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commit 2729e56d6f6aea784610e8c267d59f39c1a9b421
Author: wankai123 <wankai...@foxmail.com>
AuthorDate: Tue May 14 15:01:14 2024 +0800

    Add SkyWalking 10 release blog.
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+---
+title: "SkyWalking 10 Release: Service Hierarchy, Kubernetes Network 
Monitoring by eBPF, BanyanDB, and More"
+date: 2024-5-13
+author: Kai Wan, Sheng Wu. tetrate.io
+description: "Introduce what's new in SkyWalking 10, including Service 
Hierarchy, Kubernetes Network Monitoring by eBPF, BanyanDB, and more."
+tags:
+- Release Blog
+- Service Hierarchy
+- Kubernetes
+- eBPF
+- BanyanDB
+---
+
+## Layer and Service Hierarchy
+`Layer` concept was introduced in SkyWalking 9.0.0, it represents an abstract 
framework in computer science, 
+such as Operating System(OS_LINUX layer), Kubernetes(k8s layer). It organizes 
services and metrics into different layers based on their roles
+and responsibilities in the system. SkyWalking provides a suite of monitoring 
and diagnostic tools for each layer, but there is a gap between the layers,
+which can not easily bridge the data across different layers.
+
+In SkyWalking 10, SkyWalking provides new abilities to jump/connect across 
different layers and provide a seamless monitoring experience for users.
+
+### Layer Jump
+In the topology graph, users can click on a service node to jump to the 
dashboard of the service in another layer.
+The following figures show the jump from the `GENERAL` layer service topology 
to the `VIRTUAL_DATABASE` service layer dashboard by clicking the topology node.
+![Figure 1: Layer Jump](layer_jump.jpg)
+Figure 1: Layer Jump</br>
+
+![Figure 2: Layer jump Dashboard](layer_jump2.jpg)
+Figure 2: Layer jump Dashboard
+
+### Service Hierarchy
+SkyWalking 10 introduces a new concept called `Service Hierarchy`, which 
defines the relationships of existing logically same services in various layers.
+OAP will detect the services from different layers, and try to build the 
connections. 
+Users can click the `Hierarchy Services` in any layer's service topology node 
or service dashboard to get the `Hierarchy Topology`.
+In this topology graph, users can see the relationships between the services 
in different layers and the summary of the metrics and also can jump to the 
service dashboard in the layer.
+When a service occurrs performance issue, users can easily analyze the metrics 
from different layers and track down the root cause:
+
+The examples of the `Service Hierarchy` relationships:
+
+1. The application `song` deployed in the Kubernetes cluster with SkyWalking 
agent and Service Mesh at the same time.
+So the application `song` across the `GENERAL`, `MESH`, `MESH_DP` and 
`K8S_SERVICE` layers which could be monitoring by SkyWalking, 
+the `Service Hierarchy` topology as below:
+![Figure 3: Service Hierarchy Agent With K8s Service And Mesh With K8s 
Service](song.jpg)
+Figure 3: Service Hierarchy Agent With K8s Service And Mesh With K8s 
Service.</br>
+</br>
+And can also have the `Service Instance Hierarchy` topology to get the single 
instance status across the layers as below:
+![Figure 4: Instance Hierarchy Agent With K8s Service(Pod)](song_instance.jpg)
+Figure 4: Instance Hierarchy Agent With K8s Service(Pod)</br>
+</br>
+2. The PostgreSQL database `psql` deployed in the Kubernetes cluster and used 
by the application `song`.
+So the database `psql` across the `VIRTUAL_DATABASE`, `POSTGRESQL` and 
`K8S_SERVICE` layers which could be monitoring by SkyWalking, 
+the `Service Hierarchy` topology as below:
+![Figure 5: Service Hierarchy Agent(Virtual Database) With Real Database And 
K8s Service](postgre.jpg)
+Figure 5: Service Hierarchy Agent(Virtual Database) With Real Database And K8s 
Service
+
+For more supported layers and how to detect the relationships between services 
in different layers please refer to the [Service 
Hierarchy](https://skywalking.apache.org/docs/main/latest/en/concepts-and-designs/service-hierarchy/#service-hierarchy).
+how to configure the `Service Hierarchy` in SkyWalking, please refer to the 
[Service Hierarchy 
Configuration](https://skywalking.apache.org/docs/main/latest/en/concepts-and-designs/service-hierarchy-configuration/)
 section.
+
+## [Monitoring Kubernetes Network Traffic by using 
eBPF](https://skywalking.apache.org/blog/2024-03-18-monitor-kubernetes-network-by-ebpf/)
+
+In the previous version, skyWalking provides [Kubernetes (K8s) monitoring from 
kube-state-metrics and 
cAdvisor](https://skywalking.apache.org/docs/main/latest/en/setup/backend/backend-k8s-monitoring-metrics-cadvisor/),
 
+which can monitor the Kubernetes cluster status and the metrics of the 
Kubernetes resources.
+
+In SkyWalking 10, by leverage [Apache SkyWalking 
Rover](https://skywalking.apache.org/docs/skywalking-rover/latest/readme/) 
0.6+, 
+SkyWalking has the ability to monitor the Kubernetes network traffic by using 
eBPF, which can collect and map access logs from applications in Kubernetes 
environments.
+Through these data, SkyWalking can analyze and provide the Service Traffic, 
Topology, TCP/HTTP level metrics from the Kubernetes aspect.
+
+The following figures show the Topology and TCP Dashboard of the Kubernetes 
network traffic:
+
+![Figure 6: Kubernetes Network Traffic Topology](k8s_topology.jpg)
+Figure 6: Kubernetes Network Traffic Topology</br>
+
+![Figure 7: Kubernetes Network Traffic TCP Dashboard](k8s_dashboard.jpg)
+Figure 7: Kubernetes Network Traffic TCP Dashboard</br>
+
+More details about how to monitor the Kubernetes network traffic by using 
eBPF, please refer to the [Monitoring Kubernetes Network Traffic by using 
eBPF](https://skywalking.apache.org/blog/2024-03-18-monitor-kubernetes-network-by-ebpf/).
+
+## BanyanDB - Native APM Database
+[BanyanDB](https://skywalking.apache.org/docs/skywalking-banyandb/latest/readme/)
 0.6.0 and [BanyanDB Java 
client](https://github.com/apache/skywalking-banyandb-java-client) 0.6.0 are 
released with SkyWalking 10, 
+As a native storage solution for SkyWalking, BanyanDB is going to be 
SkyWalking's next-generation storage solution. This is recommended to use for 
medium-scale deployments from 0.6 until 1.0.  
+It has shown high potential performance improvement. Less than 50% CPU usage 
and 50% memory usage with 40% disk volume compared to Elasticsearch in the same 
scale.
+
+## Apache RocketMQ Server Monitoring
+Apache RocketMQ is an open-source distributed messaging and streaming 
platform, which is widely used in various scenarios including Internet, big 
data, mobile Internet, IoT, and other fields.
+SkyWalking provides a basic monitoring dashboard for RocketMQ, which includes 
the following metrics:
+- Cluster Metrics: including messages produced/consumed today, total 
producer/consumer TPS, producer/consumer message size, messages 
produced/consumed until yesterday, max consumer latency, max commitLog disk 
ratio, commitLog disk ratio, pull/send threadPool queue head wait time, topic 
count, and broker count.
+- Broker Metrics: including produce/consume TPS, producer/consumer message 
size.
+- Topic Metrics: including max producer/consumer message size, consumer 
latency, producer/consumer TPS, producer/consumer offset, producer/consumer 
message size, consumer group count, and broker count.
+
+The following figure shows the RocketMQ Cluster Metrics dashboard:
+![Figure 8: Apache RocketMQ Server Monitoring](active_mq.jpg)
+Figure 8: Apache RocketMQ Server Monitoring</br>
+
+For more metrics and details about the RocketMQ monitoring, please refer to 
the [Apache RocketMQ Server 
Monitoring](https://skywalking.apache.org/docs/main/latest/en/setup/backend/backend-rocketmq-monitoring/),
+
+## ClickHouse Server Monitoring
+ClickHouse is an open-source column-oriented database management system that 
allows generating analytical data reports in real-time, it is widely used for 
online analytical processing (OLAP).
+ClickHouse monitoring provides monitoring of the metrics 、events and 
asynchronous metrics of the ClickHouse server, which includes the following 
parts of metrics:
+
+- Server Metrics
+- Query Metrics
+- Network Metrics
+- Insert Metrics
+- Replica Metrics
+- MergeTree Metrics
+- ZooKeeper Metrics
+- Embedded ClickHouse Keeper Metrics
+
+The following figure shows the ClickHouse Cluster Metrics dashboard:
+![Figure 9: ClickHouse Server Monitoring](clickhouse.jpg)
+Figure 9: ClickHouse Server Monitoring</br>
+
+For more metrics and details about the ClickHouse monitoring, please refer to 
the [ClickHouse Server 
Monitoring](https://skywalking.apache.org/docs/main/latest/en/setup/backend/backend-clickhouse-monitoring/),
+and here is a blog that can help for a quick start [Monitoring ClickHouse 
through 
SkyWalking](https://skywalking.apache.org/blog/2024-03-12-monitoring-clickhouse-through-skywalking/).
+
+## Apache ActiveMQ Server Monitoring
+Apache ActiveMQ Classic is a popular and powerful open-source messaging and 
integration pattern server.
+SkyWalking provides a basic monitoring dashboard for ActiveMQ, which includes 
the following metrics:
+- Cluster Metrics: including memory usage, rates of write/read, and 
average/max duration of write.
+- Broker Metrics: including node state, number of connections, number of 
producers/consumers, and rate of write/read under the broker. Depending on the 
cluster mode, one cluster may include one or more brokers.
+- Destination Metrics: including number of producers/consumers, messages in 
different states, queues, and enqueue duration in a queue/topic.
+
+The following figure shows the ActiveMQ Cluster Metrics dashboard:
+![Figure 10: Apache ActiveMQ Server Monitoring](active_mq.jpg)
+Figure 10: Apache ActiveMQ Server Monitoring</br>
+
+For more metrics and details about the ActiveMQ monitoring, please refer to 
the [Apache ActiveMQ Server 
Monitoring](https://skywalking.apache.org/docs/main/latest/en/setup/backend/backend-activemq-monitoring/),
+and here is a blog that can help for a quick start [Monitoring ActiveMQ 
through 
SkyWalking](https://skywalking.apache.org/blog/2024-04-19-monitoring-activemq-through-skywalking/).
+
+## Support Multiple Labels Names
+Before SkyWalking 10, SkyWalking does not store the labels names in the 
metrics data, which makes MQE have to use `_` as the generic label name,
+it can't query the metrics data with multiple labels names.
+
+SkyWalking 10 supports storing the labels names in the metrics data, and MQE 
can query or calculate the metrics data with multiple labels names.
+For example:
+The `k8s_cluster_deployment_status` metric has labels `namespace`, 
`deployment` and `status`.
+If we want to query all deployment metric value with 
`namespace=skywalking-showcase` and `status=true`, we can use the following 
expression:
+```text
+k8s_cluster_deployment_status{namespace='skywalking-showcase', status='true'}
+```
+
+related enhancement:
+- Since Alarm rule configuration had migrated to the MQE in SkyWalking 9.6.0, 
the alarm rule also supports multiple labels names.
+- PromeQL service supports multiple labels names query.
+
+## Metrics gRPC exporter
+SkyWalking 10 enhanced the [metrics gPRC 
exporter](https://skywalking.apache.org/docs/main/latest/en/setup/backend/exporter/#grpc-exporter),
+it supports exporting all type metrics data to the gRPC server.
+
+## SkyWalking Native UI Metrics Query Switch to V3 APIs
+SkyWalking Native UI metrics query deprecate the V2 APIs, and all migrated to 
[V3 
APIs](https://skywalking.apache.org/docs/main/latest/en/api/query-protocol/#v3-apis)
 
+and 
[MQE](https://skywalking.apache.org/docs/main/next/en/api/metrics-query-expression/#metrics-query-expressionmqe-syntax).
+
+## Other Notable Enhancements
+1. Support Java 21 runtime and oap-java21 image for Java 21 runtime.
+2. Remove CLI(`swctl`) from the image.
+3. More MQE functions and operators supported.
+4. Enhance the native UI and improve the user experience.
+5. Several bugs and CVEs fixed.
+
+
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