managing micro-services with neo4j
TRANSCRIPT
10.21.15
Managing Microservices with Neo4j
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@lendingclub @ashleycsun @rschoening [email protected] [email protected]
Microservices
all the cool kids are doing it
Microservices
2013 2015
Because no talk on microservices would be complete without a container analogy
Can you check the load balancer?
How do we do it?
That’s not a joke
Let’s explain
Separated at Birth
Integrations
MacGyver
MacGyver
GitHub
Pager Duty
Jira
AWS
HipChatSplunk
MacGyver
GitHub
Pager Duty
Jenkins
Jira
AWS
New RelicGraphite
HipChatConfluence
Splunk
MacGyver
GitHub
SAN Storage
Pager Duty
Jenkins
Jira
AWS
New Relic
Active Directory
Graphite
HipChatConfluence
VMWare
Splunk
CloudStack
MacGyver
GitHub
SAN Storage
Load Balancer
Pager Duty
Jenkins
Jira
AWS
New Relic
Active Directory
Graphite
HipChatConfluence
VMWare
SplunkCatchpoint
Artifactory
Firewall
CloudStack
Operational Data Is Distributed
Operational Data Is Distributed
but real-time access is costly
Get It Together
Desired Database Characteristics
Near Real Time Low Latency Read Join Across Data Sets Ease of Use Ad Hoc Query
Desired Database Characteristics
Near Real Time Low Latency Read Join Across Data Sets Ease of Use Ad Hoc Query
How do we use it?
App Check-In and
Service Discovery
Problem: Keeping track of many rapidly-changing services
Problem: Keeping track of many rapidly-changing services
Solution: All app servers phone home to MacGyver and are stored in Neo4j as ‘App Instance’ nodes
MacGyver
Neo4j
App Instance
App Instance
App Instance
MacGyver
Neo4j
App Instance
App Instance
App Instance
<<REST>> <<REST>>
Real-time database of deployed infrastructure
Real-time database of deployed infrastructure
New services get auto-discovered by MacGyver
Real-time database of deployed infrastructure
New services get auto-discovered by MacGyver
Low maintenance
Real-time database of deployed infrastructure
New services get auto-discovered by MacGyver
Low maintenance
Easy scalability
Real-time database of deployed infrastructure
New services get auto-discovered by MacGyver
Low maintenance
Easy scalability
Low latency ad hoc query capability
“Show me all the instances of app X in environment Y”
“Show me all the instances of app X in environment Y”
Deployment and Release Automation
Problem: Highly manual and tedious releases
Problem: Highly manual and tedious releases Limited service visibility
Problem: Highly manual and tedious releases Limited service visibility
• What pool should I deploy to? • Is the most recent revision ‘live’ right now? • Are live pool revisions in sync in different
environments?
Problem: Highly manual and tedious releases Limited service visibility
Solution: Utilize app check-ins and Neo4j to expose info about live
and dark pools, enabling us to automate deployments in a release
Blue-Green Deployment
“Live” Pool “Dark” Pool
Server 1
Server 2
Server 3
Server 5
Server 7
Server 4 Server 8
Server 6
Service Group
Blue-Green Deployment
“Live” Pool “Dark” Pool
Server 1
Server 2
Server 3
Server 5
Server 7
Server 4 Server 8
Server 6
DEPLOY
Service Group
Blue-Green Deployment
“Draining” Pool
Server 1
Server 2
Server 3
Server 5
Server 7
Server 4 Server 8
Server 6
DEPLOY
Service Group
Blue-Green Deployment
Pool Cut-Over
Server 1
Server 2
Server 3
Server 5
Server 7
Server 4 Server 8
Server 6
DEPLOY
Service Group
Blue-Green Deployment
Dark Pool Live Pool
Server 1
Server 2
Server 3
Server 5
Server 7
Server 4 Server 8
Server 6
Service Group
App Instance
MacGyver
Neo4j
<<update app instance>>
Virtual Server
MacGyver
Neo4j
<<REST API Polling>> Load Balancer
Virtual Server
MacGyver
Neo4j
<<REST API Polling>> Load Balancer
<<update virtual server>>
Application Pools
Virtual Service
Problem: Highly manual and tedious releases Limited service visibility
• What pool should I deploy to? • Is the most recent revision ‘live’ right now? • Are live pool revisions in sync in different
environments?
What pool should I deploy to?
What pool should I deploy to?
Are live pool revisions in sync in different environments?
Are live pool revisions in sync in different environments?
Do multiple revisions exist within a single pool?
Do multiple revisions exist within a single pool?
MacGyver
Neo4j
<<REST API>> Load Balancer
<<REST API>>
App Instance
App Instance
App Instance
MacGyver
Neo4j
<<REST API>> Load Balancer
<<REST API>>
App Instance
App Instance
App Instance
Infrastructure Mapping
Problem: Limited visibility into infrastructure interdependencies
Problem: Limited visibility into infrastructure interdependencies
Solution: Use Neo4j to connect different components of our infrastructure
Are any servers in a live pool degraded?
Are any servers in a live pool degraded?
Do we have a single point of failure among any of our services?
Do we have a single point of failure among any of our services?
If storage volume #3 goes down, what services will be impacted?
If storage volume #3 goes down, what services will be impacted?
Other Use Cases
Because no talk on microservices would be complete without a lego
analogy
https://github.com/if6was9/macgyver https://github.com/if6was9/neorx
For More Info…
Lending Club Ashley Sun Rob Schoening @lendingclub @ashleycsun @rschoening