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Keynote (Cloud Developer Roadshow 2014)

Keynote (Cloud Developer Roadshow 2014)

Keynote session for the Google Cloud Platform Developer Roadshow events from July-August 2014

GoogleCloudPlatform

August 20, 2014
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Transcript

  1. Cloud Platform Roadshow

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  2. Agenda
    Keynote
    Blurring the IaaS/PaaS Divide
    From Data to Meaning
    Containerizing the Cloud
    How to Design, Build, and Run a Cloud App
    Fireside Chat

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  3. Keynote
    Key Trends, Technologies, and Ideas

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  4. of CEOs see
    technology change
    as the #1 external force that could
    most impact their organization over
    the next 3-5 years
    Transformation: Business, Technology & Culture
    71%

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  5. enabling a new
    world via mobile
    global connections
    at any moment
    connections virtually
    everywhere
    Any Place
    Any Device
    Adoption
    Speed
    Any Team
    Any Time
    Big Trends
    vitally important to
    stay ahead
    consumer leads,
    business follows
    minds of many need
    to collaborate

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  6. 95%
    using cloud services
    230k Years
    social media per month
    40%
    own a smartphone

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  7. Decreasing cost enables
    virtually limitless storage in the
    cloud. $600 can buy enough
    storage for the world’s music.
    (Source: McKinsey Global Institute May 2011)
    Computing as a utility is now
    available for easy purchase,
    provided from massively
    efficient data centers.
    (Source: Nicholas Carr, The Big Switch, 2008)
    The internet allows for a
    model of real-time access to
    new innovation, information,
    and applications from a wide
    range of devices.
    Affordable
    capacity
    On-demand
    computing
    Instant
    access
    IT Trends

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  8. 75
    years
    1957 2003 2013
    500
    25
    years
    10
    years
    (average age of a company
    joining the S&P 500)

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  9. - Google’s Mission Statement
    “Organize the world’s information and
    make it universally accessible and useful.”

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  10. For the past 15 years, Google
    has been building out the
    world’s fastest, most powerful,
    highest quality cloud
    infrastructure on the planet.

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  11. Google has been running some
    of the world’s largest distributed
    systems with unique and
    stringent requirements.

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  12. A Network that Spans the Globe

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  13. Innovating Software & Driving Technology Forward
    Spanner
    Dremel
    MapReduce
    Bigtable Colossus
    2012 2013
    2002 2004 2006 2008 2010
    GFS
    Compute
    Engine

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  14. Google Cloud Platform is built
    on the same infrastructure that
    powers Google.

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  15. Google Cloud Platform
    Storage
    Cloud
    Storage
    Cloud
    SQL
    Cloud
    Datastore
    Compute
    Compute
    Engine
    App
    Engine
    App Services
    BigQuery
    Cloud
    Endpoints

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  16. Product Momentum
    August 2013
    Encryption at Rest for
    Cloud Storage
    Layer 3 Load
    Balancing in
    Compute
    Engine
    June 2014
    Docker support
    HTTPS Load
    Balancing
    SSD Persistent Disk
    November
    2013
    Cloud Endpoints
    GA
    Dedicated
    Memcache GA
    December 2014
    Compute Engine GA
    Persistent Disk
    March 2014
    AppEngine with Managed VMs
    Windows Server, SuSE, RHEL
    support
    BigQuery
    streaming
    @100K RPS
    Major price
    drops
    February
    2014
    Cloud SQL GA
    HIPAA Support

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  17. Economies of scale from
    sharing infrastructure with
    other developers and
    reduction of
    “fragmentation”.
    Infrastructure changes too
    rapidly to be locked into
    physical platforms - you
    could miss the next
    competitive advantage.
    Every second spent on
    infrastructure and
    operations is time not
    spent on your applications,
    your customers, or your
    business.
    Always
    Lower Cost
    Flexibility
    +
    Adaptability
    Why Are Developers Moving to Cloud
    Lets You
    Focus on
    Customers

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  18. Cloud is still too hard
    Cloud Economics

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  19. $0
    100
    servers
    1,000
    servers
    10,000
    servers
    100,000
    servers
    $8,000
    $6,000
    $4,000
    $2,000
    Public
    Cloud
    Private
    Cloud
    10x cost benefit for large scale agencies
    Cloud Economics

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  20. Computing Patterns
    • On & off workloads (e.g. batch job)
    • Over provisioned capacity is wasted
    • Successful services needs to scale
    • Difficult to provision hardware
    • Unexpected/unplanned peak in demand
    • Sudden spike impacts performance
    • Can’t over-provision for extreme cases
    Growth
    Bursting
    On and Off

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  21. Prices are falling
    • Public cloud prices
    have dropped 6-8%
    annually
    Source: Google Internal Data
    2014
    2006
    Public Cloud Prices

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  22. But prices are not falling fast enough
    • Hardware costs have
    dropped 20-30%
    annually
    Hardware Cost
    Public Cloud Prices
    • Public cloud prices
    have dropped 6-8%
    annually
    Source: Google Internal Data
    2014
    2006

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  23. 100%
    0% 20% 40% 60% 80%
    Sustained Use
    Previous
    On Demand
    New
    On Demand
    $0.11
    $0.10
    $0.09
    $0.08
    $0.07
    $0.06
    $0.05
    $0.04
    $0.03
    Sustained-use discounts
    Net Price Per Hour

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  24. Cloud is still too hard
    Cloud is still too hard

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  25. Cloud is still too hard
    Developers often make trade offs to
    work around the weaknesses and
    limitations of today’s public clouds

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  26. Cloud is still too hard
    Big Data
    or
    Real Time
    Time to
    Market
    or
    Scalability
    Flexibility
    or
    Automatic
    Management

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  27. Cloud is still too hard
    Big Data
    or
    Real time
    Time to
    Market
    or
    Scalability
    Flexibility
    or
    Automatic
    Management
    We are changing or to and

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  28. Developer Productivity
    Time to
    Market
    Scale

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  29. Developer Productivity
    Time to
    Market
    Scale
    and

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  30. Developer Productivity
    • Use the tools you know and love

    • Fast, reliable deployments

    • Isolate and fix issues in production
    Developer Productivity
    Time to
    Market
    Scale
    and

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  31. Developer Productivity
    ● Single interface for
    monitoring all of your
    cloud resources
    ● Rich dashboards and
    alerting capabilities
    ● Find and fix
    performance problems
    quickly
    Cloud Monitoring
    Cloud Monitoring Powered By StackDriver

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  32. Developer Productivity
    ● Debug Production
    Applications without
    Stopping the process
    ● Inspect Stack, locals,
    parameters
    ● Safe for production: No
    user noticeable effects
    Cloud Debugger

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  33. Developer Productivity
    ● Visualize time spent in
    your application
    ● Quickly identify
    performance
    bottlenecks
    ● Compare performance
    from release to release
    Cloud Trace

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  34. IaaS vs. PaaS
    Flexibility Management

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  35. Turnkey Platform Flexible VMs
    IaaS vs. PaaS

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  36. and
    What You Need from Compute Resources
    Flexibility Management

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  37. Manage your infrastructure
    Flexibility Agility
    Google Compute Engine
    Your Code
    Compute as a Spectrum
    Replica Pools Provisioning and health checking
    Managed VMs OS management, deployments
    Your Code
    Your Code App Engine
    Managed
    Runtimes
    Manage your serving stack
    Your Code

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  38. Managed VMs
    • Flexibility of Compute Engine
    with productivity of App Engine
    • Provides best of both worlds
    Flexibility Management
    and

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  39. • Package applications Independent of the VM layer
    • Predictability
    • Quality of service
    • Efficient overcommit
    • Resource accounting
    At Google, we have been doing this for many
    years...
    Images by Connie Zhou
    Containers and Kubernetes

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  40. Networking
    • Projects are isolated private networks
    • Networks can be global
    • Addresses
    • public and private: free while in use
    • Routes, gateways, VPNs, and IP Forwarding
    • Google has a massive backbone with best in
    class throughput and performance
    • This makes GCP the prime-move for
    latency and throughput sensitive
    information -- ie content and data

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  41. Big Data
    Big Data Real Time

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  42. and
    Big Data Real Time
    Big Data

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  43. Complex technical
    infrastructure to
    support distributed
    computing
    Requires
    specialized
    expertise
    Big Data is Hard Big Data is Expensive
    Time
    consuming
    Big Data remains inaccessible
    Storage costs
    scale with larger
    datasets
    Computing
    resources must
    be provisioned
    for peak-loads
    Personnel are
    expensive

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  44. No complex data
    architecture
    required
    Use the
    technical and
    product
    skillsets you
    already have
    Big Data is Hard Big Data is Expensive
    Google is making Big Data accessible
    Pay on-demand
    for only the
    resources you
    use
    Take
    advantage of
    falling prices
    & Moore’s
    Law
    Reduce
    infrastructure
    management
    burden
    Easy
    Affordable
    Query within
    seconds and
    get real-time
    results

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  45. Store
    Capture Analyze
    We help you manage the entire lifecycle of Big Data
    BigQuery
    Dataflow
    Open Source Tools
    Pub/Sub
    Process
    Dataflow
    Storage
    Datastore
    SQL

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  46. Streaming+Batch+Graph
    • Near real-time analysis
    • High fidelity, low latency
    • Focus on results, not sharding
    and transforming
    Streaming: Real-Time Data Graph: Variable Analysis
    Batch: Volumes of Data

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  47. 1
    2
    3
    Summary
    Harness the power and flexibility of Google
    Big innovations are coming of age
    Cloud is the real deal

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  48. November 4, 2014 | San Francisco, CA | cloud.google.com/LIVE

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  49. cloud.google.com
    Images by Connie Zhou

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