the-algorithm/unified_user_actions/service/deploy/uua-enricher.aurora

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import os
import itertools
import subprocess
import math
SERVICE_NAME = 'uua-enricher'
CPU_NUM = 3
HEAP_SIZE = 6 * GB
RAM_SIZE = 8 * GB
DISK_SIZE = 3 * GB
class Profile(Struct):
package = Default(String, SERVICE_NAME)
cmdline_flags = Default(String, '')
log_level = Default(String, 'INFO')
instances = Default(Integer, 10)
kafka_bootstrap_servers = Default(String, '/s/kafka/bluebird-1:kafka-tls')
resources = Resources(
cpu = CPU_NUM,
ram = RAM_SIZE,
disk = DISK_SIZE
)
install = Packer.install(
name = '{{profile.package}}',
version = Workflows.package_version()
)
async_profiler_install = Packer.install(
name = 'async-profiler',
role = 'csl-perf',
version = 'latest'
)
setup_jaas_config = Process(
name = 'setup_jaas_config',
cmdline = '''
mkdir -p jaas_config
echo "KafkaClient {
com.sun.security.auth.module.Krb5LoginModule required
principal=\\"discode@TWITTER.BIZ\\"
useKeyTab=true
storeKey=true
keyTab=\\"/var/lib/tss/keys/fluffy/keytabs/client/discode.keytab\\"
doNotPrompt=true;
};" >> jaas_config/jaas.conf
'''
)
main = JVMProcess(
name = SERVICE_NAME,
jvm = Java11(
heap = HEAP_SIZE,
extra_jvm_flags =
'-Djava.net.preferIPv4Stack=true'
' -XX:+UseNUMA'
' -XX:+AggressiveOpts'
' -XX:+PerfDisableSharedMem' # http://www.evanjones.ca/jvm-mmap-pause.html
' -Dlog_level={{profile.log_level}}'
' -Dlog.access.output=access.log'
' -Dlog.service.output={{name}}.log'
' -Djava.security.auth.login.config=jaas_config/jaas.conf'
),
arguments =
'-jar {{name}}-bin.jar'
' -admin.port=:{{thermos.ports[health]}}'
' -kafka.bootstrap.servers={{profile.kafka_bootstrap_servers}}'
' -kafka.application.id={{name}}.{{environment}}'
' -kafka.application.num.instances={{instances}}' # Used for static partitioning
' -kafka.application.server={{mesos.instance}}.{{name}}.{{environment}}.{{role}}.service.{{cluster}}.twitter.com:80'
' -com.twitter.finatra.kafkastreams.config.principal={{role}}'
' -thrift.client.id={{name}}.{{environment}}'
' -service.identifier="{{role}}:{{name}}:{{environment}}:{{cluster}}"'
' -local.cache.ttl.seconds=86400'
' -local.cache.max.size=400000000'
' {{profile.cmdline_flags}}',
resources = resources
)
stats = Stats(
library = 'metrics',
port = 'admin'
)
job_template = Service(
name = SERVICE_NAME,
role = 'discode',
instances = '{{profile.instances}}',
contact = 'disco-data-eng@twitter.com',
constraints = {'rack': 'limit:1', 'host': 'limit:1'},
announce = Announcer(
primary_port = 'health',
portmap = {'aurora': 'health', 'admin': 'health'}
),
task = Task(
resources = resources,
name = SERVICE_NAME,
processes = [async_profiler_install, install, setup_jaas_config, main, stats],
constraints = order(async_profiler_install, install, setup_jaas_config, main)
),
health_check_config = HealthCheckConfig(
initial_interval_secs = 100,
interval_secs = 60,
timeout_secs = 60,
max_consecutive_failures = 4
),
update_config = UpdateConfig(
batch_size = 50,
watch_secs = 90,
max_per_shard_failures = 3,
max_total_failures = 0,
rollback_on_failure = False
)
)
PRODUCTION = Profile(
)
STAGING = Profile(
package = SERVICE_NAME+'-staging',
cmdline_flags = '',
kafka_bootstrap_servers = '/s/kafka/custdevel:kafka-tls'
)
DEVEL = STAGING(
log_level = 'DEBUG',
)
prod_job = job_template(
tier = 'preferred',
environment = 'prod',
).bind(profile = PRODUCTION)
staging_job = job_template(
environment = 'staging'
).bind(profile = STAGING)
devel_job = job_template(
environment = 'devel'
).bind(profile = DEVEL)
jobs = []
for cluster in ['atla', 'pdxa']:
jobs.append(prod_job(cluster = cluster))
jobs.append(staging_job(cluster = cluster))
jobs.append(devel_job(cluster = cluster))