Opening keynote at Mesoscon 2015 with announcements on creating an ecosystem for developing solutions to business problems leveraging Mesos, Mantl.io, Mesosphere Infinity, ZoomData, and Project Calico to create Fog nodes for IoE use cases.

1. Ken Owens
Enabling Microservices Frameworks to Solve Business
Problems
CTO, Cisco Intercloud Services

2. Rapid innovation in computing and application development services
No single service is optimal for all solutions
Customers want to run multiple services in a single cluster and
run multiple clusters in Intercloud environment
...to maximize utilization
...to share data between services

3. Service Product
Cloud/Virtualization CIS/AWS/Metacloud/UCS…
Provisioning Open Stack/Terraform
Automation Ansible
Clustering & Resource
Management Mesos, Marathon, Docker
Load Balancing Avi Networks
ETL & Data Shaping
Log Data Gathering Logstash
Metrics Gathering CollectD, Avi Networks
Messaging Kafka, Solace
Data Storing (Batch) HDFS
Data Storing (OLTP/Real-time) Cassandra
Data Storing (Indexing) Elastic search
Data Processing Apache Spark
Visualization Zoomdata
*Subset example

4. Can deploy in many environments
Get orchestrated by Openstack, Ansible (scripts), Cloudbreak
True Hybrid Cloud deployment: CIS, AWS, UCS, vSphere, other
CIS/AWS/Metacloud/vSphere/UCS…
VM5VM1 VM2 VM3 VM4
Terraform
REST API
REST API
Scripted provisioning
Direct provisioning
Policy, Auto-scaling

5. Microservices managed and scaled separately
Microservices managed by Mesos in a single platform
Microservices architecture for Mesos frameworks and other components
CIS/AWS/Metacloud/vSphere/UCS…
VM5VM1 VM2 VM3 VM4
Terraform
Spark
Executor N
Spark
Executor 1
Spark
Scheduler
Kafka
Broker N
Kafka
Broker 1
Kafka
Scheduler
Docker Docker
HAPROXYMicroservices …
REST API
REST API
Scripted provisioning
Direct provisioning
Policy, Auto-scaling

6. Working with partners on adopting and co-developing services
Partners Co-development Partners

7. Project
Management
Continuous
Integration
Source
Control
Continuous
Deployment
Application
Orchestration
Developer
Tools
Service
Assurance
Jira
Rally
GitHub
Consul
InfluxDB
Elasticsearch
Apache Spark
ZoomData
LogStash
Issue
Management
Mesos
Consul
Kubernetes
Kafka
Terraform
Drone
GitLab
Shipped CICD
GitHub
GitLab
Build Packs
Eclipse
Vagrant
Docker Compose
Jira
Rally
GitHub
Collaboration
Cisco Spark

10. Containers as a first-class citizen of existing
infrastructure. Co-operate with bare metal and IaaS
workloads. Enable Multicast, IPv6 and IP-per-container.
Seamlessly integrate. Allow SP’s and Enterprise to re-
use existing knowledge, skills and infrastructure by
using internet-proven networking techniques.
Allow the network to unify the platforms. Use the best
tool for the job and expose a platform-agnostic UX to
the user. Ie; K8’s workload consuming mesos service.
Define policy in your application, let the network
enforce that policy across the multi-platform stack.
Both in software / cloud or hardware if available.

12. E-commerce Application with Varying Traffic

13. Mesos Slave
Mesos Master
Mesos Slave
Mesos Slave
Zoomdata web app
Mongodb
Spark Worker
Spark Executor
Spark Executor
Proxy
(haproxy, nginx)
Kubernetes
Mongo
Service/RC
Kubernetes
Spark-Proxy
Service/RC
Spark-Proxy
Zoomdata web app
Zoomdata web app
Kubernetes
Framework
Kubernetes
Zoomdata
Scheduler
Service/RC
Zoomdata Scheduler
ProxyGen Script
User
● Every component (Zoomdata App,
MongoDB, Spark-Proxy,
Scheduler) must be started in
independent K8s Pod and there
must be exactly one MongoDB,
Spark-Proxy and Scheduler Pods
meanwhile Zoomdata App can be
scaled with help Kubernetes
Replication Controller.
● There must be defined
Kubernetes Service for MongoDB,
Spark-Proxy, Scheduler as they
will be used in Zoomdata’s App
Pod. Every docker container will
have env variables for every
present Service injected
automatically.

14. Monitoring / Analytics Cluster (local, Texas-3)
Global Monitoring / Analytics Cluster (global, Texas-1)
Monitoring / Analytics Cluster (local, Ams. -1 )
Monitoring / Analytics Cluster (local, Lon.-1)
Local components and deployment is the same as global, just smaller
Real-time and batch processing (Lambda), anomaly detection, visualization
SSL
Kafka
SSL
SSL
MQTT
TBA

15. © 2015 Mesosphere, Inc.
Mesosphere Infinity
Events
Ubiquitous data streams
from connected devices
Feeds
Kafka
Analytics
Spark
Storage
Cassandra
Reactive App
Akka
Ingest millions of
events per second
Real-time and batch
process data
Distributed & highly
scalable database
Scalable, resilient, data
driven applications
Powered by Datacenter Operating System (DCOS)
Sensors
Devices
Clients

16. © 2015 Mesosphere, Inc.© 2015 Mesosphere, Inc.
IoE PoCs with Drones

17. Drone storage
Charging and
Fog Node
Data processing for
further elaboration and
presentation
Local Pilot is present
To comply safety regulation
Flight Schedule and planning is
coordinated by the local fog Node
Issues and solutions
presented
1
2
3
4
5
6
Optimized and reduced Data
secure transmission
to the cloud is performed by
the ground station Fog Node
Fog Enabled Precision Agriculture
Data can be pre-parsed
On drones (micro fog node) and on
the ground station Fog Node

18. Hierarchical approach
Citrus
Grapes
Olives
Peaches
Regional Fog Node
Interface towards Cloud
services
Interface towards Traffic
Management systems

19. © 2015 Mesosphere, Inc.© 2015 Mesosphere, Inc.
Demo

20. • NASA Drone Demo

21. Continue partnerships and co-devlopment efforts with industry
leaders to deliver innovation that enable business to accelerate
their objectives
Continue applying new developed technology to real use cases and
PoC with customers and partners
Continue R&D activities to stay closely aligned with direction the
industry aligns
Deliver the platform for the Internet of Everything