How to Fix Meaningless 'system' Audit Trails in Spring Data JPA Services

·8 views

Spring Data JPA's auditing feature can be set up in minutes using four annotations and @EnableJpaAuditing, but audit columns often default to 'system' in ways that make them unreliable. The problem arises because scheduled jobs, queue consumers acting on behalf of real users, and sessions not yet initialized all produce identical audit entries. A developer has documented a structured approach to resolving this by defining what AuditorAware.getCurrentAuditor() should return in each scenario outside an active HTTP request. The solution involves reading user identity from a session-scoped bean rather than relying solely on Spring Security's SecurityContextHolder. A companion demo repository with Spring Boot and H2 illustrates the two key situations with runnable tests.

Read the full story at DEV Community

This is an AI-generated summary. ShortSingh links to the original source for the complete article.

Discussion (0)

What Is an AI Agent Harness and How Does It Work?

An AI agent harness is a software environment that wraps around a large language model, supplying it with tools and context to complete multi-step tasks. It operates on a reason-act-observe loop, where the model decides an action, a tool executes it, and the model evaluates the result before continuing. This cycle repeats until the task is fully completed, combining model reasoning with external tool execution. A practical implementation involves defining available tools such as a calculator, file reader, or word counter, along with a system prompt guiding the model's behavior. The concept draws from the ReAct framework, a published research approach that formalizes the synergy between reasoning and acting in language models.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

Google Gemini Enterprise Integrates PandaDoc for AI-Assisted Contract Workflows

Google has added a PandaDoc connector to Gemini Enterprise, enabling users to search, create, and manage contract documents directly within the Gemini workspace. The integration allows teams to select a PandaDoc template, populate its fields, and send the resulting document for signature without switching between platforms. Supported lifecycle actions include document creation, review, sending, and archiving, with data-store locations covering Global, US, and EU regions. The connector is particularly useful for teams that handle repetitive, standardized agreements such as client proposals or service contracts. However, the quality of outputs depends on the organization's existing PandaDoc templates and how their fields are configured, as Gemini does not replace the need for a well-structured template.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

How to Self-Host Typebot on Linux Using Docker Compose, PostgreSQL, and Traefik

Typebot is an open-source conversational form and chatbot builder that can be self-hosted, giving users full data ownership and control over integrations. A technical guide outlines deploying Typebot on a Linux server using Docker Compose alongside PostgreSQL for database storage, Redis for rate limiting and media uploads, and Traefik for reverse proxy and automatic HTTPS via Let's Encrypt. The setup requires two domain A records, Docker installed, and a generated encryption secret that must never be changed once live data is in use. Environment variables including database credentials, SMTP settings, and domain names are managed through a .env file read by Docker Compose at startup. Host-mounted volumes are used for PostgreSQL, Redis, and TLS certificate data to ensure persistence across container restarts and updates.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

How to Self-Host BookStack Documentation Platform Using Docker and Traefik

BookStack is a free, open-source platform that lets teams create and manage structured knowledge bases using a hierarchy of Shelves, Books, Chapters, and Pages. A deployment guide published on DEV Community walks through hosting BookStack on a Linux server using Docker Compose, with MariaDB handling data storage and Traefik serving as a reverse proxy for HTTPS via Let's Encrypt. The setup requires a Linux server with at least 4 CPU cores and 8 GB of RAM, along with Docker, Docker Compose, and a DNS A record pointing to the server. Persistent volumes are configured for the database, uploaded files, and application settings to ensure data survives container restarts. The guide covers environment configuration, secret key generation, and the full Docker Compose manifest needed to bring the stack online securely.

0 comments Read more at DEV Community