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Changelog

v0.3.x (development version)#

New benchmark(s):

  • Static HTTP server.
  • Redis.

v0.3.0 (Aug 20, 2024)#

New vendor(s):

  • Microsoft Azure

New feature(s):

  • Support for new hcloud CX server types.
  • Support for new hcloud region (Singapore).
  • Improved caching.

Fix(es):

  • Join references pointing to the right tables.
  • Count CPU cores in all physical CPUs.
  • Improve the standardization and cleanup of the CPU manufacturer, family, and model.
  • Extract speed from CPU description when available instead of unreliable dmidecode data.
  • Update included outbound network extractor at hcloud due to API change.
  • Check if a server is available in a gcp zone even though a related price is known.
  • Silence SAWarning on multiple relationships using overlapping compound foreign keys.
  • Fix manually collected geolocation of 3 gcp regions.
  • Fix spelling issues in benchmark and table column descriptions.

‼ Breaking changes:

  • Complex queries with joins relying on the foreign keys of the table definitions are now using the right references. This might result in different (but correct) results than before.

v0.2.1 (June 4, 2024)#

Fix(es):

  • Sort dict by its keys before passing as JSON to the database engine.

v0.2.0 (June 4, 2024)#

Database migrations:

  • Name all constraints for easier management in the future.
  • Rename the datacenter table to region, and the datacenter_id column to region_id in the zone, server_price, storage_price, traffic_price and ipv4_price tables.

‼ Breaking changes:

  • Renamed Datacenter to Region in all tables and across the codebase.

v0.1.4 (June 2, 2024)#

New feature(s):

  • Documented benchmark workloads and actual benchmark_score records loaded from sparecores-inspector-data.
  • Enriched server details loaded from sparecores-inspector-data.

Database migrations:

  • Add benchmark and benchmark_score tables.
  • Add 8 new columns to the server table.

‼ Breaking changes:

  • Renamed the memory column to memory_amount in the server table.

v0.1.3 (May 7, 2024)#

New feature(s):

  • Add api_reference and display_name to Datacenter, Zone, and Server.
  • Add latitude and longitude coordinates to Datacenter.
  • Add family to Server.

v0.1.2 (Apr 24, 2024)#

New vendor(s):

  • Google Cloud Platform (GCP)

New feature(s):

  • SVG logo for all supported vendors.

Fix(es):

  • Amazon Web Services' missed outbound traffic prices
  • Hetzner Cloud's outbound traffic price per GB instead of TB
  • Hetzner Cloud's datacenter_id reference in the server prices table

v0.1.1 (Apr 12, 2024)#

New vendors:

  • Hetzner Cloud

Infrastructure:

  • Use Alembic for database migrations.

CLI tools:

  • Database migration helpers.
  • Moved CREATE TABLE generator subcommand under schemas create.

Database migrations:

  • Add description field to Server.
  • Update Server.cpu_cores to be optional.

‼ Breaking changes:

As the database migration tool was just introduced, if you have been already using SC Crawler to initialize a database and collect data (e.g. in SCD tables), you will need to let Alembic know that you are already on v0.1.0 via the below command:

sc-crawler schemas stamp --revision 98894dffd37c

v0.1.0 (Apr 05, 2024)#

Initial PyPI release of sparecores-crawler.

CLI tools:

  • Generate database schema for standard and SCD tables of the supported records in various SQL dialects.
  • Pull records from vendor APIs and update a database with the fetched records.
  • Copy all supported tables from a database into another one.
  • Sync records of a database into another database's standard or SCD tables, with optional logging of the changes.
  • Hash database content.

Supported vendors:

  • Amazon Web Services (AWS)

Supported records:

  • country
  • compliance_framework
  • vendor
  • vendor_compliance_link
  • datacenter
  • zone
  • server
  • server_price
  • storage
  • storage_price
  • traffic_price
  • ipv4_price

Infrastructure:

  • Package documentation via MkDocs, Material for MkDocs, mkdocstrings, and bunch of other MkDocs plugins.
  • Database documentation on table schemas, relations and column comments via DBML and dbdocs.
  • Unit tests via pytest.
  • Linting via ruff.