@theburningmonk theburningmonk.com my code send metrics
@theburningmonk theburningmonk.com my code send metrics internet internet press button something happens
Serverless observability - a hero's perspective
Lambda Extension to the rescue!
Lambda Extension to the rescue! Think “sidecar” but for Lambda ;-)
@theburningmonk theburningmonk.com Your code Time Invoke Idle Shutdown Runtime shutdown
@theburningmonk theburningmonk.com Your code Time Extension Invoke Idle Runtime shutdown Shutdown
@theburningmonk theburningmonk.com Your code Time Extension Invoke Idle Runtime shutdown Shutdown
@theburningmonk theburningmonk.com Your code Time Extension Invoke Idle Shutdown 2s Extension shutdown Runtime shutdown
@theburningmonk theburningmonk.com Lambda idle garbage collection data is batched between invocations
@theburningmonk theburningmonk.com Your code Time Extension Invoke Idle Shutdown 2s Extension shutdown Runtime shutdown Flush buffered telemetry data
@theburningmonk theburningmonk.com Your code Time Extension Invoke Idle Shutdown 2s Extension shutdown Runtime shutdown 5-10 mins on average
@theburningmonk theburningmonk.com my code send metrics
@theburningmonk theburningmonk.com Your code Time Extension Invoke Idle Shutdown 2s Extension shutdown Runtime shutdown
@theburningmonk theburningmonk.com Your code Time Extension Invoke Idle Shutdown 2s Extension shutdown Runtime shutdown You pay for this time too
@theburningmonk theburningmonk.com Your code Time Extension Invoke Idle Shutdown 2s Extension shutdown Runtime shutdown Return function response
@theburningmonk theburningmonk.com Your code Time Extension Invoke Idle Shutdown 2s Extension shutdown Runtime shutdown Return function response Send telemetry data
Lots of async invocations
@theburningmonk theburningmonk.com http://bit.ly/2Dpidje
@theburningmonk theburningmonk.com ? functions are often chained together via asynchronous invocations
@theburningmonk theburningmonk.com ? SNS Kinesis EventBridge CloudWatch Logs IoT DynamoDB S3 SES
@theburningmonk theburningmonk.com S3 Lambda
@theburningmonk theburningmonk.com S3 Lambda DynamoDB Lambda
@theburningmonk theburningmonk.com S3 Lambda DynamoDB Lambda API Gateway Lambda
@theburningmonk theburningmonk.com S3 Lambda DynamoDB Lambda API Gateway Lambda EventBridge Lambda
@theburningmonk theburningmonk.com S3 Lambda DynamoDB Lambda API Gateway Lambda EventBridge Lambda Lambda
@theburningmonk theburningmonk.com Tracing through asynchronous invocations can be difficult
@theburningmonk theburningmonk.com Use correlation IDs to find related logs
@theburningmonk theburningmonk.com S3 Lambda DynamoDB Lambda API Gateway Lambda EventBridge Lambda Lambda How to inject correlation IDs?
@theburningmonk theburningmonk.com S3 Lambda DynamoDB Lambda API Gateway Lambda EventBridge Lambda Lambda How to inject correlation IDs? How to inject correlation IDs? How to inject correlation IDs?
@theburningmonk theburningmonk.com https://github.com/getndazn/dazn-lambda-powertools
@theburningmonk theburningmonk.com S3 Lambda DynamoDB Lambda API Gateway Lambda EventBridge Lambda Lambda
@theburningmonk theburningmonk.com S3 Lambda DynamoDB Lambda API Gateway Lambda EventBridge Lambda Lambda Microservice 1 Microservice 2 Microservice 3
@theburningmonk theburningmonk.com S3 Lambda DynamoDB Lambda API Gateway Lambda EventBridge Lambda Lambda Microservice 1 Microservice 2 Microservice 3 AWS account 1 AWS account 2 AWS account 3
Log Aggregation
@theburningmonk theburningmonk.com
@theburningmonk theburningmonk.com
@theburningmonk theburningmonk.com
@theburningmonk theburningmonk.com CloudWatch Logs is an async event source for Lambda
@theburningmonk theburningmonk.com Concurrent Executions Time regional max concurrency functions that are delivering business value
@theburningmonk theburningmonk.com Concurrent Executions Time regional max concurrency functions that are delivering business value ship logs
@theburningmonk theburningmonk.com either set concurrency limit on the log shipping function (and potentially lose logs due to throttling) or…
@theburningmonk theburningmonk.com
@theburningmonk theburningmonk.com 1 shard = 1 concurrent execution i.e. control the no. of concurrent executions with no. of shards
@theburningmonk theburningmonk.com or consider using Lambda Extensions
@theburningmonk theburningmonk.com or consider using Lambda Extensions Optionally disable CloudWatch Logs to save on cost
@theburningmonk theburningmonk.com Your code Time Extension Invoke Idle Shutdown 2s Extension shutdown Runtime shutdown Return function response Send logs
Distributed Tracing
@theburningmonk theburningmonk.com S3 Lambda DynamoDB Lambda API Gateway Lambda EventBridge Lambda Lambda
X-Ray
Serverless observability - a hero's perspective
Serverless observability - a hero's perspective
@theburningmonk theburningmonk.com Some services are not supported e.g. Kinesis, DynamoDB
@theburningmonk theburningmonk.com HTTP/HTTPs traffic only
@theburningmonk theburningmonk.com Requires manual instructation of AWS SDK and HTTP module
AWS offers a lot of built-in tools, but…
@theburningmonk theburningmonk.com assembly are required
@theburningmonk theburningmonk.com assembly are required lots of decisions for you to make
@theburningmonk theburningmonk.com assembly are required
@theburningmonk theburningmonk.com Have to use (and learn) multiple services
@theburningmonk theburningmonk.com Not one complete package
Many vendors cater for serverless workloads, but…
@theburningmonk theburningmonk.com Their focus is still on serverful applications, and has shallow support for serverless architectures (e.g. poor support for async workloads)
@theburningmonk theburningmonk.com
Serverless observability - a hero's perspective
@theburningmonk theburningmonk.com github.com/theburningmonk

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