Design dbt data transformations with clearly organized models, data quality tests, documentation, and incremental processing that updates only part of a dataset. Use it to structure analytics tables and organize a dbt project.
Create and maintain project documents in conductor/ covering the product, technology stack, development workflow, and work units. Extract context from existing code, check document consistency before implementation, and update documentation as the project evolves.
Set up monitoring for communication between services in Istio or Linkerd environments. Combine metrics, logs, and distributed traces, which follow requests across services, to investigate delays and errors, visualize dependencies, and define service quality targets.
Build Solidity contract tests with Hardhat and Foundry. Check individual functions, contract interactions, gas usage, and varied inputs, and use a local copy of mainnet state to test against existing contracts.
Design separate paths for updating and reading data using CQRS, an approach that splits these responsibilities. Organize read models, event handling, and validation to support complex queries and scale reads independently from writes.
Organize features, bug fixes, and refactors as Conductor tracks, units of related work. Create specifications and task plans, maintain status and dependency records, and preserve completed work with verification details and commit references.
Review and write Solidity smart contracts with security in mind. Address reentrancy, where external calls trigger repeated execution, along with numeric overflow and access control issues, using implementation patterns, security tests, and documentation for audit preparation.
Follow Conductor's development plans using test-driven development: write a failing test, implement the change, then improve the code. Manage phase verification, progress updates, and focused git commits as tasks move toward completion.
Build decentralized finance contracts from Solidity templates for staking and token swaps. Examples cover reward distribution, adding and removing pooled tokens, and swap calculations, with additional patterns for governance and flash loans.
Plan systems across AWS, Azure, GCP, and OCI by comparing services and architecture patterns. Helps guide service selection, disaster recovery, migration planning, and cost decisions while considering ways to reduce dependence on a single provider.
Configure how traffic moves between services in Istio, a system for managing service communication. Includes routing, load balancing, gradual releases, retries, failure isolation, copied traffic for testing, and commands for inspecting configuration.
Plan microservices by defining service responsibilities, communication methods, and data ownership. Use patterns for gradual migration, distributed transactions, and failure isolation to design systems made of independently responsible services.
Plan and implement user login and access permissions using sessions, JWT tokens, or OAuth2. Apply role-based permissions, protect APIs, and review common weaknesses in password handling, cookies, token expiration, and server-side checks.
Configure Linkerd to manage communication between services on Kubernetes. Covers installation, mutual authentication between services, access policies, gradual traffic shifts to new releases, retries, timeouts, and monitoring commands for inspecting traffic and diagnosing connection issues.
Turn analysis into reports and presentations that explain what the numbers mean. Combine charts, context, and a clear narrative to highlight key findings, connect them to audience goals, and propose next steps.
Plan and configure connections between on-premises data centers and AWS, Azure, GCP, or OCI using VPNs or dedicated links. Cover routing, redundant connections, security controls, monitoring, troubleshooting, and connection costs.
Test Temporal workflows in Python with pytest. Use time skipping to avoid long waits, replace activities with controlled test versions, and replay execution histories to check that workflow changes remain consistent with previous runs.
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