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pgEdge Platform Released

pgEdge announced general availability of pgEdge Platform, a fully open and fully distributed PostgreSQL database designed to run at or near the network edge and between cloud regions.

With this release – and after a seven-month beta period – pgEdge will now provide support for customers moving applications deployed on pgEdge Platform into production.

pgEdge Platform packages pgEdge Distributed PostgreSQL as downloadable software that can be self-hosted and self-managed in either on-premises environments and/or in the cloud with major providers such as AWS, Microsoft Azure and Google Cloud Platform.

For application developers and database architects looking to deploy low latency and/or high availability applications that need to be globally distributed, pgEdge Distributed PostgreSQL is a multi-master (active-active) distributed database system. Presentation, application logic and the world's most popular open source relational database can all be deployed at or close to the network edge or between cloud regions. This provides reduced data latency, better customer experiences, ultra-high availability, and a way to address data residency requirements without application code changes.

For current users of PostgreSQL who need a simpler approach to high availability, pgEdge provides great flexibility to manage application workloads and architect for rapid failover given every node can take both read and write traffic. While designed to work in edge deployments across many nodes, pgEdge also functions well running across just a few cloud regions to provide applications with lower latency, automated failover support and disaster recovery capabilities.

During the beta period pgEdge received invaluable feedback from its community of users and partners. This informed the development of several enhancements and features that make the GA release of pgEdge Platform even more robust and reliable for users' distributed computing needs.

New enhancements and features include:

- Anti-Chaos Engine: The pgEdge Anti-Chaos Engine (ACE) ensures consistency between database nodes in a pgEdge distributed cluster. ACE provides background and on-demand comparisons of tables between nodes utilizing Merkel trees for efficient comparison of tables with hundreds of millions of rows.

- Ultra-High-Availability Support: pgEdge Platform now includes support for synchronous read replicas within regions, implemented via Patroni and etcd. This complements the cross-region failover and resiliency between regions inherent to the pgEdge multi-master architecture for maximum availability.

- Support for pgCat for connection pooling.

- Validated support for pgvector, the popular Postgres extension for vector embeddings in machine learning applications. This is in addition to 20+ other commonly used PostgreSQL extensions including pgBackrest, PostGIS, PLpgSQL, PL/Profiler, pgBouncer.

pgEdge Platform runs on a variety of common hardware and OS combinations and is available to self-host or self-manage in existing cloud accounts with enterprise class support available from pgEdge. pgEdge Cloud, a fully managed cloud service based on pgEdge Platform, will be generally available within a few months.

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pgEdge Platform Released

pgEdge announced general availability of pgEdge Platform, a fully open and fully distributed PostgreSQL database designed to run at or near the network edge and between cloud regions.

With this release – and after a seven-month beta period – pgEdge will now provide support for customers moving applications deployed on pgEdge Platform into production.

pgEdge Platform packages pgEdge Distributed PostgreSQL as downloadable software that can be self-hosted and self-managed in either on-premises environments and/or in the cloud with major providers such as AWS, Microsoft Azure and Google Cloud Platform.

For application developers and database architects looking to deploy low latency and/or high availability applications that need to be globally distributed, pgEdge Distributed PostgreSQL is a multi-master (active-active) distributed database system. Presentation, application logic and the world's most popular open source relational database can all be deployed at or close to the network edge or between cloud regions. This provides reduced data latency, better customer experiences, ultra-high availability, and a way to address data residency requirements without application code changes.

For current users of PostgreSQL who need a simpler approach to high availability, pgEdge provides great flexibility to manage application workloads and architect for rapid failover given every node can take both read and write traffic. While designed to work in edge deployments across many nodes, pgEdge also functions well running across just a few cloud regions to provide applications with lower latency, automated failover support and disaster recovery capabilities.

During the beta period pgEdge received invaluable feedback from its community of users and partners. This informed the development of several enhancements and features that make the GA release of pgEdge Platform even more robust and reliable for users' distributed computing needs.

New enhancements and features include:

- Anti-Chaos Engine: The pgEdge Anti-Chaos Engine (ACE) ensures consistency between database nodes in a pgEdge distributed cluster. ACE provides background and on-demand comparisons of tables between nodes utilizing Merkel trees for efficient comparison of tables with hundreds of millions of rows.

- Ultra-High-Availability Support: pgEdge Platform now includes support for synchronous read replicas within regions, implemented via Patroni and etcd. This complements the cross-region failover and resiliency between regions inherent to the pgEdge multi-master architecture for maximum availability.

- Support for pgCat for connection pooling.

- Validated support for pgvector, the popular Postgres extension for vector embeddings in machine learning applications. This is in addition to 20+ other commonly used PostgreSQL extensions including pgBackrest, PostGIS, PLpgSQL, PL/Profiler, pgBouncer.

pgEdge Platform runs on a variety of common hardware and OS combinations and is available to self-host or self-manage in existing cloud accounts with enterprise class support available from pgEdge. pgEdge Cloud, a fully managed cloud service based on pgEdge Platform, will be generally available within a few months.

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Today, organizations are generating and processing more data than ever before. From training AI models to running complex analytics, massive datasets have become the backbone of innovation. However, as businesses embrace the cloud for its scalability and flexibility, a new challenge arises: managing the soaring costs of storing and processing this data ...

Despite the frustrations, every engineer we spoke with ultimately affirmed the value and power of OpenTelemetry. The "sucks" moments are often the flip side of its greatest strengths ... Part 2 of this blog covers the powerful advantages and breakthroughs — the "OTel Rocks" moments ...

OpenTelemetry (OTel) arrived with a grand promise: a unified, vendor-neutral standard for observability data (traces, metrics, logs) that would free engineers from vendor lock-in and provide deeper insights into complex systems ... No powerful technology comes without its challenges, and OpenTelemetry is no exception. The engineers we spoke with were frank about the friction points they've encountered ...

Enterprises are turning to AI-powered software platforms to make IT management more intelligent and ensure their systems and technology meet business needs for efficiency, lowers costs and innovation, according to new research from Information Services Group ...

The power of Kubernetes lies in its ability to orchestrate containerized applications with unparalleled efficiency. Yet, this power comes at a cost: the dynamic, distributed, and ephemeral nature of its architecture creates a monitoring challenge akin to tracking a constantly shifting, interconnected network of fleeting entities ... Due to the dynamic and complex nature of Kubernetes, monitoring poses a substantial challenge for DevOps and platform engineers. Here are the primary obstacles ...

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Real privacy protection thanks to technology and processes is often portrayed as too hard and too costly to implement. So the most common strategy is to do as little as possible just to conform to formal requirements of current and incoming regulations. This is a missed opportunity ...

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