To support multicluster setups and provide exceptional multicluster routing, discovery, security, scalability, and observability capabilities across clusters, Gloo Mesh Gateway, Gloo Mesh Enterprise, and Gloo Mesh Core share the same relay architecture. The relay architecture consists of a Gloo management server and agents. The management server is commonly installed in a standalone management cluster. The agents are installed in each workload cluster. Workload clusters host your apps, and are registered with the management cluster.

Relay components

Gloo consists of a management server (sometimes called the “relay server”) for the management plane and relay agents for each workload cluster in the data plane.

Management server

After installation, a deployment named gloo-mesh-mgmt-server runs the management server. For your workload clusters to communicate with the management server, the gloo-mesh-mgmt-server service is automatically set up as a service of type LoadBalancer on a default port of 9900/TCP. The server is responsible for configuring the Gloo agents in your workload cluster and maintaining the desired state of your environment. When you create Gloo custom resources, the server translates these to the appropriate open source custom resources that your Gloo product is based on, such as Istio or Envoy. Then, the server pushes config changes to the agents to apply in the workload clusters.

Management server replicas and clusters

By default, the management server is deployed with one replica. To increase availability, you can increase the number of replicas that you deploy in the management cluster.

Additionally, you can create multiple management clusters, and deploy one or more replicas of the management server to each cluster. For more information, see High availability and disaster recovery.

Relay agents

After registration, a deployment named gloo-mesh-agent runs the relay agent on each workload cluster. The relay agent is exposed by the gloo-mesh-agent service on the default port 9977. The agents send snapshots of the resources from each workload cluster to the management server.

Agent replicas

You can add replicas of the agent for higher availability. In such case, leader election affects which processes the agents handle. Logging and metric processes use the most resources, and scale as the number of services within the cluster grows.

The leader agent handles the following processes:

  • Relay
  • Discovery
  • Certificate management
  • Pod bouncing
  • API discovery for Gloo Portal
  • Schema reporter for Gloo Portal

All agent replicas, including the leader, handle the following processes:

  • Access log sink
  • Verifier cache clearing for CRD watch management

Relay communication

Communication between the management server and agents is initiated by the Gloo relay agents, which run in the workload clusters. The following figures outline the general flow of how the relay agents and server communicate to keep your configurations and environment up to date.

Note that these steps outline the relay process in a multicluster setup.

Workload cluster registration

The following image shows the process for registering a workload cluster with the management cluster.

Figure: Registration of Gloo agents with the Gloo management server
  1. During the workload cluster registration process, the Gloo agent in the workload cluster establishes a simple TLS connection to one of the Gloo management server replicas and sends a relay identity token. The relay identity token is a string value that is either generated during the installation of the Gloo management server and copied to the workload cluster, or provided by you in the form of a Kubernetes secret (mTLS setup) or environment variable (TLS setup) to the Gloo management server and agent.
  2. The Gloo management server verifies the relay identity token value. If the agent’s relay identity token matches the management server’s token, the management server registers the agent. In mTLS setups, the management server also issues a client TLS certificate and sends it to the agent.
  3. The Gloo agent initiates a TLS handshake. In mTLS setups, the Gloo agent verifies the identity of the Gloo management server and presents the client TLS certificate to prove its own identity. Only if both parties can be verified successfully, the TLS handshake is complete and the mTLS connection is established.

After the connection is established, the Gloo agent gathers and sends its first discovery input snapshot. For more information about this process, see Custom resource translation.

Management server and agent communication

The relay architecture provides several options for how you can secure the connection between the Gloo management server and agents. For testing environments, Gloo Mesh Enterprise generates self-signed TLS certificates that can be used to establish a simple or mutual TLS connection. For production environments, provide your own TLS certificates instead.

For an overview of supported options, see the Setup options.

Gloo custom resource translation and reconciliation

Learn how Gloo custom resources are translated into Istio, Envoy, or Cilium resources and applied in each workload cluster.

Translation process

The Gloo management server and agents use relay input and output snapshots to exchange information and reconcile the resources that must be applied in each cluster. The input snapshot includes all Gloo resources that the Gloo agent discovered on its local cluster as illustrated in the Discovery input snapshot tab. The Gloo management server translates these resources into Istio, Envoy, or Cilium resources and sends them as an output snapshot to the Gloo agent. To learn more about this process, see the Translation and output snapshot tab.

Translation process with cluster context

Review the following flow diagrams to learn more about how Gloo custom resources are translated when you apply Gloo resources in the management versus the workload clusters.

For more information about how Gloo translates custom resources, see Custom resource translation.

Translation failure scenarios

Translation can fail when individual components of the Gloo relay architecture become unavailable, such as during a restart. Review the following scenarios to understand the impact.

Redis becomes unavailable

Redis is a key component of the Gloo management plane and serves as the single source of truth for translating Gloo custom resources into Istio, Envoy, or Cilium resources. In the event that Redis becomes unavailable, translation continues as the Gloo management server uses the input snapshots that are stored in its local memory.

Flip through the following cards to learn more about this failure scenario.

Gloo agent disconnects

To translate Gloo custom resources based on the complete context of all workload clusters, each connected Gloo agent must send a discovery input snapshot with all discovered entities to the Gloo management server.

Flip through the cards to learn how translation continues if one of the Gloo agents disconnects.

Gloo management server replica unavailable

When the Gloo agent connects to the Gloo management server, a management server replica is assigned and used to establish the simple TLS or mutual TLS connection with the Gloo agent. The Gloo agent then sends an input snapshot that contains all discovered entities from its local cluster.

Flip through the cards to learn how translation continues if the assigned Gloo management server replica becomes unavailable.

Redis and Gloo management server restart

In the following scenario, Redis and the Gloo management server become unavailable at the same time, which removes all input snapshots from the Redis cache and the management server’s local memory. While Gloo agents try to reconnect, partial translation can occur.

Flip through the cards to learn more about this failure scenario.

Safe mode

In version 2.5.3, 2.4.11, and earlier a race condition was identified that could trigger during simultaneous restarts of the management plane and Redis, including an upgrade to a newer Gloo Mesh Enterprise version. If hit, this failure mode can lead to partial translations on the Gloo management server which can result in Istio resources being temporarily deleted from the output snapshots that are sent to the Gloo agents. To learn more about this failure scenario, see Redis and Gloo management server restart.

To resolve this issue, you can use the safe mode feature to ensure that the Gloo management server translates input snapshots only if all input snapshots are present in Redis or its local memory. This way, translation only occurs based on a complete translation context.

Safe mode can be configured in two ways:

Option 1: Safe mode

In the event that Redis and the Gloo management server restart simultaneously and only some agents reconnect successfully to re-populate their input snapshots in Redis and the management server’s local memory, the management server halts translation. Translation does not resume until the agents in each workload cluster reconnect to the management server and their input snapshots are re-populated in Redis. Until translation resumes, the agents use the last provided output snapshot.

To enable this setting, follow these general upgrade steps.

  1. Scale down the number of Gloo management server pods to 0.

      kubectl scale deployment gloo-mesh-mgmt-server --replicas=0 -n gloo-mesh
      
  2. Upgrade your Gloo Mesh Enterprise installation. Add the following settings in the Helm values file for the Gloo management plane.

      
    glooMgmtServer:
      safeMode: true
      
  3. Scale the Gloo management server back up to the number of desired replicas. The following example uses 1 replica.

      kubectl scale deployment gloo-mesh-mgmt-server --replicas=1 -n gloo-mesh
      

Review how safe mode works in the event that Redis and the Gloo management server restart, and only some of the Gloo agents reconnect. For more information about this scenario, see Redis and Gloo management server restart.

Option 2: Safe start window

With safe mode, the Gloo management server halts translation until the input snapshots of all workload clusters that were previously connected to the Gloo management server are present in the Redis cache. However, if clusters have connectivity issues, translation might be halted for a long time, even for healthy clusters. You might want translation to resume after a certain period of time, even if some input snapshots are missing. To do so, use the glooMgmtServer.safeStartWindow field in your Gloo management server Helm values file.

The safe start window represents the time in seconds that the Gloo management server halts translation until the Gloo agents of all workload clusters connect and send their input snapshots to populate the Redis cache. As such, the safe start window behaves the same as safe mode. After the time expires, the management server starts translation by using the input snapshots that are currently present in Redis. Missing snapshots are not included in the output snapshot for each workload cluster.

The default wait time of the Gloo management server is 180 seconds. If you do not want the management server to wait, you can set this option to 0 (zero). However, keep in mind that setting this option to 0 can lead to incomplete output snapshots in multicluster setups.

To set a safe start window, follow these general upgrade steps. Note that you must disable safe mode for the safe start window to take effect.

  1. Scale down the number of Gloo management server pods to 0.

      kubectl scale deployment gloo-mesh-mgmt-server --replicas=0 -n gloo-mesh
      
  2. Upgrade your Gloo Mesh Enterprise installation. Add the following settings in the Helm values file for the Gloo management plane.

      
    glooMgmtServer:
      safeMode: false
      safeStartWindow: 90
      
  3. Scale the Gloo management server back up to the number of desired replicas. The following example uses 1 replica.

      kubectl scale deployment gloo-mesh-mgmt-server --replicas=1 -n gloo-mesh
      

Exclude clusters from safe mode

You can optionally exclude clusters from safe mode by adding the skipWarming option to the KubernetesCluster custom resource that represents the cluster that you want to exclude. The skipWarming setting instructs the Gloo management server to not trigger safe mode and to start the translation, even if the Redis cache was not populated with the latest input snapshot for that cluster.

  
kubectl apply --context $MGMT_CONTEXT -f- <<EOF
apiVersion: admin.gloo.solo.io/v2
kind: KubernetesCluster
metadata:
  name: $REMOTE_CLUSTER1
  namespace: gloo-mesh
  labels:
    env: prod
spec:
  clusterDomain: cluster.local
  skipWarming: true
EOF
  

For example, you might want to register a new workload cluster. During the registration process, the KubernetesCluster is created. However, the agent in the workload cluster cannot connect to the management server due to a connectivity issue. If safe mode is turned on, the translation for all workload clusters halts until the connectivity issue is resolved and an input snapshot is sent from the newly registered cluster so that the Redis cache is populated. You can prevent this scenario by setting skipWarming: true in the KubernetesCluster resource of the workload cluster that you want to register. After the workload cluster connects successfully, you can remove this setting or explicitly set skipWarming: false to include the cluster in the safe mode.

Indefinite safe mode

Safe mode is intended to be a temporary state that is triggered when multiple management plane components are simultaneously restarted. Most of the time, safe mode resolves automatically as soon as all the management plane components come back healthy and the Redis cache is re-populated with the input snapshots of all agents.

However, safe mode might not get automatically resolved due to the following reasons:

  • One or more Gloo agents fail to reconnect with the Gloo management server, such as due to failing to schedule, insufficient resources, network errors, or getting rejected by the management server due to capacity issues.
  • Redis remains unstable, such as due to insufficient resources.
  • A KubernetesCluster resource was added to the Gloo management server. However, the corresponding Gloo agent is not yet set up on the workload cluster.

If any of these conditions are met, safe mode might stay intact, and translation is halted indefinitely for all connected Gloo agents. To resolve this issue, you can choose between the following options:

  • Resolve the issue that prevents the Gloo agent from reconnecting. For example, if the cluster that the Gloo agent is deployed to has insufficient resources, add the required resources. If the error is due to issue in the network, try to resolve the network error.
  • Deregister the affected workload cluster by removing the KubernetesCluster resource that represents the workload cluster.
  • Exclude the affected cluster from safe mode.

Monitor safe mode

You have multiple options to monitor if safe mode was triggered in your cluster.

Gloo UI

If a workload cluster triggered the Gloo management server to run in safe mode, a banner is shown in the Gloo UI. The banner includes the details about the workload clusters that triggered safe mode. You can use this information to investigate connectivity issues for these clusters and to troubleshoot potential Redis or Gloo management server issues.

Open the Gloo UI. The Gloo UI is served from the gloo-mesh-ui service on port 8090. You can connect by using the meshctl or kubectl CLIs.

  • meshctl: For more information, see the CLI documentation.
      meshctl dashboard
      
  • kubectl:
    1. Port-forward the gloo-mesh-ui service on 8090.
        kubectl port-forward -n gloo-mesh svc/gloo-mesh-ui 8090:8090
        
    2. Open your browser and connect to http://localhost:8090.

Metrics

You can use the gloo_mesh_safe_mode_active metric to determine if your environment currently runs in safe mode and the workload clusters that triggered safe mode. This metric is automatically collected by the Gloo telemetry pipeline and you can use the built-in Prometheus server to view this metric or run queries on that metric.

  1. Port-forward the Prometheus pod in your cluster to open the Prometheus expression browser.

  2. Run the following query to determine if your environment is currently running in safe mode, and the workload cluster that triggered it.

      count by(cluster) (sum by(cluster) (gloo_mesh_safe_mode_active !=0)) > 0
      
  3. When you run multiple replicas of the Gloo management server, you might have some replicas in safe mode and others are not. You can use the following Prometheus query to determine which workload clusters are currently connected to a management replica that runs in safe mode.

      count by(cluster) ((relay_pull_clients_connected != 0) * on(pod) group_left() (max(gloo_mesh_safe_mode_active) by (pod) >= 1)) > 0
      

KubernetesCluster resource

Safe mode is applied to workload clusters that were initially connected to the Gloo management server and sent at least one input snapshot. If a workload cluster is registered, but the Gloo agent never connected to the Gloo management server to send its first input snapshot, the cluster is not included in safe mode.

To find out if a cluster was connected to the Gloo management server, you can review the condition of the KubernetesCluster resource that represents the workload cluster. The KubernetesCluster resource can have the following conditions:

ReasonStatusTypeDescriptionIncluded in safe mode?
ClusterRegisteredFalseClusterWarmThe KubernetesCluster resource is created, but no snapshot was received from the Gloo agent yet.
FirstSnapshotReceivedTrueClusterWarmThe Gloo agent connected successfully to the Gloo management server and sent its first input snapshot. Note that this status is final and does not change, even if the Gloo agent disconnects or the Gloo management server becomes unavailable.



The following snippet shows an example for a cluster that successfully sent an input snapshot and therefore is included in safe mode.

  
conditions:
  - lastTransitionTime: "2024-04-30T15:47:06.011421879Z"
    message: The agent successfully connected to the management server and an agent
      input snapshot was stored in Redis
    reason: FirstSnapshotReceived
    status: "True"
    type: ClusterWarm