Merge branch 'v1.4' into local_secret_store_multivalued_1733

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Phil Kedy 2021-08-25 14:14:58 -04:00 committed by GitHub
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.github/workflows/dapr-bot.yml vendored Normal file
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@ -0,0 +1,32 @@
name: dapr-bot
on:
issue_comment: {types: created}
jobs:
daprbot:
name: bot-processor
runs-on: ubuntu-latest
steps:
- name: Comment analyzer
uses: actions/github-script@v1
with:
github-token: ${{secrets.DAPR_BOT_TOKEN}}
script: |
const payload = context.payload;
const issue = context.issue;
const isFromPulls = !!payload.issue.pull_request;
const commentBody = payload.comment.body;
if (!isFromPulls && commentBody && commentBody.indexOf("/assign") == 0) {
if (!issue.assignees || issue.assignees.length === 0) {
await github.issues.addAssignees({
owner: issue.owner,
repo: issue.repo,
issue_number: issue.number,
assignees: [context.actor],
})
}
return;
}

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@ -1,6 +1,6 @@
---
type: docs
title: "Dapr Concepts"
title: "Dapr concepts"
linkTitle: "Concepts"
weight: 10
description: "Learn about Dapr including its main features and capabilities"

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@ -0,0 +1,7 @@
---
type: docs
title: "Overview of the Dapr services"
linkTitle: "Dapr services"
weight: 800
description: "Learn about the services that make up the Dapr runtime"
---

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@ -0,0 +1,12 @@
---
type: docs
title: "Dapr operator service overview"
linkTitle: "Operator"
description: "Overview of the Dapr operator process"
---
When running Dapr in [Kubernetes mode]({{< ref kubernetes >}}), a pod running the Dapr operator service manages [Dapr component]({{< ref components >}}) updates and provides Kubernetes services endpoints for Dapr.
## Running the operator service
The operator service is deployed as part of `dapr init -k`, or via the Dapr Helm charts. For more information on running Dapr on Kubernetes, visit the [Kubernetes hosting page]({{< ref kubernetes >}}).

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@ -0,0 +1,16 @@
---
type: docs
title: "Dapr placement service overview"
linkTitle: "Placement"
description: "Overview of the Dapr placement process"
---
The Dapr placement service is used to calculate and distribute distributed hash tables for the location of [Dapr actors]({{< ref actors >}}) running in [self-hosted mode]({{< ref self-hosted >}}) or on [Kubernetes]({{< ref kubernetes >}}). This hash table maps actor IDs to pods or processes so a Dapr application can communicate with the actor.Anytime a Dapr application activates a Dapr actor, the placement updates the hash tables with the latest actor locations.
## Self-hosted mode
The placement service Docker container is started automatically as part of [`dapr init`]({{< ref self-hosted-with-docker.md >}}). It can also be run manually as a process if you are running in [slim-init mode]({{< ref self-hosted-no-docker.md >}}).
## Kubernetes mode
The placement service is deployed as part of `dapr init -k`, or via the Dapr Helm charts. For more information on running Dapr on Kubernetes, visit the [Kubernetes hosting page]({{< ref kubernetes >}}).

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@ -0,0 +1,26 @@
---
type: docs
title: "Dapr sentry service overview"
linkTitle: "Sentry"
description: "Overview of the Dapr sentry process"
---
The Dapr sentry service manages mTLS between services and acts as a certificate authority. It generates mTLS certificates and distributes them to any running sidecars. This allows sidecars to communicate with encrypted, mTLS traffic. For more information read the [sidecar-to-sidecar communication overview]({{< ref "security-concept.md#sidecar-to-sidecar-communication" >}}).
## Self-hosted mode
The sentry service Docker container is started automatically as part of [`dapr init`]({{< ref self-hosted-with-docker.md >}}). It can also be run manually as a process if you are running in [slim-init mode]({{< ref self-hosted-no-docker.md >}}).
<img src="/images/security-mTLS-sentry-selfhosted.png" width=1000>
## Kubernetes mode
The sentry service is deployed as part of `dapr init -k`, or via the Dapr Helm charts. For more information on running Dapr on Kubernetes, visit the [Kubernetes hosting page]({{< ref kubernetes >}}).
<img src="/images/security-mTLS-sentry-kubernetes.png" width=1000>
## Further reading
- [Security overview]({{< ref security-concept.md >}})
- [Self-hosted mode]({{< ref self-hosted-with-docker.md >}})
- [Kubernetes mode]({{< ref kubernetes >}})

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@ -0,0 +1,12 @@
---
type: docs
title: "Dapr sidecar injector overview"
linkTitle: "Sidecar injector"
description: "Overview of the Dapr sidecar injector process"
---
When running Dapr in [Kubernetes mode]({{< ref kubernetes >}}), a pod is created running the dapr-sidecar-injector service, which looks for pods initialized with the [Dapr annotations]({{< ref arguments-annotations-overview.md >}}), and then creates another container in that pod for the [daprd service]({{< ref sidecar >}})
## Running the sidecar injector
The sidecar injector service is deployed as part of `dapr init -k`, or via the Dapr Helm charts. For more information on running Dapr on Kubernetes, visit the [Kubernetes hosting page]({{< ref kubernetes >}}).

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@ -0,0 +1,51 @@
---
type: docs
title: "Dapr sidecar (daprd) overview"
linkTitle: "Sidecar"
weight: 100
description: "Overview of the Dapr sidecar process"
---
Dapr uses a [sidecar pattern]({{< ref "overview.md#sidecar-architecture" >}}), meaning the Dapr APIs are run and exposed on a separate process (i.e. the Dapr sidecar) running alongside your application. The Dapr sidecar process is named `daprd` and is launched in different ways depending on the hosting environment.
<img src="/images/overview-sidecar-model.png" width=700>
## Self-hosted with `dapr run`
When Dapr is installed in [self-hosted mode]({{<ref self-hosted>}}), the `daprd` binary is downloaded and placed under the user home directory (`$HOME/.dapr/bin` for Linux/MacOS or `%USERPROFILE%\.dapr\bin\` for Windows). In self-hosted mode, running the Dapr CLI [`run` command]({{< ref dapr-run.md >}}) launches the `daprd` executable together with the provided application executable. This is the recommended way of running the Dapr sidecar when working locally in scenarios such as development and testing. The various arguments the CLI exposes to configure the sidecar can be found in the [Dapr run command reference]({{<ref dapr-run>}}).
## Kubernetes with `dapr-sidecar-injector`
On [Kubernetes]({{< ref kubernetes.md >}}), the Dapr control plane includes the [dapr-sidecar-injector service]({{< ref kubernetes-overview.md >}}), which watches for new pods with the `dapr.io/enabled` annotation and injects a container with the `daprd` process within the pod. In this case, sidecar arguments can be passed through annotations as outlined in the **Kubernetes annotations** column in [this table]({{<ref arguments-annotations-overview>}}).
## Running the sidecar directly
In most cases you do not need to run `daprd` explicitly, as the sidecar is either launched by the CLI (self-hosted mode) or by the dapr-sidecar-injector service (Kubernetes). For advanced use cases (debugging, scripted deployments, etc.) the `daprd` process can be launched directly.
For a detailed list of all available arguments run `daprd --help` or see this [table]({{< ref arguments-annotations-overview.md >}}) which outlines how the `daprd` arguments relate to the CLI arguments and Kubernetes annotations.
### Examples
1. Start a sidecar along an application by specifying its unique ID. Note `--app-id` is a required field:
```bash
daprd --app-id myapp
```
2. Specify the port your application is listening to
```bash
daprd --app-id --app-port 5000
```
3. If you are using several custom components and want to specify the location of the component definition files, use the `--components-path` argument:
```bash
daprd --app-id myapp --components-path <PATH-TO-COMPONENTS-FILES>
```
4. Enable collection of Prometheus metrics while running your app
```bash
daprd --app-id myapp --enable-metrics
```

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@ -9,7 +9,9 @@ description: >
Dapr is a portable, event-driven runtime that makes it easy for any developer to build resilient, stateless and stateful applications that run on the cloud and edge and embraces the diversity of languages and developer frameworks.
<iframe width="1120" height="630" src="https://www.youtube.com/embed/9o9iDAgYBA8" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
<div class="embed-responsive embed-responsive-16by9">
<iframe width="1120" height="630" src="https://www.youtube.com/embed/9o9iDAgYBA8" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
</div>
## Any language, any framework, anywhere

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@ -35,6 +35,8 @@ Watch these recordings from the Dapr community calls showing presentations on ru
- General overview and a demo of [Dapr and Linkerd](https://youtu.be/xxU68ewRmz8?t=142)
- Demo of running [Dapr and Istio](https://youtu.be/ngIDOQApx8g?t=335)
Also, learn more about [running Dapr with Open Service Mesh (OSM)]({{<ref open-service-mesh>}}).
## When to choose using Dapr, a service mesh, or both
Should you be using Dapr, a service mesh, or both? The answer depends on your requirements. If, for example, you are looking to use Dapr for one or more building blocks such as state management or pub/sub, and you are considering using a service mesh just for network security or observability, you may find that Dapr is a good fit and that a service mesh is not required.

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@ -2,7 +2,7 @@
type: docs
title: "Dapr terminology and definitions"
linkTitle: "Terminology"
weight: 800
weight: 900
description: Definitions for common terms and acronyms in the Dapr documentation
---

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@ -137,7 +137,9 @@ The number of repetitions i.e. the number of times the reminder is run should be
Watch this [video](https://www.youtube.com/watch?v=B_vkXqptpXY&t=1002s) for more information on using ISO 861 for Reminders
<div class="embed-responsive embed-responsive-16by9">
<iframe width="560" height="315" src="https://www.youtube.com/embed/B_vkXqptpXY?start=1003" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
</div>
#### Retrieve actor reminder

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@ -10,8 +10,10 @@ Output bindings enable you to invoke external resources without taking dependenc
For a complete sample showing output bindings, visit this [link](https://github.com/dapr/quickstarts/tree/master/bindings).
Watch this [video](https://www.youtube.com/watch?v=ysklxm81MTs&feature=youtu.be&t=1960) on how to use bi-directional output bindings.
<iframe width="560" height="315" src="https://www.youtube.com/embed/ysklxm81MTs?start=1960" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
<div class="embed-responsive embed-responsive-16by9">
<iframe width="560" height="315" src="https://www.youtube.com/embed/ysklxm81MTs?start=1960" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
</div>
## 1. Create a binding

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@ -416,6 +416,10 @@ app.post('/dsstatus', (req, res) => {
{{< /tabs >}}
{{% alert title="Note on message redelivery" color="primary" %}}
Some pubsub components (e.g. Redis) will redeliver a message if a response is not sent back within a specified time window. Make sure to configure metadata such as `processingTimeout` to customize this behavior. For more information refer to the respective [component references]({{< ref supported-pubsub >}}).
{{% /alert %}}
## (Optional) Step 5: Publishing a topic with code
{{< tabs Node PHP>}}

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@ -93,7 +93,7 @@ Similarly, if two different applications (different app-IDs) subscribe to the sa
### Topic scoping
By default, all topics backing the Dapr pub/sub component (e.g. Kafka, Redis Stream, RabbitMQ) are available to every application configured with that component. To limit which application can publish or subscribe to topics, Dapr provides topic scoping. This enables to you say which topics an application is allowed to published and which topics an application is allowed to subscribed to. For more information read [publish/subscribe topic scoping]({{< ref pubsub-scopes.md >}}).
By default, all topics backing the Dapr pub/sub component (e.g. Kafka, Redis Stream, RabbitMQ) are available to every application configured with that component. To limit which application can publish or subscribe to topics, Dapr provides topic scoping. This enables to you say which topics an application is allowed to publish and which topics an application is allowed to subscribe to. For more information read [publish/subscribe topic scoping]({{< ref pubsub-scopes.md >}}).
### Message Time-to-Live (TTL)
Dapr can set a timeout message on a per message basis, meaning that if the message is not read from the pub/sub component, then the message is discarded. This is to prevent the build up of messages that are not read. A message that has been in the queue for longer than the configured TTL is said to be dead. For more information read [publish/subscribe message time-to-live]({{< ref pubsub-message-ttl.md >}}).

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@ -158,7 +158,9 @@ The table below shows which application is allowed to subscribe to the topics:
## Demo
<div class="embed-responsive embed-responsive-16by9">
<iframe width="560" height="315" src="https://www.youtube.com/embed/7VdWBBGcbHQ?start=513" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
</div>
## Related links

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@ -14,7 +14,10 @@ To limit the secrets to which the Dapr application has access to, you can define
The secret scoping policy applies to any [secret store]({{< ref supported-secret-stores.md >}}), whether that is a local secret store, a Kubernetes secret store or a public cloud secret store. For details on how to set up a [secret stores]({{< ref setup-secret-store.md >}}) read [How To: Retrieve a secret]({{< ref howto-secrets.md >}})
Watch this [video](https://youtu.be/j99RN_nxExA?start=2272) for a demo on how to use secret scoping with your application.
<div class="embed-responsive embed-responsive-16by9">
<iframe width="688" height="430" src="https://www.youtube.com/embed/j99RN_nxExA?start=2272" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
</div>
## Scenario 1 : Deny access to all secrets for a secret store

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@ -18,13 +18,13 @@ Dapr allows you to assign a global, unique ID for your app. This ID encapsulates
In self hosted mode, set the `--app-id` flag:
```bash
dapr run --app-id cart --app-port 5000 python app.py
dapr run --app-id cart --dapr-http-port 3500 --app-port 5000 python app.py
```
If your app uses an SSL connection, you can tell Dapr to invoke your app over an insecure SSL connection:
```bash
dapr run --app-id cart --app-port 5000 --app-ssl python app.py
dapr run --app-id cart --dapr-http-port 3500 --app-port 5000 --app-ssl python app.py
```
{{% /codetab %}}

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@ -21,7 +21,7 @@ When a TTL is not specified the default behavior of the state store is retained.
## Persisting state (ignoring an existing TTL)
To explictly persist a state (ignoring any TTLs set for the key), specify a `ttlInSeconds` value of `-1`.
To explicitly persist a state (ignoring any TTLs set for the key), specify a `ttlInSeconds` value of `-1`.
## Supported components

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@ -14,7 +14,9 @@ Bridge to Kubernetes allows you to run and debug code on your development comput
Bridge to Kubernetes supports debugging Dapr apps on your machine, while still having them interact with the services and applications running on your Kubernetes cluster. This example showcases Bridge to Kubernetes enabling a developer to debug the [distributed calculator quickstart](https://github.com/dapr/quickstarts/tree/master/distributed-calculator):
<div class="embed-responsive embed-responsive-16by9">
<iframe width="560" height="315" src="https://www.youtube.com/embed/rxwg-__otso" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
</div>
{{% alert title="Isolation mode" color="warning" %}}
[Isolation mode](https://aka.ms/bridge-isolation-vscode-dapr) is currently not supported with Dapr apps. Make sure to launch Bridge to Kubernetes mode without isolation.

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@ -63,4 +63,7 @@ Using the VS Code extension, you can debug multiple Dapr applications at the sam
### Community call demo
Watch this [video](https://www.youtube.com/watch?v=OtbYCBt9C34&t=85) on how to use the Dapr VS Code extension:
<div class="embed-responsive embed-responsive-16by9">
<iframe width="560" height="315" src="https://www.youtube.com/embed/OtbYCBt9C34?start=85" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
</div>

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@ -28,4 +28,7 @@ Dapr has pre-built Docker remote containers for NodeJS and C#. You can pick the
#### Example
Watch this [video](https://www.youtube.com/watch?v=D2dO4aGpHcg&t=120) on how to use the Dapr VS Code Remote Containers with your application.
<div class="embed-responsive embed-responsive-16by9">
<iframe width="560" height="315" src="https://www.youtube.com/embed/D2dO4aGpHcg?start=120" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
</div>

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@ -22,7 +22,9 @@ Users are able to leverage both OSM SMI traffic policies and Dapr capabilities o
Watch the OSM team present the OSM and Dapr integration in the 05/18/2021 community call:
<div class="embed-responsive embed-responsive-16by9">
<iframe width="560" height="315" src="https://www.youtube.com/embed/LSYyTL0nS8Y?start=1916" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
</div>
## Additional resources

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@ -221,7 +221,9 @@ Prerequisites:
Watch an example from the Dapr community call:
<div class="embed-responsive embed-responsive-16by9">
<iframe width="560" height="315" src="https://www.youtube.com/embed/7fP-0Ixmi-w?start=116" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
</div>
## Additional resources

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@ -125,6 +125,9 @@ spec:
secretKeyRef:
name: redis
key: redis-password
# uncomment below for connecting to redis cache instances over TLS (ex - Azure Redis Cache)
# - name: enableTLS
# value: true
```
This example uses the kubernetes secret that was created when setting up a cluster with the above instructions.
@ -153,6 +156,9 @@ spec:
secretKeyRef:
name: redis
key: redis-password
# uncomment below for connecting to redis cache instances over TLS (ex - Azure Redis Cache)
# - name: enableTLS
# value: true
```
This example uses the kubernetes secret that was created when setting up a cluster with the above instructions.
@ -179,6 +185,9 @@ spec:
value: <HOST>
- name: redisPassword
value: <PASSWORD>
# uncomment below for connecting to redis cache instances over TLS (ex - Azure Redis Cache)
# - name: enableTLS
# value: true
```
```yaml
@ -195,6 +204,9 @@ spec:
value: <HOST>
- name: redisPassword
value: <PASSWORD>
# uncomment below for connecting to redis cache instances over TLS (ex - Azure Redis Cache)
# - name: enableTLS
# value: true
```
## Apply the configuration

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@ -119,7 +119,9 @@ scopes:
## Example
<div class="embed-responsive embed-responsive-16by9">
<iframe width="560" height="315" src="https://www.youtube.com/embed/8W-iBDNvCUM?start=1763" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
</div>
## Related links

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@ -14,7 +14,10 @@ Using Dapr, you can control how many requests and events will invoke your applic
*Note that rate limiting per second can be achieved by using the **middleware.http.ratelimit** middleware. However, there is an imporant difference between the two approaches. The rate limit middlware is time bound and limits the number of requests per second, while the `app-max-concurrency` flag specifies the number of concurrent requests (and events) at any point of time. See [Rate limit middleware]({{< ref middleware-rate-limit.md >}}). *
Watch this [video](https://youtu.be/yRI5g6o_jp8?t=1710) on how to control concurrency and rate limiting ".
<div class="embed-responsive embed-responsive-16by9">
<iframe width="764" height="430" src="https://www.youtube.com/embed/yRI5g6o_jp8?t=1710" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
</div>
## Setting app-max-concurrency

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@ -11,7 +11,10 @@ Access control enables the configuration of policies that restrict what operatio
An access control policy is specified in configuration and be applied to Dapr sidecar for the *called* application. Example access policies are shown below and access to the called app is based on the matched policy action. You can provide a default global action for all calling applications and if no access control policy is specified, the default behavior is to allow all calling applications to access to the called app.
Watch this [video](https://youtu.be/j99RN_nxExA?t=1108) on how to apply access control list for service invocation.
<div class="embed-responsive embed-responsive-16by9">
<iframe width="688" height="430" src="https://www.youtube.com/embed/j99RN_nxExA?start=1108" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
</div>
## Concepts

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@ -1,6 +1,6 @@
---
type: docs
title: "Run Dapr in Self Hosted Mode"
title: "Run Dapr in self-hosted mode"
linkTitle: "Self-Hosted"
weight: 1000
description: "How to get Dapr up and running in your local environment"

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@ -74,5 +74,5 @@ By default, tailing is set to /var/log/containers/*.log. To change this setting,
* [New Relic Account Signup](https://newrelic.com/signup)
* [Telemetry Data Platform](https://newrelic.com/platform/telemetry-data-platform)
* [New Relic Logging](https://github.com/newrelic/helm-charts/tree/master/charts/newrelic-logging)
* [Types of New Relic API keys](https://docs.newrelic.com/docs/apis/intro-apis/new-relic-api-keys)
* [Types of New Relic API keys](https://docs.newrelic.com/docs/apis/intro-apis/new-relic-api-keys/)
* [Alerts and Applied Intelligence](https://docs.newrelic.com/docs/alerts-applied-intelligence)

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@ -173,4 +173,7 @@ First you need to connect Prometheus as a data source to Grafana.
* [Supported Dapr metrics](https://github.com/dapr/dapr/blob/master/docs/development/dapr-metrics.md)
## Example
<div class="embed-responsive embed-responsive-16by9">
<iframe width="560" height="315" src="https://www.youtube.com/embed/8W-iBDNvCUM?start=2577" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
</div>

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@ -22,7 +22,7 @@ This document explains how to install it in your cluster, either using a Helm ch
2. Add the New Relic official Helm chart repository following [these instructions](https://github.com/newrelic/helm-charts/blob/master/README.md#installing-charts)
3. Run the following command to install the New Relic Logging Kubernetes plugin via Helm, replacing the placeholder value YOUR_LICENSE_KEY with your [New Relic license key](https://docs.newrelic.com/docs/accounts/accounts-billing/account-setup/new-relic-license-key/):
3. Run the following command to install the New Relic Logging Kubernetes plugin via Helm, replacing the placeholder value YOUR_LICENSE_KEY with your [New Relic license key](https://docs.newrelic.com/docs/accounts/accounts-billing/account-setup/new-relic-license-key):
```bash
helm install nri-prometheus newrelic/nri-prometheus --set licenseKey=YOUR_LICENSE_KEY
@ -39,5 +39,5 @@ This document explains how to install it in your cluster, either using a Helm ch
* [New Relic Account Signup](https://newrelic.com/signup)
* [Telemetry Data Platform](https://newrelic.com/platform/telemetry-data-platform)
* [New Relic Prometheus OpenMetrics Integration](https://github.com/newrelic/helm-charts/tree/master/charts/nri-prometheus)
* [Types of New Relic API keys](https://docs.newrelic.com/docs/apis/intro-apis/new-relic-api-keys)
* [Types of New Relic API keys](https://docs.newrelic.com/docs/apis/intro-apis/new-relic-api-keys/)
* [Alerts and Applied Intelligence](https://docs.newrelic.com/docs/alerts-applied-intelligence)

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@ -111,7 +111,10 @@ dapr-prom-prometheus-server-694fd8d7c-q5d59 2/2 Running 0
```
## Example
<iframe width="560" height="315" src="https://www.youtube.com/embed/8W-iBDNvCUM?start=2577" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
<div class="embed-responsive embed-responsive-16by9">
<iframe width="560" height="315" src="https://www.youtube.com/embed/8W-iBDNvCUM?start=2577" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
</div>
## References

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@ -7,16 +7,13 @@ description: "Set up Jaeger for distributed tracing"
type: docs
---
Dapr currently supports the Zipkin protocol. Since Jaeger is
compatible with Zipkin, the Zipkin protocol can be used to talk to
Jaeger.
Dapr supports the Zipkin protocol. Since Jaeger is compatible with Zipkin, the Zipkin protocol can be used to communication with Jaeger.
## Configure self hosted mode
### Setup
The simplest way to start Jaeger is to use the pre-built all-in-one
Jaeger image published to DockerHub:
The simplest way to start Jaeger is to use the pre-built all-in-one Jaeger image published to DockerHub:
```bash
docker run -d --name jaeger \
@ -55,15 +52,19 @@ dapr run --app-id mynode --app-port 3000 node app.js --config config.yaml
```
### Viewing Traces
To view traces, in your browser go to http://localhost:16686 and you will see the Jaeger UI.
To view traces, in your browser go to http://localhost:16686 to see the Jaeger UI.
## Configure Kubernetes
The following steps shows you how to configure Dapr to send distributed tracing data to Jaeger running as a container in your Kubernetes cluster, how to view them.
### Setup
First create the following YAML file to install Jaeger
* jaeger-operator.yaml
First create the following YAML file to install Jaeger, file name is `jaeger-operator.yaml`
#### Development and test
By default, the allInOne Jaeger image uses memory as the backend storage and it is not recommended to use this in a production environment.
```yaml
apiVersion: jaegertracing.io/v1
kind: "Jaeger"
@ -80,7 +81,54 @@ spec:
base-path: /jaeger
```
#### Production
Jaeger uses Elasticsearch as the backend storage, and you can create a secret in k8s cluster to access Elasticsearch server with access control. See [Configuring and Deploying Jaeger](https://docs.openshift.com/container-platform/4.7/jaeger/jaeger_install/rhbjaeger-deploying.html)
```shell
kubectl create secret generic jaeger-secret --from-literal=ES_PASSWORD='xxx' --from-literal=ES_USERNAME='xxx' -n ${NAMESPACE}
```
```yaml
apiVersion: jaegertracing.io/v1
kind: "Jaeger"
metadata:
name: jaeger
spec:
strategy: production
query:
options:
log-level: info
query:
base-path: /jaeger
collector:
maxReplicas: 5
resources:
limits:
cpu: 500m
memory: 516Mi
storage:
type: elasticsearch
esIndexCleaner:
enabled: false ## turn the job deployment on and off
numberOfDays: 7 ## number of days to wait before deleting a record
schedule: "55 23 * * *" ## cron expression for it to run
image: jaegertracing/jaeger-es-index-cleaner ## image of the job
secretName: jaeger-secret
options:
es:
server-urls: http://elasticsearch:9200
```
The pictures are as follows, include Elasticsearch and Grafana tracing data:
![jaeger-storage-es](/images/jaeger_storage_elasticsearch.png)
![grafana](/images/jaeger_grafana.png)
Now, use the above YAML file to install Jaeger
```bash
# Install Jaeger
helm repo add jaegertracing https://jaegertracing.github.io/helm-charts

View File

@ -14,7 +14,7 @@ description: "Set-up New Relic for distributed tracing"
Dapr natively captures metrics and traces that can be send directly to New Relic. The easiest way to export these is by configuring Dapr to send the traces to [New Relic's Trace API](https://docs.newrelic.com/docs/distributed-tracing/trace-api/report-zipkin-format-traces-trace-api/) using the Zipkin trace format.
In order for the integration to send data to New Relic [Telemetry Data Platform](https://newrelic.com/platform/telemetry-data-platform), you need a [New Relic Insights Insert API key](https://docs.newrelic.com/docs/apis/intro-apis/new-relic-api-keys#insights-insert-key).
In order for the integration to send data to New Relic [Telemetry Data Platform](https://newrelic.com/platform/telemetry-data-platform), you need a [New Relic Insights Insert API key](https://docs.newrelic.com/docs/apis/intro-apis/new-relic-api-keys/#insights-insert-key).
```yaml
apiVersion: dapr.io/v1alpha1
@ -39,7 +39,7 @@ New Relic Distributed Tracing details
## (optional) New Relic Instrumentation
In order for the integrations to send data to New Relic Telemetry Data Platform, you either need a [New Relic license key](https://docs.newrelic.com/docs/accounts/accounts-billing/account-setup/new-relic-license-key) or [New Relic Insights Insert API key](https://docs.newrelic.com/docs/apis/intro-apis/new-relic-api-keys#insights-insert-key).
In order for the integrations to send data to New Relic Telemetry Data Platform, you either need a [New Relic license key](https://docs.newrelic.com/docs/accounts/accounts-billing/account-setup/new-relic-license-key) or [New Relic Insights Insert API key](https://docs.newrelic.com/docs/apis/intro-apis/new-relic-api-keys/#insights-insert-key).
### OpenTelemetry instrumentation
@ -47,7 +47,7 @@ Leverage the different language specific OpenTelemetry implementations, for exam
### New Relic Language agent
Similarly to the OpenTelemetry instrumentation, you can also leverage a New Relic language agent. As an example, the [New Relic agent instrumentation for .NET Core](https://docs.newrelic.com/docs/agents/net-agent/other-installation/install-net-agent-docker-container/) is part of the Dockerfile. See example [here](https://github.com/harrykimpel/quickstarts/blob/master/distributed-calculator/csharp/Dockerfile).
Similarly to the OpenTelemetry instrumentation, you can also leverage a New Relic language agent. As an example, the [New Relic agent instrumentation for .NET Core](https://docs.newrelic.com/docs/agents/net-agent/other-installation/install-net-agent-docker-container) is part of the Dockerfile. See example [here](https://github.com/harrykimpel/quickstarts/blob/master/distributed-calculator/csharp/Dockerfile).
## (optional) Enable New Relic Kubernetes integration
@ -109,6 +109,6 @@ All the data that is collected from Dapr, Kubernetes or any services that run on
* [Telemetry Data Platform](https://newrelic.com/platform/telemetry-data-platform)
* [Distributed Tracing](https://docs.newrelic.com/docs/distributed-tracing/concepts/introduction-distributed-tracing/)
* [New Relic Trace API](https://docs.newrelic.com/docs/distributed-tracing/trace-api/introduction-trace-api/)
* [Types of New Relic API keys](https://docs.newrelic.com/docs/apis/intro-apis/new-relic-api-keys)
* [Types of New Relic API keys](https://docs.newrelic.com/docs/apis/intro-apis/new-relic-api-keys/)
* [New Relic OpenTelemetry User Experience](https://blog.newrelic.com/product-news/opentelemetry-user-experience/)
* [Alerts and Applied Intelligence](https://docs.newrelic.com/docs/alerts-applied-intelligence)

View File

@ -1,7 +1,7 @@
---
type: docs
title: "Performance and Scalability"
linkTitle: "Performance and Scalability"
title: "Performance and scalability statistics of Dapr"
linkTitle: "Performance and scalability"
weight: 700
description: "Benchmarks and guidelines for Dapr building blocks"
---

View File

@ -10,8 +10,8 @@ aliases:
This table is meant to help users understand the equivalent options for running Dapr sidecars in different contexts--via the [CLI]({{< ref cli-overview.md >}}) directly, via daprd, or on [Kubernetes]({{< ref kubernetes-overview.md >}}) via annotations.
| daprd | dapr CLI | CLI shorthand | K8s annotations | Description
|----- | ------- | -----------| ----------| ------------ | ------------ |
| daprd | Dapr CLI | CLI shorthand | Kubernetes annotations | Description
|----- | ------- | -----------| ----------| ------------ |
| `--allowed-origins` | not supported | | not supported | Allowed HTTP origins (default "*") |
| `--app-id` | `--app-id` | `-i` | `dapr.io/app-id` | The unique ID of the application. Used for service discovery, state encapsulation and the pub/sub consumer ID |
| `--app-port` | `--app-port` | `-p` | `dapr.io/app-port` | This parameter tells Dapr which port your application is listening on |

View File

@ -7,7 +7,13 @@ description: "Detailed information on the upgrade CLI command"
## Description
Upgrade Dapr on supported hosting platforms.
Upgrade or downgrade Dapr on supported hosting platforms.
{{% alert title="Warning" color="warning" %}}
Version steps should be done incrementally, including minor versions as you upgrade or downgrade.
Prior to downgrading, confirm components are backwards compatible and application code does ultilize APIs that are not supported in previous versions of Dapr.
{{% /alert %}}
## Supported platforms
@ -23,8 +29,8 @@ dapr upgrade [flags]
| Name | Environment Variable | Default | Description
| --- | --- | --- | --- |
| `--help`, `-h` | | | Print this help message |
| `--kubernetes`, `-k` | | `false` | Upgrade Dapr in a Kubernetes cluster |
| `--runtime-version` | | `latest` | The version of the Dapr runtime to upgrade to, for example: `1.0.0` |
| `--kubernetes`, `-k` | | `false` | Upgrade/Downgrade Dapr in a Kubernetes cluster |
| `--runtime-version` | | `latest` | The version of the Dapr runtime to upgrade/downgrade to, for example: `1.0.0` |
| `--set` | | | Set values on the command line (can specify multiple or separate values with commas: key1=val1,key2=val2) |
## Examples
@ -34,15 +40,16 @@ dapr upgrade [flags]
dapr upgrade -k
```
### Upgrade specified version of Dapr runtime in Kubernetes
### Upgrade or downgrade to a specified version of Dapr runtime in Kubernetes
```bash
dapr upgrade -k --runtime-version 1.2
```
### Upgrade specified version of Dapr runtime in Kubernetes with value set
### Upgrade or downgrade to a specified version of Dapr runtime in Kubernetes with value set
```bash
dapr upgrade -k --runtime-version 1.2 --set global.logAsJson=true
```
# Related links
- [Upgrade Dapr on a Kubernetes cluster]({{< ref kubernetes-upgrade.md >}})

View File

@ -70,6 +70,8 @@ The above example uses secrets as plain strings. It is recommended to use a secr
## Binding support
This component supports both **input and output** binding interfaces.
This component supports **output binding** with the following operations:
- `create`

View File

@ -42,6 +42,8 @@ spec:
value: "bcc@example.com"
- name: subject
value: "subject"
- name: priority
value: "[value 1-5]"
```
{{% alert title="Warning" color="warning" %}}
@ -62,6 +64,7 @@ The example configuration shown above, contain a username and password as plain-
| emailCc | N | Output | If set, this specifies the email address to CC in. See [also](#example-request) | `"me@example.com"` |
| emailBcc | N | Output | If set, this specifies email address to BCC in. See [also](#example-request) | `"me@example.com"` |
| subject | N | Output | If set, this specifies the subject of the email message. See [also](#example-request) | `"subject of mail"` |
| priority | N | Output | If set, this specifies the priority (X-Priority) of the email message, from 1 (lowest) to 5 (highest) (default value: 3). See [also](#example-request) | `"1"` |
## Binding support
@ -78,6 +81,7 @@ You can specify any of the following optional metadata properties with each requ
- `emailCC`
- `emailBCC`
- `subject`
- `priority`
When sending an email, the metadata in the configuration and in the request is combined. The combined set of metadata must contain at least the `emailFrom`, `emailTo` and `subject` fields.
@ -90,7 +94,8 @@ Example:
"metadata": {
"emailTo": "dapr-smtp-binding@example.net",
"emailCC": "cc1@example.net; cc2@example.net",
"subject": "Email subject"
"subject": "Email subject",
"priority: "1"
},
"data": "Testing Dapr SMTP Binding"
}

View File

@ -61,7 +61,7 @@ spec:
my_claim := jwt.payload["my-claim"]
}
jwt = { "payload": payload } {
auth_header := input.request.headers["authorization"]
auth_header := input.request.headers["Authorization"]
[_, jwt] := split(auth_header, " ")
[_, payload, _] := io.jwt.decode(jwt)
}

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