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High Availability Explained
Maciej Lasyk
Kraków, devOPS meetup #2
2014-01-28

Maciej Lasyk, High Availability Explained

1/14
“Anything that can go wrong, will go wrong”
Murphy's law

Maciej Lasyk, High Availability Explained

2/14
“Anything that can go wrong, will go wrong”
Murphy's law

Maciej Lasyk, High Availability Explained

2/14
“Anything that can go wrong, will go wrong”
Murphy's law

An electrical explosion and fire Saturday at a Houston data
center operated by The Planet has taken the entire facility offline.
The company claimed power to the facility was interrupted when a
transformer exploded. Official reports that three walls were blown
down causing a fire.

Maciej Lasyk, High Availability Explained

2/14
“Anything that can go wrong, will go wrong”
Murphy's law

An electrical explosion and fire Saturday at a Houston data
center operated by The Planet has taken the entire facility offline.
The company claimed power to the facility was interrupted when a
transformer exploded. Official reports that three walls were blown
down causing a fire.

Three walls of the electrical equipment room on the first floor
blew several feet from their original position, and the underground
cabling that powers the first floor of H1 was destroyed.

Maciej Lasyk, High Availability Explained

2/14
High Availability is in the eye of the beholder

Maciej Lasyk, High Availability Explained

3/14
High Availability is in the eye of the beholder
CEO: we don't loose sales

Maciej Lasyk, High Availability Explained

3/14
High Availability is in the eye of the beholder
CEO: we don't loose sales
Sales: we can extend our offer basing on HA level

Maciej Lasyk, High Availability Explained

3/14
High Availability is in the eye of the beholder
CEO: we don't loose sales
Sales: we can extend our offer basing on HA level
Accounts managers: we don't upset our customers (that often)

Maciej Lasyk, High Availability Explained

3/14
High Availability is in the eye of the beholder
CEO: we don't loose sales
Sales: we can extend our offer basing on HA level
Accounts managers: we don't upset our customers (that often)
Developers: we can be proud – our services are working ;)

Maciej Lasyk, High Availability Explained

3/14
High Availability is in the eye of the beholder
CEO: we don't loose sales
Sales: we can extend our offer basing on HA level
Accounts managers: we don't upset our customers (that often)
Developers: we can be proud – our services are working ;)
System engineers: we can sleep well (and fsck, we love to!)

Maciej Lasyk, High Availability Explained

3/14
High Availability is in the eye of the beholder
CEO: we don't loose sales
Sales: we can extend our offer basing on HA level
Accounts managers: we don't upset our customers (that often)
Developers: we can be proud – our services are working ;)
System engineers: we can sleep well (and fsck, we love to!)
Technical support: no calls? Back to WoW then.. ;)

Maciej Lasyk, High Availability Explained

3/14
So how many 9's?

Maciej Lasyk, High Availability Explained

4/14
So how many 9's?

Maciej Lasyk, High Availability Explained

4/14
So how many 9's?

Monthly: 1 hour of outage means 100% - 0.13888 ~= 99.86112 of availability

Maciej Lasyk, High Availability Explained

4/14
So how many 9's?

Monthly: 1 hour of outage means 100% - 0.13888 ~= 99.86112 of availability
Yearly: 1 hour of outage means 100% - 0.01142 ~= 99.98858 of availability

Maciej Lasyk, High Availability Explained

4/14
So how many 9's?

Monthly: 1 hour of outage means 100% - 0.13888 ~= 99.86112 of availability
Yearly: 1 hour of outage means 100% - 0.01142 ~= 99.98858 of availability
Availability

Downtime (year)

Downtime (month)

90% (“one nine”)

36.5 days

72 hours

95%

18.25 days

36 hours

97%

10.96 days

21.6 hours

98%

7.30 days

14.4 hours

99% (“two nines”)

3.65 days

7.2 hours

99.5%

1.83 days

3.6 hours

99.8%

17.52 hours

86.23 minutes

99.9% (“three nines”)

4.38 hours

21.56 minutes

99.99 (“four nines”)

52.56 minutes

4.32 minutes

99.999 (“five nines”)

5.26 minutes

25.9 seconds

Maciej Lasyk, High Availability Explained

4/14
So how many 9's?

https://jazz.net/wiki/bin/view/Deployment/HighAvailability

Maciej Lasyk, High Availability Explained

4/14
HA terminology
RPO: Recovery Point Objective; how much data can we loose?

Maciej Lasyk, High Availability Explained

5/14
HA terminology
RPO: Recovery Point Objective; how much data can we loose?
RTO: Recovery Time Objective; how long does it take to recover?

Maciej Lasyk, High Availability Explained

5/14
HA terminology
RPO: Recovery Point Objective; how much data can we loose?
RTO: Recovery Time Objective; how long does it take to recover?
MTBF: Mean-Times-Between-Failures; time between failures
(density fnc -> reliability fnc)

https://en.wikipedia.org/wiki/Mean_time_between_failures

Maciej Lasyk, High Availability Explained

5/14
HA terminology
SLA: Service Level Agreement;
formal definitions (customer <-> provider)

Maciej Lasyk, High Availability Explained

5/14
HA terminology
SLA: Service Level Agreement;
formal definitions (customer <-> provider)
OLA: Operational Level Agreement; definitions within organization;
help us keeping provided SLAs

Maciej Lasyk, High Availability Explained

5/14
SLAs..
So what is written in SLAs?
Availability

Downtime (year)

Downtime (month)

90%

36.5 days

72 hours

95%

18.25 days

36 hours

97%

10.96 days

21.6 hours

98%

7.30 days

14.4 hours

99%

3.65 days

7.2 hours

99.5% (EC2, EBS)

1.83 days

3.6 hours

99.8%

17.52 hours

86.23 minutes

99.9% (SoftLayer, IBM)

4.38 hours

21.56 minutes

99.99

52.56 minutes

4.32 minutes

99.999

5.26 minutes

25.9 seconds

Maciej Lasyk, High Availability Explained

5/14
SLAs..
So what is written in SLAs?
Availability

Downtime (year)

Downtime (month)

90%

36.5 days

72 hours

95%

18.25 days

36 hours

97%

10.96 days

21.6 hours

98%

7.30 days

14.4 hours

99%

3.65 days

7.2 hours

99.5% (EC2, EBS)

1.83 days

3.6 hours

99.8%

17.52 hours

86.23 minutes

99.9% (SoftLayer, IBM)

4.38 hours

21.56 minutes

99.99

52.56 minutes

4.32 minutes

99.999

5.26 minutes

25.9 seconds

http://aws.amazon.com/ec2/sla/
http://www.softlayer.com/about/service-level-agreement
Maciej Lasyk, High Availability Explained

5/14
SLAs..

Availability mentioned in SLAs are only goals of service provider
Usually when it's not met than company pays off the fees

Maciej Lasyk, High Availability Explained

5/14
How deep is this hole?
app layer (core, db, cache)
data storage
operating system
hardware
networking
location
So we would like to achieve 99,9999% which is about 30s of downtime per year
Maciej Lasyk, High Availability Explained

6/14
How deep is this hole?
app layer (core, db, cache)
data storage
operating system
hardware
networking
location
Even Proof of Concept is very hard to provide: 5s of downtime per layer yearly!
Maciej Lasyk, High Availability Explained

6/14
Load-balancing and failover

LB:

http://www.netdigix.com/linux-loadbalancing.php

Maciej Lasyk, High Availability Explained

7/14
Load-balancing and failover

Failover:

http://www.simplefailover.com/
Maciej Lasyk, High Availability Explained

7/14
th

th

LB – 4 layer or 7 ?

4th layer:

7th layer:

- high performance

- low cost

- just do the LB work!

- good for quickfixes / patches

- reliable

- not that scalable

- scalable

- low performance
- complex codebase
- custom code for protocols
- cookies? what about memcache..

Maciej Lasyk, High Availability Explained

8/14
Disaster Recovery

Maciej Lasyk, High Availability Explained

9/14
Disaster Recovery

http://disasterrecovery.starwindsoftware.com/planning-disaster-recovery-for-virtualized-environments

Maciej Lasyk, High Availability Explained

9/14
Disaster Recovery

http://disasterrecovery.starwindsoftware.com/planning-disaster-recovery-for-virtualized-environments

Hot site: active synchronization, could be serving services. Cost can be high
Warm site: periodical synchronization, DR tests needed. Low costs
Cold site: Nothing here – just echo and some place to spin services; nightmare
Maciej Lasyk, High Availability Explained

9/14
Planning for failure

Maciej Lasyk, High Availability Explained

10/14
Planning for failure
Everything starts here - DNS:
- keep TTLs low (300s). Can't make under 60min? That's bad!
- check SLA of DNS servers (dnsmadeeasy.com history)
- what do you know about DNSes?
- zero downtime here is a must!
- this can be achieved with complicated network abracadabra
- remember what 99.9999% means?
- round robin is a load – balancer but without failover!
- GSLB – killed by OS/browser/srvs cache'ing
(GlobalServerLoadBalancing)
- GlobalIP (SoftLayer etc) – workaround for GSLB via routing

Maciej Lasyk, High Availability Explained

10/14
Planning for failure
E-mail servers:
- it's simple as MX records (delivering)
- it's almost simple as complicated system of SMTP servers (sending)
- it's not that simple when IMAP locking over DFS (reading)

5 gmail-smtp-in.l.google.com.
10 alt1.gmail-smtp-in.l.google.com.
20 alt2.gmail-smtp-in.l.google.com.
30 alt3.gmail-smtp-in.l.google.com.
40 alt4.gmail-smtp-in.l.google.com.
When MXing – watch the spam!

Maciej Lasyk, High Availability Explained

10/14
Planning for failure
WEB servers:
- it's simple as some frontend loadbalancer
- did you really stick user session to particular server? Memcache!
- LB balancing algorithm
- how many Lbs?
- what if LB goes down?

Maciej Lasyk, High Availability Explained

10/14
Planning for failure
DB servers:
- it's.. not that simple
- replication (master – master? App should be aware..)
- replication ring? Complicated, works, but in case of failure...
- let's talk about MySQL:
- NoSPOF solution: MySQL cluster
- MySQL Galera cluster – synch, active-active multi-master
- master – master – simply works
- Failover? Matsunobu Yoshinori mysql-master-ha
- MySQL utilities (http://www.clusterdb.com/mysql/mysql-utilities-webinar-qa-replay-now-available/)

Maciej Lasyk, High Availability Explained

10/14
Planning for failure
Caching servers:
- this is cache for God's sake – why would we use HA here?
- just use proper architecture like... redundancy.

Maciej Lasyk, High Availability Explained

10/14
Planning for failure
Caching servers:
- this is cache for God's sake – why would we use HA here?
- just use proper architecture like... redundancy.

Load – balancers:
- remember about failovering IP addresses!

Maciej Lasyk, High Availability Explained

10/14
Planning for failure
Caching servers:
- this is cache for God's sake – why would we use HA here?
- just use proper architecture like... redundancy.

Load – balancers:
- remember about failovering IP addresses!
Storage – DFSes:
- GlusterFS – we'll see it in action in a minute
- NFS? Could be – over some SAN / NAS (high cost solution)
- CephFS – just like GlusterFS – it's great and does the work
- DRBD – lower level, does the work on block – device layer – slow...
Maciej Lasyk, High Availability Explained

10/14
Planning for failure
GlusterFS:
- low cost (could be..)
- distributed volumes
- replicated volumes
- striped volumes
- and...
- distributed – striped volumes
- distributed – replicated volumes
- distributed – striped – replicated volumes
- sound good? :)
Maciej Lasyk, High Availability Explained

10/14
Planning for failure
GlusterFS: replicated volumes vs Geo-replication
- replicated:
- mirrors data
- provides HA
- synch – replication
- Geo-replication:
- mirrors data across geo – distributed clusters
- ensures backing up data for DR
- asynch – replica (periodic checks)

Maciej Lasyk, High Availability Explained

10/14
Planning for failure
HA for virtualization solutions?
- it's really complicated, like...

Maciej Lasyk, High Availability Explained

11/14
Planning for failure
HA for virtualization solutions?
- it's really complicated, like...

Maciej Lasyk, High Availability Explained

11/14
Tools
The most important tool would be the conclusion from the picture below:

Maciej Lasyk, High Availability Explained

12/14
Tools
The most important tool would be the conclusion from the picture below:

Maciej Lasyk, High Availability Explained

12/14
Tools
The most important tool would be the conclusion from the picture below:

Maciej Lasyk, High Availability Explained

12/14
Tools
- DNS: roundrobin, GSLB, low ttls, globalIP

Maciej Lasyk, High Availability Explained

12/14
Tools
- DNS: roundrobin, GSLB, low ttls, globalIP
- Load-Balancers (l7, stateless services)): HaProxy, Pound, Nginx

Maciej Lasyk, High Availability Explained

12/14
Tools
- DNS: roundrobin, GSLB, low ttls, globalIP
- Load-Balancers (l7, stateless services)): HaProxy, Pound, Nginx
- Failover (statefull services):
- IP: KeepAlived + sysctl

Maciej Lasyk, High Availability Explained

12/14
Tools
- DNS: roundrobin, GSLB, low ttls, globalIP
- Load-Balancers (l7, stateless services)): HaProxy, Pound, Nginx
- Failover (statefull services):
- IP: KeepAlived + sysctl
- Managing: pacemaker (manager) + corosync (message'ing)

Maciej Lasyk, High Availability Explained

12/14
Tools
- DNS: roundrobin, GSLB, low ttls, globalIP
- Load-Balancers (l7, stateless services)): HaProxy, Pound, Nginx
- Failover (statefull services):
- IP: KeepAlived + sysctl
- Managing: pacemaker (manager) + corosync (message'ing)
- (almost) All-In-One: Linux Virtual Server

Maciej Lasyk, High Availability Explained

12/14
Turn on HA thinking!
Main goal of HA? Improve user experience!
- keep the app fully functional
- keep the app resistant and tolerant to faults
- provide method for a successful audit
- sleep well (anyone awake?) ;)

Maciej Lasyk, High Availability Explained

13/14
Thank you :)
High Availability Explained
Maciej Lasyk
Kraków, devOPS meetup #2
2014-01-28
http://maciek.lasyk.info/sysop
maciek@lasyk.info
@docent-net

Maciej Lasyk, High Availability Explained

14/14

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High Availability (HA) Explained

  • 1. High Availability Explained Maciej Lasyk Kraków, devOPS meetup #2 2014-01-28 Maciej Lasyk, High Availability Explained 1/14
  • 2. “Anything that can go wrong, will go wrong” Murphy's law Maciej Lasyk, High Availability Explained 2/14
  • 3. “Anything that can go wrong, will go wrong” Murphy's law Maciej Lasyk, High Availability Explained 2/14
  • 4. “Anything that can go wrong, will go wrong” Murphy's law An electrical explosion and fire Saturday at a Houston data center operated by The Planet has taken the entire facility offline. The company claimed power to the facility was interrupted when a transformer exploded. Official reports that three walls were blown down causing a fire. Maciej Lasyk, High Availability Explained 2/14
  • 5. “Anything that can go wrong, will go wrong” Murphy's law An electrical explosion and fire Saturday at a Houston data center operated by The Planet has taken the entire facility offline. The company claimed power to the facility was interrupted when a transformer exploded. Official reports that three walls were blown down causing a fire. Three walls of the electrical equipment room on the first floor blew several feet from their original position, and the underground cabling that powers the first floor of H1 was destroyed. Maciej Lasyk, High Availability Explained 2/14
  • 6. High Availability is in the eye of the beholder Maciej Lasyk, High Availability Explained 3/14
  • 7. High Availability is in the eye of the beholder CEO: we don't loose sales Maciej Lasyk, High Availability Explained 3/14
  • 8. High Availability is in the eye of the beholder CEO: we don't loose sales Sales: we can extend our offer basing on HA level Maciej Lasyk, High Availability Explained 3/14
  • 9. High Availability is in the eye of the beholder CEO: we don't loose sales Sales: we can extend our offer basing on HA level Accounts managers: we don't upset our customers (that often) Maciej Lasyk, High Availability Explained 3/14
  • 10. High Availability is in the eye of the beholder CEO: we don't loose sales Sales: we can extend our offer basing on HA level Accounts managers: we don't upset our customers (that often) Developers: we can be proud – our services are working ;) Maciej Lasyk, High Availability Explained 3/14
  • 11. High Availability is in the eye of the beholder CEO: we don't loose sales Sales: we can extend our offer basing on HA level Accounts managers: we don't upset our customers (that often) Developers: we can be proud – our services are working ;) System engineers: we can sleep well (and fsck, we love to!) Maciej Lasyk, High Availability Explained 3/14
  • 12. High Availability is in the eye of the beholder CEO: we don't loose sales Sales: we can extend our offer basing on HA level Accounts managers: we don't upset our customers (that often) Developers: we can be proud – our services are working ;) System engineers: we can sleep well (and fsck, we love to!) Technical support: no calls? Back to WoW then.. ;) Maciej Lasyk, High Availability Explained 3/14
  • 13. So how many 9's? Maciej Lasyk, High Availability Explained 4/14
  • 14. So how many 9's? Maciej Lasyk, High Availability Explained 4/14
  • 15. So how many 9's? Monthly: 1 hour of outage means 100% - 0.13888 ~= 99.86112 of availability Maciej Lasyk, High Availability Explained 4/14
  • 16. So how many 9's? Monthly: 1 hour of outage means 100% - 0.13888 ~= 99.86112 of availability Yearly: 1 hour of outage means 100% - 0.01142 ~= 99.98858 of availability Maciej Lasyk, High Availability Explained 4/14
  • 17. So how many 9's? Monthly: 1 hour of outage means 100% - 0.13888 ~= 99.86112 of availability Yearly: 1 hour of outage means 100% - 0.01142 ~= 99.98858 of availability Availability Downtime (year) Downtime (month) 90% (“one nine”) 36.5 days 72 hours 95% 18.25 days 36 hours 97% 10.96 days 21.6 hours 98% 7.30 days 14.4 hours 99% (“two nines”) 3.65 days 7.2 hours 99.5% 1.83 days 3.6 hours 99.8% 17.52 hours 86.23 minutes 99.9% (“three nines”) 4.38 hours 21.56 minutes 99.99 (“four nines”) 52.56 minutes 4.32 minutes 99.999 (“five nines”) 5.26 minutes 25.9 seconds Maciej Lasyk, High Availability Explained 4/14
  • 18. So how many 9's? https://jazz.net/wiki/bin/view/Deployment/HighAvailability Maciej Lasyk, High Availability Explained 4/14
  • 19. HA terminology RPO: Recovery Point Objective; how much data can we loose? Maciej Lasyk, High Availability Explained 5/14
  • 20. HA terminology RPO: Recovery Point Objective; how much data can we loose? RTO: Recovery Time Objective; how long does it take to recover? Maciej Lasyk, High Availability Explained 5/14
  • 21. HA terminology RPO: Recovery Point Objective; how much data can we loose? RTO: Recovery Time Objective; how long does it take to recover? MTBF: Mean-Times-Between-Failures; time between failures (density fnc -> reliability fnc) https://en.wikipedia.org/wiki/Mean_time_between_failures Maciej Lasyk, High Availability Explained 5/14
  • 22. HA terminology SLA: Service Level Agreement; formal definitions (customer <-> provider) Maciej Lasyk, High Availability Explained 5/14
  • 23. HA terminology SLA: Service Level Agreement; formal definitions (customer <-> provider) OLA: Operational Level Agreement; definitions within organization; help us keeping provided SLAs Maciej Lasyk, High Availability Explained 5/14
  • 24. SLAs.. So what is written in SLAs? Availability Downtime (year) Downtime (month) 90% 36.5 days 72 hours 95% 18.25 days 36 hours 97% 10.96 days 21.6 hours 98% 7.30 days 14.4 hours 99% 3.65 days 7.2 hours 99.5% (EC2, EBS) 1.83 days 3.6 hours 99.8% 17.52 hours 86.23 minutes 99.9% (SoftLayer, IBM) 4.38 hours 21.56 minutes 99.99 52.56 minutes 4.32 minutes 99.999 5.26 minutes 25.9 seconds Maciej Lasyk, High Availability Explained 5/14
  • 25. SLAs.. So what is written in SLAs? Availability Downtime (year) Downtime (month) 90% 36.5 days 72 hours 95% 18.25 days 36 hours 97% 10.96 days 21.6 hours 98% 7.30 days 14.4 hours 99% 3.65 days 7.2 hours 99.5% (EC2, EBS) 1.83 days 3.6 hours 99.8% 17.52 hours 86.23 minutes 99.9% (SoftLayer, IBM) 4.38 hours 21.56 minutes 99.99 52.56 minutes 4.32 minutes 99.999 5.26 minutes 25.9 seconds http://aws.amazon.com/ec2/sla/ http://www.softlayer.com/about/service-level-agreement Maciej Lasyk, High Availability Explained 5/14
  • 26. SLAs.. Availability mentioned in SLAs are only goals of service provider Usually when it's not met than company pays off the fees Maciej Lasyk, High Availability Explained 5/14
  • 27. How deep is this hole? app layer (core, db, cache) data storage operating system hardware networking location So we would like to achieve 99,9999% which is about 30s of downtime per year Maciej Lasyk, High Availability Explained 6/14
  • 28. How deep is this hole? app layer (core, db, cache) data storage operating system hardware networking location Even Proof of Concept is very hard to provide: 5s of downtime per layer yearly! Maciej Lasyk, High Availability Explained 6/14
  • 31. th th LB – 4 layer or 7 ? 4th layer: 7th layer: - high performance - low cost - just do the LB work! - good for quickfixes / patches - reliable - not that scalable - scalable - low performance - complex codebase - custom code for protocols - cookies? what about memcache.. Maciej Lasyk, High Availability Explained 8/14
  • 32. Disaster Recovery Maciej Lasyk, High Availability Explained 9/14
  • 34. Disaster Recovery http://disasterrecovery.starwindsoftware.com/planning-disaster-recovery-for-virtualized-environments Hot site: active synchronization, could be serving services. Cost can be high Warm site: periodical synchronization, DR tests needed. Low costs Cold site: Nothing here – just echo and some place to spin services; nightmare Maciej Lasyk, High Availability Explained 9/14
  • 35. Planning for failure Maciej Lasyk, High Availability Explained 10/14
  • 36. Planning for failure Everything starts here - DNS: - keep TTLs low (300s). Can't make under 60min? That's bad! - check SLA of DNS servers (dnsmadeeasy.com history) - what do you know about DNSes? - zero downtime here is a must! - this can be achieved with complicated network abracadabra - remember what 99.9999% means? - round robin is a load – balancer but without failover! - GSLB – killed by OS/browser/srvs cache'ing (GlobalServerLoadBalancing) - GlobalIP (SoftLayer etc) – workaround for GSLB via routing Maciej Lasyk, High Availability Explained 10/14
  • 37. Planning for failure E-mail servers: - it's simple as MX records (delivering) - it's almost simple as complicated system of SMTP servers (sending) - it's not that simple when IMAP locking over DFS (reading) 5 gmail-smtp-in.l.google.com. 10 alt1.gmail-smtp-in.l.google.com. 20 alt2.gmail-smtp-in.l.google.com. 30 alt3.gmail-smtp-in.l.google.com. 40 alt4.gmail-smtp-in.l.google.com. When MXing – watch the spam! Maciej Lasyk, High Availability Explained 10/14
  • 38. Planning for failure WEB servers: - it's simple as some frontend loadbalancer - did you really stick user session to particular server? Memcache! - LB balancing algorithm - how many Lbs? - what if LB goes down? Maciej Lasyk, High Availability Explained 10/14
  • 39. Planning for failure DB servers: - it's.. not that simple - replication (master – master? App should be aware..) - replication ring? Complicated, works, but in case of failure... - let's talk about MySQL: - NoSPOF solution: MySQL cluster - MySQL Galera cluster – synch, active-active multi-master - master – master – simply works - Failover? Matsunobu Yoshinori mysql-master-ha - MySQL utilities (http://www.clusterdb.com/mysql/mysql-utilities-webinar-qa-replay-now-available/) Maciej Lasyk, High Availability Explained 10/14
  • 40. Planning for failure Caching servers: - this is cache for God's sake – why would we use HA here? - just use proper architecture like... redundancy. Maciej Lasyk, High Availability Explained 10/14
  • 41. Planning for failure Caching servers: - this is cache for God's sake – why would we use HA here? - just use proper architecture like... redundancy. Load – balancers: - remember about failovering IP addresses! Maciej Lasyk, High Availability Explained 10/14
  • 42. Planning for failure Caching servers: - this is cache for God's sake – why would we use HA here? - just use proper architecture like... redundancy. Load – balancers: - remember about failovering IP addresses! Storage – DFSes: - GlusterFS – we'll see it in action in a minute - NFS? Could be – over some SAN / NAS (high cost solution) - CephFS – just like GlusterFS – it's great and does the work - DRBD – lower level, does the work on block – device layer – slow... Maciej Lasyk, High Availability Explained 10/14
  • 43. Planning for failure GlusterFS: - low cost (could be..) - distributed volumes - replicated volumes - striped volumes - and... - distributed – striped volumes - distributed – replicated volumes - distributed – striped – replicated volumes - sound good? :) Maciej Lasyk, High Availability Explained 10/14
  • 44. Planning for failure GlusterFS: replicated volumes vs Geo-replication - replicated: - mirrors data - provides HA - synch – replication - Geo-replication: - mirrors data across geo – distributed clusters - ensures backing up data for DR - asynch – replica (periodic checks) Maciej Lasyk, High Availability Explained 10/14
  • 45. Planning for failure HA for virtualization solutions? - it's really complicated, like... Maciej Lasyk, High Availability Explained 11/14
  • 46. Planning for failure HA for virtualization solutions? - it's really complicated, like... Maciej Lasyk, High Availability Explained 11/14
  • 47. Tools The most important tool would be the conclusion from the picture below: Maciej Lasyk, High Availability Explained 12/14
  • 48. Tools The most important tool would be the conclusion from the picture below: Maciej Lasyk, High Availability Explained 12/14
  • 49. Tools The most important tool would be the conclusion from the picture below: Maciej Lasyk, High Availability Explained 12/14
  • 50. Tools - DNS: roundrobin, GSLB, low ttls, globalIP Maciej Lasyk, High Availability Explained 12/14
  • 51. Tools - DNS: roundrobin, GSLB, low ttls, globalIP - Load-Balancers (l7, stateless services)): HaProxy, Pound, Nginx Maciej Lasyk, High Availability Explained 12/14
  • 52. Tools - DNS: roundrobin, GSLB, low ttls, globalIP - Load-Balancers (l7, stateless services)): HaProxy, Pound, Nginx - Failover (statefull services): - IP: KeepAlived + sysctl Maciej Lasyk, High Availability Explained 12/14
  • 53. Tools - DNS: roundrobin, GSLB, low ttls, globalIP - Load-Balancers (l7, stateless services)): HaProxy, Pound, Nginx - Failover (statefull services): - IP: KeepAlived + sysctl - Managing: pacemaker (manager) + corosync (message'ing) Maciej Lasyk, High Availability Explained 12/14
  • 54. Tools - DNS: roundrobin, GSLB, low ttls, globalIP - Load-Balancers (l7, stateless services)): HaProxy, Pound, Nginx - Failover (statefull services): - IP: KeepAlived + sysctl - Managing: pacemaker (manager) + corosync (message'ing) - (almost) All-In-One: Linux Virtual Server Maciej Lasyk, High Availability Explained 12/14
  • 55. Turn on HA thinking! Main goal of HA? Improve user experience! - keep the app fully functional - keep the app resistant and tolerant to faults - provide method for a successful audit - sleep well (anyone awake?) ;) Maciej Lasyk, High Availability Explained 13/14
  • 56. Thank you :) High Availability Explained Maciej Lasyk Kraków, devOPS meetup #2 2014-01-28 http://maciek.lasyk.info/sysop maciek@lasyk.info @docent-net Maciej Lasyk, High Availability Explained 14/14