EaseMesh
EaseMesh
is a service mesh that is compatible with the Spring Cloud ecosystem. It is based on Easegress
for the sidecar of service management and EaseAgent
for the monitor of service observing.
Features
- Non-intrusive Design: Zero code modification for Java Spring Cloud application migration, only small configuration update needed.
- Java Register/Discovery: Compatible with popular Java Spring Cloud ecosystem’s Service registry/discovery.
- Multiple tenants(namespace) Supporting multiple tenants’ service registration, isolate services from different tenants.
- Share (global) tenant Support share tenants, all services have visibility to the service registered in the global tenant.
- Compatible
- Be compatible with the Eureka registry.
- Be compatible with the Consul registry.
- Be compatible with the Nacos registry.
- Extensibility Support registering services with metadata.
- Resource Management: Rely on Kubernetes platform for CPU/Memory resources management.
- Traffic Orchestration
- Rich Routing Rules: Exact path, path prefix, regular expression of the path, method, headers.
- Traffic Splitting Coloring & Scheduling east-west and north-south traffic to configured services.
- LoadBalance Support Round Robin, Weight Round Robin, Random, Hash by Client IP Address, Hash by HTTP Headers.
- Resilience: Including Timeout/CircuitBreaker/Retryer/Limiter, completely follow sophisticated resilience design.
- Resilience&Fault Tolerance
- Circuit breaker: Temporarily blocks possible failures.
- Rate limiter: Limits the rate of incoming requests.
- Retryer: Repeats failed executions.
- Time limiter: Limits the duration of execution.
- Chaos engineering
- Fault injection Working in progress.
- Delay injection Working in progress.
- Resilience&Fault Tolerance
- Observability:
- Logs
- Access Logs Generate HTTP access log for all requests per service.
- Application log Automatically inject the tracing context into log data.
- Tracing
- JDBC Tracing for invocation of the JDBC.
- HTTP Request Tracing for HTTP RPC.
- Kafka Tracing for messages delivered by Kafka.
- Redis Tracing for Redis cache accessing.
- RabbitMQ Tracing for messages delivered by the RabbitMQ.
- Sampling
- Support probabilistic sampling.
- Support QPS sampling.
- Metrics
- HTTP Request Reporting throughput latency per URL.
- JDBC Reporting throughput and latency per SQL.
- Kafka Reporting throughput and latency per consumer, producer, and topic.
- Redis Reporting throughput and latency per method.
- RabbitMQ Reporting throughput and latency per topic.
- Logs
- Security
- mTLS Working in progress.
- mTLS Enforcement Working in progress.
- External CA certificate Working in progress.
- Service-to-Service Authorization Rules Working in progress.
The throughput is represented by m1, m5, m15 The latency is represented by P99, P98, P95, P90, P80, P75, P50, etc…
Link
For more details, please check EaseMesh.