This presentation reviews the new dynamic and elastic scaling capabilities added in IBM Streams V4.3. Topics include serverless workloads, job resource allocation mode, job scoped resources mode, improved scheduling, and more!

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IBM Streams V4.3
Dynamic and Elastic Scaling
Brad Fawcett
IBM Streams

2. IBM Watson – IBM Streams
© 2018 IBM Corporation
Please note
▪ IBM’s statements regarding its plans, directions, and intent are subject to change
or withdrawal without notice and at IBM’s sole discretion.
▪ Information regarding potential future products is intended to outline our general
product direction and it should not be relied on in making a purchasing decision.
▪ The information mentioned regarding potential future products is not a commitment, promise,
or legal obligation to deliver any material, code or functionality. Information about potential
future products may not be incorporated into any contract.
▪ The development, release, and timing of any future features or functionality described for our
products remains at our sole discretion.
▪ Performance is based on measurements and projections using standard IBM benchmarks in
a controlled environment. The actual throughput or performance that any user will experience
will vary depending upon many factors, including considerations such as the amount of
multiprogramming in the user’s job stream, the I/O configuration, the storage configuration, and
the workload processed. Therefore, no assurance can be given that an individual user will
achieve results similar to those stated here.
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Dynamic Elastic Scaling - Serverless Workloads
Instance resource acquisition
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Instance
Resource
Management
Dynamic (Streams-initiated)
• job submission / cancellation
• dynamic UDP changes
• instance start/stop
Resource sources
• Streams domain hosts
• External resource manager
Instance resources
Static (user-initiated)
• add/remove hosts
• add/remove resource specs
(instance.dynamicResourceAllocationEnabled=true)
Mixture of static/dynamic supported:
• with static higher priority
Black text: prior functions
Red text: V4.3 new functions

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Job Resource Allocation Mode
How does application resources get allocated to jobs?
– Depends upon allocation mode
– All jobs in instance use same mode. Mode switch requires restarting instance
• Instance scoped resources (instance.applicationResourceAllocationMode = instance)
– Behavior same as previous release
– All application resources in the instance are available to all jobs
– Dynamic resources are NOT used
• Job scoped resources (instance.applicationResourceAllocationMode = job)
– Resource usage is scoped to jobs
– Static resources used first, then dynamic resources added as needed
– Dynamic resources are released whenever no longer needed
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Job Scoped Resources Mode
▪ Resource allocation
▪ job submission. how many?
▪ operator / resource ratio (default = 8, user can change)
▪ user specifies how many per host pool via JobConfigurationObject
▪ running job.
▪ dynamic UDP width increase operation
▪ Resource sharing (controlled by instance.jobResourceSharing property or submit job parm)
▪ unused resources chosen first
▪ if not enough available, check jobResourceSharing mode
▪ “sameJob” - no sharing with other jobs
▪ “sameUser” - can share with other “sameUser” jobs from same user
▪ “sameInstance” - can share with other “sameInstance” jobs
▪ Resource release
▪ job cancellation
▪ resources not being used after a submit job, restart pe operation, or parallel width change
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New Dynamic / Elastic Operation = “updateOperators”
updateOperators enables user to perform adjustments to running jobs
▪ Adjustments supported in V4.3
▪ Parallel region adjustments
▪ add or remove channels
▪ add or resources
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Improved Scheduling
▪ PE placement decisions may now consider CPU, Memory, and Network usage metrics
• User customizes the relative importance of each metric by setting upper/lower utilization thresholds
• CPU (resourceCpuUsageLowerThreshold, resourceCpuUsageUpperThreshold)
• Memory (resourceMemoryUsageLowerThreshold, resourceMemoryUsageUpperThreshold)
• Network (resourceNetworkBandwidthUsageLowerThreshold, resourceNetworkBandwidthUsageUpperThreshold)
• Comparisons of usage metrics versus thresholds results in classifications per metric, which are
combined into a composite classification for the Resource:
• Overloaded (ANY metric classification = overloaded)
• Medium loaded (not Overloaded or Underloaded)
• Underloaded (ALL metric classifications = underloaded)
• These load classifications are used in:
• Submit job - overload protection (resourceLoadProtectionEnabled=true)
• Restart PE - select resource to start PE onto
• UpdateOperators - select resource for new PEs
• Restart PE recommendations - analyze which PEs are best to restart
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CPU Mem NW
Util %
upper
lower
**
*
Note: lower = 100, disables metric consideration (default)
0
100

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Thank You