2017-06-12 red hat tech day utrecht (1) stack monitoring in a... · app app app app app api app app

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  • Full Stack Monitoring in a

    Container &

    Microservices w

    orld

  • About m

    e

    @coscale

    ww

    w.coscale.com

    @spolfliet

    stijn.polfliet@coscale.com

  • Driving

    Container A

    doption

  • Scale & D

    ynamics

    Monitoring C

    hallenges

    Num

    ber of containers >> number of servers

    Containers com

    e and go at a much faster pace

  • Monitoring C

    hallengesTechnology diversity

    100s of application technologies

    Open-source and proprietary w

    orkloads

    Overload of m

    etrics to monitor and alert on

  • Monitoring C

    hallenges

    Com

    ponent# M

    etrics

    OS

    100

    Application

    50

    Com

    ponent# M

    etrics

    OS

    100

    Orchestrator

    50

    Container

    50 per container

    Application

    50 per container

    150 metrics per host

    1000+ metrics per host

    (average 10 containers per host)

    vs

    Metrics Explosion

  • Anom

    aly detection: definition

  • Static alerts

    TOD

    O : m

    ore realistic business examples

    !!

    !

  • ?seasonality

    correlations

    changing or dynamic

    environment

    Static alert limitations

  • Performance

    is key

    Keep control of your

    production environment

  • Full Stack Monitoring for C

    ontainers & M

    icroservices

    (Virtu

    alized) O

    S

    End

    user

    System / In

    frastructu

    re mo

    nito

    ring

    Co

    ntain

    er resou

    rce mo

    nito

    ring

    Real u

    ser mo

    nito

    ring

    Co

    ntain

    er

    Ap

    plicatio

    nco

    mp

    on

    ent

    Co

    ntain

    er

    Ap

    plicatio

    nco

    mp

    on

    ent

    Co

    ntain

    er

    Ap

    plicatio

    nco

    mp

    on

    ent

    CP

    U, M

    emo

    ry, Storage, N

    etwo

    rk, ...

    Orch

    estration

    mo

    nito

    ring

    Services, volu

    mes, d

    eplo

    ymen

    ts, replicatio

    n co

    ntro

    llers, ...

    CP

    U, m

    emo

    ry, storage, n

    etwo

    rk, ...

    In-co

    ntain

    er / Ap

    plicatio

    n m

    on

    itorin

    gW

    eb service, d

    atabase, cach

    ing, ...

    Page lo

    ads, erro

    rs, resou

    rces, ...

    Orch

    estrator

  • METR

    ICS &

    EVENTS

    AU

    TOM

    ATIC A

    NO

    MA

    LY D

    ETECTION

    MICRO

    SERVICES, CON

    TAIN

    ER, A

    ND

    CLUSTER M

    ON

    ITORIN

    GIN

    TUITIVE CLICK-TH

    ROU

    GH

    DA

    SHBO

    ARD

    SIM

    PACT O

    N CU

    STOM

    AN

    D

    BUSIN

    ESS METRICS

  • Why C

    oScale?

    An

    om

    aly detectio

    nEven

    ts for co

    ntext

    Full stack + R

    UM

    + B

    usin

    ess metrics

    Lightw

    eight agen

    t Scalab

    le Platform

    Easy to u

    seQ

    uick d

    eplo

    ymen

    tSaaS

    or o

    n-p

    remise

  • Scalable C

    oScale A

    rchitectu

    re

    AP

    PAPPAP

    P

    AP

    PAPPAP

    I

    AP

    PAPP

    RU

    M

    PostgresqlM

    etadata

    Cassandra

    Metric data

    ElasticsearchE

    vent data

    HaProxy

    LoadbalancerH

    TTPS

    handling

    Analysis w

    orkers

    Alerting w

    orkers

    Data w

    orkers

    RU

    M

    Boom

    erang.js

    Agent

    Log & api parsing

  • CoScale

    Dem

    o

  • Full Stack Monitoring of

    Containers and M

    icroservicesD

    emo screenshots

  • A

    PM

    tools were designed for m

    onolithic applications

    C

    ontainers run a large variety of smaller-sized m

    icroservices

    C

    ontainers are lightweight, so m

    onitoring should also be lightweight

    P

    utting an agent inside a container is an anti-pattern

    Too m

    any dynamic m

    etrics to handle with static alerts

    Monitoring m

    icroservices with traditional A

    PM

  • E

    asy to start with, large com

    munity

    Y

    ou need comm

    ercial support / features to bring it to production

    C

    hallenges around managing large production environm

    ents

    G

    eneric tools, no specific container or cluster visualizations

    N

    o Real U

    ser Monitoring

    N

    o out-of-the-box anomaly detection and predictive analytics

    Prometheus

    Monitoring m

    icroservices with open source tools

  • Thank you!

    @coscale

    stijn.polfliet@coscale.com