This presentation shows how Nirmata's multi-cloud container management solution can manage application SLAs across across AWS Spot and On-Demand instances. Microservice are elastic and resilient by design. Application containers provide AWS Spot Instances provide market pricing on infrastructure at up to 90% cost savings. So, why not combine these trends, and using Nirmata's scheduling and application orchestration, and get DevOps agility and cost savings!

1. Microservices on AWS Spot Instances
AWS Bay Area Meetup – Jan 13, 2016
Jim Bugwadia; jim@nirmata.com

2. High-performing IT
organizations deploy 30X
more frequently with 200X
shorter lead times; they have
60X fewer failures and
recover 168X faster.
2015 State of DevOps Report, Puppet Labs

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Agenda
• AWS Spot Instances
• Microservices and Containers
• Nirmata
• Demo

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About me
• Founder at Nirmata
• Software Developer (C++, Java, Javascript, Go)
• Large-scale distributed systems

5. AWS Spot Instances

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AWS Buying Options
• On-demand Instances: hourly pricing
• Reserved Instances:
• Up to 75% cheaper than on-demand pricing
• 1 – 3 year commitment
• Large upfront costs; typical breakeven at 50-80% utilization
• Spot Instances:
• AWS sells excess capacity to higher bidder
• Hourly commitments at a price you name
• Can be up to 90% cheaper that on-demand pricing
• Dedicated Hosts: fully dedicated physical server

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How Spot pricing works
• AWS determines market price based on supply and demand
• Instance is allocated to highest bidder
• Bidder pays market price
• Allocated instance is terminated (with a 2 minute warning)
when market price increases above your bid price
• Diversification of instance families, instance types,
availability zones increases continuity

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c3.xlarge, 4 vCPU, 7.5 GiB; on demand price: $0.239 per Hour
Avg ~$0.03x
80% of on-demand
Spot Bid Advisor: https://aws.amazon.com/ec2/spot/bid-advisor/
Spot History: https://us-west-1.console.aws.amazon.com/ec2sp/v1/spot/home?region=us-west-1

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Spot Fleet
• Simplified bidding across instance types and regions
• Size based on number of instances, vCPU, or your own units
• Include multiple launch specifications, that vary by instance
type, AMI, Availability Zone, or subnet
• Select bid strategy: Lowest price or Diversified
• API and Console!
https://console.aws.amazon.com/ec2sp/v1/spot/launch-wizard?region=us-west-1

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AWS Spot Instances
 Significant savings potential
 Spot Instances are identical as On-Demand (no compromises)
But..
• Initial learning curve
• Not suitable for single point of failure applications
• Not suitable for applications coupled to infrastructure
• More complex to operate (without automation)

11. Microservices

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An initial motivation for
Microservices was scalability
* The Art of Scalability; AKF Scale Cube

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X-Axis Scaling
scale by replicating the entire application
Client Load Balancer Application
Application
Application

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Y-Axis Scaling
scale by splitting the application into services
Client Load Balancer
Customers
Service
Catalog
Service
Orders
Service
/catalog
/customers
/orders

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Z-Axis Scaling
Client Load Balancer
Catalog
Service 3
Catalog
Service 1
Catalog
Service 3
/catalog [A – I]
/catalog [J – R]
/catalog [S – Z]
scale by splitting the data

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Microservices provide Y-X axis scaling
scale by splitting the application and replicating services
Client Load Balancer
Customers
Service
Catalog
Service
Orders
Service
/catalog
/customers
/orders

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Microservices provide Y-X axis scaling
scale by splitting the application and replicating services
Client Load Balancer
Customers
Service
Catalog
Service
Orders
Service
/catalog
/customers
/orders
Best scalability
Best availability
Best efficiency

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1. Elastic: scales up or down independently of other services
2. Resilient: services provide fault isolation boundaries
3. Composable: uniform APIs for each service
4. Minimal: highly cohesive set of entities
5. Complete: loosely coupled with other services
19
A Microservices application is composed of several
cooperating but independent services. Each Service is:
http://nirmata.com/2015/02/microservices-five-architectural-constraints/

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Microservices Summary
 Programming paradigm for the DevOps era
 Builds on best practices of modular design and service-
orientation
 Enables agility at scale (organization, code, users)
But..
• Requires distributed programming, API foundation
• More complex to operate (without automation)
• Requires new tooling

21. Application Containers

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Containers are great for packaging and managing
application components!
Immutable portable application images
Standard units of operations
Separation of Dev-Ops concerns
Efficient runtime
Efficient image management

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Container Lifecycle
For a comprehensive CLI reference: http://docs.docker.com/reference/commandline/cli/

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Containers
 Immediate benefits for any application (portability and agility)
 Easy to learn and adopt
 Gateway to DevOps
 Runtime effeciencies
But..
• Requires separation of config from code (12 factor, etc.)
• Requires new tooling
• More complex to operate (without automation)

25. nirmata

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DevOps
Public or
Private Clouds
Multi-cloud Container Services
nirmata
any cloud – any device
Managed Devices
Data Centers
IT Ops

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deploy operate optimize
Turnkey application container lifecycle management
Single control plane across public & private clouds
Highly scalable cloud-native service

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Policy Based
Orchestration
Real time
Analytics
Application
Blueprints
DevOps
Integrations
Nirmata Control Plane
Host
Agent
The Nirmata Solution
Service DB
Service
Gateway
Data Plane:
• Secure agents
• Seamless Service Discovery
• Distributed Load-balancing
• Programmable routing
Host (or VM)
DNS / LB

29. Infrastructure
Container
Policy-based Orchestration
Microservices Infrastructure (optional)
Application Lifecycle Management
Resource Management & Scheduling
Host
Where Nirmata fits
You
choose

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Nirmata: Key Differentiators
1. Pure play application delivery & management
2. Non-intrusive and easy to use SaaS solution
3. Demand-driven Multi-Layer Scheduling
4. Split plane agent-based architecture
5. Integrated Microservices Infrastructure
6. Integrated monitoring & analytics

31. Demo

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Demo Steps
1. Configure a AWS Spot Fleet Request
2. Configure a Nirmata Host Group that pools on-demand and spot
instances
3. Configure scaling rules, placement rules, and constraints
4. Deploy an application across spot and on-demand instances
5. Terminate spot instances
6. Demonstrate service auto-recovery
7. Demonstrate host auto-scaling

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Nirmata continuously monitors and optimizes
application availability…
Nirmata Host Groups
Spot On-DemandSpot
1. Host Group Pooling
2. Minimum Placement Constraints
3. Spot Termination Detection
4. Host Auto-Scaling
5. Service Auto-Recovery
6. Dynamic Service Discovery &
Load Balancing

34. Summary

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Internet
Auto Scaling
Groups
Edge Tier Mid-Tier Data Tier
Spot Fleet EBS Backed
Instances
Auto-Scale
Host Group
Spot Fleet
Host Group
Launch Config
Host Group

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Key Takeways
1. AWS Spot Instances are significantly cheaper and are always
available.
2. With the Microservices approach, each individual service is
elastic and resilient.
3. Containers provide fast deployment times, improve utilization,
and enable fully automated application operations.
4. Nirmata’s multi-cloud scheduling manages hosts and containers,
provides policy-based orchestration, and maintains application
availability across Spot and On-Demand instance pools!

37. Thank you!
https://try.nirmata.io
test drive Nirmata for free at: