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| "rawSql": "with _deployment_commit_rank as(\n SELECT\n \tpm.project_name,\n \tIF(cdc._raw_data_table != '', cdc._raw_data_table, cdc.cicd_scope_id) as _raw_data_table,\n \tcdc.id,\n \tcdc.cicd_deployment_id,\n \tcdc.cicd_scope_id,\n \tresult,\n \tenvironment,\n finished_date,\n row_number() over(partition by cdc.cicd_deployment_id order by finished_date desc) as _deployment_commit_rank\n FROM cicd_deployment_commits cdc\n left join project_mapping pm on cdc.cicd_scope_id = pm.row_id and pm.`table` = 'cicd_scopes'\n WHERE\n pm.project_name in ($project)\n \tand result = 'SUCCESS'\n \tand environment = 'PRODUCTION'\n)\n\nSELECT \n project_name, \n cicd_deployment_id as deployment_id,\n -- a deployment may have multiple deployment_commits\n id as deployment_commit_id, \n result,\n environment,\n finished_date\nFROM _deployment_commit_rank\nWHERE \n _deployment_commit_rank = 1\n and $__timeFilter(finished_date)", |
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| "title": "1.1 Daily deployments in the selected project(s)", |
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| "rawSql": "-- Metric 1: Deployment Frequency\nwith last_few_calendar_months as(\n-- construct the last few calendar months within the selected time period in the top-right corner\n\tSELECT CAST(($__timeTo()-INTERVAL (H+T+U) DAY) AS date) day\n\tFROM ( SELECT 0 H\n\t\t\tUNION ALL SELECT 100 UNION ALL SELECT 200 UNION ALL SELECT 300\n\t\t) H CROSS JOIN ( SELECT 0 T\n\t\t\tUNION ALL SELECT 10 UNION ALL SELECT 20 UNION ALL SELECT 30\n\t\t\tUNION ALL SELECT 40 UNION ALL SELECT 50 UNION ALL SELECT 60\n\t\t\tUNION ALL SELECT 70 UNION ALL SELECT 80 UNION ALL SELECT 90\n\t\t) T CROSS JOIN ( SELECT 0 U\n\t\t\tUNION ALL SELECT 1 UNION ALL SELECT 2 UNION ALL SELECT 3\n\t\t\tUNION ALL SELECT 4 UNION ALL SELECT 5 UNION ALL SELECT 6\n\t\t\tUNION ALL SELECT 7 UNION ALL SELECT 8 UNION ALL SELECT 9\n\t\t) U\n\tWHERE\n\t\t($__timeTo()-INTERVAL (H+T+U) DAY) > FROM_UNIXTIME(1692502887)\n),\n\n_production_deployment_days as(\n-- 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.\n\tSELECT\n\t\tcdc.cicd_deployment_id as deployment_id,\n\t\tmax(DATE(cdc.finished_date)) as day\n\tFROM cicd_deployment_commits cdc\n\tJOIN project_mapping pm on cdc.cicd_scope_id = pm.row_id and pm.`table` = 'cicd_scopes'\n\tWHERE\n\t\tpm.project_name in ('p1')\n\t\tand cdc.result = 'SUCCESS'\n\t\tand cdc.environment = 'PRODUCTION'\n\tGROUP BY 1\n),\n\n_days_weekly_deploy as(\n-- calculate the number of deployment days every week\n\tSELECT\n\t\t\tdate(DATE_ADD(last_few_calendar_months.day, INTERVAL -WEEKDAY(last_few_calendar_months.day) DAY)) as week,\n\t\t\tMAX(if(_production_deployment_days.day is not null, 1, null)) as weeks_deployed,\n\t\t\tCOUNT(distinct _production_deployment_days.day) as days_deployed\n\tFROM \n\t\tlast_few_calendar_months\n\t\tLEFT JOIN _production_deployment_days ON _production_deployment_days.day = last_few_calendar_months.day\n\tGROUP BY week\n\t),\n\n_days_monthly_deploy as(\n-- calculate the number of deployment days every month\n\tSELECT\n\t\t\tdate(DATE_ADD(last_few_calendar_months.day, INTERVAL -DAY(last_few_calendar_months.day)+1 DAY)) as month,\n\t\t\tMAX(if(_production_deployment_days.day is not null, 1, null)) as months_deployed,\n\t\t COUNT(distinct _production_deployment_days.day) as days_deployed\n\tFROM \n\t\tlast_few_calendar_months\n\t\tLEFT JOIN _production_deployment_days ON _production_deployment_days.day = last_few_calendar_months.day\n\tGROUP BY month\n\t),\n\n_days_six_months_deploy AS (\n SELECT\n month,\n SUM(days_deployed) OVER (\n ORDER BY month\n ROWS BETWEEN 5 PRECEDING AND CURRENT ROW\n ) AS days_deployed_per_six_months,\n COUNT(months_deployed) OVER (\n ORDER BY month\n ROWS BETWEEN 5 PRECEDING AND CURRENT ROW\n ) AS months_deployed_count,\n ROW_NUMBER() OVER (\n PARTITION BY DATE_FORMAT(month, '%Y-%m') DIV 6\n ORDER BY month DESC\n ) AS rn\n FROM _days_monthly_deploy\n),\n\ncalendar_weeks as(\n select \n \tdistinct date(DATE_ADD(date(day), INTERVAL -WEEKDAY(date(day)) DAY)) as start_of_week\n FROM last_few_calendar_months\n ORDER BY 1 asc\n)\n\n\nSELECT \n concat(date_format(cw.start_of_week,'%m/%d'), ' - ', date_format(DATE_ADD(cw.start_of_week, INTERVAL +6 DAY),'%m/%d')) as week,\n days_deployed\nfrom calendar_weeks cw left join _days_weekly_deploy b on cw.start_of_week = b.week", |
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| "rawSql": "-- Metric 1: Deployment Frequency\nwith last_few_calendar_months as(\n-- construct the last few calendar months within the selected time period in the top-right corner\n\tSELECT CAST(($__timeTo()-INTERVAL (H+T+U) DAY) AS date) day\n\tFROM ( SELECT 0 H\n\t\t\tUNION ALL SELECT 100 UNION ALL SELECT 200 UNION ALL SELECT 300\n\t\t) H CROSS JOIN ( SELECT 0 T\n\t\t\tUNION ALL SELECT 10 UNION ALL SELECT 20 UNION ALL SELECT 30\n\t\t\tUNION ALL SELECT 40 UNION ALL SELECT 50 UNION ALL SELECT 60\n\t\t\tUNION ALL SELECT 70 UNION ALL SELECT 80 UNION ALL SELECT 90\n\t\t) T CROSS JOIN ( SELECT 0 U\n\t\t\tUNION ALL SELECT 1 UNION ALL SELECT 2 UNION ALL SELECT 3\n\t\t\tUNION ALL SELECT 4 UNION ALL SELECT 5 UNION ALL SELECT 6\n\t\t\tUNION ALL SELECT 7 UNION ALL SELECT 8 UNION ALL SELECT 9\n\t\t) U\n\tWHERE\n\t\t($__timeTo()-INTERVAL (H+T+U) DAY) > FROM_UNIXTIME(1692502887)\n),\n\n_production_deployment_days as(\n-- 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.\n\tSELECT\n\t\tcdc.cicd_deployment_id as deployment_id,\n\t\tmax(DATE(cdc.finished_date)) as day\n\tFROM cicd_deployment_commits cdc\n\tJOIN project_mapping pm on cdc.cicd_scope_id = pm.row_id and pm.`table` = 'cicd_scopes'\n\tWHERE\n\t\tpm.project_name in ('p1')\n\t\tand cdc.result = 'SUCCESS'\n\t\tand cdc.environment = 'PRODUCTION'\n\tGROUP BY 1\n),\n\n_days_weekly_deploy as(\n-- calculate the number of deployment days every week\n\tSELECT\n\t\t\tdate(DATE_ADD(last_few_calendar_months.day, INTERVAL -WEEKDAY(last_few_calendar_months.day) DAY)) as week,\n\t\t\tMAX(if(_production_deployment_days.day is not null, 1, null)) as weeks_deployed,\n\t\t\tCOUNT(distinct _production_deployment_days.day) as days_deployed\n\tFROM \n\t\tlast_few_calendar_months\n\t\tLEFT JOIN _production_deployment_days ON _production_deployment_days.day = last_few_calendar_months.day\n\tGROUP BY week\n\t),\n\n_days_monthly_deploy as(\n-- calculate the number of deployment days every month\n\tSELECT\n\t\t\tdate(DATE_ADD(last_few_calendar_months.day, INTERVAL -DAY(last_few_calendar_months.day)+1 DAY)) as month,\n\t\t\tMAX(if(_production_deployment_days.day is not null, 1, null)) as months_deployed,\n\t\t COUNT(distinct _production_deployment_days.day) as days_deployed\n\tFROM \n\t\tlast_few_calendar_months\n\t\tLEFT JOIN _production_deployment_days ON _production_deployment_days.day = last_few_calendar_months.day\n\tGROUP BY month\n\t),\n\n_days_six_months_deploy AS (\n SELECT\n month,\n SUM(days_deployed) OVER (\n ORDER BY month\n ROWS BETWEEN 5 PRECEDING AND CURRENT ROW\n ) AS days_deployed_per_six_months,\n COUNT(months_deployed) OVER (\n ORDER BY month\n ROWS BETWEEN 5 PRECEDING AND CURRENT ROW\n ) AS months_deployed_count,\n ROW_NUMBER() OVER (\n PARTITION BY DATE_FORMAT(month, '%Y-%m') DIV 6\n ORDER BY month DESC\n ) AS rn\n FROM _days_monthly_deploy\n)\n\n\n\nSELECT \n DATE_FORMAT(month, '%y/%m') as month, days_deployed\nFROM _days_monthly_deploy", |
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| "rawSql": "-- Metric 1: Deployment Frequency\nwith last_few_calendar_months as(\n-- construct the last few calendar months within the selected time period in the top-right corner\n\tSELECT CAST(($__timeTo()-INTERVAL (H+T+U) DAY) AS date) day\n\tFROM ( SELECT 0 H\n\t\t\tUNION ALL SELECT 100 UNION ALL SELECT 200 UNION ALL SELECT 300\n\t\t) H CROSS JOIN ( SELECT 0 T\n\t\t\tUNION ALL SELECT 10 UNION ALL SELECT 20 UNION ALL SELECT 30\n\t\t\tUNION ALL SELECT 40 UNION ALL SELECT 50 UNION ALL SELECT 60\n\t\t\tUNION ALL SELECT 70 UNION ALL SELECT 80 UNION ALL SELECT 90\n\t\t) T CROSS JOIN ( SELECT 0 U\n\t\t\tUNION ALL SELECT 1 UNION ALL SELECT 2 UNION ALL SELECT 3\n\t\t\tUNION ALL SELECT 4 UNION ALL SELECT 5 UNION ALL SELECT 6\n\t\t\tUNION ALL SELECT 7 UNION ALL SELECT 8 UNION ALL SELECT 9\n\t\t) U\n\tWHERE\n\t\t($__timeTo()-INTERVAL (H+T+U) DAY) > FROM_UNIXTIME(1692502887)\n),\n\n_production_deployment_days as(\n-- 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.\n\tSELECT\n\t\tcdc.cicd_deployment_id as deployment_id,\n\t\tmax(DATE(cdc.finished_date)) as day\n\tFROM cicd_deployment_commits cdc\n\tJOIN project_mapping pm on cdc.cicd_scope_id = pm.row_id and pm.`table` = 'cicd_scopes'\n\tWHERE\n\t\tpm.project_name in ('p1')\n\t\tand cdc.result = 'SUCCESS'\n\t\tand cdc.environment = 'PRODUCTION'\n\tGROUP BY 1\n),\n\n_days_weekly_deploy as(\n-- calculate the number of deployment days every week\n\tSELECT\n\t\t\tdate(DATE_ADD(last_few_calendar_months.day, INTERVAL -WEEKDAY(last_few_calendar_months.day) DAY)) as week,\n\t\t\tMAX(if(_production_deployment_days.day is not null, 1, null)) as weeks_deployed,\n\t\t\tCOUNT(distinct _production_deployment_days.day) as days_deployed\n\tFROM \n\t\tlast_few_calendar_months\n\t\tLEFT JOIN _production_deployment_days ON _production_deployment_days.day = last_few_calendar_months.day\n\tGROUP BY week\n\t),\n\n_days_monthly_deploy as(\n-- calculate the number of deployment days every month\n\tSELECT\n\t\t\tdate(DATE_ADD(last_few_calendar_months.day, INTERVAL -DAY(last_few_calendar_months.day)+1 DAY)) as month,\n\t\t\tMAX(if(_production_deployment_days.day is not null, 1, null)) as months_deployed,\n\t\t COUNT(distinct _production_deployment_days.day) as days_deployed\n\tFROM \n\t\tlast_few_calendar_months\n\t\tLEFT JOIN _production_deployment_days ON _production_deployment_days.day = last_few_calendar_months.day\n\tGROUP BY month\n\t),\n\n_days_six_months_deploy AS (\n SELECT\n month,\n SUM(days_deployed) OVER (\n ORDER BY month\n ROWS BETWEEN 5 PRECEDING AND CURRENT ROW\n ) AS days_deployed_per_six_months,\n COUNT(months_deployed) OVER (\n ORDER BY month\n ROWS BETWEEN 5 PRECEDING AND CURRENT ROW\n ) AS months_deployed_count,\n ROW_NUMBER() OVER (\n PARTITION BY DATE_FORMAT(month, '%Y-%m') DIV 6\n ORDER BY month DESC\n ) AS rn\n FROM _days_monthly_deploy\n)\n\n\n\nSELECT \n CONCAT(DATE_FORMAT(DATE_SUB(month, INTERVAL 5 MONTH), '%y/%m'), ' ~ ', DATE_FORMAT(month, '%y/%m')) AS month_range, days_deployed_per_six_months as days_deployed\nFROM _days_six_months_deploy\nORDER BY month", |
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| "rawSql": "-- Metric 1: Deployment Frequency\nwith last_few_calendar_months as(\n-- construct the last few calendar months within the selected time period in the top-right corner\n\tSELECT CAST(($__timeTo()-INTERVAL (H+T+U) DAY) AS date) day\n\tFROM ( SELECT 0 H\n\t\t\tUNION ALL SELECT 100 UNION ALL SELECT 200 UNION ALL SELECT 300\n\t\t) H CROSS JOIN ( SELECT 0 T\n\t\t\tUNION ALL SELECT 10 UNION ALL SELECT 20 UNION ALL SELECT 30\n\t\t\tUNION ALL SELECT 40 UNION ALL SELECT 50 UNION ALL SELECT 60\n\t\t\tUNION ALL SELECT 70 UNION ALL SELECT 80 UNION ALL SELECT 90\n\t\t) T CROSS JOIN ( SELECT 0 U\n\t\t\tUNION ALL SELECT 1 UNION ALL SELECT 2 UNION ALL SELECT 3\n\t\t\tUNION ALL SELECT 4 UNION ALL SELECT 5 UNION ALL SELECT 6\n\t\t\tUNION ALL SELECT 7 UNION ALL SELECT 8 UNION ALL SELECT 9\n\t\t) U\n\tWHERE\n\t\t($__timeTo()-INTERVAL (H+T+U) DAY) > $__timeFrom()\n),\n\n_production_deployment_days as(\n-- When deploying multiple commits in one pipeline, GitLab and BitBucket may generate more than one deployment. However, DevLake consider these deployments as ONE production deployment and use the last one's finished_date as the finished date.\n\tSELECT\n\t\tcdc.cicd_deployment_id as deployment_id,\n\t\tmax(DATE(cdc.finished_date)) as day\n\tFROM cicd_deployment_commits cdc\n\tJOIN project_mapping pm on cdc.cicd_scope_id = pm.row_id and pm.`table` = 'cicd_scopes'\n\tWHERE\n\t\tpm.project_name in (${project})\n\t\tand cdc.result = 'SUCCESS'\n\t\tand cdc.environment = 'PRODUCTION'\n\tGROUP BY 1\n),\n\n_days_weekly_deploy as(\n-- calculate the number of deployment days every week\n\tSELECT\n\t\t\tdate(DATE_ADD(last_few_calendar_months.day, INTERVAL -WEEKDAY(last_few_calendar_months.day) DAY)) as week,\n\t\t\tMAX(if(_production_deployment_days.day is not null, 1, null)) as weeks_deployed,\n\t\t\tCOUNT(distinct _production_deployment_days.day) as days_deployed\n\tFROM \n\t\tlast_few_calendar_months\n\t\tLEFT JOIN _production_deployment_days ON _production_deployment_days.day = last_few_calendar_months.day\n\tGROUP BY week\n\t),\n\n_days_monthly_deploy as(\n-- calculate the number of deployment days every month\n\tSELECT\n\t\t\tdate(DATE_ADD(last_few_calendar_months.day, INTERVAL -DAY(last_few_calendar_months.day)+1 DAY)) as month,\n\t\t\tMAX(if(_production_deployment_days.day is not null, 1, null)) as months_deployed,\n\t\t COUNT(distinct _production_deployment_days.day) as days_deployed\n\tFROM \n\t\tlast_few_calendar_months\n\t\tLEFT JOIN _production_deployment_days ON _production_deployment_days.day = last_few_calendar_months.day\n\tGROUP BY month\n\t),\n\n_days_six_months_deploy AS (\n SELECT\n month,\n SUM(days_deployed) OVER (\n ORDER BY month\n ROWS BETWEEN 5 PRECEDING AND CURRENT ROW\n ) AS days_deployed_per_six_months,\n COUNT(months_deployed) OVER (\n ORDER BY month\n ROWS BETWEEN 5 PRECEDING AND CURRENT ROW\n ) AS months_deployed_count,\n ROW_NUMBER() OVER (\n PARTITION BY DATE_FORMAT(month, '%Y-%m') DIV 6\n ORDER BY month DESC\n ) AS rn\n FROM _days_monthly_deploy\n),\n\n_median_number_of_deployment_days_per_week_ranks as(\n\tSELECT *, percent_rank() over(order by days_deployed) as ranks\n\tFROM _days_weekly_deploy\n),\n\n_median_number_of_deployment_days_per_week as(\n\tSELECT max(days_deployed) as median_number_of_deployment_days_per_week\n\tFROM _median_number_of_deployment_days_per_week_ranks\n\tWHERE ranks <= 0.5\n),\n\n_median_number_of_deployment_days_per_month_ranks as(\n\tSELECT *, percent_rank() over(order by days_deployed) as ranks\n\tFROM _days_monthly_deploy\n),\n\n_median_number_of_deployment_days_per_month as(\n\tSELECT max(days_deployed) as median_number_of_deployment_days_per_month\n\tFROM _median_number_of_deployment_days_per_month_ranks\n\tWHERE ranks <= 0.5\n),\n\n_days_per_six_months_deploy_by_filter AS (\nSELECT\n month,\n days_deployed_per_six_months,\n months_deployed_count\nFROM _days_six_months_deploy\nWHERE rn%6 = 1\n),\n\n\n_median_number_of_deployment_days_per_six_months_ranks as(\n\tSELECT *, percent_rank() over(order by days_deployed_per_six_months) as ranks\n\tFROM _days_per_six_months_deploy_by_filter\n),\n\n_median_number_of_deployment_days_per_six_months as(\n\tSELECT min(days_deployed_per_six_months) as median_number_of_deployment_days_per_six_months, min(months_deployed_count) as is_collected\n\tFROM _median_number_of_deployment_days_per_six_months_ranks\n\tWHERE ranks >= 0.5\n),\n\n_tolal_production_deployment_days as(\n\tselect \n\tcount(*) as tpdd,\n\tcount(distinct day) as dtpdd\n\tfrom _production_deployment_days\n)\n\nSELECT \n -- tpdd as \"Production Deploy Counts\",\n\tdtpdd as \"Production Deployment Days\",\n median_number_of_deployment_days_per_week as \"Median weekly deployment days\",\n\tmedian_number_of_deployment_days_per_month as \"Median monthly deployment days\",\n\tmedian_number_of_deployment_days_per_six_months as \"Median semi-annual deployment days\"\nFROM _median_number_of_deployment_days_per_week, _median_number_of_deployment_days_per_month, _median_number_of_deployment_days_per_six_months, _tolal_production_deployment_days", |
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| "rawSql": "select \n count(distinct pr.id) as 'Merged PRs'\nfrom \n pull_requests pr\n join project_mapping pm on pr.base_repo_id = pm.row_id and pm.`table` = 'repos'\nwhere \n pm.project_name in ($project)\n and pr.merged_date is not null\n ", |
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| "rawSql": "-- Metric 2: median lead time for changes\nwith _pr_stats as (\n-- get the cycle time of PRs deployed by the deployments finished in the selected period\n\tSELECT\n\t\tdistinct pr.id,\n\t\tppm.pr_cycle_time\n\tFROM\n\t\tpull_requests pr \n\t\tjoin project_pr_metrics ppm on ppm.id = pr.id\n\t\tjoin project_mapping pm on pr.base_repo_id = pm.row_id and pm.`table` = 'repos'\n\t\tjoin cicd_deployment_commits cdc on ppm.deployment_commit_id = cdc.id\n\tWHERE\n\t pm.project_name in (${project}) \n\t\tand pr.merged_date is not null\n\t\tand ppm.pr_cycle_time is not null\n\t\tand $__timeFilter(cdc.finished_date)\n),\n\n_median_change_lead_time_ranks as(\n\tSELECT *, percent_rank() over(order by pr_cycle_time) as ranks\n\tFROM _pr_stats\n),\n\n_median_change_lead_time as(\n-- use median PR cycle time as the median change lead time\n\tSELECT max(pr_cycle_time) as median_change_lead_time\n\tFROM _median_change_lead_time_ranks\n\tWHERE ranks <= 0.5\n)\n\nSELECT \n\t-- median_change_lead_time/24 as 'median_change_lead_time_in_hours',\n\tCOUNT(distinct id) as \"Associated PRs\"\nFROM _median_change_lead_time, _pr_stats\n-- group by 1", |
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| "rawSql": "-- Metric 3: change failure rate\nwith _deployments as (\n-- When deploying multiple commits in one pipeline, GitLab and BitBucket may generate more than one deployment. However, DevLake consider these deployments as ONE production deployment and use the last one's finished_date as the finished date.\n\tSELECT\n\t\tcdc.cicd_deployment_id as deployment_id,\n\t\tmax(cdc.finished_date) as deployment_finished_date\n\tFROM \n\t\tcicd_deployment_commits cdc\n\t\tJOIN project_mapping pm on cdc.cicd_scope_id = pm.row_id and pm.`table` = 'cicd_scopes'\n\tWHERE\n\t\tpm.project_name in (${project})\n\t\tand cdc.result = 'SUCCESS'\n\t\tand cdc.environment = 'PRODUCTION'\n\tGROUP BY 1\n\tHAVING $__timeFilter(max(cdc.finished_date))\n)\n\nselect \n COUNT(*) as 'Successful Production Deployments'\nFROM _deployments", |
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| "rawSql": "-- Metric 3: change failure rate\nwith _deployments as (\n-- When deploying multiple commits in one pipeline, GitLab and BitBucket may generate more than one deployment. However, DevLake consider these deployments as ONE production deployment and use the last one's finished_date as the finished date.\n\tSELECT\n\t\tcdc.cicd_deployment_id as deployment_id,\n\t\tmax(cdc.finished_date) as deployment_finished_date\n\tFROM \n\t\tcicd_deployment_commits cdc\n\t\tJOIN project_mapping pm on cdc.cicd_scope_id = pm.row_id and pm.`table` = 'cicd_scopes'\n\tWHERE\n\t\tpm.project_name in (${project})\n\t\tand cdc.result = 'SUCCESS'\n\t\tand cdc.environment = 'PRODUCTION'\n\tGROUP BY 1\n\tHAVING $__timeFilter(max(cdc.finished_date))\n),\n\n_failure_caused_by_deployments as (\n-- calculate the number of incidents caused by each deployment\n\tSELECT\n\t\td.deployment_id,\n\t\td.deployment_finished_date,\n\t\tcount(distinct case when i.type = 'INCIDENT' then d.deployment_id else null end) as has_incident\n\tFROM\n\t\t_deployments d\n\t\tleft join project_issue_metrics pim on d.deployment_id = pim.deployment_id\n\t\tleft join issues i on pim.id = i.id\n\tGROUP BY 1,2\n),\n\n_change_failure_rate as (\n\tSELECT \n\t sum(has_incident) as \"incident count\",\n\t count(deployment_id) as \"deployment count\",\n\t\tcase \n\t\t\twhen count(deployment_id) is null then null\n\t\t\telse sum(has_incident)/count(deployment_id) end as change_failure_rate\n\tFROM\n\t\t_failure_caused_by_deployments\n)\n\nselect\n*\nfrom _change_failure_rate", |
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| "content": "<img src = 'https://devlake.apache.org/assets/images/cfr-definition-94d92cc75f857f183443ad5390d31d65.png' />\n\n- In this case:\n - Deployment-1 maps to Incident-1\n - Deployment-3 maps to Incident-2 and Incident-3\n - Deployment-2,4,5 doesn't map to any Incident", |
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| "rawSql": "with _deployments as(\n select distinct \n d.cicd_deployment_id as deployment_id,\n d.result,\n d.environment,\n d.finished_date,\n d.cicd_scope_id,\n pm.project_name\n from \n cicd_deployment_commits d\n join project_mapping pm on d.cicd_scope_id = pm.row_id and pm.`table` = 'cicd_scopes'\n where \n -- only result needs to specified, not envioronment\n d.result = 'SUCCESS'\n -- choose your project_name\n and pm.project_name in ($project)\n),\n\n_incidents as(\n select distinct \n i.id as issue_id,\n i.type,\n i.created_date,\n pm.project_name\n from \n issues i\n join board_issues bi on i.id = bi.issue_id\n join project_mapping pm on bi.board_id = pm.row_id \n where \n i.type = 'INCIDENT'\n -- choose your project_name\n and pm.project_name in ($project)\n)\n\nselect finished_date as time, deployment_id as id, 'DEPLOYMENT' as type from _deployments\nunion\nselect created_date as time, issue_id as id, 'INCIDENT' as type from _incidents\norder by time", |
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| "rawSql": "-- Metric 3: change failure rate\nwith _deployments as (\n-- When deploying multiple commits in one pipeline, GitLab and BitBucket may generate more than one deployment. However, DevLake consider these deployments as ONE production deployment and use the last one's finished_date as the finished date.\n\tSELECT\n\t\tcdc.cicd_deployment_id as deployment_id,\n\t\tmax(cdc.finished_date) as deployment_finished_date\n\tFROM \n\t\tcicd_deployment_commits cdc\n\t\tJOIN project_mapping pm on cdc.cicd_scope_id = pm.row_id and pm.`table` = 'cicd_scopes'\n\tWHERE\n\t\tpm.project_name in (${project})\n\t\tand cdc.result = 'SUCCESS'\n\t\tand cdc.environment = 'PRODUCTION'\n\tGROUP BY 1\n\tHAVING $__timeFilter(max(cdc.finished_date))\n),\n\n_failure_caused_by_deployments as (\n-- calculate the number of incidents caused by each deployment\n\tSELECT\n\t\td.deployment_id,\n\t\td.deployment_finished_date,\n pim.id as incident_id,\n i.created_date,\n\t\ti.resolution_date,\n\t\tif (pim.id is not null, 'TRUE', 'FALSE') as is_related\n\tFROM\n\t\t_deployments d\n\t\tleft join project_issue_metrics pim on d.deployment_id = pim.deployment_id\n\t\tleft join issues i on pim.id = i.id\n\tORDER BY 2\n)\n\nselect\n*\nfrom _failure_caused_by_deployments", |
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| "rawSql": "-- ***** 2023 report ***** --\n-- Metric 4: Failed deployment recovery time\nwith _deployments as (\n SELECT\n cdc.cicd_deployment_id as deployment_id,\n max(cdc.finished_date) as deployment_finished_date\n FROM \n cicd_deployment_commits cdc\n JOIN project_mapping pm on cdc.cicd_scope_id = pm.row_id and pm.`table` = 'cicd_scopes'\n WHERE\n pm.project_name in ($project)\n and cdc.result = 'SUCCESS'\n and cdc.environment = 'PRODUCTION'\n GROUP BY 1\n HAVING $__timeFilter(max(cdc.finished_date))\n),\n\n_incidents_for_deployments as (\n SELECT\n\t\tfd.deployment_id as \"deployment_id\",\n fd.deployment_finished_date,\n date_format(fd.deployment_finished_date,'%y/%m') as deployment_finished_month,\n i.id as incident_id,\n i.created_date as incident_create_date,\n i.resolution_date as incident_resolution_date,\n\t\tTIMESTAMPDIFF(HOUR, fd.deployment_finished_date, i.resolution_date) as \"failed_deployment_recovery_time\"\n FROM\n issues i\n left join project_issue_metrics pim on i.id = pim.id\n join _deployments fd on pim.deployment_id = fd.deployment_id\n WHERE\n i.type = 'INCIDENT'\n and $__timeFilter(i.resolution_date)\n),\n\n\n-- ***** 2021 report ***** --\n-- Metric 4: Median time to restore service \n_incidents as (\n-- get the incidents created within the selected time period in the top-right corner\n\tSELECT\n\t distinct i.id as \"incident_id\",\n i.resolution_date,\n i.created_date,\n\t cast(lead_time_minutes as signed) as lead_time_minutes\n\tFROM\n\t\tissues i\n\t join board_issues bi on i.id = bi.issue_id\n\t join boards b on bi.board_id = b.id\n\t join project_mapping pm on b.id = pm.row_id and pm.`table` = 'boards'\n\tWHERE\n\t pm.project_name in ($project)\n\t and i.type = 'INCIDENT'\n and $__timeFilter(i.created_date)\n)\n\nselect \n * \nFROM \n _incidents_for_deployments\nWHERE \n '$dora_report' = '2023' ", |
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