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Assimilation Project Distributed Computing Overview

Assimilation Project Distributed Computing Overview

This talk gives an overview of the Assimilation Project from the perspective of it's distributed computing aspects - hitting on scalability, protocol, encryption, etc.

Alan Robertson

December 09, 2014
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    Distributed Computing
    in
    The Assimilation Project
    #AssimProj @OSSAlanR
    http://assimproj.org/
    Alan Robertson
    Assimilation Systems Limited
    http://assimilationsystems.com
    © 2014 Assimilation Systems Limited

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    © 2014 Assimilation Systems Limited
    Biography

    35+ years in IT/development – 10 years in
    system management (SysAdmin)

    Founded Linux-HA project - led 1998-2007
    – aka “Heartbeat” - now called Pacemaker

    Founded Assimilation Project in 2010

    Founded Assimilation Systems Limited in
    2013

    Alumnus of Bell Labs(21), SuSE(1), IBM(13)

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    © 2014 Assimilation Systems Limited
    Highly Scalable Discovery-
    Driven Automation
    Continuous Discovery integrated with
    extreme-scale Monitoring

    Continuous extensible discovery
    – systems, switches, services, dependencies –
    zero network footprint discovery process

    Extensible exception monitoring
    – more than 100K systems

    All data goes into central graph CMDB

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    © 2014 Assimilation Systems Limited
    Assimilation Project History

    Inspired by 2 million core computer (cyclops64)

    Concerns for extreme scale

    Topology aware monitoring

    Topology discovery w/out security issues
    =►Discovery of everything!
    Basically a C2I system:
    Command, Communication and Intelligence

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    © 2014 Assimilation Systems Limited
    A seven-dimensional overview

    Problems Addressed

    Unique Capabilities

    Distribution of Work

    Architectural Components

    Communications Protocol

    Current Status

    Project Needs

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    © 2014 Assimilation Systems Limited
    First Dimension:
    Problems Addressed
    1. Risk Management at extreme scale
    2. Maintaining detailed discovery database
    3. Discovering systems you've forgotten
    4. Discovering vulnerable and licensed
    software you're running – and where
    5. Monitoring services, systems & switches
    6. Finding services you aren't monitoring

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    © 2014 Assimilation Systems Limited
    Second Dimension:
    Unique Powerful Features
    1. Continuous Discovery
    2. Discovery: Zero network footprint
    3. Centralized graph database
    4. We know everything that changes
    5. Discover and update dependency
    information
    6. Discovery and monitoring tightly
    integrated – discovery drives automation

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    (even more) Features...
    7. Discovery and monitoring easily
    extensible
    8. Naturally scalable to > 100K systems
    9. Minimal network load
    10.Server failures distinguishable
    from switch failures
    11.Best practice and vulnerability alerts
    12.Multi-tenant support

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    © 2014 Assimilation Systems Limited
    This all sounds unreasonable...

    Huge scalability without complexity?

    Discovery without pings or port scans?
    Really?

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    Typical Monitoring Algorithm

    A system sends out pings to see if systems are alive

    Probe each service over the network
    – sometimes aggregated by endpoint agents

    Load on system rises rapidly

    Load on network rises rapidly with a hot spot around
    monitoring system

    Growth accomplished by more systems, proxies,
    and other forms of complexity

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    © 2014 Assimilation Systems Limited
    More about Cyclops64

    Specialized monitoring hardware

    Cube communication topology
    ● 24●24●24●160 [2,216,204] cores (!)

    Round trip costs up to 132 forwards

    Traditional monitoring protocol:
    – really, really bad idea

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    Typical Discovery Algorithms

    Turn off intrusion detection system
    – Ping every address
    – Port scans every address
    – SNMP and other probes done against
    open ports
    – Walk network to find switch connections

    Turn intrusion detection back on

    Repeat annually, quarterly, monthly or weekly

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    Third Dimension:
    Fully distributed work
    Two philosophical underpinnings
    1. Monitoring and Discovery are fully distributed
    2. Reliable “no news is good news”
    Only responses to changes are centralized

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    Simple Scalability
    I can explain how we scale so your
    grandmother would understand...

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    © 2014 Assimilation Systems Limited
    Simple Scalability
    I can explain how we scale so your
    grandmother would understand...
    istockphoto
    ©bowdenimages

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    Massive Scalability – or
    “I see dead servers in O(1) time”

    Adding systems does not increase the monitoring work on any
    system

    Each server monitors 2 (or 4) neighbors

    Each server monitors and discovers its own services

    Ring repair and alerting is O(n) – but a very small amount of work
    Current Implementation

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    Minimizing Network Footprint
    (planned)

    Support diagnosing switch issues

    Minimize network traffic

    Ideal for multi-site arrangements

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    © 2014 Assimilation Systems Limited
    Fourth Dimension:
    Architectural Components
    Three Architectural Components
    1. Collective Management Authority

    One CMA per installation
    2. Nanoprobes (agents)

    One per system
    3. Data Storage

    Central Neo4j graph database (CMDB)

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    Basic CMA Functions (python)
    Nanoprobe management

    Configure & direct

    Hear alerts & discovery

    Update rings: join/leave
    Update database
    Issue alerts
    -- provide event notification

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    Nanoprobe Functions ('C')
    Announce self to CMA

    Default: use reserved multicast address
    Do what CMA says

    receive configuration information
    – CMA addresses, ports, defaults

    send/expect heartbeats

    perform discovery actions

    perform monitoring actions
    No persistent state across reboots

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    Service Monitoring based on
    HA Technologies

    Well-proven architecture:
    – “no news is good news” AKA
    management by exception

    Implements Open Cluster Framework
    standard (LSB and others)

    Each system monitors own services

    Can also start, stop, migrate services

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    © 2014 Assimilation Systems Limited
    Monitoring Pros and Cons
    Pros
    Simple & Scalable
    Uniform work distribution
    No single point of failure
    Distinguishes switch vs
    host failure
    Easy on LAN, WAN
    Multi-tenant approach
    Cons
    Active agents
    Potential slowness
    at power-on

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    © 2014 Assimilation Systems Limited
    Why a graph database? (Neo4j)

    Humans describe systems as graphs

    Dependency & Discovery information: graph

    Speed of graph traversals depends on size of
    subgraph, not total graph size

    Root cause queries  graph traversals –
    notoriously slow in relational databases

    Visualization is Natural

    Schema-less design: good for constantly changing
    heterogeneous environment

    Graph Model === Object Model

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    © 2014 Assimilation Systems Limited
    A multi-dimensional demo

    Demonstrate basic capabilities
    – Discovery
    – Discovery-driven monitoring configuration
    – Discovery-driven 'tripwire-like' checksums
    – Monitoring – failures / successes
    – Host down notification

    No configuration was supplied
    – everything comes from discovery
    http://assimilationsystems.com/90_second_demo/

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    Communications Attributes

    Non-heartbeat communication is rare
    – could be months or years between packets

    Some data sent to CMA is sensitive

    Command sent to nanoprobes are
    potentially dangerous

    CMA connects to up to 106 clients

    No news is good news: cannot lose
    information

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    Fifth Dimension
    Communications Protocol

    UDP with reliable transmission protocol
    – packets ACKed when acted on

    Includes signatures, encryption,
    compression

    Communication resets happen on next
    communication – not immediately

    Encryption is almost done (this week!)
    – using libsodium – curve25519 encryption

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    Key Management Scenarios

    Nanoprobe one-time initialization

    CMA one-time initialization

    Nanoprobe startup

    Command flow

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    Nanoprobe one-time
    initialization

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    CMA one-time initialization

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    Nanoprobe Startup

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    Command Processing

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    © 2014 Assimilation Systems Limited
    Sixth Dimension:
    Current Status

    Fourth release out 20 October 2014
    – next release (December?) will have encrypted comm

    Great unit tests

    Several discovery methods written

    Extensible Automated Discovery Triggers

    Discovery => Automatic Monitoring (WOOT!)

    Discovery => Network-Facing Checksums

    Command Line Queries

    Licenses: Commercial or GPLv3

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    Seventh Dimension:
    Get Involved!
    We need you!

    Early adopters

    Testers, Continuous Integration

    Best practice experts

    Designers

    Developers (C,Python, Shell, PowerShell, JavaScript)

    Porters (esp Windows)

    Promoters, Publicists, Packagers, etc.

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    © 2014 Assimilation Systems Limited
    Resistance Is Futile!
    These slides: bit.ly/AssimDCM14
    Mailing List bit.ly/AssimML
    #AssimProj @OSSAlanR
    #assimilation on freenode IRC
    Project Web Site
    assimproj.org
    Company Web Site
    assimilationsystems.com

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    © 2014 Assimilation Systems Limited
    Fifth Dimension:
    Discovery API
    Scripts perform discovery
    – output JSON
    Three Sample Discovery Snippets

    OS information

    Service discovery

    Client discovery

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    How does discovery work?
    Nanoprobe scripts perform discovery

    Each discovers one kind of information

    Can take arguments from environment

    Output JSON
    CMA stores Discovery Information

    JSON stored in Neo4j database

    CMA discovery plugins => graph nodes
    and relationships

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    A Few Canned Queries
    allipports get all port/ip/service/hosts
    allswitchports get switch connections
    crashed get crashed servers
    shutdown get gracefully shutdown servers
    downservices get nonworking services
    findip get system owning IP
    findmac get system owning MAC
    unknownips get unknown IP addresses
    unmonitored get unmonitored services

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    OS discovery JSON Snippet
    { "nodename": "alanr-1225B",
    "operating-system": "GNU/Linux",
    "machine": "x86_64",
    "processor": "x86_64",
    "hardware-platform": "x86_64",
    "kernel-name": "Linux",
    "kernel-release": "3.8.0-31-generic",
    "kernel-version": "#46-Ubuntu SMP ...",
    "Distributor ID": "Ubuntu",
    "Description": "Ubuntu 13.04",
    "Release": "13.04",
    "Codename": "raring" }

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    "sshd": {
    "exe": "/usr/sbin/sshd",
    "cmdline": [ "/usr/sbin/sshd", "-D" ],
    "uid": "root",
    "gid": "root",
    "cwd": "/",
    "listenaddrs": {
    "0.0.0.0:22": {
    "proto": "tcp",
    "addr": "0.0.0.0",
    "port": 22 },
    sshd Service JSON Snippet
    (from netstat and /proc)

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    "ssh": {
    "exe": "/usr/sbin/ssh",
    "cmdline": [ "ssh", "servidor" ],
    "uid": "alanr",
    "gid": "alanr",
    "cwd": "/home/alanr/monitor/src",
    "clientaddrs": {
    "10.10.10.5:22": {
    "proto": "tcp",
    "addr": "10.10.10.5",
    "port": 22 },
    ssh Client JSON Snippet
    (from netstat and /proc)

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    Two Schema subgraphs

    Client / server
    dependency

    Switch interconnect

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    ssh -> sshd dependency graph

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    © 2014 Assimilation Systems Limited
    Switch Discovery Data
    from LLDP (or CDP)

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