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Hey everyone!

We just released Atlas Kubernetes Operator v0.8, which adds drift detection before and between deployments, security scanning for deployed databases, and a setting for controlling dev databases per resource:

• Pre-Apply Drift Check: policy.drift on an AtlasMigration checks the database for drift before pending migrations are applied, and can block the deployment.
• Scheduled Drift Checks: AtlasDriftCheck checks the database of an AtlasMigration for drift on an interval and reports the result through conditions and Kubernetes events.
• Security Scanning: AtlasSecurityScan scans a database for extensions affected by published CVEs, on a schedule or after a schema change, and grades the findings against a policy.
• Per-Resource Dev Database Prewarming: AtlasSchema and AtlasMigration accept prewarmDevDB, overriding the operator-wide default.

"Managing schema as code was the mindset we were looking for, and it was a perfect match with Atlas. It's able to support our database and others, which gives us flexibility going forward."

– Raunak Kathuria, VP of Engineering, Deriv

Company Background​

Deriv is one of the world's largest online brokers, and was recently named Best Fintech Broker (Global) at the 2026 Global Forex Awards. They offer CFDs and other derivatives on forex, stocks and indices, cryptocurrencies, commodities, and Derived Indices to millions of registered users across the globe.

The company runs on PostgreSQL across many schemas and databases, including multi-tenant setups, and relies on advanced features like views, functions, triggers, stored procedures, and row-level security. All of it operates under compliance requirements, including SOC 2, HIPAA, and PCI, that demand full audit trails on every change. Deriv's engineering teams also actively use AI agents in their development work.

If you've searched for "DACPAC for PostgreSQL," you already know the answer: there isn't one. DACPAC is a Microsoft file format, built into SQL Server Data Tools and deployed with SqlPackage, and it has no equivalent outside the SQL Server ecosystem. What you're actually looking for isn't the file format, it's the workflow: define the schema once, let the tool diff it against a live database, and deploy the result without hand-written migration scripts. Atlas gives you that workflow for PostgreSQL.

Anthropic recently published The AI-Native SDLC playbook, and it's the most concrete writeup I've seen discussing the effects of cheaper code generation on a delivery process, written by a company where AI authors 80% of merged code. If you run engineering at any scale, I suggest you read it.

It consists of six stages from Plan to Maintain that work in a loop rather than a linear chain of handoffs. Each stage commits an artifact that the next stage reads. The chain of commits is the audit trail. Humans stop reading every line and start judging intent and risk.

GitLab's CEO responded with the line that will likely outlive the playbook itself: "when implementation becomes abundant, trust becomes scarce."

Code is abundant now. Your data is not. An agent can regenerate your code in an afternoon, but it cannot regenerate the production state your company accumulated over years. The playbook's recovery model quietly assumes otherwise, which leads to our claim: the loop does not close at the database.

The database is the one stateful component in your infrastructure. It's where the history lives, and you cannot roll back history by redeploying an older version of it.

"Everybody should be using Atlas. If anyone is still trying to manage their database objects in some more traditional way, they really need to get on board and start using Atlas."

– Kevin Hochhalter, VP of IT Operations, Health in Tech

Company Background​

Health in Tech (Nasdaq: HIT) is an AI-driven insurtech company that automates and streamlines self-funded health insurance plans for small and medium-sized businesses. Through integrated platforms like its eDIYBS quoting engine and HI Card claims system, Health in Tech reduces administrative friction across underwriting, risk management, and network pricing workflows, letting brokers, carriers, and third-party administrators design, price, and bind customized health plans within minutes.

Hey everyone!

We're excited to announce Atlas v1.3. This release delivers on a promise we made in v1.2: the security graph is now live in Atlas Cloud, mapping your entire database attack surface. It also introduces Atlas Scripts for running data operations as code, safer and faster migrations, and a new command group for working with the Atlas Registry from the CLI.

Here is what you can find in this release:

• Security Graph for Databases - Map your entire database attack surface: permissions, misconfigurations, and CVEs across every object, with severity tiers and blast-radius tracing.
• Atlas Scripts: DataOps as Code - Backfills, GDPR purges, and reports declared as code: transactional mutations, masked queries, and batched loops, reviewed and tested in CI.
• atlas cloud: Manage Registry Resources from the CLI - Repositories, databases, and deployment history from the terminal, with JSON output for scripts, CI gates, and AI agents, plus security graph and lineage graph exports.
• Schema Annotations - Attach type-safe metadata to schema resources and render GraphQL, OpenAPI, or any other format from it with templates.
• Pre-Apply Drift Detection - Block a deployment when the database drifted from the expected state, with the diff printed before any statement runs.
• Database Driver Improvements - Lock-safe NOT NULL and 8x-10x faster schema tests on PostgreSQL, Oracle roles and storage, Snowflake Iceberg tables, ClickHouse row policies, and more.
• Simpler Licensing and No AI Training - One agreement replaces the separate EULA and SaaS terms, with a written commitment that we never train AI models on your data.

Company Background​

Aryon Security is a preventative cloud security platform that enforces security policies at the point of deployment, stopping misconfigurations before they ever reach production rather than flagging them after the fact. Acting as a source-agnostic gatekeeper across AWS, Azure, and GCP, Aryon applies the same protection whether infrastructure is provisioned through IaC, ClickOps, or third-party providers, letting security and platform teams define a policy once and ensure only compliant infrastructure is ever deployed.

"The biggest win of any tool is when you don't need to look at it ever again and it just works."

– Wai Ho Choy, Infrastructure Lead, Gumloop

Company Background​

Gumloop is a collaborative platform that empowers anyone in a company to build AI agents using their preferred models and integrations, while giving IT enterprise-grade visibility and control. Whether these agents are deployed in Gumloop's secure environment or within your own infrastructure, your data always stays entirely in your systems.

Company Background​

EliseAI transforms complex housing and healthcare systems, helping property managers and healthcare providers handle leasing, maintenance, and resident engagement. By deeply integrating into workflows and automating operations, it cuts costs for all parties. EliseAI powers 1 in 6 rental apartment units in the U.S., processing hundreds of thousands of messages and thousands of voice calls per day.

"Atlas just works behind the scenes. We don't need to pay attention to it – we can trust that it's getting the job done."

– Armon Avrahamy, CTO and Co-Founder, Wenrix

Company Background​

Wenrix is the AI infrastructure for profitable growth in air. Since 2018, leading travel agencies have relied on Wenrix to help them grow revenue, protect margin, and scale more efficiently in an increasingly complex and competitive air retail landscape.