When the Service Mesh operator createsServiceMeshControlPlane
The resource can also create resources for distributed tracing. Service Mesh uses Jaeger for distributed discovery.
You can specify the Jaeger configuration in two ways:
jaeger configuration i
ServiceMeshControlPlane
resource. There are some limitations with this approach.Configure Jaeger in a custom
jaeger
feature and then referring to the Jaeger example atServiceMeshControlPlane
resource. If a Jaeger resource matches its valuename
exists, the control layer will use the existing installation. This approach allows you to fully customize your Jaeger configuration.
The default Jaeger parameters specified inServiceMeshControlPlane
The following is:
predefinedAll in one
Jaeger parameters
apiVersion: maistra.io/v1friendly: ServiceMeshControlPlanespecification: version: v1.1 good luck: monitoring: activated: right jaeger: model: All in one
Parameter | Description | values | Standard value |
---|---|---|---|
Detection: Enabled: | This parameter enables/disables Service Mesh operator installation and deployment detection. Jaeger installation is enabled by default. To use an existing Jaeger implementation, set this value to |
|
|
jaeger: default: | This parameter determines which Jaeger deployment strategy to use. |
|
|
The standard model i |
Configuring Elasticsearch
The default Jaeger deployment strategy usesAll in one
standard, so that installation can be performed with minimal resources. But whyAll in one
The template uses in-memory storage, is recommended for development, demonstration, or testing purposes only, and is NOT to be used for production environments.
If you are deploying Service Mesh and Jaeger in a production environment, change the template toelastic production research
model, which uses Elasticsearch for Jaeger's storage needs.
Elasticsearch is a memory intensive application. The initial set of nodes specified in the default installation of OpenShift Container Platform might not be large enough to support the Elasticsearch cluster. You must modify the default Elasticsearch configuration to match the use case and requested features for your OpenShift Container Platform installation. You can adjust CPU and memory limits for each component by modifying the resource block with valid CPU and memory values. Additional nodes must be added to the cluster if you want to run with the recommended amount (or more) of memory. Make sure you do not exceed the required resources for installing OpenShift Container Platform.
Default Jaeger "production" parameters with Elasticsearch
apiVersion: maistra.io/v1friendly: ServiceMeshControlPlanespecification: good luck: monitoring: activated: right Prohibited: activated: right jaeger: model: elastic production research looking for elastic: NodeCount: 3 termination policy: resources: forms: Processor: "1" memory: "16" borders: Processor: "1" memory: "16"
Parameter | Description | values | Standard value | Examples |
---|---|---|---|---|
Detection: Enabled: | This parameter enables/disables tracing in Service Mesh. Jaeger is installed by default. |
|
| |
input: enabled: | This parameter enables/disables input for Jaeger. |
|
| |
jaeger: default: | This parameter determines which Jaeger deployment strategy to use. |
|
| |
elasticsearch: nodeCount: | Number of Elasticsearch nodes to create. | Integer value. | 1 | Proof of concept = 1, minimal development = 3 |
requests: cpu: | The number of request processing cores based on your environment configuration. | It is specified in cores or millicolors (eg 200m, 0.5, 1). | 1 Gi | Proof of concept = 500m, minimum development = 1 |
requests: memory: | Memory available for requests based on your environment configuration. | It is specified in bytes (eg 200Ki, 50Mi, 5Gi). | 500m | Proof of concept = 1Gi, minimum implementation = 16Gi* |
limits: cpu: | Limit the number of CPUs based on your environment configuration. | It is specified in cores or millicolors (eg 200m, 0.5, 1). | Proof of concept = 500m, minimum development = 1 | |
limits: memory: | Available memory limit based on your environment configuration. | It is specified in bytes (eg 200Ki, 50Mi, 5Gi). | Proof of concept = 1Gi, minimum implementation = 16Gi* | |
* However, each Elasticsearch node can run with a smaller memory configurationnorecommended for production development. For production use, by default you should have no less than 16 Gi allocated to each pod, but preferably allocate as much as you can, up to 64 Gi per pod. pod. |
Procedure
Log in to the OpenShift Container Platform web console as a user with
cluster administrator
rolle.navigate tooperators→installed operators.
Clique no operador Red Hat OpenShift Service Mesh.
click inService Istio grid control planeear.
Click on the filename of the control layer, for example
basic installation
.click inYAMLear.
Edit Jaeger parameters and override default parameters
All in one
model with parameters forelastic production research
model, modified for your use. Make sure the indentation is correct.cliquesaving.
cliquereplenishmentOpenShift Container Platform reinstalls Jaeger and creates Elasticsearch resources based on the specified parameters.
Connects to an existing Jaeger instance
In order for SMCP to connect to an existing Jaeger instance, the following must be true:
The Jaeger instance is implemented in the same namespace as the control plane, for example in
web system
namespace.To enable secure communication between services, enable the oauth proxy that secures communication with your Jaeger instance and make sure the secret is set for your Jaeger instance so that Kiali can communicate with it.
To use a custom or pre-existing Jaeger instance, click here
spec.istio.tracing.enabled
to "false" to disable the deployment of a Jaeger instance.Give the mixer the correct jaeger sink endpoint with the setting
spec.istio.global.tracer.zipkin.address
in the hostname and port of the jaeger-collector service. Service hostname is normal
.-collector. .svc.cluster.local Provide correct jaeger query endpoint for Kiali to collect configuration traces
spec.istio.kiali.jaegerInClusterURL
in the jaeger-query service hostname - the port is usually not needed as it uses 443 by default. Service hostname is normal
.-request. .svc.cluster.local Enter the control panel URL for your instance of Jaeger on Kiali to allow access to Jaeger via the Kiali console. You can retrieve the OpenShift path URL generated by the Jaeger operator. If your Jaeger resource is called
outside hunter
and lives inweb system
project, you can get the path using the following command:$ and get route-nthis system exterior jaeger
sample output
NAME ΥΠΗΡΕΣΙΕΣ HOST/PORT PATH [...]external-jaeger external-jaeger-istio-system.apps.test external-jaeger-query [...]
price below
HOST/PORT
is the externally accessible URL of the Jaeger control panel.
Jaeger resource example
apiVersion: jaegertracing.io/v1friendly: "Hunter"metadata: name: "External Jaeger" # Expand into the control layer namespace namespace: web systemspecification: # set authentication Prohibited: activated: right security: oauth-proxy open shift: # This restricts user access to the Jaeger instance to users who have access # in the control plane namespace. Make sure you set the correct namespace here sar: '{"namespace": "web system", "resource": "bellows", "verb": "I get"}' htpasswdFil: /etc/proxy/htpasswd/auth Volume Mounts: - name: secret-htpasswd mountPath: /etc/proxy/htpasswd amounts: - name: secret-htpasswd secret: secret name: htpasswd
to followServiceMeshControlPlane
The example assumes that you have implemented Jaeger using the Jaeger operator and the Jaeger resource example.
ExampleServiceMeshControlPlane
with external Jaeger
apiVersion: maistra.io/v1friendly: ServiceMeshControlPlanemetadata: name: outside hunter namespace: web systemspecification: version: v1.1 good luck: monitoring: # Disable the Jaeger implementation of the service mesh handler activated: False global: trace element: zipper: # Define endpoint for collecting tracks address: ekstern-jaeger-collector.istio-system.svc.cluster.local:9411 kiali: # Set the URL to the Jaeger control panel panel: jaegerURL: https://external-jaeger-istio-system.apps.test # Define endpoint for tracking queries jaegerInClusterURL: ekstern-jaeger-query.istio-system.svc.cluster.local
Configuring Elasticsearch
The default Jaeger deployment strategy usesAll in one
standard, so that installation can be performed with minimal resources. But whyAll in one
The template uses in-memory storage, is recommended for development, demonstration, or testing purposes only, and is NOT to be used for production environments.
If you are deploying Service Mesh and Jaeger in a production environment, change the template toelastic production research
model, which uses Elasticsearch for Jaeger's storage needs.
Elasticsearch is a memory intensive application. The initial set of nodes specified in the default installation of OpenShift Container Platform might not be large enough to support the Elasticsearch cluster. You must modify the default Elasticsearch configuration to match the use case and requested features for your OpenShift Container Platform installation. You can adjust CPU and memory limits for each component by modifying the resource block with valid CPU and memory values. Additional nodes must be added to the cluster if you want to run with the recommended amount (or more) of memory. Make sure you do not exceed the required resources for installing OpenShift Container Platform.
Default Jaeger "production" parameters with Elasticsearch
apiVersion: maistra.io/v1friendly: ServiceMeshControlPlanespecification: good luck: monitoring: activated: right Prohibited: activated: right jaeger: model: elastic production research looking for elastic: NodeCount: 3 termination policy: resources: forms: Processor: "1" memory: "16" borders: Processor: "1" memory: "16"
Parameter | Description | values | Standard value | Examples |
---|---|---|---|---|
Detection: Enabled: | This parameter enables/disables tracing in Service Mesh. Jaeger is installed by default. |
|
| |
input: enabled: | This parameter enables/disables input for Jaeger. |
|
| |
jaeger: default: | This parameter determines which Jaeger deployment strategy to use. |
|
| |
elasticsearch: nodeCount: | Number of Elasticsearch nodes to create. | Integer value. | 1 | Proof of concept = 1, minimal development = 3 |
requests: cpu: | The number of request processing cores based on your environment configuration. | It is specified in cores or millicolors (eg 200m, 0.5, 1). | 1 Gi | Proof of concept = 500m, minimum development = 1 |
requests: memory: | Memory available for requests based on your environment configuration. | It is specified in bytes (eg 200Ki, 50Mi, 5Gi). | 500m | Proof of concept = 1Gi, minimum implementation = 16Gi* |
limits: cpu: | Limit the number of CPUs based on your environment configuration. | It is specified in cores or millicolors (eg 200m, 0.5, 1). | Proof of concept = 500m, minimum development = 1 | |
limits: memory: | Available memory limit based on your environment configuration. | It is specified in bytes (eg 200Ki, 50Mi, 5Gi). | Proof of concept = 1Gi, minimum implementation = 16Gi* | |
* However, each Elasticsearch node can run with a smaller memory configurationnorecommended for production development. For production use, by default you should have no less than 16 Gi allocated to each pod, but preferably allocate as much as you can, up to 64 Gi per pod. pod. |
Procedure
Log in to the OpenShift Container Platform web console as a user with
cluster administrator
rolle.(Video) [ Kube 50.1 ] Deploying Istio Service Mesh in Kubernetes using Istioctlnavigate tooperators→installed operators.
Clique no operador Red Hat OpenShift Service Mesh.
click inService Istio grid control planeear.
Click on the filename of the control layer, for example
basic installation
.click inYAMLear.
Edit Jaeger parameters and override default parameters
All in one
model with parameters forelastic production research
model, modified for your use. Make sure the indentation is correct.cliquesaving.
cliquereplenishmentOpenShift Container Platform reinstalls Jaeger and creates Elasticsearch resources based on the specified parameters.
Configure the Elasticsearch index cleanup task
When the Service Mesh operator createsServiceMeshControlPlane
it also creates the custom resource (CR) for the Jaeger. The operator of the Red Hat OpenShift Distributed Discovery Platform uses this CR when creating Jaeger instances.
When you use the Elasticsearch repository, by default a job is created to clean up old traces of it. To configure the options for this task, edit the Jaeger Custom Resource (CR) to suit your usage. Relevant options are listed below.
apiVersion: jaegertracing.io/v1 friendly: jaeger specification: strategy: Production saving: type: looking for elastic esIndexCleaner: activated: False number of days: 7 program: "55 23 * * *"
Parameter | values | Description |
---|---|---|
able: | True or false | Enable or disable index cleanup task. |
number of days: | integer value | Number of days to wait before deleting an index. |
program: | "55 23 * * *" | cron expression to run the job |
For more information on configuring Elasticsearch with OpenShift Container Platform, seeConfigure record storage.
FAQs
What are the features of a service mesh? ›
Common features provided by a service mesh include service discovery, load balancing, encryption and failure recovery. High availability is also common through the use of software controlled by APIs rather than through hardware. Service meshes can make service-to-service communication fast, reliable and secure.
What are the drawbacks of service mesh? ›Some of the drawbacks of service meshes are: The use of a service mesh can increase runtime instances. Communication involves an additional step—the service call first has to run through a sidecar proxy. Service meshes don't support integration with other systems or services.
What's a service mesh and why do I need one? ›tl;dr: A service mesh is a dedicated infrastructure layer for making service-to-service communication safe, fast, and reliable. If you're building a cloud native application, you need a service mesh.
What does service mesh solve? ›A service mesh solves some of the challenges introduced by distributed microservices by abstracting necessary functions (service discovery, connection encryption, error and failure handling, and latency detection and response) to a separate entity called proxy.
What are the two major components of service mesh? ›A service mesh consists of two elements: the data plane and the control plane. As the names suggest, the data plane handles the actual forwarding of traffic, whereas the control plane provides the configuration and coordination.
What are the two types of mesh? ›- Full mesh topology. Every device in the network is connected to all other devices in the network. ...
- Partial mesh topology. Only some of the devices in the network are connected to multiple other devices in the network.
In conclusion, a Service Mesh is not a must for every Cloud-Native Kubernetes-based deployment. It does have a lot of benefits and features out of the box but comes with its own set of challenges that you have to take into consideration before using a Mesh.
What is service mesh in simple terms? ›A Service Mesh is a configurable infrastructure layer that makes communication between microservice applications possible, structured, and observable. A service Mesh also monitors and manages network traffic between microservices, redirecting and granting or limiting access as needed to optimize and protect the system.
What are the advantages and disadvantages of a mesh network? ›- Advantage #1: Prevents Downtime. ...
- Advantage #2: Easy to Install. ...
- Advantage #3: Scales Well. ...
- Advantage #4: Multi-Device Handling is Top-Notch. ...
- Disadvantage #1: Alternative Solutions May Be Better for Some People. ...
- Disadvantage #2: Unattainable for Low-Broadband Regions.
Microservices have specific security needs, such as protection against third-party attacks, flexible access controls, mutual Transport Layer Security (TLS) and auditing tools. Service Mesh offers comprehensive security that gives operators the ability to address all of these issues.
What is the difference between API gateway and service mesh? ›
The API gateway is the component responsible for routing external communications. For example, the API gateway handles chatbot connections, purchase orders and visits to specific pages. Conversely, the service mesh is responsible for internal communications in the system.
What is difference between service mesh and Istio? ›Whereas upstream Istio takes a single tenant approach, Red Hat OpenShift Service Mesh supports multiple independent control planes within the cluster. Red Hat OpenShift Service Mesh uses a multitenant operator to manage the control plane lifecycle.
How do I choose a service mesh? ›- Determine the Need for a Service Mesh Architecture.
- Choose a Base Service Mesh Platform.
- Choose Between Open Source, Commercial, or Managed.
- Testing and Production Deployment.
...
Security
- The authentication of services.
- The encryption of traffic between services.
- Security-specific policy enforcement.
Service meshes generate a visible infrastructure layer that documents the health of different parts of apps as they interact, making it easier to optimize communication and avoid downtime as your app grows.
What are examples of service meshes? ›- Istio. Istio is an extensible open-source service mesh built on Envoy, allowing teams to connect, secure, control, and observe services. ...
- Linkerd. ...
- Consul Connect. ...
- Kuma. ...
- Maesh. ...
- ServiceComb-mesher. ...
- Network Service Mesh (NSM) ...
- OpenShift Service Mesh by Red Hat.
Load balancing.
A service mesh implements more sophisticated Layer 7 (application layer) load balancing, with richer algorithms and more powerful traffic management. Load‑balancing parameters can be modified via API, making it possible to orchestrate blue‑green or canary deployments.
Data Mesh is founded in four principles: "domain-driven ownership of data", "data as a product", "self-serve data platform" and a "federated computational governance".
Which type of mesh is better? ›If the accuracy is of the highest concern then hexahedral mesh is the most preferable one.
What are the three mesh components? ›A 3D mesh model is a collection of vertices, edges, and faces that together form a three-dimensional object. The vertices are the coordinates in three-dimensional space, the edges each connect two adjacent vertices, and the faces (also called polygons ) enclose the edges to form the surface of the object.
What are the levels of mesh? ›
Patch and Element Levels used in manual meshing | |
---|---|
1 | 21 = 2 rectangles on each side, 4 rectangles per surface. |
2 | 22 = 4 rectangles on each side, 16 rectangles per surface. |
3 | 23 = 8 rectangles on each side, 64 rectangles per surface. |
4 | 24 = 16 rectangles on each side, 256 rectangles per surface. |
If you are looking to increase your WiFi speeds overall, a mesh system, or WiFi booster like a range extender, will not improve your Internet speed. They increase coverage.
Is Kubernetes a service mesh? ›A Kubernetes service mesh is a tool that inserts security, observability, and reliability features to applications at the platform layer instead of the application layer.
What is the disadvantage of mesh router? ›The biggest downside to a mesh WiFi router system is that you need to keep routers plugged into outlets in multiple rooms of your home. If you live in an apartment, or older house with fewer outlets, this may be hard to justify. It can also be a little off putting to have WiFi routers strewn throughout your house.
What is a service mesh also known as? ›A service mesh is a mechanism for managing communications between the various individual services that make up modern applications in a microservice-based system.
What is the difference between proxy and service mesh? ›A service mesh handles internal traffic between services inside a cluster, and the proxy is deployed alongside the application. In contrast, an API gateway handles external traffic coming to a cluster — often referred to as north/south communication.
What is the difference between Kubernetes and service mesh? ›Kubernetes is essentially about application lifecycle management through declarative configuration, while a service mesh is essentially about providing inter-application traffic, security management and observability.
Is a mesh network overkill? ›Going for a complete mesh system may be overkill unless you consistently have multiple users and connected devices competing for bandwidth. A Wi-Fi extender can be a worthwhile investment instead if you decide to stay with a traditional home router but need to expand coverage.
Is mesh network better than WiFi? ›In some situations, mesh Wi-Fi can allow for faster speeds, better reliability and greater wireless coverage of your home than a conventional router would. As systems, they're also very scalable and quick to customize.
When should you use a mesh network? ›Mesh routers are worth the price if you have connectivity issues in multiple parts of your home and want an easy way to get a stable, fast, expandable network. However, if just a single room has WiFi issues, it might be more cost-effective to go with an extender paired with a traditional router.
Is service mesh a load balancer? ›
In Mesh, a load balancer is the same as a reverse proxy and is configured to have multiple endpoints for a server. It distributes load of incoming client requests based various scheduling algorithms, for example, round robin, weighted least request, random, ring-hash etc.
Is service mesh a middleware? ›Dedicated infrastructure layer: A service mesh is not designed to solve business issues, but is a dedicated infrastructure layer (middleware).
When shouldn t you use microservices? ›When your application size does not justify the need to split it into many smaller components, using a microservices framework may not be ideal. There's no need to further break down applications that are already small enough as-is.
Why you should use a service mesh with microservices? ›A service mesh helps organizations run microservices at scale by providing: A more flexible release process (for example, support for canary deployments, A/B testing, and blue/green deployments) Availability and resilience (for example, setup retries, failovers, circuit breakers, and fault injection)
Is Istio a service mesh or API gateway? ›One of the most important examples of popular service meshes is Istio, CNCF project, and Linkerd. And keep in mind that you need API gateways to use Service mesh because API Gateways overlap with service mesh for functionality.
Is service mesh a platform? ›Service Mesh Platforms Overview
Service meshes are an infrastructure layer within an application or system that uses the Kubernetes container management platform. They allow microservices to communicate with each other within the application itself.
Linkerd is said to be the lightest and fastest service mesh as of now. It makes running Cloud-Native services easier, more reliable, safer, and more visible by providing observability for all Microservices running in the cluster. All of this without requiring any Microservices source code changes.
What is the best service mesh for Kubernetes? ›- Apache ServiceComb.
- Network Service Mesh (NSM)
- Kiali Operator.
- NGINX Service Mesh.
- Aspen Mesh.
- Open Service Mesh (OSM)
- Grey Matter.
- OpenShift Service Mesh.
SideCars reduce the code complexity by segregating APIs with business logic from code with infrastructure concerns. Service Mesh helps in secure communication by enforcing network policies on the sidecar layer, thus isolating the application layer from rogue traffic.
Is service mesh only for containers? ›The service mesh pattern is only relevant to systems made up of multiple services that communicate over a network. You must have access to all machines or containers that host the services making up the system so that you can deploy the network proxy on them.
What is Istio used for? ›
Istio is an open source service mesh platform that provides a way to control how microservices share data with one another. It includes APIs that let Istio integrate into any logging platform, telemetry, or policy system.
How to implement service mesh in Kubernetes? ›- Sample Application.
- Git Repository.
- Running Our Microservices-Based Project Using Istio and Kubernetes.
- Shadowing.
- Traffic Splitting.
- Canary Deployments.
- A/B Testing.
- Retry Management.
A service mesh, like the open source project Istio, is a way to control how different parts of an application share data with one another. Unlike other systems for managing this communication, a service mesh is a dedicated infrastructure layer built right into an app.
What is a service mesh sidecar? ›Service mesh architecture
It is called a sidecar because a proxy is attached to each application, much like a sidecar attached to a motorbike. In Kubernetes, the application container sits alongside the proxy sidecar container in the same pod.
Istio is an open source service mesh that helps organizations run distributed, microservices-based apps anywhere. Why use Istio? Istio enables organizations to secure, connect, and monitor microservices, so they can modernize their enterprise apps more swiftly and securely.
Is ingress a service mesh? ›Ingress is a Kubernetes API object that manages external access to multiple resources running in a cluster. Most often, these resources are Kubernetes Services. Underneath, Ingress is a kind of proxy, typically for HTTP or HTTPS traffic, so it works at L7, similar to a service mesh.
Which of these features is provided by Istio? ›- Secure cloud-native apps. ...
- Manage traffic effectively. ...
- Monitor service mesh. ...
- Easily deploy with Kubernetes and virtual machines. ...
- Simplify load balancing with advanced features. ...
- Enforce policies.
Service mesh in Kubernetes enables services to detect each other and communicate. It also uses intelligent routing to control API calls and the flow of traffic between endpoints and services. This further enables canaries or rolling upgrades, blue/green, and other advanced deployment strategies.
What are the risks of Istio? ›The Istio control plane, istiod, is vulnerable to a request processing error, allowing a malicious attacker that sends a specially crafted or oversized message, to crash the control plane process. This can be exploited when the Kubernetes validating or mutating webhook service is exposed publicly.
What are the main components of Istio? ›Istio has two components: the data plane and the control plane. The data plane is the communication between services.
What is Istio in layman terms? ›
Istio is an independent, open source service mesh technology that enables developers to connect, secure, control, observe and run a distributed microservice architecture (MSA), regardless of platform, source or vendor. Istio manages service interactions across both container and virtual machine (VM) based workloads.
What is the difference between service mesh Kubernetes and Istio? ›Istio's control plane provides an abstraction layer over the underlying cluster management platform, such as Kubernetes, Mesos, etc. On the other hand, Kubernetes is detailed as "Manage a cluster of Linux containers as a single system to accelerate Dev and simplify Ops".
How do you implement a service mesh? ›To implement a service mesh, you need to deploy the control plane components to a machine in the cluster, inject the data plane proxy alongside each service replica and configure their behavior using policies. In a multi-cluster or multi-zone deployment, a global control plane is used to coordinate across clusters.
Is service mesh a framework? ›Service mesh comes with its own terminology for component services and functions: Container orchestration framework. As more and more containers are added to an application's infrastructure, a separate tool for monitoring and managing the set of containers – a container orchestration framework – becomes essential.
What is the difference between service discovery and service mesh? ›A service mesh works with a service discovery protocol to detect services as they come up. Then, the mesh ages them gracefully when they disappear. Service discovery is a container management framework that keeps a list of instances that are ready to receive requests – or be discovered – by other services.