| KPI | Health | Reason(s) |
| Security Hiring Actual vs Plan | Okay |
|
| Security Average Location Factor | Attention |
|
| MTTM (Mean-Time-To-Mitigation) for S1-S2-S3 security vulnerabilities | Okay |
|
| Blocked Abuse Activity | Attention |
|
| HackerOne budget vs actual (with forecast of 'unknowns') | Attention |
|
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` and department is `security`. This KPI is tracked and reported on a monthly basis but year to date (headcount v plan) is also measured.
URL(s)
Health: Okay
Maturity: Level 1 of 3
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.
URL(s)
Health: Attention
Maturity: Level 1 of 3
The MTTM metric is an indicator of our efficiency in mitigating security vulnerabilities, whether they are reported through HackerOne bug bounty program (or other external means, such as security@gitlab.com emails) or internally-reported. The average days to close issues in the GitLab CE project (project_id = '13083') that are have the label `security` and S1, S2, or S3; this excludes issues with variation of the security label (e.g. `security review`) and S4 issues. Issues that are not yet closed are excluded from this analysis. This means historical data can change as older issues are closed and are introduced to the analysis. The average age in days threshold is set at the daily level.
URL(s)
Health: Okay
Maturity: Level 1 of 3
This metric is focused around the efficacy of our Abuse Handling and Abuse Operations. The Abuse Team is responsible for tracking, automating, and reporting on blocked abusive accounts on GitLab.com, and tracking reduction in cloud spend where the activities are due to abuse.
URL(s)
Health: Attention
Maturity: Level 1 of 3
We currently run a public bug bounty program through HackerOne, and this program has been largely successful - we get a lot of hacker engagement, and since the program went public, we have been able to resolve nearly 100 reported security vulnerabilities. The bounty spend is however, a budgeting forecast concern because of the unpredictability factor from month to month.
Health: Attention
Maturity: Level 1 of 3
The true mark of a successful public bug bounty program is partially tied to hacker outreach and engagement. We’ve already implemented quite a bit of security automation to engage hackers. For example, when findings are submitted by hackers, an automated dynamic message is generated by our automation scripts and they receive a response with expected ETA on a reply (this ETA is dependent on how many findings are in our ‘to be triaged’ bucket at that time, so the ETA changes). This ensures the hacker knows 1) we received the report, 2) a human will be reading the report within a certain ETA, and 3) a human will be replying within an ETA. Our program went public in mid-December 2018, and we are now focusing on outreach and incentive programs to retain the top hackers to our program - about 90%+ of the most impactful reports are currently submitted by our Top 5-10 hackers, so it is imperative we retain those individuals.
Health: Attention
Maturity: Level 1 of 3
Although the Security Department is always working towards minimizing friction to day-to-day company operations, it is never possible to be 100% frictionless when adding an additional step into an existing process. As cumbersome as this may feel (despite our best efforts), this is usually a necessary step to maturing our security posture and meeting customer requirements (especially large enterprise customers). We plan to measure Security response times to new processes such as access request approval issues and security reviews for 3rd party vendor requests to highlight where bottlenecks are to the current process, and use a data-driven approach to iterate on better processes.
Health: Unknown
Maturity: Level 1 of 3
| 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. |
| 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 |
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:
: in strings as it's an important character in YAML and will confuse the data parsing process. Put the string in "quotes" if you really need to use a :urls: should be an array (indented lines starting with dashes) even if you only have one urlmaturity.level and health.level take a number between 0 and 3 (inclusive)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.
