Pivotal Cloud Foundry view


TheBMC Helix Continuous Optimization - Pivotal Cloud Foundry view enables you to manage the capacity and efficiency of containerized environment and applications

You can use the Pivotal Cloud Foundry view to complete tasks such as:

  • Understand resource bottlenecks and aggregate residual capacity of Pivotal Cloud foundry Diego cells and other virtual machines
  • Detect current or imminent resource saturation conditions and days before the resource is saturated for every major Pivotal Cloud Foundry resource
  • Assess the level of infrastructure efficiency, by comparing allocated vs actually resources, and identify most wasteful virtual machine or applications
  • Identify application in resource usage patterns and detect resource shortage conditions


Requirements

Supported versions of

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Certified data sources

Data Visibility

Conventions

View Structure

Thresholds, Status & Bottleneck

Materializer Task

There are the Page Overviews:


Requirements

Certified data sources

The certified data sources for the views are the following:

  • Pivotal CF Connector

You must configure and run one of these ETL modules to have data visible in the view

Data Visibility

Conventions

The Pivotal Cloud Foundry view provides summarized, high-level capacity KPIs designed for capacity management.The following common conventions around naming and metrics aggregation are valid for all data presented in the view:

  • Standard table column names: Metric name [unit of measurement] (ex. "Memory [GB]")
  • Unit of measurement is omitted when implicitly evident
  • The metric value is the aggregation of the last 1, 7, and 30 days
  • The metric value is computed as follows: for each day, the daily peak is considered (at daily resolution). Then, the mean value of the daily peak over the last 30 days is shown.
  • For "days to saturation", if the value is greater than 90 days, the view will show "No Saturation"

This is only valid for summary metrics presented in tables and overall page. The charts presented in the details pages follow regular over time metrics semantics, whose time frame and time resolution available as filters in the top of the page.

View Structure

The Pivotal Cloud Foundry view is composed of the following first-level pages:

  • Overview: it presents a summary of Pivotal Cloud Foundry's Applications and Foundation (Deployment) information, including risk score, efficiency score and usage score
  • PCF Domain: it shows capacity metrics for Pivotal Cloud Foundry Domains, which are configured when setup Pivotal CF service ETL, aggregated from diego_cells
  • PCF Foundation: it shows capacity metrics for Pivotal Cloud Foundry Foundations (deployments), aggregated from diego_cells
  • Diego Nodes: it shows capacity metrics for Pivotal Cloud Foundry Diego Nodes (diego_cell, diego_database, diego_brain, tcp_router and router)
  • PCF Services: it shows capacity metrics for Pivotal Cloud Foundry Services (Other component VMs except Diego Nodes)
  • PCF Applications: it shows capacity metrics for Pivotal Cloud Foundry applications (both system default applications and user created) 


From all the overview page, you can drill-down to an entity detail page, which presents the most relevant performance metrics as time charts and tables for the most important configuration properties.

Thresholds, Staus and Bottleneck

The table below reports the thresholds used in the view

EntitiesResourcesGood ThresholdsWarn Thresholds
PCF DomainsUsage Score70%90%

Efficiency Score


Risk Score70%90%

Days to Saturation> 30 days< 30 days
PCF FoundationsUsage Score70%90%

Efficiency Score


Risk Score70%90%

Days to Saturation> 30 days< 30 days
PCF ServicesUsage Score70%90%

Efficiency Score


Risk Score70%90%

Days to Saturation> 30 days< 30 days
Diego NodesUsage Score70%90%

Efficiency Score


Risk Score70%90%

Days to Saturation> 30 days< 30 days
PCF ApplicationsUsage Score70%90%

Efficiency Score


Risk Score70%90%

Days to Saturation> 30 days< 30 days

The following shows how resources are considered for days to Saturation for each entities:

Bottleneck is also determined by identify which is the least days to saturation for each entities:

EntityResources entitiesDays to Saturation MarkEfficiency Mark
PCF DomainCPU_UTIL95%75%

MEM_UTIL95%75%

DISK_USED_SPACE_PCT95%75%

Container Number95%75%
PCF Foundation

CPU_UTIL

95%75%

MEM_UTIL95%75%

DISK_USED_SPACE_PCT95%75%

DISK_EPHEMERAL_USED_PCT95%75%
PCF Services

CPU_UTIL

95%75%

MEM_UTIL95%75%

DISK_USED_SPACE_PCT95%75%

DISK_EPHEMERAL_USED_PCT95%75%
Diego Nodes

CPU_UTIL

95%75%

MEM_UTIL95%75%

DISK_USED_SPACE_PCT95%75%

DISK_EPHEMERAL_USED_PCT95%75%
PCF ApplicationsCPU_UTIL95%75%

MEM_UTIL95%75%

Disk_Used_Space_Pct95%75%


The following shows how each entities' Efficiency score, Usage score and Risk score is calculated:

EntityUsage ScoreEfficiency ScoreRisk Score
PCF Domaincpu_util*0.4 +mem_util*0.4+disk_used_space_pct*0.2cpu_util_efficiency*0.3 +mem_util_efficiency*0.3+disk_used_space_pct_efficiency*0.4Days to saturation for each entities compare to 30 days
PCF Foundationcpu_util*0.4 +mem_util*0.4+biggest(disk_used_space_pct, disk_ephemeral_used_pct)*0.2cpu_util_efficiency*0.3 +mem_util_efficiency*0.3+biggest(disk_used_space_pct_efficiency, disk_ephemeral_used_pct_efficiency)*0.4Days to saturation for each entities compare to 30 days
PCF Servicescpu_util*0.4 +mem_util*0.4+biggest(disk_used_space_pct, disk_ephemeral_used_pct)*0.2cpu_util_efficiency*0.3 +mem_util_efficiency*0.3+biggest(disk_used_space_pct_efficiency, disk_ephemeral_used_pct_efficiency)*0.4Days to saturation for each entities compare to 30 days
Diego Nodescpu_util*0.4 +mem_util*0.4+biggest(disk_used_space_pct, disk_ephemeral_used_pct)*0.2cpu_util_efficiency*0.3 +mem_util_efficiency*0.3+biggest(disk_used_space_pct_efficiency, disk_ephemeral_used_pct_efficiency)*0.4Days to saturation for each entities compare to 30 days
PCF Applicationcpu_util*0.4 +mem_util*0.4+disk_used_space_pct*0.2cpu_util_efficiency*0.3 +mem_util_efficiency*0.3+disk_used_space_pct_efficiency*0.4Days to saturation for each entities compare to 30 days

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