Serverless in production (O'Reilly Software Architecture)

Serverless in production
an experience report
Yan Cui

What’s in this talk?
! how to responsibly run a serverless architecture (aka. how to do
ops in serverless)
! testing, CI/CD
! logging, distributed tracing, monitoring
! conﬁg management, securing secrets
! coldstarts
! gotchas/limitations + workarounds/hacks

hi,I’mYanCui
AWS user since 2009

Before
! hidden complexities and dependencies
! low utilisation to leave headroom for large spikes
! EC2 scaling is slow, so scale earlier
! paying for lots of used resources
! up to 30 mins to deploy
! deployments required downtime

- Dan North
“lead time to someone saying
thank you is the only reputation
metric that matters.”

“what would good look like for us?”

Deployments should…
! be small
! be fast
! have zero downtime
! require no lock-step

Features should…
! be independently deployable
! be loosely-coupled

We want to…
! minimise cost of unused resources
! minimise ops effort
! reduce technical mess
! deliver visible improvements to users faster

170 Lambda functions in prod
1.2 GB deployment packages in prod
95% cost saving vs EC2
15x no. of prod releases per month

1st function in prod!
time
is a good fit

?
time
is a good fit

Practices ToolsPrinciples
what is good? how to make it good? with what?

ALERTING
CI / CD
TESTING
LOGGING
MONITORING

170 functions
WOOF!
? ?
time
is a good fit

CONFIG MANAGEMENT
SECURITY
DISTRIBUTED TRACING

building a better search experience

Legacy Monolith Amazon Kinesis Amazon Lambda
Amazon CloudSearch

Amazon CloudSearchAmazon API Gateway Amazon Lambda

building an analytics pipeline

Google BigQuery

Google BigQuery
1 developer, 2 days
design production
(his 1st serverless project)

Google BigQuery
“thank you, nothing ever got
done this fast at Skype!”

rebuilding the timeline feature

building better user recommendations

https://github.com/awslabs/serverless-application-model

https://github.com/claudiajs/claudia

https://github.com/Miserlou/Zappa

Level of Testing
1.Unit
do our objects do the right thing?
are they easy to work with?

1.Unit
2.Integration
does our code work against code we
can’t change?
Level of Testing

handler
test by invoking the handler

Level of Testing
1.Unit
2.Integration
3.Acceptance
does the whole system work?

Level of Testing
unit
integration
acceptance
feedback
confidence

“…We find that tests that mock external libraries
often need to be complex to get the code into the
right state for the functionality we need to exercise.
The mess in such tests is telling us that the design
isn’t right but, instead of fixing the problem by
improving the code, we have to carry the extra
complexity in both code and test…”
Don’t Mock Types You Can’t Change

“…The second risk is that we have to be sure
that the behaviour we stub or mock matches
what the external library will actually do…
Even if we get it right once, we have to make
sure that the tests remain valid when we
upgrade the libraries…”

Services

Paul Johnston
The serverless approach
to testing is different and
may actually be easier.
http://bit.ly/2t5viwK

LambdaAPI Gateway DynamoDB
Unit Tests

Unit Tests
Mock/Stub

is our request correct?
is the request
mapping set up
is the API resources
conﬁgured correctly?
are we assuming the
correct schema?
is Lambda proxy
conﬁgured correctly?
is IAM policy set up
correctly?
is the table created?
what unit tests will not tell you…

most Lambda functions are simple have
single purpose, the risk of shipping broken
software has largely shifted to how they
integrate with external services
observation

But it slows down
my feedback loop…
IT’S NOT
ABOUT YOU!

me
test your system,
not (just) your code

API Gateway
IOT
Kinesis
SNS
ElastiCache
CloudWatch
DynamoDB
IAM
S3
Auth0
GrapheneDB
SES
Twilio
Google BigQuery
MongoLab
CloudSearch
APN
GCM
Lambda
EC2

…if a service can’t provide you with
a relatively easy way to test the
interface in reality, then you should
consider using another one.
Paul Johnston

“…Wherever possible, an acceptance test
should exercise the system end-to-end without
directly calling its internal code.
An end-to-end test interacts with the system
only from the outside: through its interface…”
Testing End-to-End

Test Input

Test Input
Validate

integration tests exercise
system’s Integration with its
external dependencies

acceptance tests exercise
system End-to-End from
the outside

integration tests differ from
acceptance tests only in HOW the
Lambda functions are invoked
observation

“…We prefer to have the end-to-end tests
exercise both the system and the process
by which it’s built and deployed…
This sounds like a lot of effort (it is), but has
to be done anyway repeatedly during the
software’s lifetime…”
Testing End-to-End

me
Deployment scripts that only
live on the CI box is a disaster
waiting to happen.

Jenkins build config deploys and tests
unit + integration tests
deploy
acceptance tests

if [ "$1" = "deploy" ] && [ $# -eq 4 ]; then
STAGE=$2
REGION=$3
PROFILE=$4
npm install
AWS_PROFILE=$PROFILE 'node_modules/.bin/sls' deploy -s $STAGE -r $REGION
…

if [ "$1" = "deploy" ] && [ $# -eq 4 ]; then
STAGE=$2
REGION=$3
PROFILE=$4
npm install
AWS_PROFILE=$PROFILE 'node_modules/.bin/sls' deploy -s $STAGE -r $REGION
…
install serverless framework as
dev dependency

can be run locally & on the CI box

2016-07-12T12:24:37.571Z 994f18f9-482b-11e6-8668-53e4eab441ae
GOT is off air, what do I do now?

2016-07-12T12:24:37.571Z 994f18f9-482b-11e6-8668-53e4eab441ae
GOT is off air, what do I do now?
UTC Timestamp API Gateway Request Id
your log message

function name
date
function version

me
Logs are not easily searchable
in CloudWatch Logs.

CENTRALISE LOGS
MAKE THEM EASILY
SEARCHABLE

CloudWatch Logs AWS Lambda ELK stack

“my followers didn’t
receive my new post!”
- a user

correlation IDs*
* eg. request-id, user-id, yubl-id, etc.

kinesis client
http client
sns client

http://bit.ly/2k93hAj
kinesis
global.CONTEXT
log.info(…)
api-b
global.CONTEXT
global.CONTEXT
global.CONTEXT
x-correlation-id = …
x-correlation-xxx = …
API Gateway Kinesis
SNS
API Gateway
API Gatewayapi-a api-c
sns
headers[“User-Agent”]
headers[“Debug-Log-Enabled”]
MessageAttributes: [
“x-correlation-id”: …
“User-Agent”: …
“Debug-Log-Enabled”: …
]
global.CONTEXT
headers[“x-correlation-id”]
headers[“x-correlation-id”]
data.__context
capture
forward
function
event

traces do not span over
API Gateway

“where do I install
monitoring agents?”

• invocation Count
• error Count
• latency
• throttling
• granular to the minute
• support custom metrics

Why not IOPipe?
! pervasive access to your entire application
! adds latency for tracking

me
The only “background”
processing you get are the
capabilities the platform
provides out of the box.

“how do I batch up and
send logs/metrics in the
background?”

console.log(“hydrating yubls from db…”);
console.log(“fetching user info from user-api”);
console.log(“MONITORING|1489795335|27.4|latency|user-api-latency”);
console.log(“MONITORING|1489795335|8|count|yubls-served”);
timestamp metric value
metric type
metric namemetrics
logs

CloudWatch Logs AWS Lambda
ELK stack
logs
metrics
CloudWatch

CloudWatch Logs AWS Lambda
ELK stack
logs
metrics
CloudWatch
memory used
memory size
billed duration

DASHBOARDS
SET ALARMS
TRACK APP-LEVEL
METRICS

don’t put all your eggs in one basket
aka. you don’t want your monitoring system to
fail at the same time as the systems it monitors

me
Environment variables make it
hard to share conﬁgurations
across functions.

me
Environment variables make it
hard to implement ﬁne-grained
access to sensitive info.

couples ability to deploy with access to sensitive
data, which often don’t overlap in a large
engineering team or in a regulated environment

Why not consul or etcd?
! multiple EC2 instances in multi-AZ for HA
! have to manage servers, patch OS, patch software, etc.
! learning curve for conﬁguring the service
! learning curve for using the CLI tools

SSM Parameter Store
HTTPS
role-based access
encrypted in-flight

SSM Parameter Store
encrypt
role-based access

SSM Parameter Store
encrypted at-rest

HTTPS
role-based access
SSM Parameter Store
encrypted in-flight

SSM Parameter Store
decrypt
role-based access

CENTRALISED
CONFIG SERVICE
CLIENT LIBRARY

Requirements for client library
! standardise and encapsulate how you manage conﬁgs
! supports client-side caching (fetch & cache at coldstart)
! invalidate cache at interval
! invalidate cache explicitly when staleness is detected

max 75 GB total deployment package size*
* limit is per AWS region

Janitor Lambda
http://bit.ly/2xzVu4a

install Serverless framework as dev
dependency at project level
dev dependencies are excluded since 1.16.0

Amazon X-Ray
1st invocation
2nd invocation
cold start

http://bit.ly/2rtCCBz
NodeJs, Python

me
C# and Java experiences ~100
times the cold start time of
Python and also suffer from
much higher standard deviation

me
memory size improves cold
start time linearly

CloudWatch Event AWS Lambda
ping
ping
ping
ping

CloudWatch Event AWS Lambda
ping
ping
ping
ping
HEALTH CHECKS?

AWS Lambda
docs
Take advantage of container re-use to improve the
performance of your function. Make sure any
externalized conﬁguration or dependencies that your
code retrieves are stored and referenced locally after initial
execution. Limit the re-initialization of variables/objects on
every invocation. Instead use static initialization/
constructor, global/static variables and singletons. Keep
alive and reuse connections (HTTP, database, etc.) that
were established during a previous invocation.
http://amzn.to/2jzLmkb

AWS Lambda
docs
AWS Lambda polls your stream and
invokes your Lambda function.
Therefore, if a Lambda function fails,
AWS Lambda attempts to process the
erring batch of records until the time
the data expires.
http://amzn.to/2vs2lIg

vs
processing halts until failed
events are retried successfully/
expired from stream
prioritize realtime-ness,
retry failed events with best effort,
then skip

SNS
Kinesis
SQS
after 3 attempts
share processing logic
events are processed in
chronological order
failed events are retried out
of sequence

PROCESS SQS
WITH RECURSIVE
FUNCTIONS

AWS Lambda
docs
Each shard can support up to
5 transactions per second for
reads, up to a maximum total data
read rate of 2 MB per second.
http://amzn.to/2ubyaot

AWS Lambda
docs
If your stream has 100 active
shards, there will be 100 Lambda
functions running concurrently.
Then, each Lambda function
processes events on a shard in
the order that they arrive.
http://amzn.to/2ubyaot

when no. of processors goes up…

ReadProvisionedThroughputExceeded
can have too many Kinesis read operations…

ReadRecords.IteratorAge
unpredictable spikes in read ‘latency’…

new tool, new problems
but they’re easier to deal with

@theburningmonk
theburningmonk.com
github.com/theburningmonk

Serverless in production (O'Reilly Software Architecture)

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