Microservices Split the Stack, but Agents Want It Whole

Explore how Harper brings search, embeddings, model access, and controlled AI decisions into one runtime, reducing the services around your AI application.

What If Your AI App Didn’t Need All Those Services?

Aleks Haugom

Oct 2026

Explore how Harper brings search, embeddings, model access, and controlled AI decisions into one runtime, reducing the services around your AI application.

What If Your AI App Didn’t Need All Those Services?

Aleks Haugom

Explore how Harper brings search, embeddings, model access, and controlled AI decisions into one runtime, reducing the services around your AI application.

What If Your AI App Didn’t Need All Those Services?

Aleks Haugom

Most real-time apps need a broker, a bridge, and a cache to keep state in sync. This is a live MQTT scoring demo on Harper, where the topic and the database record are the same write.

The Topic Is the Record: Real-Time Fan-Out Without a Broker, a Bridge, and a Cache

Blog

Most real-time apps need a broker, a bridge, and a cache to keep state in sync. This is a live MQTT scoring demo on Harper, where the topic and the database record are the same write.

Austin Akers

Head of Developer Relations

Most real-time apps need a broker, a bridge, and a cache to keep state in sync. This is a live MQTT scoring demo on Harper, where the topic and the database record are the same write.

The Topic Is the Record: Real-Time Fan-Out Without a Broker, a Bridge, and a Cache

Most real-time apps need a broker, a bridge, and a cache to keep state in sync. This is a live MQTT scoring demo on Harper, where the topic and the database record are the same write.

The Topic Is the Record: Real-Time Fan-Out Without a Broker, a Bridge, and a Cache

Most real-time apps need a broker, a bridge, and a cache to keep state in sync. This is a live MQTT scoring demo on Harper, where the topic and the database record are the same write.

The Topic Is the Record: Real-Time Fan-Out Without a Broker, a Bridge, and a Cache

Cross-region latency comes from distance, not slow queries. Why centralized data paths cost you latency, uptime, and money, with a benchmark you can run.

The Distance Problem: Why Centralized Data Paths Cost You Latency, Uptime, and Money

System Design

Blog

Cross-region latency comes from distance, not slow queries. Why centralized data paths cost you latency, uptime, and money, with a benchmark you can run.

Austin Akers

Head of Developer Relations

Cross-region latency comes from distance, not slow queries. Why centralized data paths cost you latency, uptime, and money, with a benchmark you can run.

The Distance Problem: Why Centralized Data Paths Cost You Latency, Uptime, and Money

Cross-region latency comes from distance, not slow queries. Why centralized data paths cost you latency, uptime, and money, with a benchmark you can run.

The Distance Problem: Why Centralized Data Paths Cost You Latency, Uptime, and Money

Cross-region latency comes from distance, not slow queries. Why centralized data paths cost you latency, uptime, and money, with a benchmark you can run.

The Distance Problem: Why Centralized Data Paths Cost You Latency, Uptime, and Money

InfoQ examines benchmark results comparing co-located and serverless architectures, highlighting faster personalized-data paths, serverless advantages under heavy fan-out, and the performance implications of eliminating network hops between services at scale.

Harper Argues Against the Multi-System Stack and Releases 5.2

Media Coverage

InfoQ examines benchmark results comparing co-located and serverless architectures, highlighting faster personalized-data paths, serverless advantages under heavy fan-out, and the performance implications of eliminating network hops between services at scale.

Renato Losio

InfoQ Staff Editor

InfoQ examines benchmark results comparing co-located and serverless architectures, highlighting faster personalized-data paths, serverless advantages under heavy fan-out, and the performance implications of eliminating network hops between services at scale.

Harper Argues Against the Multi-System Stack and Releases 5.2

Renato Losio

InfoQ examines benchmark results comparing co-located and serverless architectures, highlighting faster personalized-data paths, serverless advantages under heavy fan-out, and the performance implications of eliminating network hops between services at scale.

Harper Argues Against the Multi-System Stack and Releases 5.2

Renato Losio

InfoQ examines benchmark results comparing co-located and serverless architectures, highlighting faster personalized-data paths, serverless advantages under heavy fan-out, and the performance implications of eliminating network hops between services at scale.

Harper Argues Against the Multi-System Stack and Releases 5.2

Renato Losio

Harper 5.2 attacks database performance on three fronts: a per-worker record cache validated through lock-free atomic version slots, isolated commit scheduling to keep database writes off the application thread, and query planner improvements that route through the shortest available data path.

Faster by Doing Less: How Harper 5.2 Engineers Database Performance

Cache

Blog

Harper 5.2 attacks database performance on three fronts: a per-worker record cache validated through lock-free atomic version slots, isolated commit scheduling to keep database writes off the application thread, and query planner improvements that route through the shortest available data path.

Kris Zyp

SVP of Engineering

Harper 5.2 attacks database performance on three fronts: a per-worker record cache validated through lock-free atomic version slots, isolated commit scheduling to keep database writes off the application thread, and query planner improvements that route through the shortest available data path.

Faster by Doing Less: How Harper 5.2 Engineers Database Performance

Kris Zyp

Harper 5.2 attacks database performance on three fronts: a per-worker record cache validated through lock-free atomic version slots, isolated commit scheduling to keep database writes off the application thread, and query planner improvements that route through the shortest available data path.

Faster by Doing Less: How Harper 5.2 Engineers Database Performance

Kris Zyp