Capacity & Performance Management in Solaris Virtualized Environment

Capacity & Performance Management
in Solaris Virtualized Environment

Neeraj Bhatia
Neeraj Bhatia | Capacity & Performance Management in Solaris Virtualized Environment

About Me

 ~ 10 years of experience in Oracle Database Performance Optimization and IT
Services/Infrastructure Capacity Planning.
 Certified Oracle DBA – OCP 9i, 10g, 11g, RAC Expert
 Other Certifications – ISO/20000 Certified Auditor, ITIL V3 Practitioner, Base
SAS
 Currently working with Barclays Bank PLC as a Capacity Manager
 When time allows I blog at http://neerajbhatia.wordpress.com/


Agenda
Section - 1
• Virtualization Basics
• Different Oracle Virtualization techniques
• When to use which
• Basics – Zones, Containers etc
Section - 2
• Capacity Planning Goals and Basics
• Challenges to Capacity & Perf Management in Solaris Zones Environment
• Resource Management techniques
Section - 3
• Implementing Foundation for Effective Capacity and Perf Management
• Case Study -1: Applications Consolidation with Advance Resource Utilization
Techniques
• Case Study -2: Tweaking configuration for additional application load.


Virtualization: Basics
 Virtualization is a technology which enables multiple applications/operating systems
to run on one computer system as if they have exclusive access to the computer.
 Three commonly used Virtualization technologies are:
1. Operating System Virtualization
o This provides multiple isolated execution environments in one OS instance.
o In this model environment thinks that it got an exclusive access to the OS.
o Suitable in case of application Consolidation.
2. Server Virtualization
o In this technology, multiple operating system instances (also different OS) run on
a common system.
o This is helpful in case of Server consolidation.
3. Hardware Virtualization
o In this model, server hardware is partitioned and provides multiple independent
computers within one computer.
o Suitable in case of Server consolidation with high degree of isolation and
security.


Oracle Virtualization Technologies

Trend to Flexibility

Trend to Isolation

Source: Oracle VM Server for SPARC Overview @OTN

What is Capacity Planning
“Capacity Planning is the process of predicting when future load
levels will saturate the system and determining the most costeffecting way of delaying system saturation as much as possible”
- by Daniel A. Menasce and Virgilio A.F. Almeida
(Authors of Capacity Planning for Web Services: Metrics, Models & Methods)


6

Capacity Management Methodology
1. State Goals
2. Define the System
Configuration
3. Classify Workload
4. Quantify & Control
Resource Usage
5. Analyze and Model Data
and Interpret the Results


Resource Management: Why?
• In Consolidation/Virtualization Scenarios, each workload may have different priority
and resource Demand.
• One workload may hog all the resources of underlying server and thus affecting the
performance of other workloads.
• Resource Management allows to create limits for Resource Usage.
• Three Important Roles of Resource Management Framework:
1. Classify Workload: Achieved with the help of Projects and Zones
2. Quantify Resource Usage: Measure how much Resources a particular
Workload is consuming
3. Control the Resource Usage: To eliminate cross-workload interference using 3
techniques:
 Constraints - This defines the upper bound on specific resources
 Scheduling - This defines run-time priorities among the Workloads
 Partitioning - Isolate workload from each other


Workload Classification
• The first step in laying down effective Capacity & Performance Management is to
identify the workloads running on the System.
• A Conventional and often challenging way is to identify Workloads by Username OR
Process Name.
• Oracle Solaris Containers like Zones and Projects provide a systematic way to Identify
and Manage Workloads.
• For example – Multiple instances of the same Application can run on the same
system and provided separate Containers are defined for each, one would be able to
ultimately control the workloads .


Zones Basics
• Solaris Zones is a Software-partitioning technology introduced in Solaris 10 Operating
System.
• Each Zone acts like a separate Operating System although each shares a single
instance of Solaris Operating system.
• Provides an isolated and Secured Environment for running Applications; processes in
a zone can’t interact with processes in other Zones.
• Some Possible Use cases:
o To consolidate several small Solaris/Legacy servers
o To consolidate many lowly-utilized servers
o To enable the migration of Solaris 8 Application Environments
o To provide Maximum Isolation and Security by integrating with Oracle VM
Server with SPARC


Resource Capping Techniques
• Limits the amount of CPU and Memory resources for a Workload.
• Prevents a Workload from using excess CPU/Memory and interfere with other
Workloads.
• Restrict a Workload to excess additional CPU even if other Workloads are Idle.
• When used with Processor sets, it limits CPU usage within a set.
zonecfg:my-zone> add capped-cpu
zonecfg:my-zone:capped-cpu> set ncpus=3.5
zonecfg:my-zone:capped-cpu> end
Note: ncpus = 3.5 will limit the workload to 3.5 CPUs
zonecfg:my-zone> add capped-memory
zonecfg:my-zone:capped-memory> set physical=512m
zonecfg:my-zone:capped-memory> set swap=1024m
zonecfg:my-zone:capped-memory> set locked=100m
zonecfg:my-zone:capped-memory> end


Scheduling Classes (FSS)
• By default Solaris dispatcher uses TS scheduler which gives relatively equal access to
CPU resources.
• Priority among workloads for CPU can be set using FSS (Fair Share Scheduler).
• FSS achieves Resource Efficiency & Fairness by:
o Increasing workload entitlement in case of low usage
o Reducing workload’s entitlement in the case of heavy CPU usage.
• Workload’s relative importance is expressed in number of CPU shares and is not
equivalent to percentages of CPU resources.
• NO meaning in absolute terms; define the relative importance of workloads.
• To optimally set CPU Shares to a workload – understand total number of workloads on
a system, their relative importance and usage profile.
• Can be configured with Processor Sets for granular control over resources.

Resource Partitioning Techniques
• Oracle Solaris Resource Pools partition the System resources and limit Workloads to
specific subsets of the resources.
• This helps in avoiding system-wide overcommitment. However may result in lower
utilization of system resources.
• Possible Use cases:
o Mixed Workloads
o Phased approach for Applications release
o Resource allocation based on user role
o Implementing chargeback model


• Resource Pool Configuration have following parameters:
• Pool: Example - pool.importance
• Pset: Example - pset.min and pset.max
• CPU: Example - cpu.pinned
• Dynamic resource pools provide a mechanism for dynamically adjusting each pool's
resource allocation in response to system events and application load changes.
• DRPs simplify and reduce the number of decisions required from an administrator.
• Adjustments are automatically made through system daemon poold.
• Poold daemon acts on Constraints and Objectives provided by an Administrator.
• Constraints:
o Min/Max CPU Allocation: pset.min and pset.max place limits on the number of
processors that can be allocated to a processor set.
o CPU Pinning: cpu.pinned constraint indicates that a particular CPU should not
be moved by DRP from the processor set in which it is located. This is to achieve
maximum cache utilization for a particular application that is executing within a
processor set.
o Pool Importance: The pool.importance property describes the relative
importance of a pool.

• Objectives:
• Weighted Load Objective: The wt-load objective favors configurations that match
resource allocations to resource utilizations.
• Useful in situations where you are satisfied with the minimum and maximum
properties constraints.
• Utilization Objective (0-100%)
•The utilization objective favors configurations that allocate resources to partitions
that are not meeting the specified utilization objective.
oThis objective is specified by using operators and values.
o The “less than” operator (<) indicates maximum target value.
o The “greater than” operator (>) indicates minimum target value.
o The “about” operator (~) indicates a target value with some acceptable
fluctuation.


• The dedicated-cpu resource specifies that a subset of the System’s processors should
be dedicated to a Workload.
• System on runtime creates a temporary pool till the Workload’s lifetime.
• The dedicated-cpu resource has 2 properties; ncpus and importance
• ncpus: It specifies the number of CPUs or a range, such as 2-4 CPUs.
• Importance: An optional property, defines the relative importance of the workload,
in case a range is provided for ncpus.
zonecfg:my-zone> add dedicated-cpu
zonecfg:my-zone:dedicated-cpu> set ncpus=1-3
zonecfg:my-zone:dedicated-cpu> set importance=2
zonecfg:my-zone:dedicated-cpu> end


Case Study -1: Application Consolidation
• Three Applications are being consolidated onto a single system.
• Applications have different resource requirements.
o Batch Workload: Heavy batch programs, primary concern is throughput.
o OLTP Workload: Heavy transaction processing, primary concern is response time.
Driven from Web, headroom should be there to accommodate transaction spikes.
o Admin Workload: It provides admin console to manage tools and applications.
• Due to business priority you want to make sure a fixed Capacity is always available for
an Application.
• Also unused Capacity by less-important Applications should be available to other
applications.


Process Sets and CPU Shares - Examples
• Total CPU on the Target Server = 8
• Three Processor Sets:
o Processor Set 1 = CPU numbers { 0, 1 }
o Processor Set 2 = CPU numbers { 2, 3 }
o Processor Set 3 = CPU numbers { 4, 5, 6, 7 }
• Three Workloads on the System:
o W1 (Admin Processes), CPU Shares =1, on Processor Set -1
o W2 (Batch Processes), CPU Shares =2, on Processor Set -1, 2
o W3 (OLTP Application Processes), CPU Shares =3, on Processor Set- 1, 2, 3


Workload’s CPU Allocation = For Each Processor Set
Total system-wide CPU allocation for workloads can be calculated as follows:
 Total Admin Workload CPU Allocation:
(1/6 X 2/8)pset1 = 4.17%
 Total Batch Workload CPU Allocation:
(2/6 X 2/8)pset1 + (2/5 X 2/8)pset2 = 18.33%
 Total OLTP Workload CPU Allocation:
(3/6 X 2/8 )pset1 + (3/5 X 2/8)pset2 + (3/3 X 4/8)pset3 = 77.50%
 These figures represent minimum guaranteed CPU shares assuming all workloads
are CPU bound.
 Each Workload could use 100% of CPU resources in their processor sets provided
other Workloads are idle.


Figure: CPU Utilization in the
absence of sophisticated
Resource Utilization techniques

Figure: CPU Utilization in case of
Processor Sets and FSS


The Future lies in the History
"I have seen the future and it is very much like the present,
only longer."
--Kehlog Albran, The Profit

This philosophy is actually a concise description of statistical forecasting. We search
for statistical properties of a time series that are constant in time - trends, seasonal
patterns, correlations etc. We then predict that these properties will also describe the
future.


Case Study -2: Capacity Forecasting
Scenario: There are 2 applications running on a system with 8 CPU cores. One of the
application (Oracle Database) is anticipating additional workload. The objective is to
assess if the system has sufficient Capacity to sustain the workload and is there any
scope to tweak the configuration to reduce the pressure on additional CPUs.
Current Configuration:
• Total CPUs on the System: 8
• Total Zones running on system: 2
• Zone-1 (Oracle Database) CPU Shares: 3
• Zone-2 (Test Environment) CPU Shares: 2


Usage profile of Zones are depicted below:

Test Env Zone using
unused Capacity

With current Resource Management settings of 3 and 2 CPU Shares, Database
application can access up to 60% CPU and Test environment Zone up to 40% CPU
Capacity.

Case Study -2: Observations/Questions
• System has some headroom for additional which can be used by additional

load on Oracle Database Zone.
• With current configuration, there would be no chance of Test environment
getting idle Capacity if Database Zone happens to be using all the Capacity at it’s
disposal.
• Is that a Concern?
• Consider the intrinsic nature of the Test environments.
• Now what If we reduce the Capacity that can be accessed by Test environment
by reducing the CPU shares?
• This will increase the guaranteed Capacity that database Zone can have at any
given point of time.
• The Key is to strike a balance between both Zones.
• If still Capacity asks of database application can’t be satisfied without
compromising with the Test environment, Capacity upgrade is inevitable.


Figure: Effect of additional Capacity usage by
Database Zone

Figure: CPU Shares changed to 4 and 1
respectively, and database is able to
process additional load.
Also, Test zone can go beyond 20% in case
of idle Capacity is available.


Case Study -2: Conclusions
Provided Database workload is going to increases in phased manner, we can
delay the configuration change/Capacity upgradation.
o In Phase-1 additional workload can be supported by leveraging the
available headroom.
o In Phase-2, further increase in the database workload can be sustained by
putting constraint on Test environment.
o If further increase in the database workload is expected, Capacity
upgradation is inevitable.


Quotation
"I hear and I forget. I see and I remember. I do and I understand."
-- Chinese Proverb

The best way to learn a subject is to apply the concepts to a real system. The
techniques presented in this presentation may appear simple on the surface, their
applications to real world may offer a different experience.



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Capacity & Performance Management in Solaris Virtualized Environment

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