scalability delivering the promise of the cloud
DESCRIPTION
View the webinar recording here: http://www.activestate.com/webinars/scalabilitypromise Don't you wish you could do more than one thing at a time? The same goes for your cloud. What's the use of all this great raw computing power if your applications can't adapt to load requirements as demand fluctuates? Now, with Platform-as-a-Service, elastic scalability is not only possible in the cloud, but practical and necessary as well. In this webinar, John Wetherill and Ho Ming Li will address some of the challenges involved in scaling applications today and show how Stackato Private PaaS alleviates many of these issues. They will also cover: - Auto-scaling vs. manual scaling (semi-auto) - Scaling up or down - Costs of scaling - Resource planning - Monitoring and metrics - Designing to scaleTRANSCRIPT
Scaling the Cloud with PaaSScaling the Cloud with PaaS
John WetherillHo Ming LiJune 26, 2013
Today’s Speakers
John Wetherill Developer Evangelist
Ho Ming Li Cloud Engineer
Topics
Scaling in the Cloud
Scaling with PaaS
Measurement Tools
Best Practices/Antipatterns
Scaling in the Hybrid Cloud
Recent Events
often painfulnot always necessaryfrequently overdone
prerequisite: understanding
Scaling
scale from day onescale early and often
always profile before optimize
Practices
Scaling with Stackato
Using PaaS to Scale
Resource limits/management
load balancing
instant app scaling
auto-scaling
clustering and role distribution
performance monitoring
log aggregation
lxc containers
Resource Management
resources can be capped
per user and per app
memory/disk/URIs
log drains
services
Demo: resource caps
Load Balancing
automatically configured/enabled
round-robin between app instances
handles udp and tcp traffic
any port or protocol
Instant App Scaling
one-click spawn multiple instances
rapid launch by copying existing instance
adjust resource allocation too
scriptable, can be automated
can trigger “autoscaling” events
Demo: app scaling
Clustering / Role Distribution
multiple coordinating nodes
scale out
can be configured by CLI, API, or web ui
roles are assigned to individual nodes
multiple role instances (eg 3 routers)
Demo: Clustering
Log Aggregation
collect all logs from all app instances
forward to aggregation service
no SPOF
logs available via web ui, command line, and REST API
log streams can be filtered and formatted
can generate json logs
Demo: Logging to Loggly
Performance and Health Monitoring
monitor performance data
transactions / applications / websites
simple integration with third-party tools like New Relic
graphical view of cloud performance and resource usage
can trigger REST calls based on performance characteristics
scriptable, customizable
Demo: Stackato and New Relic
LXC Containers
safe isolation between applications
namespaces: processes, network, mount-points, hostname
port uniqueness, isolation, iptables
allows packing as many app instances into a VM as possible
Thank you!Thank you!
Any questions?Any questions?
John WetherillJohn Wetherill
Developer Evangelist, ActiveStateDeveloper Evangelist, [email protected]
@bcferrycoder
Ho Ming LiHo Ming Li
Cloud Engineer, Cloud Engineer, [email protected]
@HoReaL
Today’s Presenters:
Scaling Practices
measure
stateless
websockets
REST
Scaling Practices
meter monitor measure
quantify
session store - but no sticky session
scale out
mature optimization