Single tenant software to multi-tenant SaaS using K8S
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Transcript of Single tenant software to multi-tenant SaaS using K8S
Back Story
§ Successful Linux distro for service providers
o That sell shared hosting
§ Started to work on platform to sell Docker
o Added multi-tenancy
o Network isolation
o Resource metering
o billing
Back Story
§ Realized smaller hosts cannot
out-compete AWS/Google
Application hosting?§ Decided to pivot to
Application Hosting
o Wordpress
o Joomla
o ElasticSearch
§ Each app would be a pod
o But we need persistence
• K8s Volumes
Our KD hat with apps going out of it?
Where do we fit in?
§ We would simplify packaging
o integrate billing
• Prepare signup
o Do user management
o Use k8s to orchestrate
Can we have more fun?
§ Realized there is more interesting case
o Single tenant to SaaS
§ Or “new” way to do SaaS
New way? Huh?
Where are my microservices?
§ More like really old way
o Wrong way
• Against all the best practices
way
So, what is the new way
§Single tenant
o Single instance of application
• Single or multiple containers (pods)
§K8S to orchestrate
SaaS burden
§ SaaS companies have an idea that they love to implement
o Yet, they also have to implement…
• registration
• customer management
• billing
• upgrade procedures
SaaS burden
o They also have to deal with
• scalability
• reliability
• QoS
• backups
Multi-tenancy
Subscription & Billing
Customization & Configurability
Scalability & Availability
Integration
Security
§ High availability
§ Upgrades
o Rollbacks
o Staged upgrades
§ A/B testing
§ Custom deployments
§ on demand scalability
§ caching proxy
§ CDN
SaaS: Nice To Have
§ Single entity -> small amount of data (10mb?
10gb?)
o easy to deal with
o easy to process
o fast to access
§ Multiply by 10,000x customers
o 100GB to 100T
o Requires advanced database clustering
o costly to access
o waste of resources scanning other’s people data
§ 100,000 customers - petabytes...
Scalability / Data
Sharding at it best
§ Perfect sharding
o single shard / single customer
Shard A Shard B Shard C Shard DCollection I
256GB 256GB 256GB 256GB
Collection I
1 TB
Large Scale Database HA
mm m m
Apps§ Large clusters are hardo requires advance knowledge
o requires advance tuning• support contracts
• high end db admins
Small Scale Database HA
§ Trivial to setupo easy to maintain
MySQL Master
Clients/Web apps
MySQL Replication
MySQL Slave
Reads and writes Only reads
Requests/Second
§ If one client generates 1 request per second at peak time
o 10,000 clients could easily generate 2,000 requests per second at peak time
It is a HARD problem to scale a single application to 2,000 requests per second.
APP
The end of ‘Old’ SaaS
§ Hard to deploy
§ Difficult to update
§ Huge overhead
§ Impossible to manage
The end of ‘Old’ SaaS
Nah, Just Kidding
But we do solve problems
§Easy to make existing single tenants apps into SaaS
oJust package as a pod (group of pods)
§Easy to write new ones
oAll the plumbing done
oNo need to deal with lots of data
APP
Solve§ scalability, reliability & high availability
§ customer signup & managemento billing integration
§ QoSo on demand scalability
o customer separation
§ rolling upgrades
§ a/b testing
KuberDock for ISV
But what about density?
§OverlayFS is great
oSaves plenty of memory & IO
§Container check pointing (future)
oNo tenant activity – checkpoint all the pods
• Bring the back up on first packet for the tenant
o In the right order
Why it wasn’t done before
§Wrong technologies
o50k VMs are much scarier then 50k containers
oPuppet is great
• no atomic updates
§OverlayFS is important – saves tons of
memory
§Some hybrids were done before
But how much would it scale
§Don’t know yet…
§Not recomended design for your b2c venture
software with 100M free users
But how much would it scale
§But it would work for:
oB2B software with deployment of 50k users
• Especially if each tenant needs a lot of data
o 100MB+
Did we ever…
§Work in progress..oLaunch in a month
oBilling software (PHP/MySQL) – 5+ years old• Used by 10K+ companies
• Single tenant application, runs on client’s servers
oHad demand for hosted version• No resources to re-design
• No resources to automate
What does it take?
§TimelineoMinor software redesign:
• putting all customizable files into single folder
• Changing setup wizard
• Adjusting licensing process
• Packaging as pod
Total dev time so far < 40h
EASY SCALABILITY
§ Scale to more customers just by adding serverso Limited only k8s scalability
• support for multiple k8s clusters
§ Using native k8s replication & load balancing functionality to
scale for larger customers
Implementable QoS
§ Tenants isolation
o make sure that one tenant never affects other tenants,
no matter what they do
§ Native high availability
§ Issues affects subset of the customers - if any
Upgrades
§ Docker ‘image’ based upgradeso Roll updates to X% of customer base
• multiple versions in production
• A/B testing
o Roll back updates
o Custom releases for those who need it
All managed using centralized UI
Easy Packaging Provisioning
§ Applications described as YAML
o multi-server, high availability, custom settings…
§ Instantiated using native KuberDock/k8s YAML provisioning
Complex Apps
BILLING MADE EASY
§ Integrate with common billing platforms
§ Let ISV bill per resources, customers, or other metrics
DevOps & Programmers friendly
§ Fully automated
§ micro-services or monolithic
§ any programming language
§ any DBMS
SIGNIFICANTLY SIMPLIFIED DEVELOPMENT
Resource Management
§ Dashboard on server utilization, peak usage
o allows for planing & scaling
§ Vertical scale out using public clouds (AWS) when additional computing needs
required
More to come...
§ Provide platform for in-app user management
o dual auth
o facebook/google auth
§ Built in help desk integration
§ build it app monitoring
§ cross customer jobs
