This presentation explores a broad cross-section of enterprise Postgres deployments to identify key usage patterns and reveals important aspects of performance, scalability, and availability including: * Challenges organizations encounter most frequently during the stages of database development, deployment and maintenance * Tuning parameters used most frequently to improve performance of production databases * Frequently problematic database maintenance processes and configuration parameters * Most commonly-used database back-up and recovery strategies

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Postgres in Production –
Enterprise Best Practices

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• Explore key Postgres usage patterns, to expose
− Challenges users face in adoption, development, deployment
and maintenance
− Frequently used tuning parameters
− Common database maintenance practices
− Database back-up and recovery strategies
• Provide empirical data to help you anticipate needs
during your database lifecycles
• Share ideas and resources to help you address
problems before they occur
Objectives

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• EnterpriseDB Overview (quick)
• Postgres Support Experiences
Explore what kinds of issues your peers are experiencing with
Postgres, and when they’re encountering those issues
• Database Health Checks
Share what we’ve learned in the field about how Postgres
databases are deployed, tuned and supported
• Summary and Useful Resources
• Q&A
Agenda
We will take two brief
polls during the webinar
to gather some group
info about your
Postgres usage and
areas of need

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Brief EDB Overview

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Postgres Plus
Advanced Server Postgres Plus
Cloud Database
High Availability
PerformanceManagement
REMOTE
DBA 24x7
SUPPORT
PROFESSIONAL
SERVICES
TRAINING
EDB Serves
All Your Postgres Needs
PostgreSQL
Security

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POSTGRES
innovation
ENTERPRISE
reliability
24/7
support
Services
& training
Enterprise-class
features & tools
Indemnification
Product
road-map
Control
Thousands
of developers
Fast
development
cycles
Low cost
No vendor
lock-in
Advanced
features
Enabling commercial
adoption of Postgres

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Postgres Support Experiences

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• Adoption of Postgres is growing fast
− More and more Postgres users are not not ‘dyed in the wool’ Postgres
users – they come from Oracle, MS SQL, DB2, etc.
• Postgres is moving into complex, mission-critical applications
− Question patterns are changing from simple to complex
− Expertise level is changing – when the customer calls, it is with a
(more) difficult problem or urgent issue
• How do we make Postgres users even more successful?
− Targeted white papers
− Targeted training for support team
− Pro-active training for users as part of our customer enablement
process
− Balanced product strategy of new features, new capabilities and
usability
Why We Analyze Support Tickets

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Ticket Volumes & Multi Year Growth
• Q1 2014: ~ 2500 total customers
• Analysis in this presentation is based on a representative
sample of tickets raised over a 12 months period

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Observations
• Postgres Plus Advanced Server: Strong emphasis on proprietary or commercially
supported OSS
• PostgreSQL: Significantly less emphasis on proprietary or commercially supported
OSS – even though the customer has commercially supported Postgres
Distribution
Tickets and Platforms

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When do customers call?

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What Do Customers Call About?
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
POC Dev Deployment Maintenance
Tuning
Product Awareness
How to
Enhancements
Corruption
Bug
# Tickets Phase
Category POC Dev Deployment Maintenance Grand Total
Bug 8% 22% 9% 7% 10%
Corruption 0% 0% 0% 6% 2%
Enhancements 3% 4% 1% 0% 1%
How to 41% 33% 41% 29% 35%
Product Awareness 46% 39% 44% 39% 41%
Tuning 3% 2% 5% 19% 10%
Grand Total 100% 100% 100% 100% 100%

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Where Do Users Need Help
# Tickets Phase
Category POC Dev Deployment Maintenance Grand Total
Connectors 0% 2% 1% 0% 3%
Bug 0% 0% 0% 0% 1%
How to 0% 1% 0% 0% 1%
Product Awareness 0% 1% 0% 0% 1%
Database 10% 9% 17% 37% 73%
Bug 1% 2% 1% 2% 6%
Corruption 0% 0% 0% 2% 2%
Enhancements 0% 0% 0% 0% 1%
How to 4% 3% 6%
10%
23%
Product Awareness 4% 3% 8%
15%
31%
Tuning 0% 0% 1% 7%
9%
Replication 1% 4% 4% 2% 12%
Bug 0% 1% 0% 0% 2%
How to 0% 0% 3% 1% 4%
Product Awareness 1% 2% 1% 0% 4%
Tuning 0% 0% 0% 1% 1%
Utilities 1% 3% 6% 3% 12%
Bug 0% 1% 1% 0% 2%
Enhancements 0% 0% 0% 0% 0%
How to 1% 1% 3% 1% 6%
Product Awareness 0% 1% 3% 1% 5%
Grand Total 12% 17% 28% 42% 100%

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Deployment/Database/Product Awareness & How To
− How to set up connection pooling?
− How to set up Hot Standby and Streaming Replica?
− How to add table spaces?
− How to partition?
− How to upgrade from major version?
Maintenance/Database/Product Awareness & How To
− How to find bloat in tables & indexes?
− How to enable auditing selectively without performance impact?
− What are the effects of changes to the values of postgresql.conf
file parameters wal_writer_delay, bgwriter_delay?
− What is the correct configuration of hba_conf?
Select Top questions (not in rank order)

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• The majority of questions arise after PoC and
Development
• Deployment and Maintenance are the more
challenging phases
• Plan early to understand necessary practices
− Backup, recovery, high availability strategies
− Configuration parameter tuning to support growth
− Vacuum and bloat
− Connection pooling
Best Practices and Lessons from Support

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Lessons Learned from the AHC

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• Systematic top-to-bottom review of the customer’s
Postgres production installation
• Identifies issues and improvement opportunities in:
− Performance
− Scalability and support for business and data growth
− Availability – Backup strategies, recovery, replication and
failover
− Maintenance and tuning
− Upgrades
• The following analysis is based on a set of 20 AHCs
executed in 2013
Architectural Health Check

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0%#
10%#
20%#
30%#
40%#
50%#
60%#
70%#
80%#
90%#
100%#
effec0ve_cache_size#
shared_buffers#
bgw
riter_lru_m
axpages#
w
al_buffers#
m
aintenance_w
ork_m
em
#
bgw
riter_lru_m
ul0plier#
w
ork_m
em
#
random
_page_cost#
checkpoint_segm
ents#
cpu_tuple_cost#
checkpoint_com
ple0on_target#
checkpoint_0m
eout#
log_line_prefix#
log_lock_w
aits#
log_m
in_dura0on_statem
ent#
autovacuum
_vacuum
_scale_factor#
checkpoint_w
arning#
autovacuum
_vacuum
_cost_delay#
autovacuum
_vacuum
_threshold#
autovacuum
_nap0m
e#
log_autovacuum
_m
in_dura0on#
Top$Database$Parameter$Adjustments$3$Ordered$by$Frequency$
Red bars:
experts expected top parameters,
including vacuum_cost_limit,
log_line_prefix,
log_min_duration_statement,
log_checkpoints
Top Database Parameter Adjustments – Ordered by Frequency

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Kernel Parameters
0
2
4
6
8
10
12
14
16

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Backup and Standby
hot
47%
warm
23%
None
18%
cold
12%
Standby Approach
Physical
Only
36%
Logical
Only
29%
Physical
and
Logical
14%
FS
Snapshot
7%
None
14%
Backup Approach
43% of customers could not execute
PITR (prior to AHC) – some had NO
backup in place
30% of customers would have been
slow or unable to recover from failure

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Maintenance Tasks
Unused
Indexes
39%
Bloated
Indexes
30%
Bloated Tables
13%
Missing
Indexes
9%
Missing
PK
9%
Bloat management
(43%) is a key
production
problem
specific to
Postgres

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• Majority of Postgres production deployments are on
Linux based OS
• Storage system is a key deployment consideration –
DAS/SAN/NFS
• OS System Adjustments (dirty_background_ratio &
dirty_ratio) are also a major adjustment (70% & 45%)
Observations from the AHCs

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Stage: post-production
Primary Issue:
• Outage due to replication
failure - insufficient log info to
determine true root cause
Potential Pain Points
• Concerns have reached limits
of scale and meeting
anticipated growth demands
Recommendations
• Backup and recovery strategies
• Implement continuous archive
recovery in addition to streaming
replication
• Revised backup strategy with PITR
• Tune auto-vacuum settings and
manually vacuum large tables
• Indexes – create concurrent
indexes, REINDEX to reduce bloat
• Parameter tuning – various for
kernel, memory settings and WALs
AHC Case Study #1
Use Case: on-line advertising service with hosted chat

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Stage: pre-deployment
Primary Issues:
• Performance in returning
results and timeouts
• No backup strategy in place
Potential Pain Points
• Expected data volume growth
and increased analysis –
scalability concerns
Recommendations
• Kernel param updates (8)-
kernel.shmmax, kernel.shmall,
vm.dirty_ratio,
vm.dirty_background_ratio,…!
• Database param changes (11) -
effective_cache_size,
shared_buffers,
bgwriter_lru_maxpages,
wal_buffers, work_mem, …
• Re-architect specific heavily-
used database function
• Detailed backup and availability
strategies
AHC Case Study #2
Use Case: data warehouse reporting at customer sites

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Stage: post-production
Primary Issues:
• System performance
• Running out of connections
• Slow queries/ locked tables
• Advice on new SW release
Potential Pain Points
• Concern for increased
workloads and scalability
Recommendations
• max_connections was actually too
high, work_mem too low
• Increase checkpoint parameters
− checkpoint_segments,
checkpoint_timeout,
checkpoint_completion_
target, checkpoint_warning
• Tune storage-related params (SAN)
- DB, memory, file system
work_mem, random_page_cost
• Upgrade for performance and
security improvements
• As workload increases, increase
RAM and re-tune related memory
config. parameters
AHC Case Study #3
Use Case: claims mgmt. system and reporting application

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Summary and Useful Resources

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• Postgres users consistently experience different kinds
of challenges throughout the database lifecycle
− Postgres product knowledge is a critical need at all lifecycle
stages
• Many DBAs would benefit from better knowledge of
tuning Postgres for their storage infrastructures
• Tuning databases early in the lifecycle can save a lot of
time, hassle and user friction after they’re deployed
• Many organizations lack appropriate backup and
recovery strategies
Summary

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• Why do you need backup and recovery? Backup and
Recovery Strategies protect you in case of:
− Catastrophic Device Failure
− Site Failure
− Maintenance
− Operator Error
− Compliance
− Data Corruption
• Key takeaways:
− Logical backup provides granularity in objects (tables, table
spaces, databases); Physical backups provide granularity in
time for PITR.​
− Understand requirements before diving into technology
solution
Backup and Recovery Strategies

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• Postgres provides
− Logical backup (pg_dump)
− Binary/physical backup (Filesystem Snapshots &
pg_basebackup)
− WAL (write ahead logs)
− Streaming replication
− Delayed replication
• Advanced solutions, such as RHCS, Veritas Clustering​,
EFM​​ and ​EDB BART - (now in Beta) augment
the basic capabilities
Backup and Recovery Strategies

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• Performance, Scalability, Availability
• Three-day in-depth Postgres database review
• Analysis of platform, database architecture and application usage
• Provides tuning and management guidance based on EDB’s
expert best practices
Get an Architectural Health Check when you are
− Not 100% sure about your backup/recovery strategy
− Unsure your database is optimally tuned for your apps
− Moving Postgres databases to the Cloud
− Upgrading your servers to multi-core, high memory devices
− Experiencing high growth in application usage
− Experiencing deterioration of read and/or write throughput
Architectural Health Check
http://enterprisedb.com/services/packaged-services/health-check

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For more information about an Architectural Health Check,
please visit www.enterprisedb.com/ahc
or email us - sales@enterprisedb.com