- [Docs] Added 0.11.1 blog post

docs/blog/posts/managed-gateways.md

@@ -0,0 +1,91 @@
+---
+title: "Managed gateways for serving LLMs across clouds"
+date: 2023-09-01
+description: "The dstack 0.11.1 update introduces default gateways and wildcard domains to make it easier to serve LLMs via public endpoints."
+slug: "managed-gateways"
+categories:
+- Releases
+---
+
+# Managed gateways for serving LLMs across clouds
+
+__The dstack 0.11.1 update makes it easier to serve LLMs via public endpoints.__
+
+Services is a preview feature that allows serving LLMs via public endpoints using multiple clouds
+(AWS, GCP, Azure, Lambda, etc.) 
+The latest update of `dstack` makes the use of services much easier by introducing default gateways and wildcard domains.
+
+<!-- more -->
+
+## Default gateways
+
+Previously, to run a service, you had to create a gateway using the `dstack gateway create` command and pass its address via the `gateway` property in the service configuration file.
+
+Now, you don't need to use the `gateway` property anymore, as you can create a gateway via the UI and mark it as default.
+
+![](../../assets/images/dstack-hub-view-project-empty.png){ width=800 }
+
+## Wildcard domain
+
+Once the gateway is created (and assigned an external IP), you can set up an A record with your DNS provider to map `*.<your domain name>` to the gateway's IP and specify this wildcard domain in the gateway's settings.
+
+![](../../assets/images/dstack-hub-edit-gateway.png){ width=800 }
+
+If a wildcard domain is configured, dstack automatically enables HTTPS and runs services at `https://<run name>.<your domain name>`.
+
+<div class="termy">
+
+```shell
+$ dstack run . -f text-generation-inference/serve.dstack.yml --gpu A100 -y
+
+ RUN           BACKEND  INSTANCE              SPOT  PRICE STATUS    SUBMITTED
+ tasty-zebra-1 lambda   200GB, 1xA100 (80GB)  no    $1.1  Submitted now
+
+Privisioning...
+---> 100%
+
+Serving on https://tasty-zebra-1.mydomain.com
+```
+
+</div>
+
+
+!!! info "Why this matters?"
+    The gateway feature makes it very easy to serve LLMs using GPUs across multiple regions and cloud providers (AWS, GCP,
+    Azure, Lambda, etc.), while providing convenient endpoints via HTTPS.
+
+## Task scheduling
+
+In other news, the update fixes a few bugs with the `--retry-limit` argument in `dstack run`. Now, it works again,
+allowing you to schedule tasks even if there is no required capacity at the moment.
+
+<div class="termy">
+
+```shell
+$ dstack run . -f text-generation-inference/serve.dstack.yml --gpu A100 --retry-limit 1h
+
+ RUN           BACKEND  INSTANCE  SPOT  PRICE STATUS  SUBMITTED
+ tasty-zebra-1 lambda   -         no    -     Pending now
+
+Waiting for capacity... To exit, press Ctrl+C.
+```
+
+</div>
+
+Last but not least, we've updated the entire [documentation](https://dstack.ai/docs/) and [examples](https://dstack.ai/examples/).
+
+## Give it a try
+
+Getting started with `dstack` takes less than a minute. Go ahead and give it a try.
+
+<div class="termy">
+
+```shell
+$ pip install "dstack[aws,gcp,azure,lambda]" -U
+$ dstack start
+```
+</div>
+
+!!! info "Feedback and support"
+    Questions and requests for help are very much welcome in our 
+    [Slack chat](https://join.slack.com/t/dstackai/shared_invite/zt-xdnsytie-D4qU9BvJP8vkbkHXdi6clQ).