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Full Stack Chronicles

website·Indexed 32 days ago

https://fullstackchronicles.io/

A technical blog and knowledge base covering full-stack development, cloud infrastructure, and data engineering. Topics include Google Cloud Platform (GCP), AWS, Azure, Terraform, Kubernetes, Apache Beam, Spark, and various DevOps workflows such as DataOps container lifecycles and IAM identity management.

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What's inside Full Stack Chronicles

  1. Overview of Snowflake SQL API capabilities and limitations

    The Snowflake SQL API allows applications and deployment pipelines to execute most DDL and DML statements via REST API requests.

    Limitations:

    • Interactions with stages using PUT and GET are not supported.
    • Stored procedure operations using CALL are not supported.

  2. Overview of the okta-admin CLI tool

    okta-admin is an open-source command-line interface tool designed to administer an Okta organization. It is built using the Golang SDK for Okta, Cobra, Viper, and GJson to provide a programmatic way to manage Okta resources, serving as an alternative to the web-based Admin interface.
    # Source code available at:
https://github.com/gammastudios/okta-admin

  3. Overview of Forseti Terraform Validator

    Terraform Validator by Forseti allows developers to declare policies as code and check the compliance of Terraform plans against these policies. It can automatically fail violating plans in a CI step without requiring additional servers or agents. It is primarily focused on GCP resources (e.g., BigQuery, IAM, GKE, MySQL) but can be extended to other providers if custom Rego templates are written.

  4. Overview of Forseti Terraform Validator

    Terraform Validator by Forseti is a tool that allows developers to declare Policy as Code and check the compliance of Terraform plans against those policies. It can be integrated into CI/CD pipelines to automatically fail violating plans. It is primarily focused on GCP resources (e.g., BigQuery, IAM, GKE, MySQL) but can potentially be extended to other providers by writing custom Rego templates.

  5. Overview of Apache Beam SDK and Execution Framework

    Apache Beam is an open-source unified programming model for creating both batch and streaming data pipelines. Developers define pipelines as a Directed Acyclic Graph (DAG) of transformation steps using SDKs (such as Java or Python). These pipelines are executed on backend services using Runners. Common runners include DirectRunner for local execution and DataflowRunner for Google Cloud Dataflow.

  6. Overview of dbt (Data Build Tool)

    dbt is an open-source command-line tool written in Python that focuses on the Transform (T) part of the ELT (Extract, Load, Transform) process. It allows data engineers to manage transformations using software engineering best practices such as version control, automated testing, and reviews. dbt acts as a templating engine using Jinja to generate SQL commands that are executed directly on the underlying database.

  7. Overview of BigQuery Federated Queries for Cloud SQL

    BigQuery Federated Queries allow users to query tables and views in Cloud SQL (MySQL and Postgres) directly from the BigQuery console. This approach provides several advantages over traditional VPC access methods:

    • Users authenticate via the GCP console and Cloud IAM rather than managing individual database usernames and passwords.
    • No direct IP connectivity, additional routes, or firewall rules are required for the end-user.
    • Queries can be executed against a Cloud SQL read replica to offload I/O from the master instance.

  8. Overview of Deno runtime and package management

    Deno is a runtime for JavaScript and TypeScript that eliminates the need for a package manager. Unlike Node.js, Deno does not use package.json, package-lock.json, or a node_modules folder. Instead of relying on npm, Deno imports packages directly via URLs. Packages are downloaded to a local cache and TypeScript modules are transpiled to JavaScript the first time the code is executed.

  9. Overview of docusaurus-plugin-structured-data

    The docusaurus-plugin-structured-data plugin for Docusaurus implements JSON-LD structured data, which is the recommended approach by Google. It supports multi-level structured data including Organization, WebSite, WebPage, Article, and Breadcrumb levels. The plugin derives page-level data from the postBuild lifecycle API and injects it into the <head> of each page as a <script type="application/ld+json"> block.

  10. Overview of Metadata Hub (MDH)

    Metadata Hub (MDH) serves as the central source of truth for metadata across the company's platform. It is designed to be 'Config-Driven', allowing authorized users to add new metadata (e.g., via table-info.yaml files) without requiring code changes. MDH performs two primary functions: loading metadata configuration from YAML to serve via API, and storing pipeline information during file ingestion.

  11. Overview of BigQuery Federated Queries for Cloud SQL

    BigQuery Federated Queries allow you to query tables and views in Cloud SQL (MySQL and Postgres) directly from the BigQuery console. This approach leverages Cloud IAM for authorization instead of database-level user accounts and removes the need for direct IP connectivity, VPC firewall changes, or the Cloud SQL proxy. It is also possible to execute these queries against a read replica to offload I/O from the master instance.

  12. Overview of Snowflake SQL API

    The Snowflake SQL API allows applications and deployment pipelines to execute most DDL and DML statements via REST API requests. Note that certain operations are not supported, specifically interactions with stages (PUT and GET) and stored procedure operations (CALL).