From 6aabb49c9bd95a4039313911b1dc81732dfa327b Mon Sep 17 00:00:00 2001 From: Pablo Seibelt Date: Tue, 13 Aug 2024 17:17:58 -0400 Subject: [PATCH 01/11] [DRAFT] Add blogpost for tap-pulumi-cloud --- .../index.md | 88 ++++++++++++++++++ .../schema.png | Bin 0 -> 115372 bytes data/team/team/lucas-crespo.toml | 11 +++ static/images/team/lucas-crespo.jpg | Bin 0 -> 20488 bytes 4 files changed, 99 insertions(+) create mode 100644 content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md create mode 100644 content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/schema.png create mode 100644 data/team/team/lucas-crespo.toml create mode 100644 static/images/team/lucas-crespo.jpg diff --git a/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md b/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md new file mode 100644 index 000000000000..880835111564 --- /dev/null +++ b/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md @@ -0,0 +1,88 @@ +--- +title: "Import your Pulumi Cloud data into your Data Warehouse with tap-pulumi-cloud" +date: 2024-08-13T15:01:40-04:00 +draft: false +meta_desc: Using the Meltano Singer SDK we have expanded the tap-pulumi-cloud connector to be able to export all the pulumi cloud data into your own Data Warehouse +meta_image: schema.png +authors: + - pablo-seibelt + - lucas-crespo + +tags: + - data-warehouse + - meltano + - api + - data + + +social: + twitter: "Your Pulumi Data in your Warehouse: See how the tap-pulumi-cloud extractor helps you export your Pulumi data into your own Data Warehouse. #DataWarehouse #Pulumi #Meltano #ELT" + linkedin: | + See how the tap-pulumi-cloud extractor helps you export your Pulumi data into your own Data Warehouse. + We show how you can use this connector to download Pulumi Cloud data into any destination of your choice; helping you to track infrastructure metrics alongside the rest of your data. + +--- + +The [Pulumi Cloud REST API](https://www.pulumi.com/docs/pulumi-cloud/cloud-rest-api) allows our users to read the same data available in the [Pulumi Cloud UI](https://app.pulumi.com) and this presents an opportunity for data teams trying to integrate metrics of their Pulumi usage, by accessing said API. + + + +However, manually integrating dozens of API endpoints into a data pipeline can be a time consuming effort, having to figure out the intricacies of each API, how each endpoint is structured, how to work with the api's paging method, etc. + +This is where the [Meltano SDK shines](https://sdk.meltano.com/en/latest/index.html) - It allows anyone to build "Taps" and "Targets" that read and write data, respectively. This way, we can use [tap-pulumi-cloud](https://github.com/pulumi/tap-pulumi-cloud) with loaders such as [target-snowflake](https://hub.meltano.com/loaders/target-snowflake), [target-bigquery](https://hub.meltano.com/loaders/target-bigquery), [target-redshift](https://hub.meltano.com/loaders/target-redshift) or even [target-postgres](https://hub.meltano.com/loaders/target-postgres); allowing us to load the data into our own Data Warehouse easily. + +## Set up + +First of all set up your environment [by following Meltano's installation guide](https://docs.meltano.com/guide/installation-guide), when this is done, continue by adding tap-pulumi-cloud and your choice of loader into your environment, we'll use target-duckdb for this example: + + +```bash +meltano add extractor tap-pulumi-cloud +meltano add loader target-duckdb +``` + +Then switch your tap variant to use Pulumi's instead of the default, open meltano.yml and change the pip_url to `git+https://github.com/pulumi/tap-pulumi-cloud.git` + +```yml +version: 1 +default_environment: dev +project_id: be90b150-3e48-4ecd-be9d-161ef7417e3c +environments: +- name: dev +- name: staging +- name: prod +plugins: + extractors: + - name: tap-pulumi-cloud + variant: meltanolabs + pip_url: git+https://github.com/pulumi/tap-pulumi-cloud.git + loaders: + - name: target-duckdb + variant: jwills + pip_url: target-duckdb~=0.6 +``` + +And run `meltano install` to make sure the right version is installed + +## Configure + +To configure all settings available for this tap, you can use Meltano's interactive config running: + +```bash +meltano config tap-pulumi-cloud set --interactive +``` + +The required variables are the `token` [(Get one from the Pulumi Cloud)](https://app.pulumi.com/) and organizations needs to have the org/s you want to extract data from. + +## Load data + +When your configuration has been finished, you can run the data pipeline like so: + +```bash +meltano run tap-pulumi-cloud target-duckdb +``` + +After the run finishes, you can access the exported tables and create whichever analytics you need on top of them + +![Data loaded into DuckDB](schema.png) + diff --git a/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/schema.png b/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/schema.png new file mode 100644 index 0000000000000000000000000000000000000000..f946816f9cdde634b1b95bbcf97581305c959951 GIT binary patch literal 115372 zcmZVl1yozXoA?h?ph$6Vad&qQ?p|DrTX853#ogT+ic=_5a4qf*rN!MLc#z0H{qF8> z_q=b;xhIo5^UU0lJM+jV2|8NJIIqZGAt52*sH!OFAt9kCA|WAbW1u1K{B#X>L_&ID z;w&$(qbe^?tK;qA;QZbm35hksZI(}cK!zCoGTgP&#;lfBi~jEy9d%WSL>&%OSvvip zlU!!EvWhDehMj{mPWOf#vUFVW2Lc7zK2_O1i_xt!2j7^OsVifLgLdBs zaL5e#qN`@g3A&q!Z7Npu4?FuA`+oF2f;ehLX+q%;Af{2M)raZ&+@w8MZ#@Bn5{QbH zQKxtL1dglGb5K-3XqQ9dR~@QKsaQf{730`s$&-pewF4(5ICxJ&O7ZNYH4SddyI;}j zp)b{5b1sf1efvxoC1|2#xW?rG4UUzq>P2ct3w5C%ZOQr-gN_YEH#tcNJ49{M%Ri|B 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z&(fk|06R|MjSF7DnR6e{qEm|TV~qqqZkWNN%F=B>xyF`BXMkSqM>jVGN&H7>S|1qa8F7} z5MfU_AXOkUrX);g)-rK5-zw!S60Pj*|#JF2*IV2qP6%;X? zlr7ZeqjG%IOypFO5(^MW!J!GF8~cr+lo5b-jyu&v{oh^&I?|9HT(>($Mty03mUhof z^rAYumuo8o{6x%p8m}6Xg99h6OL?3Qe+rH^Dw!0Y#d6leorqNg4c)2Zpv^H!EtAiF LX$!G6Ab Date: Tue, 13 Aug 2024 17:18:15 -0400 Subject: [PATCH 02/11] Fix linting --- .../index.md | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md b/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md index 880835111564..a44c3e2a2334 100644 --- a/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md +++ b/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md @@ -1,5 +1,5 @@ --- -title: "Import your Pulumi Cloud data into your Data Warehouse with tap-pulumi-cloud" +title: "Import Pulumi into your Data Warehouse with tap-pulumi-cloud" date: 2024-08-13T15:01:40-04:00 draft: false meta_desc: Using the Meltano Singer SDK we have expanded the tap-pulumi-cloud connector to be able to export all the pulumi cloud data into your own Data Warehouse @@ -35,7 +35,6 @@ This is where the [Meltano SDK shines](https://sdk.meltano.com/en/latest/index.h First of all set up your environment [by following Meltano's installation guide](https://docs.meltano.com/guide/installation-guide), when this is done, continue by adding tap-pulumi-cloud and your choice of loader into your environment, we'll use target-duckdb for this example: - ```bash meltano add extractor tap-pulumi-cloud meltano add loader target-duckdb @@ -64,7 +63,7 @@ plugins: And run `meltano install` to make sure the right version is installed -## Configure +## Configure To configure all settings available for this tap, you can use Meltano's interactive config running: @@ -85,4 +84,3 @@ meltano run tap-pulumi-cloud target-duckdb After the run finishes, you can access the exported tables and create whichever analytics you need on top of them ![Data loaded into DuckDB](schema.png) - From e2542126c28b5d842d137a4d4a41f8f30ba297f4 Mon Sep 17 00:00:00 2001 From: Pablo Seibelt Date: Tue, 13 Aug 2024 17:32:21 -0400 Subject: [PATCH 03/11] Add dora metrics note --- .../index.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md b/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md index a44c3e2a2334..f8cf3dcd9f37 100644 --- a/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md +++ b/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md @@ -71,7 +71,7 @@ To configure all settings available for this tap, you can use Meltano's interact meltano config tap-pulumi-cloud set --interactive ``` -The required variables are the `token` [(Get one from the Pulumi Cloud)](https://app.pulumi.com/) and organizations needs to have the org/s you want to extract data from. +The required variables are the `token` [(Get one from the Pulumi Cloud)](https://app.pulumi.com/) and `organizations` is a list of organizations you want to extract data from. ## Load data @@ -81,6 +81,6 @@ When your configuration has been finished, you can run the data pipeline like so meltano run tap-pulumi-cloud target-duckdb ``` -After the run finishes, you can access the exported tables and create whichever analytics you need on top of them +After the run finishes, you can access the exported tables and create whichever analytics you need on top of them, for example, you could combine this dataset with [tap-github](https://github.com/MeltanoLabs/tap-github) in order to calculate DORA Metrics. ![Data loaded into DuckDB](schema.png) From 80347fc7e73edf703c42edb0073ad3947e33c1a4 Mon Sep 17 00:00:00 2001 From: Pablo Seibelt Date: Wed, 14 Aug 2024 11:07:42 -0400 Subject: [PATCH 04/11] Add orchestration --- .../index.md | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md b/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md index f8cf3dcd9f37..22636b01f56e 100644 --- a/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md +++ b/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md @@ -84,3 +84,9 @@ meltano run tap-pulumi-cloud target-duckdb After the run finishes, you can access the exported tables and create whichever analytics you need on top of them, for example, you could combine this dataset with [tap-github](https://github.com/MeltanoLabs/tap-github) in order to calculate DORA Metrics. ![Data loaded into DuckDB](schema.png) + +## Orchestration + +Once you have this working, you'll need to establish some way of running this regularly in an automated fashion, to keep the data fresh. A popular way to do this is to use an orchestration tool such as [Airflow](https://airflow.apache.org/), [Dagster](https://dagster.io/) or [Mage](https://www.mage.ai/) (Among others) - An easy way to set up Meltano to run in this way is to use [a Docker container with your Meltano project.](https://docs.meltano.com/guide/containerization/) + +Another option is to use [Arch which is based on Meltano](https://arch.dev/), which path you choose will depend on your requirements and existing stack. From 8e3922c7a05560464183fa5ba0d3f3c6d9fac158 Mon Sep 17 00:00:00 2001 From: Pablo Seibelt Date: Wed, 14 Aug 2024 12:48:26 -0400 Subject: [PATCH 05/11] Add Pk details --- .../index.md | 11 +++++++++++ 1 file changed, 11 insertions(+) diff --git a/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md b/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md index 22636b01f56e..591e53335e41 100644 --- a/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md +++ b/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md @@ -90,3 +90,14 @@ After the run finishes, you can access the exported tables and create whichever Once you have this working, you'll need to establish some way of running this regularly in an automated fashion, to keep the data fresh. A popular way to do this is to use an orchestration tool such as [Airflow](https://airflow.apache.org/), [Dagster](https://dagster.io/) or [Mage](https://www.mage.ai/) (Among others) - An easy way to set up Meltano to run in this way is to use [a Docker container with your Meltano project.](https://docs.meltano.com/guide/containerization/) Another option is to use [Arch which is based on Meltano](https://arch.dev/), which path you choose will depend on your requirements and existing stack. + +Since each table is created with primary keys, when the process is run again, each run will "upsert" (update+insert) new data, replacing rows which match the same primary keys; e.g. stream Stacks has a primary key by `org_name, project_name and stack_name`, so if the same combination of keys arrives in the next update, the row will be updated instead of a new row being inserted. + +If building a landing zone with all historical changes instead of just the current status, this behavior might not be the desired one, to ignore primary keys and only insert new data, you can add this setting to meltano.yml on the plugin configuration for tap-pulumi-cloud: + +```yml + metadata: + '*': + table-key-properties: [] + key-properties: [] +``` From 662ef1dfb5993f900138fd55be4e4d6997edaf85 Mon Sep 17 00:00:00 2001 From: Pablo Seibelt Date: Wed, 14 Aug 2024 13:14:44 -0400 Subject: [PATCH 06/11] Adjust timestamp --- .../index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md b/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md index 591e53335e41..48b096662759 100644 --- a/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md +++ b/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md @@ -1,6 +1,6 @@ --- title: "Import Pulumi into your Data Warehouse with tap-pulumi-cloud" -date: 2024-08-13T15:01:40-04:00 +date: 2024-08-14T12:00:00-07:00 draft: false meta_desc: Using the Meltano Singer SDK we have expanded the tap-pulumi-cloud connector to be able to export all the pulumi cloud data into your own Data Warehouse meta_image: schema.png From e35a6ae74f0c57104c49bf030e584a1571b1c66b Mon Sep 17 00:00:00 2001 From: Pablo Seibelt Date: Thu, 15 Aug 2024 13:08:45 -0400 Subject: [PATCH 07/11] Add Metrics SQL --- .../index.md | 61 +++++++++++++++++++ 1 file changed, 61 insertions(+) diff --git a/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md b/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md index 48b096662759..8b43d49074ed 100644 --- a/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md +++ b/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md @@ -101,3 +101,64 @@ If building a landing zone with all historical changes instead of just the curre table-key-properties: [] key-properties: [] ``` + +## Generate metrics + +With all of the data in one place, you can generate metrics based on Pulumi data, and combine it with other data sources, for example if you wanted to look at your average Resources Under Management (RUM) monthly (Using DuckDB's SQL Flavor, adjust to your specific database): + +```sql +WITH monthly_rum_average AS ( + SELECT + DATE_TRUNC('month', MAKE_DATE(CAST(year AS INT), CAST(month AS INT), CAST(day AS INT))) AS rum_month, + org_name, + AVG(resources) AS monthly_avg_rum + FROM + pulumicloud.daily_rum_usage + GROUP BY + rum_month, org_name +) +SELECT + rum_month, + org_name, + monthly_avg_rum, + LAG(monthly_avg_rum) OVER (ORDER BY rum_month) AS previous_month_avg_rum, + CASE + WHEN LAG(monthly_avg_rum) OVER (ORDER BY rum_month) IS NULL THEN NULL + ELSE ((monthly_avg_rum - LAG(monthly_avg_rum) OVER (ORDER BY rum_month)) / LAG(monthly_avg_rum) OVER (ORDER BY rum_month)) * 100 + END AS month_over_month_rum_growth_percentage +FROM + monthly_rum_average +``` + +Or if you want to see the total updates per user: + +```sql +WITH operations_by_members AS ( + SELECT + org_name, + REPLACE(CAST(json_extract(requested_by, '$.github_login') AS STRING), '"', '') AS github_login, + COUNT(*) AS total_updates + FROM + pulumicloud.stack_updates + GROUP BY + org_name, github_login + ORDER BY + total_updates DESC +) +SELECT + om.org_name, + om.role, + om.user_github_login, + om.user_name, + obm.total_updates +FROM + pulumicloud.organization_members om +INNER JOIN + operations_by_members obm +ON + om.org_name = obm.org_name + AND om.user_github_login = obm.github_login +ORDER BY + total_updates DESC +``` + From 846c9610c4bc6f2431c8e00f319b677491801b41 Mon Sep 17 00:00:00 2001 From: Pablo Seibelt Date: Thu, 15 Aug 2024 13:56:03 -0400 Subject: [PATCH 08/11] Fix blank line --- .../import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md | 1 - 1 file changed, 1 deletion(-) diff --git a/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md b/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md index 8b43d49074ed..f1d322ecff28 100644 --- a/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md +++ b/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md @@ -161,4 +161,3 @@ ON ORDER BY total_updates DESC ``` - From 84dbebc42895eb9a7deb3d4b63c4c772ac8e8065 Mon Sep 17 00:00:00 2001 From: Pablo Seibelt Date: Thu, 15 Aug 2024 14:33:10 -0400 Subject: [PATCH 09/11] Add lead time for changes --- .../index.md | 23 +++++++++++++++++++ 1 file changed, 23 insertions(+) diff --git a/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md b/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md index f1d322ecff28..bd6950630a55 100644 --- a/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md +++ b/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md @@ -130,6 +130,29 @@ FROM monthly_rum_average ``` +If you want to see the average time to deploy changes, excluding console-initiated deploys (Similar to what is tracked for "Lead time for changes"): + +```sql +WITH stack_deployments AS ( + SELECT + CAST(json_extract(jobs, '$[0].started') AS TIMESTAMP) AS start_time, + CAST(json_extract(jobs, '$[0].last_updated') AS TIMESTAMP) AS end_time, + initiator + FROM + pulumicloud.stack_deployments + WHERE + initiator IS NOT NULL + AND initiator <> 'console' +) +SELECT + initiator, + AVG(DATE_DIFF('second', start_time, end_time)) / 60 AS avg_deploy_time_in_minutes +FROM + stack_deployments +GROUP BY + initiator +``` + Or if you want to see the total updates per user: ```sql From 67d83bfc6ddf8e89e2eecfa331a41b2495aa3559 Mon Sep 17 00:00:00 2001 From: meagancojocar <50200557+meagancojocar@users.noreply.github.com> Date: Sat, 31 Aug 2024 11:52:02 -0700 Subject: [PATCH 10/11] copy changes and added meta image! --- .../index.md | 53 +++++++++++------- .../meta.png | Bin 0 -> 486766 bytes 2 files changed, 34 insertions(+), 19 deletions(-) create mode 100644 content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/meta.png diff --git a/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md b/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md index bd6950630a55..78fb89dd68d6 100644 --- a/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md +++ b/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md @@ -1,9 +1,9 @@ --- -title: "Import Pulumi into your Data Warehouse with tap-pulumi-cloud" -date: 2024-08-14T12:00:00-07:00 +title: "Tap-Pulumi-Cloud: Simplifying Pulumi Cloud Data Integration" +date: 2024-09-03T09:00:00-07:00 draft: false -meta_desc: Using the Meltano Singer SDK we have expanded the tap-pulumi-cloud connector to be able to export all the pulumi cloud data into your own Data Warehouse -meta_image: schema.png +meta_desc: We have released a tap-pulumi-cloud connector to be able to export Pulumi Cloud data into your own Data Warehouse. +meta_image: meta.png authors: - pablo-seibelt - lucas-crespo @@ -14,26 +14,35 @@ tags: - api - data - social: - twitter: "Your Pulumi Data in your Warehouse: See how the tap-pulumi-cloud extractor helps you export your Pulumi data into your own Data Warehouse. #DataWarehouse #Pulumi #Meltano #ELT" + twitter: "Your Pulumi Data in your Warehouse: See how the tap-pulumi-cloud extractor helps you export your Pulumi data into your own Data Warehouse." linkedin: | See how the tap-pulumi-cloud extractor helps you export your Pulumi data into your own Data Warehouse. We show how you can use this connector to download Pulumi Cloud data into any destination of your choice; helping you to track infrastructure metrics alongside the rest of your data. --- -The [Pulumi Cloud REST API](https://www.pulumi.com/docs/pulumi-cloud/cloud-rest-api) allows our users to read the same data available in the [Pulumi Cloud UI](https://app.pulumi.com) and this presents an opportunity for data teams trying to integrate metrics of their Pulumi usage, by accessing said API. +Integrating various infrastructure data sources into your data warehouse has long been a challenge for Platform Teams. Whether it’s dealing with multiple API endpoints, managing complex authentication processes, or just trying to get a consistent, reliable data feed, the process can be daunting and time-consuming. Especially when you factor in the various cloud providers, and the inconsistency in data formats across them all. + +These pain points can slow down your ability to get actionable insights from your infrastructure data, leaving you with more questions than answers. +The [tap-pulumi-cloud connector](https://github.com/pulumi/tap-pulumi-cloud), announced today, is designed to address these challenges head-on by offering a simple solution for automating the process of accessing infrastructure data. +Leveraging Pulumi Cloud data about your infrastructure instead of going directly to the provider eliminates the need for custom API integrations and handles the data consistency problem. And while all this data existed before today, by using the [Pulumi Cloud console](https://app.pulumi.com) or [Pulumi Cloud REST API](/docs/pulumi-cloud/cloud-rest-api) directly, the `tap-pulumi-cloud` connector handles complex interactions with the API, transforming the raw data into a structured format that’s ready for analysis as soon as it lands in your data warehouse. This means less time spent on data wrangling and more time on generating insights. -However, manually integrating dozens of API endpoints into a data pipeline can be a time consuming effort, having to figure out the intricacies of each API, how each endpoint is structured, how to work with the api's paging method, etc. +A few examples of the types of analytics you can build on top Pulumi Cloud data: -This is where the [Meltano SDK shines](https://sdk.meltano.com/en/latest/index.html) - It allows anyone to build "Taps" and "Targets" that read and write data, respectively. This way, we can use [tap-pulumi-cloud](https://github.com/pulumi/tap-pulumi-cloud) with loaders such as [target-snowflake](https://hub.meltano.com/loaders/target-snowflake), [target-bigquery](https://hub.meltano.com/loaders/target-bigquery), [target-redshift](https://hub.meltano.com/loaders/target-redshift) or even [target-postgres](https://hub.meltano.com/loaders/target-postgres); allowing us to load the data into our own Data Warehouse easily. +1. Average resources under management overtime [(code example)](#see-average-resources-under-management) +2. The average time to deploy changes [(code example)](#see-the-average-time-to-deploy-changes) +3. See the total updates per user [(code example)](#see-the-total-updates-per-user) +4. Join with CI/CD provider data to generate DORA metrics and reporting +5. Join with resource cost data to generate infrastructure cost reporting + +As it is built on the [Meltano SDK](https://sdk.meltano.com/en/latest/index.html), you can use [tap-pulumi-cloud](https://github.com/pulumi/tap-pulumi-cloud) with loaders such as [target-snowflake](https://hub.meltano.com/loaders/target-snowflake), [target-bigquery](https://hub.meltano.com/loaders/target-bigquery), [target-redshift](https://hub.meltano.com/loaders/target-redshift) or even [target-postgres](https://hub.meltano.com/loaders/target-postgres); allowing us to load the data into our own data warehouse easily. ## Set up -First of all set up your environment [by following Meltano's installation guide](https://docs.meltano.com/guide/installation-guide), when this is done, continue by adding tap-pulumi-cloud and your choice of loader into your environment, we'll use target-duckdb for this example: +Firstly, set up your environment [by following Meltano's installation guide](https://docs.meltano.com/guide/installation-guide). Once this is done, continue by adding `tap-pulumi-cloud` and your choice of loader into your environment, we'll use `target-duckdb` for this example: ```bash meltano add extractor tap-pulumi-cloud @@ -61,9 +70,9 @@ plugins: pip_url: target-duckdb~=0.6 ``` -And run `meltano install` to make sure the right version is installed +Then run `meltano install` to make sure the right version is installed. -## Configure +## Configure it To configure all settings available for this tap, you can use Meltano's interactive config running: @@ -71,11 +80,11 @@ To configure all settings available for this tap, you can use Meltano's interact meltano config tap-pulumi-cloud set --interactive ``` -The required variables are the `token` [(Get one from the Pulumi Cloud)](https://app.pulumi.com/) and `organizations` is a list of organizations you want to extract data from. +The required variables are the `token` [(Get one from Pulumi Cloud)](https://app.pulumi.com/) and `organizations` is a list of Pulumi Cloud organizations you want to extract data from. ## Load data -When your configuration has been finished, you can run the data pipeline like so: +When your configuration has been finished, you can run the data pipeline: ```bash meltano run tap-pulumi-cloud target-duckdb @@ -87,9 +96,7 @@ After the run finishes, you can access the exported tables and create whichever ## Orchestration -Once you have this working, you'll need to establish some way of running this regularly in an automated fashion, to keep the data fresh. A popular way to do this is to use an orchestration tool such as [Airflow](https://airflow.apache.org/), [Dagster](https://dagster.io/) or [Mage](https://www.mage.ai/) (Among others) - An easy way to set up Meltano to run in this way is to use [a Docker container with your Meltano project.](https://docs.meltano.com/guide/containerization/) - -Another option is to use [Arch which is based on Meltano](https://arch.dev/), which path you choose will depend on your requirements and existing stack. +Once you have this working, you'll need to establish some way of running this regularly in an automated fashion, to keep the data fresh. A popular way to do this is to use an orchestration tool such as [Airflow](https://airflow.apache.org/), [Dagster](https://dagster.io/) or [Mage](https://www.mage.ai/), among others. An easy way to set up Meltano to run in this way is to use [a Docker container with your Meltano project.](https://docs.meltano.com/guide/containerization/). Another option is to use [Arch which is based on Meltano](https://arch.dev/), which path you choose will depend on your requirements and existing stack. Since each table is created with primary keys, when the process is run again, each run will "upsert" (update+insert) new data, replacing rows which match the same primary keys; e.g. stream Stacks has a primary key by `org_name, project_name and stack_name`, so if the same combination of keys arrives in the next update, the row will be updated instead of a new row being inserted. @@ -104,7 +111,9 @@ If building a landing zone with all historical changes instead of just the curre ## Generate metrics -With all of the data in one place, you can generate metrics based on Pulumi data, and combine it with other data sources, for example if you wanted to look at your average Resources Under Management (RUM) monthly (Using DuckDB's SQL Flavor, adjust to your specific database): +With all of the data in one place, you can generate metrics based on Pulumi Cloud data, and combine it with other data sources, for example if you wanted to look at your average Resources Under Management (RUM) monthly (Using DuckDB's SQL Flavor, adjust to your specific database): + +### See average resources under management ```sql WITH monthly_rum_average AS ( @@ -130,6 +139,8 @@ FROM monthly_rum_average ``` +### See the average time to deploy changes + If you want to see the average time to deploy changes, excluding console-initiated deploys (Similar to what is tracked for "Lead time for changes"): ```sql @@ -153,7 +164,7 @@ GROUP BY initiator ``` -Or if you want to see the total updates per user: +### See the total updates per user ```sql WITH operations_by_members AS ( @@ -184,3 +195,7 @@ ON ORDER BY total_updates DESC ``` + +## Conclusion + +Integrating Pulumi Cloud data into your data warehouse has never been easier with `tap-pulumi-cloud`. 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zyhLBy*eCdYjHC3OMb0%WZ-2Fb;!%mR-C(EH(QZWyGjlUZbMX!+5zH1C>Q9XC=BE(i zeAe||2N%STHOX`Aum3_o9p?R3zU+8Ft78KOp&x_{KSIdUUEZj{OKaVTrrS-jf3$&o zt>Y(|fF9h)7`Ax0ZSQTCH+KIF+G@#Dq%QI~&a#2O_8M_h=CVHrwt3HMK~!-K6RdD6 z_gU9(M7M4Dp0!umT1}4%BKy`_TX>wh!`(9uf5X^&Id*<;X=kav0|***rz{aL#NZq0 zHSBX~k$I)q6?!#R0=e@X5IG@($G=TV4Vp*1YhyCH`G&(ha3K)__T`}u5$AvQ!30ae zYsoD46gIM5dSErp8@Zq_f^8{&t~MUume&CET;sokbWnMqm1e$WP1|J3L Date: Sat, 31 Aug 2024 15:09:46 -0700 Subject: [PATCH 11/11] Update index.md --- .../index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md b/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md index 78fb89dd68d6..56d0dc5a00dd 100644 --- a/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md +++ b/content/blog/import-your-pulumi-cloud-data-with-tap-pulumi-cloud/index.md @@ -72,7 +72,7 @@ plugins: Then run `meltano install` to make sure the right version is installed. -## Configure it +## Configure it To configure all settings available for this tap, you can use Meltano's interactive config running: