docs/Metrics/DeploymentFrequency.md - devlake-website - Git at Google

 ---
 title: "DORA - Deployment Frequency"
 description: >
   DORA - Deployment Frequency
 sidebar_position: 26
 ---

 ## What is this metric?

 How often an organization deploys code to production or release it to end users.

 ## Why is it important?

 Deployment frequency reflects the efficiency of a team's deployment. A team that deploys more frequently can deliver the product faster and users' feature requirements can be met faster.

 ## Which dashboard(s) does it exist in

 DORA dashboard. See [live demo](https://grafana-lake.demo.devlake.io/grafana/d/qNo8_0M4z/dora?orgId=1).

 ## How is it calculated?

 Deployment frequency is calculated based on the number of deployment days, not the number of deployments, e.g., daily, weekly, monthly, yearly.

 When there are multiple deployments triggered by one pipeline, tools like GitLab and BitBucket will generate more than one deployment. In these cases, DevLake will consider these deployments as ONE deployment and use the last deployment's finished date as the deployment finished date.

 Below are the benchmarks for different development teams from Google's report. DevLake uses the same benchmarks.

 | Groups            | Benchmarks                                     | DevLake Benchmarks                             |
 | ----------------- | ---------------------------------------------- | ---------------------------------------------- |
 | Elite performers  | On-demand (multiple deploys per day)           | On-demand                                      |
 | High performers   | Between once per week and once per month       | Between once per week and once per month       |
 | Medium performers | Between once per month and once every 6 months | Between once per month and once every 6 months |
 | Low performers    | Fewer than once per six months                 | Fewer than once per six months                 |

 <p><i>Source: 2021 Accelerate State of DevOps, Google</i></p>

 <b>Data Sources Required</b>

 This metric relies on deployments collected in multiple ways:

 - Open APIs of Jenkins, GitLab, GitHub, etc.
 - Webhook for general CI tools.
 - Releases and PR/MRs from GitHub, GitLab APIs, etc.

 <b>Transformation Rules Required</b>

 This metric relies on the deployment configuration in Jenkins, GitLab or GitHub transformation rules to let DevLake know what CI builds/jobs can be regarded as deployments.

 <b>SQL Queries</b>

 If you want to measure the monthly trend of deployment count as the picture shown below, run the following SQL in Grafana.

 ![](/img/Metrics/deployment-frequency-monthly.jpeg)

 ```
 -- Metric 1: Number of deployments per month
 with _deployments as(
 -- When deploying multiple commits in one pipeline, GitLab and BitBucket may generate more than one deployment. However, DevLake consider these deployments as ONE production deployment and use the last one's finished_date as the finished date.
 	SELECT
 		date_format(deployment_finished_date,'%y/%m') as month,
 		count(cicd_deployment_id) as deployment_count
 	FROM (
 		SELECT
 			cdc.cicd_deployment_id,
 			max(cdc.finished_date) as deployment_finished_date
 		FROM cicd_deployment_commits cdc
 		JOIN project_mapping pm on cdc.cicd_scope_id = pm.row_id and pm.`table` = 'cicd_scopes'
 		WHERE
 			pm.project_name in ($project)
 			and cdc.result = 'SUCCESS'
 			and cdc.environment = 'PRODUCTION'
 		GROUP BY 1
 		HAVING $__timeFilter(max(cdc.finished_date))
 	) _production_deployments
 	GROUP BY 1
 )

 SELECT
 	cm.month,
 	case when d.deployment_count is null then 0 else d.deployment_count end as deployment_count
 FROM
 	calendar_months cm
 	LEFT JOIN _deployments d on cm.month = d.month
 	WHERE $__timeFilter(cm.month_timestamp)
 ```

 If you want to measure in which category your team falls as in the picture shown below, run the following SQL in Grafana.

 ![](/img/Metrics/deployment-frequency-text.jpeg)

 ```
 with last_few_calendar_months as(
 -- construct the last few calendar months within the selected time period in the top-right corner
 	SELECT CAST((SYSDATE()-INTERVAL (H+T+U) DAY) AS date) day
 	FROM ( SELECT 0 H
 			UNION ALL SELECT 100 UNION ALL SELECT 200 UNION ALL SELECT 300
 		) H CROSS JOIN ( SELECT 0 T
 			UNION ALL SELECT  10 UNION ALL SELECT  20 UNION ALL SELECT  30
 			UNION ALL SELECT  40 UNION ALL SELECT  50 UNION ALL SELECT  60
 			UNION ALL SELECT  70 UNION ALL SELECT  80 UNION ALL SELECT  90
 		) T CROSS JOIN ( SELECT 0 U
 			UNION ALL SELECT   1 UNION ALL SELECT   2 UNION ALL SELECT   3
 			UNION ALL SELECT   4 UNION ALL SELECT   5 UNION ALL SELECT   6
 			UNION ALL SELECT   7 UNION ALL SELECT   8 UNION ALL SELECT   9
 		) U
 	WHERE
 		(SYSDATE()-INTERVAL (H+T+U) DAY) > $__timeFrom()
 ),

 _production_deployment_days as(
 -- When deploying multiple commits in one pipeline, GitLab and BitBucket may generate more than one deployment. However, DevLake consider these deployments as ONE production deployment and use the last one's finished_date as the finished date.
 	SELECT
 		cdc.cicd_deployment_id as deployment_id,
 		max(DATE(cdc.finished_date)) as day
 	FROM cicd_deployment_commits cdc
 	JOIN project_mapping pm on cdc.cicd_scope_id = pm.row_id
 	WHERE
 		pm.project_name in ($project)
 		and cdc.result = 'SUCCESS'
 		and cdc.environment = 'PRODUCTION'
 	GROUP BY 1
 ),

 _days_weeks_deploy as(
 -- calculate the number of deployment days every week
 	SELECT
 			date(DATE_ADD(last_few_calendar_months.day, INTERVAL -WEEKDAY(last_few_calendar_months.day) DAY)) as week,
 			MAX(if(_production_deployment_days.day is not null, 1, 0)) as weeks_deployed,
 			COUNT(distinct _production_deployment_days.day) as days_deployed
 	FROM
 		last_few_calendar_months
 		LEFT JOIN _production_deployment_days ON _production_deployment_days.day = last_few_calendar_months.day
 	GROUP BY week
 	),

 _monthly_deploy as(
 -- calculate the number of deployment days every month
 	SELECT
 			date(DATE_ADD(last_few_calendar_months.day, INTERVAL -DAY(last_few_calendar_months.day)+1 DAY)) as month,
 			MAX(if(_production_deployment_days.day is not null, 1, 0)) as months_deployed
 	FROM
 		last_few_calendar_months
 		LEFT JOIN _production_deployment_days ON _production_deployment_days.day = last_few_calendar_months.day
 	GROUP BY month
 	),

 _median_number_of_deployment_days_per_week_ranks as(
 	SELECT *, percent_rank() over(order by days_deployed) as ranks
 	FROM _days_weeks_deploy
 ),

 _median_number_of_deployment_days_per_week as(
 	SELECT max(days_deployed) as median_number_of_deployment_days_per_week
 	FROM _median_number_of_deployment_days_per_week_ranks
 	WHERE ranks <= 0.5
 ),

 _median_number_of_deployment_days_per_month_ranks as(
 	SELECT *, percent_rank() over(order by months_deployed) as ranks
 	FROM _monthly_deploy
 ),

 _median_number_of_deployment_days_per_month as(
 	SELECT max(months_deployed) as median_number_of_deployment_days_per_month
 	FROM _median_number_of_deployment_days_per_month_ranks
 	WHERE ranks <= 0.5
 )

 SELECT
 	CASE
 		WHEN median_number_of_deployment_days_per_week >= 3 THEN 'On-demand'
 		WHEN median_number_of_deployment_days_per_week >= 1 THEN 'Between once per week and once per month'
 		WHEN median_number_of_deployment_days_per_month >= 1 THEN 'Between once per month and once every 6 months'
 		ELSE 'Fewer than once per six months' END AS 'Deployment Frequency'
 FROM _median_number_of_deployment_days_per_week, _median_number_of_deployment_days_per_month
 ```

 ## How to improve?

 - Trunk development. Work in small batches and often merge their work into shared trunks.
 - Integrate CI/CD tools for automated deployment
 - Improve automated test coverage
	---
	title: "DORA - Deployment Frequency"
	description: >
	DORA - Deployment Frequency
	sidebar_position: 26
	---

	## What is this metric?

	How often an organization deploys code to production or release it to end users.

	## Why is it important?

	Deployment frequency reflects the efficiency of a team's deployment. A team that deploys more frequently can deliver the product faster and users' feature requirements can be met faster.

	## Which dashboard(s) does it exist in

	DORA dashboard. See [live demo](https://grafana-lake.demo.devlake.io/grafana/d/qNo8_0M4z/dora?orgId=1).

	## How is it calculated?

	Deployment frequency is calculated based on the number of deployment days, not the number of deployments, e.g., daily, weekly, monthly, yearly.

	When there are multiple deployments triggered by one pipeline, tools like GitLab and BitBucket will generate more than one deployment. In these cases, DevLake will consider these deployments as ONE deployment and use the last deployment's finished date as the deployment finished date.

	Below are the benchmarks for different development teams from Google's report. DevLake uses the same benchmarks.

	\| Groups \| Benchmarks \| DevLake Benchmarks \|
	\| ----------------- \| ---------------------------------------------- \| ---------------------------------------------- \|
	\| Elite performers \| On-demand (multiple deploys per day) \| On-demand \|
	\| High performers \| Between once per week and once per month \| Between once per week and once per month \|
	\| Medium performers \| Between once per month and once every 6 months \| Between once per month and once every 6 months \|
	\| Low performers \| Fewer than once per six months \| Fewer than once per six months \|

	<p><i>Source: 2021 Accelerate State of DevOps, Google</i></p>

	<b>Data Sources Required</b>

	This metric relies on deployments collected in multiple ways:

	- Open APIs of Jenkins, GitLab, GitHub, etc.
	- Webhook for general CI tools.
	- Releases and PR/MRs from GitHub, GitLab APIs, etc.

	<b>Transformation Rules Required</b>

	This metric relies on the deployment configuration in Jenkins, GitLab or GitHub transformation rules to let DevLake know what CI builds/jobs can be regarded as deployments.

	<b>SQL Queries</b>

	If you want to measure the monthly trend of deployment count as the picture shown below, run the following SQL in Grafana.

	![](/img/Metrics/deployment-frequency-monthly.jpeg)

	```
	-- Metric 1: Number of deployments per month
	with _deployments as(
	-- When deploying multiple commits in one pipeline, GitLab and BitBucket may generate more than one deployment. However, DevLake consider these deployments as ONE production deployment and use the last one's finished_date as the finished date.
	SELECT
	date_format(deployment_finished_date,'%y/%m') as month,
	count(cicd_deployment_id) as deployment_count
	FROM (
	SELECT
	cdc.cicd_deployment_id,
	max(cdc.finished_date) as deployment_finished_date
	FROM cicd_deployment_commits cdc
	JOIN project_mapping pm on cdc.cicd_scope_id = pm.row_id and pm.`table` = 'cicd_scopes'
	WHERE
	pm.project_name in ($project)
	and cdc.result = 'SUCCESS'
	and cdc.environment = 'PRODUCTION'
	GROUP BY 1
	HAVING $__timeFilter(max(cdc.finished_date))
	) _production_deployments
	GROUP BY 1
	)

	SELECT
	cm.month,
	case when d.deployment_count is null then 0 else d.deployment_count end as deployment_count
	FROM
	calendar_months cm
	LEFT JOIN _deployments d on cm.month = d.month
	WHERE $__timeFilter(cm.month_timestamp)
	```

	If you want to measure in which category your team falls as in the picture shown below, run the following SQL in Grafana.

	![](/img/Metrics/deployment-frequency-text.jpeg)

	```
	with last_few_calendar_months as(
	-- construct the last few calendar months within the selected time period in the top-right corner
	SELECT CAST((SYSDATE()-INTERVAL (H+T+U) DAY) AS date) day
	FROM ( SELECT 0 H
	UNION ALL SELECT 100 UNION ALL SELECT 200 UNION ALL SELECT 300
	) H CROSS JOIN ( SELECT 0 T
	UNION ALL SELECT 10 UNION ALL SELECT 20 UNION ALL SELECT 30
	UNION ALL SELECT 40 UNION ALL SELECT 50 UNION ALL SELECT 60
	UNION ALL SELECT 70 UNION ALL SELECT 80 UNION ALL SELECT 90
	) T CROSS JOIN ( SELECT 0 U
	UNION ALL SELECT 1 UNION ALL SELECT 2 UNION ALL SELECT 3
	UNION ALL SELECT 4 UNION ALL SELECT 5 UNION ALL SELECT 6
	UNION ALL SELECT 7 UNION ALL SELECT 8 UNION ALL SELECT 9
	) U
	WHERE
	(SYSDATE()-INTERVAL (H+T+U) DAY) > $__timeFrom()
	),

	_production_deployment_days as(
	-- When deploying multiple commits in one pipeline, GitLab and BitBucket may generate more than one deployment. However, DevLake consider these deployments as ONE production deployment and use the last one's finished_date as the finished date.
	SELECT
	cdc.cicd_deployment_id as deployment_id,
	max(DATE(cdc.finished_date)) as day
	FROM cicd_deployment_commits cdc
	JOIN project_mapping pm on cdc.cicd_scope_id = pm.row_id
	WHERE
	pm.project_name in ($project)
	and cdc.result = 'SUCCESS'
	and cdc.environment = 'PRODUCTION'
	GROUP BY 1
	),

	_days_weeks_deploy as(
	-- calculate the number of deployment days every week
	SELECT
	date(DATE_ADD(last_few_calendar_months.day, INTERVAL -WEEKDAY(last_few_calendar_months.day) DAY)) as week,
	MAX(if(_production_deployment_days.day is not null, 1, 0)) as weeks_deployed,
	COUNT(distinct _production_deployment_days.day) as days_deployed
	FROM
	last_few_calendar_months
	LEFT JOIN _production_deployment_days ON _production_deployment_days.day = last_few_calendar_months.day
	GROUP BY week
	),

	_monthly_deploy as(
	-- calculate the number of deployment days every month
	SELECT
	date(DATE_ADD(last_few_calendar_months.day, INTERVAL -DAY(last_few_calendar_months.day)+1 DAY)) as month,
	MAX(if(_production_deployment_days.day is not null, 1, 0)) as months_deployed
	FROM
	last_few_calendar_months
	LEFT JOIN _production_deployment_days ON _production_deployment_days.day = last_few_calendar_months.day
	GROUP BY month
	),

	_median_number_of_deployment_days_per_week_ranks as(
	SELECT *, percent_rank() over(order by days_deployed) as ranks
	FROM _days_weeks_deploy
	),

	_median_number_of_deployment_days_per_week as(
	SELECT max(days_deployed) as median_number_of_deployment_days_per_week
	FROM _median_number_of_deployment_days_per_week_ranks
	WHERE ranks <= 0.5
	),

	_median_number_of_deployment_days_per_month_ranks as(
	SELECT *, percent_rank() over(order by months_deployed) as ranks
	FROM _monthly_deploy
	),

	_median_number_of_deployment_days_per_month as(
	SELECT max(months_deployed) as median_number_of_deployment_days_per_month
	FROM _median_number_of_deployment_days_per_month_ranks
	WHERE ranks <= 0.5
	)

	SELECT
	CASE
	WHEN median_number_of_deployment_days_per_week >= 3 THEN 'On-demand'
	WHEN median_number_of_deployment_days_per_week >= 1 THEN 'Between once per week and once per month'
	WHEN median_number_of_deployment_days_per_month >= 1 THEN 'Between once per month and once every 6 months'
	ELSE 'Fewer than once per six months' END AS 'Deployment Frequency'
	FROM _median_number_of_deployment_days_per_week, _median_number_of_deployment_days_per_month
	```

	## How to improve?

	- Trunk development. Work in small batches and often merge their work into shared trunks.
	- Integrate CI/CD tools for automated deployment
	- Improve automated test coverage