trivadis techevent 2016 capacity management with tvd-capman - recent projects and interesting...

BASLE BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENEVA

HAMBURG COPENHAGEN LAUSANNE MUNICH STUTTGART VIENNA ZURICH

CAPACITY MANAGEMENTWITH TVD-CapManTM

RECENT PROJECTS AND FEATURES

ROBERT KRUZYNSKI

AGENDA

1. INTRODUCTION TO CAPACITY MANAGEMENT

2. INTRODUCTION TO TVD-CapManTM

3. EXAMPLES FROM RECENT PROJECTS

09.09.2016 CAPACITY MANAGEMENT WITH TVD-CAPMAN2

INTRODUCTION

TO CAPACITY MANAGEMENT


Capacity Management

A process to ensure that capacity of database systems

– meets current and future business requirements

– in a cost-effective manner

The goals are

– avoid resource shortages

• they may result in performance and stability problems

– avoid wastage of resources and overcapacity

• negative influence on TCO


What resources are we talking about?

These are the most relevant resources when doing Capacity Management

– CPU usage

• database instance

• database user/application

• server

– IO-Rate, IO-Throughput

• differentiated by reads and writes, small and large operations

• including the I/O category (backup, redo logging, archiving, data file, etc.)

– Memory usage

• database instance: SGA, PGA, process memory

• server: busy/free memory, swap space, huge page


Capacity Management Approach (1)

Record the usage of relevant resources

– in bigger environments or on complex database systems we suggest to install TVD-

CapManTM

Look for resource shortages

– high CPU busy

– high memory usage

– high IO rates (e.g. small SGAs with high IO rates, small DBs with high IO rates)

Look for spare capacities

– low CPU busy

– low memory usage

– large instances with potential to decrease the SGA size



Find the top consumers

– databases or database-applications

– most important: CPU and IO

Perform proactive performance analysis on top consumers

– implement and document performance tuning activities and resulting changes

– control their impact on the usage of resources

If applicable: check utilization of clustered systems

– can one node handle the whole load?

– control the memory (SGA+PGA) and the number of processes

– control CPU and IO usage



After some time

– look at the trend

– check the impact of accomplished changes

– repeat capacity analyses

Further steps may include

– improving the distribution of the systems

– supporting consolidation activities

– sizing new systems

– forecasting capacity needs

– implementing performance monitoring


INTRODUCTION TO TVD-CapManTM


TVD-CapManTM

Motto

– enterprise wide capacity-, resource- and performance management, consolidation,

sizing and accounting of Oracle database systems

Features

– collects data about servers, database instances and optionally about application

sessions

– processes and stores collected data and executes predefined reports

– allows various analyses including trend and forecast

– allows distribution and consolidation computations

– shows a big picture of your database environment


TVD-CapManTM

Technical features

– uses only standard Oracle features (no extract cost features)

– supports Oracle >= 8.1.7, including multitenant 12c

– gathering of up to 500 databases on 50 servers per minute

– data gathering is agentless

– collector gathers over SSH or using DB-Links

– data is stored in a repository schema


Collected Metrics

Metrics are collected or aggregated on server, database and applications levels and include

– CPU time consumed by databases and applications

– IO consumed by databases and applications

– redo volume, user calls, transactions, executions, DB time, number of sessions, number

of logons per database and per application

– SGA memory of database instances

– PGA memory consumed by databases and applications

– server's load, CPU usage, memory, huge page memory and swap usage

– database space total, used, free

– wait time per wait class per database and per application

– user-defined metrics can be configured, collected and displayed in the GUI


EXAMPLES FROM RECENT

PROJECTS


Feature: Periodic Reports

Customizable reports

– Time-Series charts

– Spread sheets

Configuration

– Periods (weekly, monthly, yearly, all-time)

– Server/database groups

– Optional prediction

Customization

– Adding/removing lines to charts

– Adding/removing columns to sheets

– Defining new reports


Prediction Report Example

Prediction is based on linear regression analysis, yearly trend considered


Prediction Report Example

Moving average added


T-Shirt Report ExampleUsed in a migration project for sizing of target servers


T-Shirt Report ExampleUses a custom T-Shirt function (PL/SQL) that implements customer standards


Interactive Status Reports


Shows average and

trend values per

server, database or

database instance

Easy filtering

Allows definition of

server and instance

groups

Trend Line Example


A trend line

displayed on every

chart

Numeric trend value

allows to search for

systems with

growing or falling

values

Distribution & Consolidation Algorithms

Algorithms

– Distribution from scratch - fixed system count

– Distribution minimal invasion - current system count

– Consolidation from scratch - minimal system count

Input

– A list of database instances

– Time range

– Constraints (e.g. number of CPUs, RAM Size, maximum IO.rate/ throughput)

– Grouping type (standalone instance, RAC node, RAC cluster)

Output

– A list of database instances with affiliation to systems



Multiple statistics can (and should) be used as criteria and constraints

– weight can be added

– normalization factor is computed automatically

SQL> SELECT display_name,weight,value_max_limit,value_percentile_limit,normalization_factor

FROM stat s, optim_stat os WHERE s.stat_id=os.stat_id AND optim_id=21;

DISPLAY_NAME WEIGHT VALUE_MAX_LIMIT VALUE_PERCENTILE_LIMIT NORMALIZATION_FACTOR

-------------------- ---------- --------------- ---------------------- --------------------

total physical requests 2 5000 .048396502

DB CPU total 2 8 40.2723377

DB total space 1 .006282116

SGA size 0 16 1.57759328

DB total memory 1 32 1.17342449



The key of the algorithms is the rating of an allocation

An allocation describes which elements (database instances) are allocated on which

systems

The rating is computed for each situation and compared with previous ratings

– lowest rating is best

• only if all elements could be allocated

– rating formula

• sum of the standard deviation of all normalized, weighted statistics curves of all

allocations

• a statistic curve is described by the sum of its average and standard deviation


Distribution Example


Distribution Example

Relevant time frame: last week in July

CapMan generates a list of instances to be

moved from current to future allocation

DB Name Current Allocation Future Allocation

F115 3 1

P111 0 1

P115 2 1

P117 6 1

P124 3 1

P133 6 2

P133 3 2

P134 0 1

P135 6 1

P135 3 1

P137 0 1

P140 0 2

P141 6 3

P142 2 1

P144 2 1

P153 6 1

P179 0 3

P180 2 3

P191 2 1

P193 0 2

P222 0 2

P235 0 1

P250 6 2

P250 3 2

P251 6 2

P255 6 2

P265 0 2

P271 0 2

P272 0 1

P290 0 2

P95 0 2

P998 0 3


Big Picture ExampleColor: AVG(CPU busy)

Area: AVG(DB CPU)

P1342P1801

P2301

P971

P1802 P1912


Big Picture ExampleColor: MAX(CPU busy)

Area: AVG(DB CPU)

P1342P1801

P2301

P971

P1802 P1912


IO-Statistics per File Type

Datafile-IOPS ~ 53% of

total IO

Controlfile IOPS ~ 19%

of total IO


Questions & AnswersRoland Stirnimann

Business Development Manager

[email protected]

Phone +41 58 459 52 47

09.09.2016 CAPACITY MANAGEMENT WITH TVD-CAPMAN

Robert Kruzynski

Principal Consultant / Partner

[email protected]

Phone +49 89 99 27 59 30

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trivadis techevent 2016 capacity management with tvd-capman - recent projects and interesting...

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