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Databricks uses Lakebase branching to create an independent database per PR: a CI/CD practice

Databricks describes Snorkel AI's CI/CD solution that uses Lakebase branching to create an independent read-write database for each open PR, reducing branch readiness time from over 30 minutes to under 60 seconds. Branches use copy-on-write; on a production dataset of about 2.5 TB, 100 concurrent PR branches store only 5 to 10 GB of data each for their own changes, and TTL automatically cleans them up after the PR ends. Production data is continuously synchronized to the main branch via AWS DMS; developers log in with Okta SSO, and the CI pipeline authenticates with a service principal and short-lived OAuth tokens.

End-to-End Amazon Bedrock Cost Management: A Practical Handbook for FinOps and Platform Teams

AWS presents a five-step closed loop for managing Amazon Bedrock costs: attribute by IAM principal, record request observability, control spending with budget alerts and hard blocks, optimize platform defaults such as model routing and caching, and review on a regular cadence. Amazon Bedrock now supports automatically attributing inference costs to the IAM principal that initiated the call, with the caller ARN written to the line_item_iam_principal column in CUR 2.0, covering IAM users, roles, federated identities, and API keys. In shared gateway scenarios, role session names and session tags can be set per user, credentials are cached for up to 1 hour, and attribution by user and tenant is restored.

Who Is Really Eating the AI Dividend: Looking at Profit Distribution Through Tech Giants' Financial Reports

The article reviews the latest financial reports of tech giants such as Meta, Amazon, and Google, noting that AWS revenue grew 39% year-over-year, but the group's free cash flow over the past 12 months turned negative at -$42.4 billion, and Alphabet's stock price fell 12.64% in a single day. Anthropic's prospectus shows revenue of $16.286 billion in the first half of 2026, a year-over-year increase of 1300%; compute and infrastructure costs during the same period reached $8.945 billion, and it signed minimum purchase commitments totaling $269.4 billion with Google, Amazon, and Microsoft. In a McKinsey survey, 80% of respondents said AI improved work efficiency, but only 37% believed AI made a positive contribution to corporate EBIT.

Microsoft, Google, and Amazon Earnings Side by Side: The AI Infrastructure Race Reaches a Watershed

The latest earnings reports from the three cloud providers Microsoft, Google, and Amazon show cloud businesses accelerating across the board: AWS third-quarter revenue was $45.98 billion, up 39.3% year over year; Azure posted $33.165 billion for the quarter, up 48%; Google Cloud revenue was $30.71 billion, more than doubling year over year; and their backlogs reached $578 billion, $677 billion, and $561 billion, respectively. Over the same period, all three posted negative free cash flow: Amazon had a net outflow of $42.36 billion over the past 12 months, Alphabet was negative $9.07 billion, and Meta had a net outflow of $2.12 billion, while only Microsoft remained positive at $18.6 billion. Market reactions diverged; Alphabet fell 12.64% in a single day on slowing advertising growth and its swing to negative cash flow, and the article argues that the competitive bottleneck is shifting from chips to power, land, and grid-connection approvals.

Amazon's Q3 revenue grew 12%, AI infrastructure spending pushes free cash flow down to negative $4.24 billion

Amazon's third-quarter revenue grew 12% year-over-year to $201.9 billion, of which AWS revenue reached $46 billion, up 39% year-over-year, and operating profit grew 56% to $17.8 billion. To meet AI computing demand, capital expenditure over the past 12 months was $94.8 billion more than the same period last year, free cash flow fell to negative $42.4 billion, and the stock price fell about 8% after hours. Amazon expects fourth-quarter revenue between $240 billion and $247 billion, and CEO Andy Jassy said AWS growth of more than 40% will not appear until 2027 to 2028.

The AI agent was decommissioned long ago—so why is its access key still alive?

OWASP ranks the failure to decommission non-human identities as the top risk in its 2025 Top 10, and AWS IAM user access keys do not expire automatically—forgotten keys remain valid until someone manually disables or deletes them. The article presents a three-step governance plan: use CloudQuery queries to find keys that have been unused for more than 90 days and are still active, use OPA policies to block the creation of long-term credentials during the Terraform/OpenTofu plan phase, and set a finite lifecycle for each key.