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Infrastructure Department Performance Indicators

Executive Summary

KPI Health Reason(s)
Infrastructure Hiring Actual vs Plan Okay
  • Engineering is on plan. But we are lending some of our recruiters to sales for this quarter. And we just put in place a new "one star minimum" rule that might decrease offer volume.
  • Health: Monitor health closely
  • Infrastructure Average Location Factor Okay
  • We are close to our target of 0.58 overall, but trending upward.
  • GitLab.com Availability Attention
  • Today the apdex and error ratio thresholds that go into availability may change based on amount of alerts they create
  • None of the data used for these metrics is in the data warehouse yet, therefore we cannot embed Periscope charts in the handbook
  • Infrastructure Hosting Cost per GitLab.com Monthly Active Users Okay
  • there is additional work needed to make it transparent what is driving this metric from a granular perspective
  • GitLab.com Performance Attention
  • We are experiencing occasionally slowness of both the frontend and git operations.
  • Infrastructure Hosting Cost vs Plan Okay
  • There was no locked plan for hosting services, so we are using the latest forecast until next plan lock
  • Key Performance Indicators

    Infrastructure Hiring Actual vs Plan

    Are we able to hire high quality workers to build our product vision in a timely manner? Hiring information comes from BambooHR where employees are in the division `Engineering`.

    Target: 39 by Dec 31, 2019

    URL(s)

    Health: Okay

    Maturity: Level 2 of 3

    Infrastructure Average Location Factor

    We remain efficient financially if we are hiring globally, working asynchronously, and hiring great people in low-cost regions where we pay market rates. We track an average location factor by function and department so managers can make tradeoffs and hire in an expensive region when they really need specific talent unavailable elsewhere, and offset it with great people who happen to be in low cost areas.

    Target: 0.58

    URL(s)

    Chart (Periscope↗)

    Health: Okay

    Maturity: Level 3 of 3

    GitLab.com Availability

    Percentage of time during which GitLab.com is fully operational and providing service to users within SLO parameters.

    Target: 99.95%

    URL(s)

    Health: Attention

    Maturity: Level 2 of 3

    Infrastructure Hosting Cost per GitLab.com Monthly Active Users

    This metric reflects an estimate of the dollar cost necessary to support one user in GitLab.com. It is an important metric because it allows us to estimate infrastructure costs as our user base grows. Infrastructure Hosting Cost comes from Netsuite; it is a sum of actual amounts with the unique account name '5026 - Hosting Services COGS' or '6026 - Hosting Services'. This cost is divided by MAU

    Target: 1.5

    URL(s)

    Health: Okay

    Maturity: Level 2 of 3

    GitLab.com Performance

    This metric needs to reflect the performance of GitLab as experienced by users. It should capture both frontend and backend performance. Even though the Infrastructure will be responsible for this metric they will need other departments such as Development, Quality, PM, and UX to positively affect change.

    URL(s)

    Health: Attention

    Maturity: Level 1 of 3

    Infrastructure Hosting Cost vs Plan

    Tracks our actual infrastructure hosting costs against our planned infrastructure hosting costs for GitLab.com. We need this metric to manage our financial position.

    URL(s)

    Health: Okay

    Maturity: Level 1 of 3

    Regular Performance Indicators

    Apdex and Error SLO per Service

    Each service at GitLab has two general metrics SLOS. "Apdex Score" is simply put, this is a measure of the percentage of requests to that service that complete within a satisfactory amount of time. The thresholds are defined per service, so for some services it will be in microseconds for others it could be seconds. "Error Ratio" is the percentage of requests to a service which end in error. For each service in the system we define an acceptable threshold for these values. For apdex we want the actual score to be above the threshold, for error ratio, we want it to be below the threshold. We don’t expect the apdex to be a perfect 100%, and we don’t expect the error rate to be a perfect 0%, but we would like these values to be within their predefined thresholds 100% of the time. The actual amount of time that they adhere to their SLO thresholds is far below this currently

    URL(s)

    Health: Unknown

    Maturity: Level 1 of 3

    Mean Time To Detection (MTTD)

    Measures the elapsed time it takes us to detect the onset of an anomalous condition and its actual detection, and serves as an indicator of our ability to monitor the environment and minimize incident resolution.

    URL(s)

    Health: Unknown

    Maturity: Level 1 of 3

    Mean Time To Resolution (MTTR)

    Measures the elapsed time in hours it takes us to recover when an incident occurs, and serves as an indicator of our ability to execute said recoveries. (Only includes S1 & S2 incidents)

    Target: 1

    URL(s)

    Chart (Periscope↗)

    Health: Attention

    Maturity: Level 3 of 3

    Mean Time Between Failures (MTBF)

    Measures the mean amount of time in days elapsed between incidents that affect GitLab.com’s availability. (Only includes S1 & S2 incidents)

    Target: 7

    URL(s)

    Chart (Periscope↗)

    Health: Attention

    Maturity: Level 3 of 3

    Mean Time To Production (MTTP)

    Measures the elapsed time it takes us deploy changes in production, and serves as an indicator of our speed capabilities to deploy changes into production.

    Target: 60m

    URL(s)

    Health: Unknown

    Maturity: Level 2 of 3

    Deploys to Production per Month

    Tracks the total number of deployments to production over the course of the month due to regressions and/or outages, which allows us to measure our deployment speed to production.

    Target: 30

    URL(s)

    Health: Attention

    Maturity: Level 2 of 3

    Number of abandoned deployments per month

    Tracks number of failed deployments to production over the course of the month due to regressions and/or outages, which allows us to measure our production deployment readiness.

    Target: 0

    Health: Problem

    Maturity: Level 2 of 3

    Disaster Recovery (DR) Time-to-Recover

    Tracks time to recover full operational status in case of a catastrophic incident in our primary production environment.

    Target: 60m

    Health: Unknown

    Maturity: Level 2 of 3

    Other PI Pages

    Legends

    Maturity

    Level Meaning
    Level 3 of 3 Has a description, target, and periscope data.
    Level 2 of 3 Missing one of: description, target, or periscope data.
    Level 1 of 3 Missing two of: description, target, or periscope data.
    Level 0 of 3 Missing a description, a target, and periscope data.

    Health

    Level Meaning
    Okay The KPI is at an acceptable level compared to the threshold
    Attention This is a blip, or we’re going to watch it, or we just need to enact a proven intervention
    Problem We'll prioritize our efforts here
    Unknown Unknown

    How to work with pages like this

    Data

    The heart of pages like this is a data file called /data/performance_indicators.yml which is in YAML format. Almost everything you need to do will involve edits to this file. Here are some tips:

    Pages

    Pages like /handbook/engineering/performance-indicators/ are rendered by and ERB template.

    These ERB templates call the helper function performance_indicators() that is defined in /helpers/custom_helpers.rb. This helper function calls in several partial templates to do it's work.

    This function takes a required argument named org in string format that limits the scope of the page to a portion of the data file. Possible valid values for this org argument are listed in the org property of each element in the array in /data/performance_indicators.yml.